Advances in Health Care Management, Volume 3 (Advances in Health Care Management) (Advances in Health Care Management)

LIST OF CONTRIBUTORS John D . Blair Rawls College of Business, Texas Tech University, USA Starr A . Blair Gateways ...

Author: G. Savage | J. Blair | M. Fottler

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LIST OF CONTRIBUTORS

John D . Blair

Rawls College of Business, Texas Tech University, USA

Starr A . Blair

Gateways Counseling Center, Lubbock, Texas, USA

Mark P. Brown

College of Business Administration, Bradley University, USA

David D. Dawley

College of Business and Economics, West Virginia University, USA

Laurette Dube

Faculty of Management, McGill University, Canada

Amy C. Edmondson

Technology and Operations Management, Harvard Business School, USA

Joan Finegan

Department of Psychology, The University of Western Ontario, Canada

Myron D . Fottler

College of Health and Public Affairs, University of Central Florida, USA

Josiah Hawkins

Faculty of Medicine and Faculty of Management, McGill University, Canada

Mark Hoelscher

College of Business, Illinois State University, USA

James J. Hoffman

Rawls College of Business, Texas Tech University, USA ix

x

LIST OF CONTRIBUTORS

Marilyn Kaplow

McGill University Health Center, McGill University, Canada

Adelaide Wilcox King

McIntire School of Commerce, University of Virginia, USA

Heather K. Spence Laschinger

School of Nursing, The University of Western Ohio, USA

Donna Malvey

College of Public Health, University of South Florida, USA

Timothy W. Nix


G. Tyne Payne

College of Business Administration, University of Texas at Arlington, USA

David F. Robinson


Grant T. Savage

Culverhouse College of Commerce and Business Administration, The University of Alabama, USA

Judith Shamian

Health Canada, Ottawa, Ontario, Canada

Marcia J. Simmering

College of Business Administration, Louisiana State University, USA

Michael C. Sturman

School of Hotel Administration, Cornell University, USA

Lefa Teng

Faculty of Commerce and Administration, Concordia University, USA

Sharon Topping

College of Business Administration, University of Southern Mississippi, USA

xi

List ~f Contributors Anita L. Tucker

Technology and Operations Management, Harvard Business School, USA

Lynn E Unruh

College of Health and Public Affairs, University of Central Florida, USA

Carl P. Ziethaml

McIntire School of Commerce, University of Virginia, USA

REVIEW BOARD MEMBERS Jeff Alexander

Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI, USA

James Begun

Department of Healthcare Management, Carlson School of Management, University of Minnesota, Minneapolis, MN, USA

Thomas D'Aunno

Health Care Management Initiative, INSEAD, Fontainebleau, France

W. Jack Duncan

Department of Management, Marketing and Industrial Distribution, School of Business, University of Alabama at Birmingham, Birmingham, AL, USA

Peter M. Ginter

Department of Health Care Organization and Policy, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA

James Hoffman

Area of Management, Rawls College of Business, Texas Tech University, Lubbock, TX, USA

xiv

REVIEW BOARD MEMBERS

Arnold Kaluzny

Department of Health Policy and Administration, School of Public Health, University of North Carolina, Chapel Hill, NC

Stephen J. O'Connor

Department of Health Services Administration, School of Health Related Professions, University of Alabama at Birmingham, Birmingham, AL, USA

Keith Provan

School of Public Administration and Policy, University of Arizona, Tuscon, AZ, USA

Howard Zuckerman

Center for Health Management Research, School of Public Health and Community Medicine, University of Washington, Seattle, WA, USA

REVIEWERS Ruth A . Anderson

School of Nursing, Duke University, USA

Donde Ashmos

College of Business Administration, University of Texas at San Antonio, USA

Diane Brannon

Department of Health Policy and Administration, Pennsylvania State University, USA

Jon Chilingerian

Heller School for Social Policy and Management, Brandeis University, USA

Kathryn Danskv

Department of Health Policy and Administration, Penn State University, USA

Eric Kirby

Department of Management and Marketing, Southwest Texas State University, USA

Beaufort Longest

Health Policy Institute, University of Pittsburgh, USA

Donna Malvey

College of Public Health, University of South Florida, USA

Kathleen Montgomery

Anderson Graduate School of Management, University of California, Riverside, USA

Timothy W. Nix


G . Tyne Payne

College of Business Administration, The University of Texas at Arlington, USA xv

REVIEWERS

Xvi

Mary Richardson

School of Public Health and Community Medicine, University of Washington, USA

David F. Robinson


Donna Slovensky

School of Health Related Professions, The University of Alabama at Birmingham, USA

Marietta P. Stanton

Capstone College of Nursing, The University of Alabama, USA

ADVANCES IN HEALTH CARE MANAGEMENT: OVERVIEW Grant T. Savage, John D. Blair and Myron D. Fouler

Just as a decade ago, the U .S . health care delivery system approaches a crisis . Now, and for the past few years, the costs of health insurance and health services have exceeded the rate of inflation (Levit, Smith, Cowan, Lazenby & Martin, 2002) . With an economic recession and reduced state budgets for Medicaid, the number of uninsured is expected to increase at an alarming rate (Rowland, 2002) . At the same time, the quality of care for all insured patients is threatened both by medical errors (America, 2001 ; Kohn, Corrigan & Donaldson, 2000) and by nursing and other health professional shortages (First Consulting Group, 2001) . While these problems with the U .S . health system seem intractable, they can be mitigated and often addressed by the significant improvements offered through the study of health care management . Indeed, at the behavioral, organizational, and strategic levels, evidence-based management can make a difference (Walshe & Rundall, 2001) . As with previous volumes, this research volume underscores the diversity and excellence in the health care management field . Volume 3 includes authors, both new and established, whose contributions range from state-of-the-art reviews to rigorous quantitative and qualitative studies . Thematically, the volume is arranged in three sections . A special research forum on management issues in nursing comprises section one . Section two focuses on clinical and technological issues, while section three concentrates on organizational and strategic issues in health care management .

Advances in Health Care Management, Volume 3, pages 1-8 . Copyright © 2002 by Elsevier Science Ltd . All rights of reproduction in any form reserved. ISBN : 0-7623-0961-X 1

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GRANT T . SAVAGE, JOHN D. BLAIR AND MYRON D . FOTTLER

SPECIAL RESEARCH FORUM ON MANAGEMENT ISSUES IN NURSING The nursing shortage (First Consulting Group, 2001) in the U .S . and elsewhere in the developed world (Buchan, 2002) underscores the importance of this special research forum on management issues in nursing . Producing more nurses, Buchan (2002) argues, will not solve this problem . Rather, a variety of approaches should be used to address the work context concerns that drive nurses away from health care . The articles in this special research forum examine the causes of the nursing shortage and its impact on performance, as well as how wage increases, staffing increases, empowerment, and organizational design might address and alleviate some of the root causes for this problem . The lead article, "Nurse Staffing and Nursing Performance : A Review and Synthesis of the Relevant Literature" provides a comprehensive review of the relationship between nurse staffing and performance . The authors, Lynn Y . Unruh and Myron D . Fottler, present the results of an extensive literature review of quantitative and qualitative studies that relate the internal work environment to nurse withdrawal behavior and performance . Based on this review, they develop a model depicting the interrelationships as a "vicious spiral to the bottom" whereby cuts in nurse staffing result in a negative work environment characterized by work overload, poor nurse physical and mental health, and low job satisfaction . The environment, in turn, increases nurse withdrawal behavior and adversely affects nurse performance . Implications for public policy, management and future research are discussed . The second article, "The Benefits of Staffing and Paying More : The Effects of Staffing Levels and Wage Practices for Registered Nurses on Hospitals' Average Lengths of Stay," draws upon a 2001 best paper from the Health Care Management Division of the Academy of Management . The authors, Mark P . Brown, Michael C . Sturman and Marcia J. Simmering, examine the effects that staffing levels and wages of registered nurses have on hospitals' average lengths of stay . Specifically, they ask the following research questions : (a) do hospitals that hire more RNs have better outcomes ; (b) do hospitals that pay RNs more have better outcomes ; and (c) what is the relative advantage of greater staffing versus greater wages? Based on 1996-1999 pooled data from 352 short-term care hospitals in California, they show that both increased staffing levels and increased wage rates correlate with decreased average lengths of stay . Furthermore, it appears that wage may be more effective for improving the average lengths of stay than would increasing the quantity of RNs . The authors discuss the implications for human resource practices and future research on health care management .

Overview

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"The Impact of Workplace Empowerment, Organizational Trust on Staff Nurses' Work Satisfaction and Organizational Commitment," is the third article . This manuscript is extended and reprinted from Health Care Management Review, and is based on the 2001 best theory to practice paper from the Health Care Management Division, Academy of Management . The authors - Heather K . Spence Laschinger, Joan Finegan and Judith Shamian - use a predictive, nonexperimental design to test Kanter's work empowerment theory in a random sample of 412 Canadian staff nurses . Empowering work environments are ones that provide access to information, to resources necessary to do the job, to support, and to opportunities for learning and developing . The results from the structural equation model show that nurses' sense of workplace empowerment strongly affected their trust in management, satisfaction with their workplace, their belief and acceptance of organizational goals and values, their willingness to exert effort in the workplace and desire to stay in the organization (affective commitment) . These findings highlight the importance of creating environments that provide access to structures that empower nurses to accomplish their tasks . Moreover, in alignment with research demonstrating that affective commitment is related to productivity, their results suggest that fostering environments that enhance perceptions of empowerment will have positive effects on employees and, ultimately, enhance organizational effectiveness . The fourth and last article in the special research forum examines how hospital work environments and manager behavior influence nurses' responses when faced with unexpected problems . Anita Tucker and Amy C . Edmondson's "Managing Routine Exceptions : A Model of Nurse Problem Solving Behavior," draws from yet another 2001 best paper from the Health Care Management Division of the Academy of Management . Data from a qualitative study involving 239 hours of observation of 26 hospital nurses at nine hospitals suggest that exceptions occur frequently and that the work design of hospitals leads nurses to respond to exceptions through first-order problem solving, addressing only immediate symptoms without attempting to alter underlying causes . This pattern of behavior contrasts with recommended approaches found in the quality improvement literature . Indeed, health care managers may need to tailor front line quality improvement processes to meet the demands of the health care delivery environment in which exceptions are so frequent as to be considered virtually routine . Building on empirical observations from the study and drawing from two literatures - healthcare management and organizational behavior - Tucker and Edmondson develop a model of problem solving behavior by hospital nurses . The model proposes that nurse manager coaching, support, and proficiency, together with features of the organizational context - training, self management, work design, group norms, and reward interdependence -

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GRANT T . SAVAGE, JOHN D . BLAIR AND MYRON D . FOTTLER

influence nurses' problem solving behavior through the mediating variable of nurse cognition (psychological safety and motivation). The use of a problem solving coordinator moderates the problem-solving behavior's impact on performance outcomes .

CLINICAL AND TECHNOLOGICAL ISSUES IN HEALTH CARE MANAGEMENT While the nursing shortage provides the context for the special research forum, this section on clinical and technological issues explores population health management, emotions and patient-centered care management, and the impact of regulations on medical innovations . These articles touch upon how health care costs can be lowered and the quality of care can be improved through better clinical and technological management, themes raised by two studies issued by the Institute of Medicine (Committee on Quality of Health Care in America, 2001 ; Kohn et al ., 2000) . Ann Scheck McAlearney's, "Population Health Management in Theory and Practice," provides a state-of-the-art review of five population health management initiatives . Lifestyle management strategies emphasize health risk reduction and prevention techniques as they target a relatively healthy population . Demand management approaches extend lifestyle management strategies by concentrating on consumer demand for medical care services. When an individual has a health or medical problem and desires attention, demand management strategies provide advice, counseling, and referrals to appropriate providers as they address the issue of demand for medical care and services . Disease management techniques typically focus on individuals with chronic conditions . Focused on diseases such as diabetes, congestive heart failure, or asthma, disease management programs offer targeted health and care management services to help coordinate the needs and care of individuals with those specific diseases . Catastrophic care management services extend the disease management approach to provide health management services for individuals with catastrophic illnesses or injuries . Finally, disability management approaches are designed from an employer's perspective to improve worker productivity by focusing on strategies to reduce injuries, avoid illness, and better manage employee disability . After reviewing each form of population health management, McAlearney highlights the critical role of information technologies in the development of population health management strategies, and presents a conceptual model of population health management on both individual and organizational levels . She concludes by discussing the practical and research issues around developing and applying a population health management model in the U .S . health services sector.

Overview

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Laurette Dube, Lefa Teng, Josiah Hawkins and Marilyn Kaplow are authors of the second article in this section . Their paper, "Emotions, the Neglected Side of Patient-Centered Health Care Management : The Case of Emergency Department Patients Waiting to See a Physician," addresses both the practical consequences of triaging patients and its emotional impact . Patient emotions have not been sufficiently integrated into patient-centeredness, a wellestablished organizing principle of health care management . To offset this imbalance, Dube and her colleagues review the scientific knowledge on emotions that is of relevance to support it being a core component of patientcenteredness and conduct a field study to investigate the mechanisms by which emotions influence care outcomes (specifically, patient satisfaction) . Structural analyses performed on self-reports from 283 minor care patients in an Emergency Department reveal that both positive and negative emotions influence satisfaction indirectly by biasing patient perceptions of quality of care in a valence-congruent direction . Negative emotions have an additional direct effect on satisfaction . Patients who were made to wait longer to see the physician not only manifested a progressive deterioration of their emotional states (i .e . decrease in positive affects and increase in negative affects) but their satisfaction judgments became more importantly formed on the basis of emotions . Implications of the research for healthcare management are discussed . The closing paper in this section, "Innovation in Medical Devices and Medical Electronics : Are European Regulations and Practices Shifting Innovation to Europe?" examines the recent changes in European regulations of medical devices and electronics . Specifically, David F. Robinson explores the relationship between the complex process of innovation, the role of regulation, and the incentives in the development of new technology . A key issue in innovation research is to understand the effects of changes in regulatory practices and incentive systems on how much innovation takes place and where those inventive activities will occur . There is anecdotal evidence and some empirical evidence that changes in medical device regulation in Europe may be shifting new product development research, clinical trials and experimentation from North America to Europe . Results from this study indicate that for medical devices, patents granted to European inventors have increased at a faster rate from 1995 through 2000 than for North American inventors . These results reverse the trend found from 1991 through 1995 . Organizational learning theory implies that if this trend in growth continues, there may be serious consequences for the future of medical device innovation in North America, health consequences for patients in need of access to clinical trials of new technology, and changes in the training of future researchers and physicians .

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GRANT T . SAVAGE, JOHN D . BLAIR AND MYRON D. FOTTLER ORGANIZATIONAL AND STRATEGIC ISSUES IN HEALTH CARE MANAGEMENT

While the themes of cost control and improving the quality of care via clinical practices and technology underlie the previous section, the four papers that conclude this volume focus on organizational and strategic issues in health care management . Improving the overall performance of health care service organizations both under varying environmental conditions and given varying managerial perceptions is the thematic common ground for these papers . Adelaide Wilcox King and Carl P . Zeithaml's article, "Managers' Perceptions of Hospital Capabilities : A Theoretical and Empirical Study," explores the relationship between what managers believe are their organizational capabilities and actual performance . The management literature has explored and recognized that managers' perceptions of their hospitals' external conditions or environment are important antecedents to effective strategic choices and, therefore, superior performance . We have less understanding, however, of the relationship between managers' perceptions of their hospitals' internal conditions or capabilities and performance . This study draws upon resource-based, cognitive, and knowledge theories to develop and examine measures of hospital managers' perceptions of capabilities . These organizational theories suggest that, due to the unique nature of capabilities, assessment of managers' perceptions of capabilities is also important to shaping strategy . An extensive field study identifies capabilities and explores relationships between managers' perceptions of capabilities and an objective measure of hospital success . Sharon Topping and Donna Malvey's paper, "Management of Academic Health Centers : The Past, Present, and Future," reviews the literature on this important subset of health care service organizations . There are approximately 120 academic health centers (AHC) in the U .S . whose mission is to deliver critical, tertiary care while also providing graduate medical education and conducting cutting-edge medical research . This traditional, tripartite mission often is overlaid by the social mission of providing highly specialized, complex or innovative care not readily available from other community providers to those who need it, including the under-served and uninsured . Taken together, these missions make AHCs unique ; however, they also are the focus of much controversy surrounding the management of AHCs . On one hand, there are those who advocate that AHCs should operate similarly to business organizations, adapting competitive strategies and revising their missions to fit their external environment . On the other hand, there are those who believe in the uniqueness of AHCs and the necessity of upholding their traditional missions . Topping and

Overview

7

Malvey focus on the dynamic environment AHCs face and their strategic responses to this dynamism . They argue that many AHCs engage in "copy cat" strategies that may be successful for community hospitals and general business organizations but may not necessarily be appropriate for AHCs . The debate over the mission and strategic direction of AHCs, particularly in light of the business enterprise model, raises significant questions about the future management of these institutions . David D Dawley, James J . Hoffman, and Mark Hoelscher's, "A Strategic Change/Organizational Ecology Based Theory of Post-Bankruptcy Performance in Healthcare Firms," expounds upon a theory for the determinants of postbankruptcy performance among healthcare firms . Specifically, they examine the potential effects of strategic change (i .e . refocusing), organizational size, slack and munificence on post-bankruptcy performance . On one hand, bankrupt healthcare firms that refocus should have better post-bankruptcy performance than should firms that maintain diversified services . On the other hand, greater organizational size, slack, and munificence should enhance post-bankruptcy performance . This paper highlights the benefits of refocusing the diversified healthcare firm, the liabilities associated with diversification in the healthcare industry, and organizational ecology theories and perspectives regarding organizational size, slack, and munificence . In addition, the paper aims to provide richer insight into our understanding of the post-bankruptcy performance of healthcare firms . The closing paper, "From Stakeholder Management Strategies to Stakeholder Management Styles : Serendipitous Research on Organizational Configurations," revisits how health care managers make sense of stakeholders and act strategically within these inter-organizational relationships . The authors - John D . Blair, Starr A . Blair, Myron D . Fouler, Timothy W . Nix, G . Tyge Payne, and Grant T . Savage - question existing research on stakeholder management that has focused on managing dyadic relationships with stakeholders . They propose, based on serendipitous findings from a prior research study, that organizations exhibit distinct configurations in the ways in which they manage their key stakeholders . To explicate this notion, Blair and his colleagues review potential theoretical configurations of stakeholder management styles, including a wellknown stakeholder typology, which focuses on the concepts of threat and cooperation . Based on this review, they develop a new typology that shifts the focus from individual stakeholders to a focus on the organizations and their fundamental orientation toward managing a portfolio of stakeholders . Lastly, Blair et al . use secondary data analyses of a national sample of 686 medical group executives to examine how and whether stakeholder management styles are likely to impact multiple indicators of organizational performance .

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GRANT T . SAVAGE, JOHN D . BLAIR AND MYRON D. FOTTLER Taken together, these 11 papers provide a wide-ranging articulation of

research in health care management . From management issues in nursing to clinical and technological issues to organizational and strategic issues, this

volume offers papers that will interest health care management researchers from

a variety of perspectives . We hope that they will also inspire researchers to ask new theoretical and empirical questions, facilitating the scientific advance of health care management.

REFERENCES Buchan, J . (2002) . Global nursing shortages . British Medical Journal, 324(7340), 751-752 . Committee on Quality of Health Care in America (2001) . Crossing the quality chasm : A new health system for the 21st century. Washington, D .C . : National Academy Press . First Consulting Group (2001) . The healthcare workforce shortage and its implications for America's hospitals, 34 . Long Beach, CA : First Consulting Group . Kohn, L . T ., Corrigan, J . M ., & Donaldson, M . S . (Eds) (2000) . To err is human: Building a safer health system . Washington, D .C . : National Academy Press . Levit, K ., Smith, C ., Cowan, C ., Lazenby, H ., & Martin, A . (2002) . Inflation spurs health spending in 2000. Health Affairs, 21(1), 172-181 . Rowland, D . (2002) . The new challenge of the uninsured : Coverage in the current economy, 1-24 . Washington, D .C . : Testimony to Subcommitte on Health, Committee on Energy and Commerce, U .S . House of Representatives . Walshe, K., & Rundall, T . G . (2001) . Evidence-based management : From theory to practice in health care . Milbank Quarterly, 79(3), 429-457, IV-V .

NURSE STAFFING AND NURSING PERFORMANCE : A REVIEW AND SYNTHESIS OF THE RELEVENT LITERATURE Lynn Y . Unruh and Myron D . Fottler

ABSTRACT This paper presents the results of an extensive literature review of quantitative and qualitative studies that relate the internal work environment to nurse withdrawal behavior and nurse performance . A model depicting the interrelationships and descriptive tables are developed on the basis of this review . Studies indicate a "vicious spiral to the bottom" whereby cuts in nurse staffing result in a negative work environment characterized by work overload, poor nurse physical and mental health, and low job satisfaction . This environment, in turn, increases nurse withdrawal behavior and adversely affects nurse performance . Implications for public policy, management and future research are discussed .

INTRODUCTION During the U .S . health care system restructuring of the 1990s, reductions in hospital nursing staff, changes in skill mix, and reorganization of the nursing process were common organizational responses by hospitals to their financial

Advances in Health Care Management, Volume 3, pages 11-44 . © 2002 Published by Elsevier Science Ltd . ISBN : 0-7623-0961-X 11

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LYNN Y . UNRUH AND MYRON D . FOTTLER

pressures (Aiken et al ., 2000 ; Leatt et al ., 1997 ; Lee & Alexander, 1999 ; Shortell et al ., 1995 ; Unruh, 2001). Although initially little was known about the impact of such changes on the quality of care, it was assumed - as in the industrial sector which had made such changes a decade earlier - that nurse staffing and process changes would increase productivity without a loss of quality (Arikian, 1991 ; Herrmann, 1995 ; Leatt et al ., 1997 ; Shortell et al ., 1995) . As the decade progressed, concerns arose over inadequate nurse staffing (registered nurses in particular) and the possibility that the quality of care was suffering (AHA, 1997 ; Gordon, 1995 ; Pindus & Greiner, 1997 ; ShindulRothschild et al ., 1996 ; Wunderlich et al ., 1996) . To accentuate the issue, in 1999 hospitals began reporting a shortage of registered nurses (RNs) (AHA, 1999) . This shortage is seen as much more significant than prior ones, which were businesscycle generated . In the current shortage, in addition to the usual cyclical demand and supply factors, the supply of RNs is declining due to the aging of the workforce without adequate numbers of replacements, and the demand for nursing care is rising due to the aging of the overall population (Bednash, 2001 ; Kimball & O'Neil, 2001 ; White, 2001) . So we currently have a shortage of RNs on top of the workforce reductions that occurred in the 1990s, with expectations of even greater shortages in the future . This unfortunate situation lends credence to the common perception of nurses and the public that hospitals are dangerously understaffed, and this understaffing is one of the most serious problems facing the health care industry today (Crawshaw, 2001 ; Freudenheim & Villarosa, 2001 ; Shapiro, 2001) . Research on the contribution of RN staffing to the quality of care in hospitals began in the 1980s . Research conducted since 1989 focuses on the relationship between RN staffing and patient outcomes, and frequently establishes that better staffing is related to better patient outcomes (ANA, 1997 ; Blegen et al ., 1998 ; Blegen & Vaughn, 1998 ; Fridkin et al ., 1996 ; Hartz et al ., 1989 ; Kovner & Gergen, 1998 ; Krakauer et al ., 1992 ; Manheim et al ., 1992 ; Needleman et al ., 2001) . However, because these studies do not contain a framework identifying how staffing affects patient outcomes through the nursing process, little is known about why this relationship exists . Of studies that attempt a framework, very little is advanced to fill in the relevant variables, together with their connections and relationships . (Mitchell et al ., 1989 ; Shindul-Rothschild et al ., 1997 ; Unruh, 2000) . Related research does not fill in the gaps . Magnet hospital studies have shown that RNs' job satisfaction and productivity are better in hospitals known to be good places to work and to be capable of recruiting and retaining RNs (Aiken et al ., 1994 ; Kramer, 1990 ; Kramer & Schmalenberg, 1988a, b) . The studies illuminate a set of structural and contextual components in nursing care, such as

Nurse Staffing and Nursing Performance

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administrative style and leadership, and educational and professional attributes of nursing staff, that are associated with hospitals known to be attractive places for RNs to work . In some studies, magnet hospitals are also found to have lower patient mortality (Aiken et al ., 1994) . However, the interrelationships between nurse staffing and job satisfaction and productivity, or between staffing and the other structural variables, are not assessed . Therefore, the studies do not tell us how staffing issues contribute to nurse satisfaction, productivity, or performance, how staffing may be connected to other organizational aspects such as administration and nursing autonomy, or how these interrelationships may impact patient outcomes . A few studies examine the impact of work environment issues, such as stress, on patient outcomes, but do not directly link this to staffing (Dugan et al ., 1996 ; Packard & Motowildo, 1987) . Other studies assess the responsibility of some general process problems, such as error or negligence, in the generation of adverse events, but again, without a connection to staffing (Brennan et al ., 1991 ; Leape et al ., 1991 ; Leape et al ., 1995) . We are not aware of any study that connects nurse staffing with the nursing process and with patient outcomes . So while it is believed that nurse staffing impacts the nursing process, and this process affects patient outcomes, the exact details of each of these steps are hazy and empirically unexplored . The purpose of this review is to fill in details about the relationships between nurse staffing, other aspects of the work environment, and nurse performance, and to pull the pieces together into an integral whole . By making connections between the various disconnected relationships that currently form the research literature, we synthesize the parts into a more complete, yet complex, picture . Through a review of the literature, we examine why nurse staffing matters in the delivery of nursing care . What does inadequate staffing do to the work environment? How does this affect nurses and their performance? Are there any interconnections and feedback mechanisms at work that make the situation worse? Understanding these relationships is important, especially given the dual punch to health care delivery of hospital downsizing followed by nursing workforce shortages . Consequently, an understanding of the processes by which nurse staffing influences nursing performance and nurse withdrawal behavior is crucial because alleviation of this situation requires increased incentives both to enter the profession and to stay in the profession . As we develop a fuller understanding of the dynamics of the impact of staffing in the workplace, we will be able to engage in organizational changes that support positive outcomes for staff and patients . This review describes and synthesizes the literature on nurse staffing and nursing performance, and any literature that focuses on any of the intermediate

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or mediating details . By nurse staffing we include studies addressing any skill level of nurses, but we find that most studies focus on RNs or do not specifically define the term "nurses ." Through our review, we piece together a richer framework for future research on nurse staffing, and we identify themes and recommendations for health care management and policy .

THEORETICAL FRAMEWORK In this review we use Donabedian's structure-process-outcomes (SPO) quality framework to explore the literature on the relationship between the structure and process components in nursing care . In his framework (1966), structural measures of quality are the professional and organizational resources available to provide care . Process measures refer to the things that are done to, and for, the patients by practitioners . Outcomes are the patient states resulting from the care processes . These three quality indicators are causally related . Structure leads to process which leads to outcome (Donabedian, 1988) . Structure can also directly influence outcome . In an examination of nursing care, the structural aspects are the numbers and skill mix of nursing staff, educational level and experience, nursing administration, and nursing staff organization . The process components are the nursing processes, and therefore the actual care delivered to the patient . Patient outcomes can be both positive states such as improved functional status or recovery after surgery, or they can be negative states such as acquired infections and injuries . In the SPO framework, the relationship between the structural aspects such as nurse staffing and patient outcomes are mediated through process components of nursing care . Patient outcomes are in part the results of the provision of nursing care, which is impacted by nurse staffing and other organizational factors . In this review, we limit the structural components to those involved with staffing issues . These include the numbers of nursing staff to the numbers of patients (or some other patient load indicator), the skill mix of the nursing staff, and the amount of overtime (Cho, 2001) . The process components include any aspect of nursing performance . The patient outcomes of nursing care are not examined in this paper . We are interested in looking at the relationship between structure (nurse staffing) and process (nursing performance) . Other research examines the impact of nurse staffing on patient outcomes (Aiken et al ., 2000 ; Aiken et al., 1994 ; ANA, 1997 ; Blegen et al ., 1998 ; Blegan & Vaughn, 1998 ; Cho, 2001 ; Kovner & Gergen, 1998) . In terms of the relationship between structure and process, we first explore nurses' emotional, physical, and behavioral responses to nurse staffing factors,


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and how their responses may feed into their withdrawal behavior and the type of care they provide . We next review the literature that assesses the overall impact of nurse staffing on the nursing process . The nursing process is a set of complex acts of problem-solving and decision-making that include many different types of cognitive, behavioral and manual tasks (Mitty, 1997) . Due to the complexity of nursing care, and the difficulty in measuring it, the relationship of nurse staffing to the nursing process is rarely explored . When the relationship is examined, as will be seen in the review below, the analysis required to speak to these complexities is often a qualitative one . In a feedback loop, we also find evidence that performance can impact nurses' emotional state . Our general theoretical framework is that nurse staffing impacts the work environment and nurse performance, both directly and indirectly . Poorer performance may also feed back into the system .

METHODS The review was accomplished through a search of literature from 1990 to the present . English-language research journals from the following economic, health services management, medical, nursing, and social science databases were searched : Academic Search Elite, Alt-Health Watch, CINAHL, Ebsco on-line citations, EconLit, Health Source Plus, Medline, and Social Sciences Citation Index . Search keywords were : work environment, working conditions, workload, understaffing, overwork, nursing turnover, absenteeism, performance, nurse staffing and quality of care, nurse staffing and performance, work environment and quality of care, working conditions and quality of care, work environment and nursing care, working conditions and nursing care, overwork and nursing care, understaffing and nursing care . As references were collected, additional citations from the assembled literature were obtained . This resulted in the utilization of some sources from the 1980s . Nurse staffing was defined as any educational/skill level of nurses (RNs, LPNs or nursing assistants, or any combination thereof) in order to explore the impact of any level and/or mix of nursing staff on performance . We found, however, that most studies focused on either : (1) RNs and RN to nursing staff skill mix ; (2) RNs and LPNs and their mix ; or (3) something called "nurses" that wasn't well-defined . A few studies clearly included nursing assistants . One group of articles was selected if relationships between nurse staffing and performance, or between nurse staffing and the quality of care was addressed . A second group of articles was selected if the focus was on the relationship between nurse staffing and any hypothesized mediating factor between nurse

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LYNN Y . UNRUH AND MYRON D . FOULER

staffing and performance, such as staff exhaustion, burnout, or turnover . Articles were also selected if they addressed the relationship between mediating factors (such as nursing staff burnout or turnover) and nurse performance or the quality of nursing care .

MODEL After reviewing the literature, we developed the model shown in Fig . 1, which describes the processes and linkages between nurse staffing and nursing performance . The box at the left summarizes some of the external environmental changes that impact the internal work environment in which nursing care is provided . All of these environmental changes, which are well known, create changes in the internal work environment in terms of restructuring, downsizing, and lower nurse staffing ratios (measured in various ways) . These changes in the internal work environment, in turn, create a variety of impacts on the work environment including adverse physical and mental health, lower job satisfaction, lower intent to stay, work overload, and reduced workgroup cohesion (Arrow A) . Both the changes in the internal work environment and their impact create lower levels of nursing performance as measured by lower levels of quality nursing care, patient satisfaction, and nurse productivity (Arrow B) . In addition, they also create higher levels of nurse withdrawal behavior in terms of higher levels of nurse absenteeism, turnover, and withdrawal from the nursing profession (Arrow C) . Finally, these higher levels of nurse withdrawal behavior also negatively impact nursing performance (Arrow D) . Lower levels of nursing performance then feed back into the internal environment (Arrow E) . In addition, the negative internal work environment feeds back into the external environment in terms of the willingness of young people to enter the nursing profession (Arrow F) .

RESULTS Table 1 summarizes research relating the impacts of the internal work environmental changes (i .e . lower staffing levels) on nurses' attitudes and well-being (i .e . adverse physical and mental health) noted by Arrow A in Fig . l . The 10 studies identified here consist of three qualitative studies, and seven quantitative studies . It appears that the internal work environments have changed over time in many industrialized countries . Nurse job satisfaction, health, job security, communication, morale, promotion opportunities, cohesion, and professionalism have declined while perceptions of work overload, physical and mental exhaustion, stress, burnout, and role conflict have increased .


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Table 2 summarizes literature addressing the impact of nurse staffing and workload on nurses (internal work environment issues) and on nursing performance, and feedback from performance to staffing . All of these connections were addressed in the same table because much of the literature addressed them together, while some connections did not have enough literature to support a separate table . The studies are represented by the three arrows in Fig . I labeled A, B, and E . Relationships between "changes" and "impacts" in "Internal Work Environment" were addressed (Arrow A) . Arrow B, from "Changes in the Internal Work Environments," leads to "Lower Levels of Nursing Performance ." Arrow E, from "Lower Levels of Nursing Performance" leads back to "Internal Work Environment." The 17 studies summarized include nine qualitative studies, one literature review, and seven quantitative studies . Results of these research studies show strong support for the following relationships :

• High or increased patient workloads cause nurses to provide only basic patient care and endanger patient safety . • High or increased patient workloads negatively impact staff well-being and job satisfaction which, in turn, negatively impact the quality of nursing care provided to patients . • Deskilling, or the substitution of less-skilled for more skilled nursing personnel causes increased nurse stress, disruption in work, confusion about roles, lower morale, and reduced quality care . • Heavy workloads and lack of sufficient time to provide a high quality of care and a meaningful nurse-patient relationship is found in most developed countries . • Nurses' subjective evaluation of poor performance causes higher levels of stress and low levels of job satisfaction . Tables 3, 4, and 5 show the relationship between various internal environmental impacts on nurses (i .e . lower job satisfaction, etc .) and on nurse withdrawal behavior (Arrow C in Fig . 1) . Table 3 summarizes six studies that examine the link between those impacts and nurse absence from work (Arrow C) . It appears absence is not strongly related to job satisfaction . However, the most comprehensive study (a meta analysis) by Scott and Taylor (1985) did find a strong negative relationship between job satisfaction and nurse absence . There was also some evidence that higher than average levels of absence precede turnover (Table 5) . Table 4 summarizes the relationship between various internal environmental impacts on nurses and nurse turnover in 13 studies (Arrow C) . Turnover was

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33

significantly related to intent to leave in several studies . The most important internal environmental factors impacting high turnover were lower levels of experience, inadequate salary, inadequate staffing, excessive workload, and work schedule problems . Reasons for leaving the nursing profession (Fottler & Widra, 1995) were quite similar . Table 5 shows a summary of four studies of the stages in the nurse withdrawal process (Arrow C) . It appears there is a progression of withdrawal from lateness to absenteeism to turnover . Although not documented here, it is not unreasonable to assume that higher organizational turnover precedes withdrawal from the nursing profession . We were unable to find studies linking nurse withdrawal behavior to lower levels of nurse performance (Arrow D in Fig. 1) . However, note that the Arrow C between the internal work environment and withdrawal behavior is a twoway arrow . This means that while the internal environmental changes and their impacts cause nurse withdrawal behavior, withdrawal behavior also impacts the internal environment . As noted in Table 2, the internal environmental changes and their impacts do affect nurse performance . Thus, it is not unreasonable to assume that nurse withdrawal behavior does impact nurse performance (Arrow D) . We found one study (not in a table) that documents a relationship between negative internal environment and entry of young people into the nursing profession (Arrow F) . In a recent survey of 700 former and current direct-care RNs, stressful working conditions were the biggest reason to leave nursing . Inadequate staffing, heavy workloads and the increased use of overtime were key areas of job dissatisfaction . 81-87% of the potential leavers said that better staffing ratios and more time with patients would be very effective in recruiting and retaining quality nurses . (a study by the Federation of Nurses and Health Professionals, reported by the U .S . GAO, 2001) .

DISCUSSION Summary and Synthesis of the Literature

The literature reviewed in this article presents some underlying themes . In the articles linking staffing and workload to nurses' attitudes (Table 1), an excessive workload is linked to job dissatisfaction, burnout, stress, and turnover . In the articles examining the connections between nurse staffing and performance (Table 2), the recurring theme is inadequate staffing leading to insufficient time to provide good or even adequate care . Due to the insufficient time, nurses describe an assembly-line quality to nursing care today, and even unsafe

34

LYNN Y. UNRUH AND MYRON D. FOTTLER

practices . Given their workload, there is just not enough time for them to provide quality care . In these articles, work overload also created job dissatisfaction, stress, and burnout, which negatively impacted their care . In a feedback loop, when nurses felt they were giving poor care, they were dissatisfied with their job . Too little time to give good care was a major source of job dissatisfaction In the articles relating nurses' attitudes and absenteeism and turnover (Tables 3 and 4), there were not strong connections . Absenteeism and turnover were more strongly related to intent to leave than job satisfaction, or they were not related to job dissatisfaction at all, in several studies . This result could be due to two reasons : first, workers have many other reasons to be absent from the job, or to leave the job, other than dissatisfaction with the job (they may have personal issues, especially in a workforce employing mostly women) ; second, the study results may have been biased due to endogeneity of job satisfaction . For example, when job satisfaction is related to absenteeism or turnover at the same level as intent to stay, yet intent to stay may be related to job satisfaction, there is an endogeneity or multicolinearity problem that may reduce the significance of the relationship between job satisfaction and absenteeism or turnover. Finally, the articles describing the withdrawal behavior process (Table 5) are interesting for the clear progression of events which management could monitor and alleviate . What is less clear is whether those withdrawing at different stages are the "brightest and best," the worst, or a cross-section of nurses. Putting all the pieces together, it is apparent that all these issues are linked and interdependent . When staffing is inadequate, a vicious cycle develops of stressed and dissatisfied staff, poor performance, withdrawal, indirect impacts of staffing on performance through burnout and withdrawal, feedback impacts of poor performance on dissatisfaction, and so-on . A final note is that the issue of adequate staffing has become an international one . Many of the articles in our search were from other developed countries with varied health care systems . What appears to be happening is that cost-cutting has become endemic world-wide, regardless of the health care system . Developed countries should take note of the similarities of problems associated with nursing staff reductions . Even more noteworthy is an emerging theme in Britain and elsewhere of staff reductions giving way to nursing shortages, just as in the U .S . It is very likely that in these countries (as in the U .S .), the nursing staff reductions of the 1990s significantly contributed to the current shortages through the alienation and withdrawal of nurses from the profession and the repelling of potential new nurses .


35

Implications for Public Policy We show that inadequate staffing and work overload lead to a multitude of employee physical, emotional, behavioral and performance problems . The only way to improve staffing is to provide adequate job positions in work environments that are attractive to current and potential nurses, and to build the supply of nurses available to fill these positions . This will require a set of conditions that could be called the "professionalization" of nursing (Gardner, 1992) . The professionalization of nursing may be addressed through regulation, reimbursement, or both . The Joint Commission on Accreditation of Healthcare Organizations (JCAHO) has recently begun a pilot project to assess the relationship between adequate nurse staffing and clinical outcomes (Lovern, 2001) . By 2002 health care organizations may be required to use JCAHO-prescribed screening indicators to monitor staffing levels to gain accreditation . JCAHO president Dennis O'Leary, MD noted that "all of us believe that there is a link between staffing and safety" (Lovern, 2001, p . 7) . The authors also believe that improving staffing to enhance patient safety will also help to increase the incentives to enter and remain in the nursing profession . The Joint Commission has noted that their intent is to create a system that will reveal staffing problems when they occur, but not to establish "magic ratios" for staffing (Lovern, 2001) . However, Professor Lucian Leape, MD recently said that it is critical that the health care industry establish adequate nurse staffing ratios and predicted these would eventually be regulated . The problem, of course, is that "one size does not fit all ." That is, we do not yet have generally acceptable staffing ratios which measure both quantity and quality of nursing inputs relative to some output which cover widely varying situations regarding patient diagnoses, case severity, other support, etc . Since the number of permutations and combinations is very large, the task is formidable . Even if such ratios existed today, they would tend to be interpreted as maximum rather than minimum standards . Despite such concerns, California is currently attempting to implement nurse staffing regulations under a first-of-its-kind law passed in 1999 . As of January 2002, each of the states' 450 acute care hospitals will have to comply with mandated nurse-patient ratios defined on a unit-by-unit basis . As of this date (December 2001), labor unions and hospitals are meeting in committees to debate what these specific standards should be . Whatever the outcome of these regulatory initiatives, merely requiring health care organizations to meet certain minimum staffing levels will not help them to find the resources to implement these standards . It would also require that

36

LYNN Y . UNRUH AND MYRON D. FOULER

health care facilities price their products and services higher to generate revenue to cover the increased staffing . Since such prices are typically negotiated with third party payers, this means the U .S . Congress would need to provide additional reimbursement for services under Medicare and Medicaid . Private insurers would need to do the same . While there will be resistance to such cost increases, they will be necessary to prevent nurse staffing from deteriorating further in a "vicious spiral to the bottom" where cost concerns drive out all concerns for quality of care . In the future, all health care initiatives should use the following questions as a screen to determine their likely impacts on the nursing profession :

• Will this policy initiative enhance, reduce, or have no effect on incentives for young people to enter the nursing profession? • Will this policy initiative enhance, reduce, or have no effect on incentives for RNs to remain in the profession? • Will this policy initiative enhance, reduce, or have no effect on incentives for inactive RNs to return to the profession? Implications for Healthcare Executives The research reviewed in this paper indicates that nurse performance is impacted by a wide range of factors in the internal work environment . However, inadequate staffing in terms of the quantity and quality of nursing personnel negatively impacts all areas of the internal work environment as well as nurse performance . Reducing staffing ratios alters the quality of nursing care provided to patients because nurses no longer have time to engage in patient education, counseling, etc . Beyond a certain minimum point, even provision of necessary clinical functions may be compromised . Consequently, the assumption held by many health care executives that productivity can be enhanced by reducing nurse staffing is fallacious . The "product" is not the same when staffing is reduced . Taken to its logical extreme, responding to a resource-constrained environment by reducing nurse staffing will create a "vicious spiral to the bottom ." Once "the bottom" is reached, all clinical care (other than physician care) will be provided by underpaid and under-trained nursing assistants who will provide minimal care at best . This scenario has already occurred in long-term care facilities and is likely to occur in acute-care facilities in the absence of managerial or policy changes . Health care executives need to break the "vicious cycle" by addressing the workplace issues that cause nurses to be absent, leave the organization, or leave the profession . Professionalizing the RN role will be necessary if we are to


37

attract more young people to nursing, retain current nurses, and attract inactive nurses back to the profession (Gardner, 1992) . Health care executives can professionalize the nursing role by :

• • • • • • • • • • • • • •

Improving wages and benefits Increasing nurse staffing Encouraging nurses to participate in professional activities Rewarding and supporting additional education Increasing recognition of nurse performance Monitoring nurse attitudes and morale Following up on identified problems Developing the managerial skills of front-line nursing supervisors Improving communication between administration and RNs Encouraging more RN participation in decision-making Supporting nurse career planning and career ladders Tying compensation to education and expertise Providing more part-time and flexible scheduling options Job redesign

Job redesign requires health care executives to better match nurse qualifications to job functions by delegating lower level functions to nurse assistants, retaining higher level functions for which nurses are trained, reducing paper work, computerizing record-keeping, and allowing nurses to perform all functions for which they are qualified . Research Needs

One of the major challenges in synthesizing previous research on nurse staffing is that definitions of nursing staff are not always precise and clearly defined . In some cases, the type of nursing personnel studied is not defined at all or not clearly defined . For example, the term "nurse" may or may not include LPNs and nurse assistants . Other studies may define "nurse" as any type of nursing staff member, but then fail to differentiate the different categories of nurses (i .e . they combine "apples and oranges") . We urge future researchers to clearly define their terms and differentiate nursing staff by skill level . In conducting this review, we found that many more articles speak to pieces of the picture rather than to the whole relationship between nurse staffing and performance . Table 2, which lists studies that relate work environment changes and impacts on nurse performance (representing more of the "whole"), has a total of 17 articles, while the rest of the tables (the "pieces") contain a total of

38


33 articles . On the other hand, those 17 studies addressing the overall connection between staffing and performance often do not examine in sufficient detail the relationship . The problem is, the studies that provide significant detail don't make the linkages and examine the big picture ; alternatively, those that examine the big picture do not provide sufficient detail . Future research should focus on both the entire relationship and on how the pieces fit together . Because of the seriousness of the nursing shortage in exacerbating staffing problems, studies that examine the relationship between work environment and withdrawal from the profession are crucial, as are any studies on factors that might bring young people into the profession or inactive nurses back in . Studies that relate staffing issues to performance reveal the extreme complexity of the relationship, largely because of the intricacies of nursing care and the difficulties in measuring it and relating it to staffing . Two types of research designs appeared to be well-suited for analysis : various types of qualitative studies that describe the details and the complexities of the main relationship and sub-relationships ; and quantitative studies, such as structural equation modeling and path analysis, that utilize complex models and statistical methods capable of drawing out complex relationships among a large set of variables . We see these designs as complementary . Qualitative studies on this subject, such as case studies, are helpful in exploring, in-depth and in detail, the relationships between nurse staffing and performance, but they lack confirmatory power in terms of statistical quantification . Whereas quantitative studies provide statistical probability of the relationships examined, they are limited in depth and complexity, even in their more complex forms . We also note that our study was only the first half of the structureprocess-outcomes equation . Studies connecting nurse performance to clinical outcomes or linking up all three components do not seem to exist . Finally, these studies generally examine negative factors such as inadequate staffing, too high workload, nursing burnout, dissatisfaction or withdrawal, and the negative impacts of many of these factors on performance or other factors . But what is adequate staffing, workload, etc .? Under what conditions? How do we know what will make an improvement over the current situation? Legislators and regulators are looking for some guidelines for setting minimum standards . It is possible that some method such as Data Envelope Analysis (DEA) could be employed to establish ratios under varying conditions of internal and external environments . Cost-benefit analysis, using high quality nursing care and positive patient outcomes for the benefits, is another possibility . Given these issues, we conclude with the following suggestions for future research :


39

• A meta-analysis of the issues, engaging in an exhaustive search of the literature and developing specific research propositions . • Analyses of the impact of nurse staffing and workload on job dissatisfaction, stress, burnout, absenteeism, turnover, etc . • Analyses of the relationship between nursing performance and patient outcomes . • Analyses of the predictability of job dissatisfaction, stress, burnout, absenteeism and turnover in nurses' withdrawal from the profession . • Analyses of the impact of nurse staffing and workload on patient satisfaction . • Analyses of what would induce people to go into or get back into nursing . • Analyses of the relationship between nurse staffing and performance utilizing qualitative and quantitative designs that bring out the details and complexities of the relationships . • Analyses in which structure, process and outcomes are detailed and linked . • Estimations of adequate staffing given performance standards and patient outcomes goals .

CONCLUSION This paper provides a synthesis and overview of the complex research relationships among the constructs of nurse staffing, other aspects of the nurses' internal work environment, nurse withdrawal behavior, and nurse performance . These constructs are interrelated with well-documented empirical relationships for some paths and inadequately-documented relationships for other paths . Previous research has not addressed the "big picture" - a model or entire system that includes all the various constructs and how they relate to each other . This is understandable in light of the complexity of the relationships and the cost and difficulty of conducting large cross-sectional or longitudinal research with large enough samples of nurses to generate valid and reliable conclusions . Most of the studies we reviewed were cross-sectional or case studies and typically explored only one of the path relationships shown in Fig . 1 . The research issues identified above will need to be addressed through large-scale cross-sectional or longitudinal research utilizing structural equation or growthcurve modeling . In addition, there is a place for rich, in-depth case studies that examine the nursing process in light of staffing and other issues . The issue of nurse staffing and its impacts is an extremely significant one for the nursing profession, health care organizations, and public policy in general . If we are unable or unwilling to attract and retain an adequate number and quality of nursing personnel, the quality of patient care available to our

40


society will be in jeopardy . Public policy needs to address the nurse staffing issue by providing resources to adequately fund patient care for the Medicare and Medicaid programs . The nursing profession and academic researchers need to better document the complex relationships outlined in this paper . Finally, health care organizations and their executive leadership teams need to make nurse staffing one of their two or three highest priorities because of its linkage to nurse performance and patient outcomes . Otherwise, our health care system will remain in crisis to the detriment of us all .

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THE BENEFITS OF STAFFING AND PAYING MORE: THE EFFECTS OF STAFFING LEVELS AND WAGE PRACTICES FOR REGISTERED NURSES ON HOSPITALS' AVERAGE LENGTHS OF STAY Mark P . Brown, Michael C . Sturman and Marcia J. Simmering

ABSTRACT With health care costs rising, increased attention has been paid to the human resource practices of hospitals . This chapter examines the effects that staffing levels and wages of registered nurses have on hospitals' average lengths of stay . Based on data from 352 California hospitals, we show that both increased staffing levels and wage rates relate to decreased average lengths of stay. Furthermore, based on our most complete and accurate models, it appears that wage may be more effective for improving the average lengths of stay than would increasing the quantity of RNs . The results of this chapter have a number of implications for human resource practices of RNs and for future research on health care management practices . Advances in Health Care Management, Volume 3, pages 45-57 . Copyright © 2002 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN : 0-7623-0961-X 45

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M . P. BROWN, M. C . STURMAN AND M. J . SIMMERING

INTRODUCTION The precipitous rise in health care costs over the past 20 years has been well documented . Among the factors that contribute to increases in health care costs, those associated with providing hospital care have received considerable attention (Carey, 2000) . Numerous factors are believed to contribute to hospitals' costs (e .g . patient case mix, physician practice patterns, etc .) . Particular attention by both health care managers and the public has been focused on the impact of hospital's labor expenses on their costs, and thus health care costs in general . Moreover, since labor costs represent over 50% of hospitals' total costs, they are of marked importance in understanding the rapid rise in health care costs (American Hospital Association, 1993 ; Langland-Orban, Gapenski & Vogel, 1996) . Two important contributors to hospitals' labor costs are staffing levels and wage practices for registered nurses (RNs) . Staffing levels and wage costs for RNs likely explain a substantial portion of hospitals' total labor expenses . Thus, staffing and compensation practices for RNs seem to be a particularly relevant area of investigation when considering healthcare costs (Melberg, 1997 ; Robertson, Dowd & Hassan, 1997) . Moreover, while RN labor costs have a significant economic effect, the services provided by these RNs affect important indicators of hospitals' operational effectiveness (Melberg, 1997 ; Robertson et al ., 1997) . Specifically, they may influence the efficiency of patient care through their influence on the quality of nursing care (Melberg, 1997 ; Robertson et al ., 1997) . While a positive relation between nursing practices and patient outcomes is largely accepted (e .g . Melberg, 1997), the relationship between RN staffing levels, wage practices, and patient outcomes remains less clear (Melberg, 1997 ; Robertson et al ., 1997) . While some evidence shows that hospitals hiring more RNs have better patient outcomes than those with fewer RNs (e .g . Needleman, Buerhaus, Mattke, Stewart & Zelevinsky, 2001), only anecdotal evidence suggests paying RNs more will lead to better patient outcomes . Staffing levels for RNs affect outcomes by influencing the quantity and quality of care nurses render . Staffing related quality of care decreases have been attributed to numerous factors including the deleterious effect of deficient RN staffing levels on the incidence of nursing mistakes (Aiken, Clarke, Sloane, Sochalski et al ., 2001) . Prevailing arguments assert that RN wages influence patient outcomes by affecting the quality and quantity of RNs that can be hired and retained, and subsequently the quality of patient care (Melberg, 1997 ; Robertson et al ., 1997) . While some attention has been devoted to understanding the relationship between RN staffing levels and hospitals' effectiveness, little empirical attention has been devoted to simultaneously considering the relationship between RN staffing levels . RN wage practices, and hospitals' effectiveness . Thus, because

The Benefits of Staffing and Paying More

47

staffing and wage practices for RNs are important for clinical as well as economic reasons, this manuscript examines the effect of hospitals' staffing and wage levels for RNs on hospitals' operational effectiveness . We ask the following questions : (a) do hospitals that hire more RNs have better outcomes ; (b) do hospitals that pay RNs more have better outcomes ; and (c) what is the relative advantage of greater staffing vs . greater wages? One important indicator of hospitals' operational effectiveness is their average length of stay (Melberg, 1997 ; Robertson et al ., 1997) . Average length of stay (ALOS) is the average time, measured in days, which patients stay in a particular hospital . ALOS has been used as a measure of performance in previous hospital research (e .g . Needleman et al ., 2001 ; Phillips, 1999 ; Sear, 1992) and is often seen as an important measure of both treatment quality and efficiency (Thomas, Guire, & Horvat, 1997) . Typically, hospitals with shorter length of stay are considered to provide better and more efficient care, whereas hospitals with longer lengths of stays are presumed to provide lower quality less efficient care (Thomas et al ., 1997) . Because RNs provide much of the skilled care patients receive in hospitals, their performance has important implications for hospitals' level of care, efficiency, and thus their ALOS (Groshen & Krueger, 1990 ; Melberg, 1997 ; Robertson et al ., 1997 ; Thomas et al ., 1997) . The research reported in this chapter should be useful in several arenas . For the public, it should be useful in clarifying arguments surrounding the impact of human resource practices on hospitals' clinical outcomes . Considerable media attention has been focused on working conditions in hospitals (Aiken et al ., 2001) . Among the most vocal of critics have been RNs (e.g . SEIU, 2002) . Citing wage issues and insufficient staffing levels as paramount among a host of other concerns, RNs have emphasized the implications of these conditions for hospitals' patient care (e .g . SEIU, 2002) . This chapter should give the public some direction regarding the validity of these concerns . For healthcare managers, the manuscript should be useful in clarifying the operational implications of pursuing particular staffing or wage strategies for RNs . In particular, since healthcare managers face competing demands to maintain economic efficiency while sustaining acceptable levels of care, this chapter should be useful in assessing the potential tradeoff between the pursuit of economic efficiency and the objective of providing high quality care .

THE EFFECT OF REGISTERED NURSES' STAFFING LEVELS AND WAGES ON HOSPITAL EFFICIENCY Past research has shown that a hospital's quantity of RNs is associated with greater hospital effectiveness (Needleman et al ., 2001) . The logic behind this,

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M . P. BROWN, M . C . STURMAN AND M . J. SIMMERING

clearly, is that more nurses can provide more and better service to a set of patients . We expect to replicate this finding in this chapter, too . However, as of yet not addressed, is the extent to which greater pay for the same number of nurses may be associated with greater hospital efficiency . Efficiency wage theory suggests three explanations for the positive effects of hospitals' RN wage practices on ALOS . According to the principles of efficiency wage theory, higher wages will : (a) help recruit better qualified and more capable RNs ; (b) cause present RNs to be more efficient ; and (c) engender in RNs a sense of obligation to the hospital, which makes them more efficient . High RN wages should improve employee and organizational efficiency because hospitals that offer high relative wages can attract and retain highly qualified job candidates (Akerlof & Yellen, 1986 ; Campbell, 1993 ; Yellen, 1984 ; Weiss, 1988) . Higher wages also generate larger applicant pools that allow hospitals to be more selective when hiring (Bordeau & Rynes, 1985 ; Raff & Summers, 1987 ; Williams & Dreher, 1992) . Because hospitals that pay more for RNs should be able to hire and retain the most capable applicants (i .e . RNs who are the most efficient and provide the best care), hospitals that pay higher wages should experience both quality of care and efficiency increases (Becker & Huselid, 1998 ; Bordreau & Rynes, 1985 ; Campbell, 1993 ; Hunter & Hunter, 1984 ; Williams & Dreher, 1992) . Thus, the ability to attract and retain more qualified RNs, due to high relative wages, will decrease (i .e . improve) hospitals' ALOS . Efficiency wage theory also suggests that higher wages improve employee and organizational efficiency by decreasing employees' unproductive or shirking behavior (Akerlof & Yellen, 1984 ; Milkovich & Newman, 2002) . These effects may be particularly important when employees' job performance is costly and/or difficult to monitor, which is likely the case with some RNs' positions (Capelli & Chauvin, 1991 ; Rebitzer & Taylor, 1995 ; Walsh, 1999) . Indeed, when wages are high, employees who shirk may suffer personal economic costs from involuntary turnover (Akerlof & Yellen . 1984; Capelli & Chauvin, 1991) . Thus, RNs in hospitals with higher wages may be more efficient and provide higher quality patient care, because, if they lose their job, they may be unable to find similarly high-paying positions . Norm-gift exchange models provide another efficiency wage theory-based explanation for the positive effects of RN wages on hospitals' ALOS (Akerlof, 1982 ; Gerhart & Milkovich, 1992) . Norm-gift exchange models assert that, as a consequence of employee-firm exchanges, employees acquire sentiments for their firms and feel obliged to maintain equity in these exchanges (Akerlof, 1982 ; Cropanzano & Greenberg, 1997 ; Gerhart & Milkovich, 1992 ; Yellen 1984) . Therefore, when inequity occurs in these exchanges, employees seek to


49

return the relationship to a state of equity (Adams, 1963 ; Akerlof, 1982 ; Cropanzano & Greenburg, 1997 ; Festinger, 1954 ; Gerhart & Milkovich, 1992 ; Yellen, 1984). Accordingly, one explanation for the positive influence of greater pay for employees is that it creates a disequilibrium in the employee-firm relationship resulting in increases in employee effort and efficiency (Adams, 1963 ; Akerlof, 1982 ; Copanzano & Greenberg, 1997 ; Festinger, 1954 ; Gerhart & Milkovich, 1992 ; Akerlof, 1982) . Yellen (1984) describes this as firms paying "workers a gift of wages in excess of the minimum required, in return for [workers'] gift of effort above the minimum required" (p . 204) . Thus, RNs in hospitals paying higher wages may make a concerted effort to perform effectively to reward their employing hospitals . This extra effort by these RNs will improve these hospitals' efficiency and quality of care (i .e . decrease ALOS) . To summarize, the quantity and quality of RNs in a hospital should improve the efficiency and quality of patient care . Increases in RNs' efficiency and quality of patient care should increase hospitals' efficiency, thus lowering their ALOS . Like previous research has shown (e .g . Needleman et al ., 2001), we expect this can be achieved by staffing more RNs . We also argue above that this can be achieved by providing greater pay for RNs . Thus, we predict that hospitals with greater wages will have lower (i.e . better) ALOS. We will test this hypothesis below .

METHOD Sample

The sample for this research is 352 short-term stay acute care general hospitals in the state of California . Short-term stay hospitals are defined as those facilities with average lengths of stay less than thirty days (OSHPD, 1991) . Acute care general hospitals are those hospitals that provide a comprehensive range of services as opposed to those hospitals that provide only specialized services such as a psychiatric care (MacEachern, 1962) . Data is drawn from state mandated (i .e . Chapter 1326, California statuses of 1984) annual hospital disclosure reports provided by hospitals to the California Office of Statewide Health Planning and Development (OSHPD) . Annual reports from 1996 to 1999 are used in this research . Dependent Measure

ALOS is calculated by dividing a hospital's total number of patient days by their total discharges (OSHPD, 1991) . Lower ALOS is indicative of organiza-

50

M . P. BROWN, M . C . STURMAN AND M. J. SIMMERING

tional efficiency . Furthermore, some research suggests that ALOS may be a more appropriate indicator of hospitals' treatment quality than other indicators of hospitals' treatment quality (e .g . their mortality rates and their risk adjusted early readmission rates) (Thomas, 1996 ; Thomas et al ., 1997 ; Thomas & Hofer, 1998 ; Thomas & Hofer, 1999) . Poor quality care is associated with higher ALOS because quality of care failures lead to greater patient complications, which in turn lead to higher lengths of stay (Thomas et al ., 1997) . Independent Measure The primary variables of interest in this study are the staffing and wage levels for RNs . Staffing levels were calculated by taking the total number of hours worked by RNs in each hospital . The mean RN hours in our samples of hospitals was 352,712 (median = 229,327 ; SD = 352,202) . This is roughly equivalent to 170 full time equivalents (assuming one full time equivalent works 2080 hours per year) . Because the hours worked variable was heavily skewed, we used the logarithm of its value for subsequent analyses to make the variable better approximate a normal distribution and thus better meet the assumptions of our analytic methods . Average wage levels were reported by each hospital in our sample . The mean RN hourly wage was $25 .48 (median = $24 .99 ; SD = 3 .90) . The distribution of wage levels were approximately normal, so no transformation of the data was necessary . Control Variables We controlled for other variables that could impact the relationship between staffing levels, wage rates and hospitals' ALOS . These variables included whether each hospital was publicly or privately owned and whether the hospitals were either profit or not for profit . Additional variables controlled for included the year in which the data was collected, the percent of patient days in each hospital with a Medicare financial class, differences in each hospital's patient populations using each hospital's case mix index, each hospital's size using a staffed beds measure, each hospital's prior financial performance using prior year return on assets (ROA), and the total number of patient days for each hospital . Procedure A sample of 1,324 pooled cross sections from the previously described longitudinal unbalanced panel data sample of 352 California hospitals was used


51

to test the hypotheses . We investigated the hypotheses using an ordinary least squares model, a least squares dummy variables model, and a random effects model . The average size of the hospitals is 181 staffed beds (SD = 138) . Approximately 56% of the hospitals are private and non-profit, 26% of the hospitals are private and for profit, and 19% of the hospitals are publicly owned . The mean for the ALOS dependent measure is 5 .87 (SD = 3 .57) . The mean for the ROA is 3 .87% (SD = 14 .8) . A correlation table is not presented as correlations among pooled variables are inappropriate and potentially misleading . All variables were entered into the regression models simultaneously . Dummy variables representing each hospital were used in the LSDV analysis . In all other analyses, dummy variables for each of the longitudinal years of data were included to control for unobserved year effects . To better allow causality inferences, compensate for effect lags, and consider policy implications, the hypotheses were tested using a dependent variable at time (t) one time period after the independent variables at time (t-1) (Cook & Campbell, 1979 ; Huselid & Becker, 1996 ; Kerlinger, 1986 ; Rogers & Wright, 1999) . A lag of one year has been used in previous research investigating the performance implications of compensation practices (Gerhart & Milkovich, 1990) . Having a time lag between our dependent and independent variables helps control for the potential that the causal relation might be reversed . For example, the lagged ROA measure controls for the possibility that, rather than hospitals who pay high wages having low ALOS, hospitals that have low ALOS are able to pay high wages due to the efficiency benefits associated with having low ALOS .

RESULTS Table 1 presents the results of the three models investigating the hypotheses that hospitals' RN staffing practices and wage levels are negatively related to hospitals' ALOS . All three models support the study's hypotheses . As shown in each model, greater RN hours were associated with lower (i .e . more efficient) ALOS levels . Similarly, greater wage levels are also associated with lower ALOS levels . While the magnitude of these effects varied somewhat across all three models, they were all at least significant atp < 0 .01 . Thus, these results consistently show that increases in staffing levels and increases in wage levels are both associated with improved hospital efficiency, even after controlling for a wide array of organizational variables . The significance of both staffing and wage effects lead to an immediate practical question : what provides a better return for a hospital : an increase in

52 Table 1 .

M . P. BROWN, M . C . STURMAN AND M . J. SIMMERING The Effects of Hospitals' RN Staffing Levels and Wage Practices on Hospitals' Average Lengths of Stay.

Independent Variables (at t-1) Coefficient Organizational Control Variables

Profit Status Ownership Size (Staffed Beds) In (Total Patient Days) % Medicare Days Case Mix ROA

Independent Variables

In (Total RN Hours) RN Wage Level Overall R squared Adjusted R squared F-value of model

OLS

LSDV

Random Effects

Coefficient

Coefficient

Coefficient

-0 .33 (0 .08)*** -0 .43 (0 .09) *** -0 .000088 (0 .00078) 4 .58 (0.17) *** -5 .03 (0 .43) *** 5 .10 (0.35) *** -0 .14 (0.46)

0.073 (0.11) 0.00051 (0.10) 0.00049 (0.00065) 1 .52 (0.17)* * * -0.75 (0.46) 0.89 (0.41)* -0.46 (0.23)*

0 .081 (0 .096) -0 .16 (0.093) 0 .00010 (0 .00062) 1 .66 (0.16) * ** -1 .29 (0.43)** 1 .36 (0.37)*** -0 .43 (0.23)*

-5 .29 (0 .14)*** -0 .059 (0 .017'***

-0 .70 (0.14)*** -0.046 (0.015)**

-1 .40 (0.13)*** -0 .071 (0 .014)***

0.61 0 .61 164 .84* **

0.98 0.97 119 .60***

0.97 0 .97 114.25 * **

Note : For each model, N = 1262 . All models include dummy variables representing the year of

data. The LSDV model also includes a dummy variable for each hospital . The effects associated with the firm and time variables are not shown. All data is derived from reports using July-June reporting periods except the case mix control variable which is a calendar year measure . p < 0.05 P < 0 .01 p < 0 .001

staffing, or an increase in wages? More specifically, if a hospital had the choice of increasing staffing levels by one full time equivalent (at a cost of 2080 hours at the current wage level), or increasing wages by the same amount (2080 hours times the current wage level divided by the total number of RN hours worked), which would yield the greatest ALOS benefit?


53

To try to answer this question, we used the results of all three models . Using the beta-values from Table 1, we first estimated ALOS for each hospital, but assuming that RN hours were increased by 2080 . Second, we estimated the ALOS for each hospital, assuming that the RN wage level was increased by (2080 * current wage level/total RN hours) . Both estimates were intended to be a result of an equal increase in human resource costs . It should be noted that the estimates may not truly be equal, as we are relying on average staffing levels (we do not know overtime costs), and are not including the costs associated with payroll taxes, benefits, etc . Nonetheless, this monetary equivalent method provides a reasonable estimate of the relative value of increased staffing vs . increased wages . The results of these estimates across all three models are somewhat inconsistent . The estimates for the LSDV and random effects models both suggest that, for most hospitals (96% and 93% respectively for the two models), increases in wages led to a greater improvement in ALOS than an increase by one RN . The OLS model, however, suggested that increased staffing had a more beneficial effect for all hospitals .

DISCUSSION This research investigated the relation between hospitals' RN staffing levels, RN wage practices, and ALOS . Findings support the hypothesized relations that more RNs, and better paid RNs, will be associated with improved (i .e . lower) ALOS . Efficiency wage theory, applied to a health care setting, suggests that high wages beneficially influences RN's efficiency, quality of care, and thus hospitals' ALOS . These findings, while consistent with those from other settings (e .g . Capelli & Chauvin, 1991 ; Lazear, 1979 ; Raff & Summers, 1987), represent a largely unexplored approach to understanding factors that may affect hospitals' ALOS . Specifically, the results show that a human resource practice (i .e . number of RNs and wage practices for RNs), relates to hospitals' performance (i .e . hospitals' ALOS) . Thus, consistent with the tenets of strategic human resource management, this research strongly supports the view that the management of health care staff, through human resource practices, potentially affects hospitals' performance . Our results also show the relative benefit of greater staffing versus greater compensation . Although our results are different for the OLS model in comparison to the LSDV and random effects models, we suggest that data support the view that compensation may play the larger role . The LSDV and

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M . P . BROWN, M . C . STURMAN AND M . J. SIMMERING

random effects models are both more predictive than the OLS model in terms of F-tests and R-squared values, and from a statistical perspective it has been proposed that LSDV and random effects models are superior to OLS models when analyzing pooled cross sections (Sayrs, 1989) . While certainly more research is needed before definitive conclusions can be drawn, our results suggest that if considering the allocation of a limited set of resources, hospitals may be better served increasing RN pay than increasing RN staff . For practice, these results suggest that hospitals' human resource practices likely influence the quality of care hospitals render . In particular, these results suggest the importance of considering RN compensation practices . Specifically, the results provide some support for RNs' arguments that hospitals' compensation practices do affect the standard of care . For healthcare managers, these results indicate that clinical consequences likely result from decisions related to RN compensation practices and that there are negative consequences associated with paying RNs below average wages (i .e . increased ALOS), and positive consequences from paying RNs above average wages (i .e . decreased ALOS) . While cost increases clearly result from hiring more RNs and paying RNs greater wages, the efficiency benefits of lower ALOS should not be discounted . In particular, health care managers should investigate the cost dynamics of their specific institutions and assess the degree to which increased RN labor costs may be offset by the financial benefits associated with efficiency increases due to decreased ALOS . Of course, caution must be used in inferring a causal relationship between hospitals' RN wage practices and hospitals' ALOS . Specifically, as this research is of a cross sectional nature lacking experimental design, the direction of causal relations and the influence of third variables remains unclear (Cook & Campbell, 1979 ; Kerlinger, 1986) . By using a dependent variable from one year later than the independent variables, our results are somewhat more suggestive of a causal relationship . Nonetheless, more in depth research is needed to truly understand the mechanisms through which staffing and compensation practices relate to hospital efficiency and patient care . In particular, our results do directly show how compensation practices are associated with greater efficiency . Our hypothesis is based on the precepts of efficiency theory, and indeed it is supported . However, we do not actually examine the effects of wages on recruiting levels, individual motivation, individual performance, etc . Our results at the hospital-level of analysis are useful, but individual-level analyses will help explain how pay leads to greater efficiency . For example, it is possible that greater pay leads to greater motivation ; or, it is possible that pay is associated with greater RN experience, which is what leads to better ALOS . Our results do provide some useful information


55

for health care management practice, but they also generate a host of new questions meriting further research . Future research should also continue to investigate the effect of other compensation and human resource management practices on hospitals' ALOS . For example, what are the effects of merit pay, bonuses, etc? How does training enhance ALOS? What sort of hiring practices improve efficiency? It would also be valuable to examine other positions in the hospitals . One potential area of investigating is a consideration of hospitals' human resource practices and their effects on employee physicians . Traditionally, physicians have been self employed practitioners . However, recent trends in the healthcare industry have led to some physicians (e .g . hospitalists) becoming hospital employees . In these cases, consideration of human resource management practices' effects on hospitals' ALOS may be particularly relevant . Another interesting area of research might be to investigate the effects of human resource management practices in specific clinical areas on performance measures relevant to these areas . For instance, research could investigate the effect of human resource management practices (e .g . incentive compensation, etc .) designed to improve specific types of care or outcomes (e .g . ALOS for particular diagnosis related groupings) in particular clinical areas .

CONCLUSION This study indicates that the number of nurses on staff, and the pay of those nurses, is significantly related to hospitals' ALOS . Furthermore, our findings suggest that pay may have a greater influence on ALOS than staffing . Our findings are both theoretically and practically important, and future research should continue to explore the link between hospitals' human resource practices and their operational performance .

REFERENCES Adams, J . S . (1963) . Toward an understanding of inequity . Journal of Abnormal and Social Psychology, 67, 422-436 . Aiken, L. A . . Clarke, S. P ., Sloane, D . M ., Sochalski, J . A . et al. (2001) . Nurses' reports of hospital quality of care and working conditions in five countries . Health Affairs, 20 . 43-53 . Akerlof, G . A . (1982) . Labor contracts as partial gift exchange . The Quarterly Journal of Economics . 97,543-569 . Akerlof, G . A ., & Yellen, J . L . (1984) . Efficiency Wage Models of the Labor Market . Cambridge : Cambridge University Press . American Hospital Association (1993) . AHA Hospital Statistics (1992-1993 ed .) . Chicago : American Hospital Association .

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Becker, B . E., & Huselid, M . A . (1998) . High performance work systems and firm performance : A synthesis of research and managerial implications . Research in Personnel and Human Resources Management, 16, 53-101 . Boudreua, J . W ., & Rynes, S . L . (1985). The role of recruitment in staffing utility analysis . Journal of Applied Psychology, 70, 354-366 . Campbell, C . M ., III . (1993) . Do firms pay efficiency wages? Evidence with data at the firm level . Journal of Labor Economics, 11, 442-470 . Cappelli, P ., & Chauvin, K . (1991) . An interplant test of the efficiency wage hypothesis . The Quarterly Journal of Economics, 106, 769-787 . Carey, K. (2000). Hospital cost containment and length of stay : An econometric analysis. Southern Economic Journal, 67, 414-426 . Cook, T . D ., & Campbell, D . T. (1979). Quasi-Experimentation : Design and Analysis for Field Settings . Boston: Houghton Mifflin Company . Cropanzano, R ., & Greenberg, J . (1997) . Progress in organizational justice : Tunneling through the maze . In : C. L . Cooper & I . T . Robertson (Eds), International Review of Industrial and Organizational Psychology: 1997. New York : John Wiley & Sons . Festinger, L . A . (1954) . A theory of social comparison processes . Human Relations, 7, 117-140 . Gerhart, B ., & Milkovich, G . T. (1990) . Organizational differences in managerial compensation and financial performance . Academy of Management Journal, 33, 663-691 . Gerhart, B ., & Milkovich, G . T. (1992). Employee compensation : Research and practice . In : M . D . Dunnette (Ed .), Handbook of Industrial and Organizational Psychology, (Vol . 3, pp . 481-569) . Palo Alto, CA : Consulting Psychologists Press . Hunter, J. E., & Hunter, R. F . (1984) . Validity and alternative predictors of job performance . Psychological Bulletin, 96, 72-98. Kerlinger, F . N . (1986) . Foundations of Behavioral Research (3rd ed .) . Fort Worth : Harcourt Brace College Publishers . Langland-Orban, B ., Gapenski, L . C ., & Vogel, W . B . (1996) . Differences in characteristics of hospitals with sustained high and sustained low profitability . Hospital and Health Services Administration, 41, 385-405 . Lazear, E . P . (1979) . Why is there mandatory retirement . Journal of Political Economy, 87, 1261-1284 . MacEachern, M . T . (1962) . Hospital Organization and Management (3rd ed .) . Berwyn : Physicians' Record Company . Melberg, S . E. (1997) . Effects of changing skill mix . Nursing Management, 28, 47-48 . Milkovich, G. T., & Newman, J . M . (2002) . Compensation . Chicago : Irwin . Needleman, J., Buerhaus, P ., Mattke, S ., Stewart, M., & Zelevinsky, K . (2001) . Nurse Staffing and Patient Outcomes in Hospitals . Boston: Harvard School of Public Health : Final Report for the Health Resources and Services Administration under contract 230-99-0021 . OSHPD (1991). Accounting and Reporting Manual for California Hospitals . Sacremento : Office of Statewide Health Planning and Development . Phillips, J . F. (1999) . Do managerial efficiency and social responsibility drive long-term financial performance of not-for-profit hospitals before acquisition? Journal of Health Care Finance, 25, 67-76 . Raff, D . M. G ., & Summers, L. H . (1987) . Did henry ford pay efficiency wages? Journal of Labor Economics, 5, S57-S86 . Rebitzer, J . B ., & Taylor, L . J . (1995) . Efficiency wages and employment rents : The employersize wage effect in the job market for lawyers . Journal of Labor Economics, 13, 678-707 .


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Robertson, R . H ., Dowd, S . B ., & Hassan, M . (1997). Skill-specific staffing intensity and the cost of hospital care . Health Care Management Review, 22, 61-71 . Rogers, E .W ., & Wright, P . W . (1999) . Measuring organizational performance in strategic human resource management : Looking beyond the lamp post . Center for Advanced Human Resource Studies (Working Paper No . 98-24) . Sayrs, L . W . (1989) . Pooled time series analysis . In : M . S . Lewis-Beck (Ed .) . Quantitative Applications in the Social Sciences (Number 70) . Sage Publications. Sear, A . M . (1992) . Operating characteristics and comparative performance of investor owned multihospital systems . Hospital and Health Services Administration, 37, 403-416 . SEIU (2002) . The Service Employees International Union Nurse Alliance World Wide Web Site (15 April) . www .nursealliance .org : The Service Employees International Union . Thomas, J. W . (1996) . Does risk adjusted readmission rate provide valid information on hospital quality? Inquiry, 33, 258-270 . Thomas, J . W ., Guire, K . E ., & Horvat, G . G . (1997) . Is patient length of stay related to quality of care? Hospital and Health Services Administration, 42, 489-505 . Thomas, J . W ., & Hofer, T . P . (1998) . Research evidence on the validity of risk-adjusted mortality rate as a measure of hospital quality of care, Medical Care Research and Review, 55, 371-404. Thomas, J . W ., & Hofer, T . P . (1999) . Accuracy of risk-adjusted mortality rate as a measure of hospital quality and care. Medical Care, 37, 83-92 . Walsh, F . (1999) . A multiscetor model of efficiency wages . Journal of Labor Economics, 17, 351-376. Weiss, A . (1980) . Job queues and layoffs in labor markets with flexible wages . Journal of Political Economy. 88, 526-538. Williams, M . L ., & Dreher, G . F . (1992) . Compensation system attributes and applicant pool characteristics . Academy of Management Journal, 35, 571-595 . Yellen, J . L . (1984) . Efficiency wage models of unemployment . American Economic Review, 74, 200-205 .

THE IMPACT OF WORKPLACE EMPOWERMENT, ORGANIZATIONAL TRUST ON STAFF NURSES' WORK SATISFACTION AND ORGANIZATIONAL COMMITMENT Heather K. Spence Laschinger, Joan Finegan and Judith Shamian

ABSTRACT A predictive,

nonexperimental design was used to test Kanter's work

empowerment theory in a random sample of 412 Canadian staff nurses . Empowered individuals reported higher affective commitment and work satisfaction. Moreover, empowered employees experienced greater organizational trust, which in turn influenced these job attitudes . Since research has shown that affective commitment is related to productivity, our results suggest that fostering environments that enhance perceptions of empowerment will have positive effects on employees and ultimately, enhance organizational effectiveness .

Advances in Health Care Management, Volume 3, pages 59-85 . © 2002 Published by Elsevier Science Ltd . ISBN : 0-7623-0961-X 59

60

HEATHER K . SPENCE LASCHINGER ET AL .

INTRODUCTION As current organizations restructure and re-engineer in the name of efficiency and effectiveness, trust in management has become an increasingly important element in determining organizational climate, employee performance and commitment to the organization . Employees who have survived downsizing are understandably wary about the future direction of the organization and their roles within it . Cook and Wall (1980) define organizational trust as the extent to which one is willing to ascribe good intentions to, and have confidence in the words and actions of other people . Trust has a significant impact on important organizational factors such as group cohesion (Podsakoff, MacKenzie & Bommer, 1996), perceived fairness of decisions (Korsgaard, Schweiger & Sapienza, 1995), organizational citizenship behavior (McAllister, 1993), job satisfaction (Cook & Wall, 1980 ; Driscoll, 1978 ; Podsakoff et al ., 1996), and organizational effectiveness (Daley, 1991 ; Mishra & Morrisey, 1990) . Mistrust results when information is withheld, resources are allocated inconsistently, and when employees have no support from management . Without trust, people cannot or will not work together except under conditions of stringent control (Whitney, 1994) . Ironically, at a time when trust is most needed for successful organizational transformation, the changes resulting from restructuring have diminished trust within the work setting . This state of affairs has serious implications for organizational performance (Ouchi, 1981) . Nurses, the largest group of health-care providers in hospitals, have been particularly hard hit by recent downsizing . It is quite possible that their mistrust of the system could potentially threaten the quality of patient care . Kanter (1977, 1993) maintains that work environments that provide access to information, resources, support and the opportunity to learn and develop are empowering and enable employees to accomplish their work . As a result, employees are more satisfied with their work and sense that management can be trusted to do whatever is necessary to assure that high quality outcomes are achievable . According to Kanter, employees in environments such as these are more committed to the organization and more likely to engage in positive organizational activities . Kanter's theory provides an explanatory framework for investigating the role of trust in empowering nurses to function effectively in today's dramatically restructured health-care settings . The purpose of this study was to test a model linking staff nurses' workplace empowerment, organizational trust, job satisfaction, and organizational commitment .

The Impact of Workplace Empowerment

61

THEORETICAL FRAMEWORK Kanter's Theory of Organizational Empowerment

Rosabeth Moss Kanter (1977, 1993) argues that people react rationally to the situations in which they find themselves . When situations are structured in such a way that employees feel empowered, the organization is likely to benefit both in terms of the attitudes of employees and the organization's effectiveness . In fact, Kanter argues that the impact of organizational structures on organizational behavior is far greater than the impact of employee personality predispositions . The organizational structures that Kanter believes particularly important to the growth of empowerment are : having access to information, receiving support, having access to resources necessary to do the job, and having the opportunity to learn and grow . Access to these empowering structures is facilitated by formal job characteristics . That is, jobs which are visible and central to the organization's goals and which allow the employee flexibility enhance empowerment . In addition, informal job characteristics such as alliances with superiors, peers and subordinates within the organization further influence empowerment . According to Kanter, the mandate of management is to create conditions for work effectiveness by ensuring employees have access to the information, support, and resources necessary to accomplish work and are provided ongoing opportunities for employee development . Having access to these structures results in increased levels of organizational commitment, feelings of autonomy, and self-efficacy . Consequently, employees are more productive and effective in meeting organizational goals . Relationships among constructs in Kanter's theory are presented in Fig . 1 . Organizational Trust

Trust is increasingly important to organizational relationships, particularly in light of dramatic organizational changes designed to flatten organizational structures and place more decisional control in the hands of front-line employees (Hart, Capps, Cangemi & Caillouet, 1996) . According to Kanter, trust evolves from a mutual understanding based on shared values and is essential for employee loyalty and commitment . Organizational trust is defined by Gilbert and Tang (1998) as the belief that an employer will be straightforward and follow through on commitments . Trust refers to employee faith in organizational leaders and the belief that ultimately organizational actions will prove beneficial for employees . Mishra and Morrissey (1990) argue that open communication, sharing of critical information, sharing of perceptions and feelings, and greater

62

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worker involvement in decisions facilitate trust in organizations . Butler (1991) identified I I conditions of trust : discreetness, availability, competence, consistency, fairness, integrity, loyalty, openness, overall trust, promise fulfillment, and receptivity . Trust must be an integral and coherent part of the organizational culture if change is to be implemented effectively and sustained . According to Johns (1996), empowering employees involves understanding the needs and capabilities of employees, trusting them, and helping them to maximize their fulfillment while pursuing corporate goals . Mutual trust is a critical component of this process . Managers must be willing to empower employees and employees must accept the challenge inherent in empowerment and commit to organizational goals (Davidhizar, 1989) . High levels of organizational trust are needed to accomplish change, yet paradoxically, the change itself may destroy trust and threaten organizational effectiveness . Research on organizational downsizing has shown that decreased levels of trust are associated with decreased communication and increased conflict (Mishra & Spreitzer, 1998) . As hospitals continue to downsize, employee trust and morale are eroded as workloads increase and job insecurity escalates (McNeese-Smith, 1995) . In such low trust organizations, behaviors such as high absenteeism, prolonged breaks, limited learning, low accountability, reactionary thinking, and low creativity are predictably common (Cangemi, Rice & Kowalski, 1989) . Kramer, Brewer, and Hanna (1996) maintain that employees in low power/low status positions depend on others for a variety of critical organizational resources and that uncertainty limits access to information needed to make judgments about trustworthiness . Similarly, Daley (1991) claims that vulnerability and uncertainty are central to the issue of trust and that violations of trust take on greater significance for those in relatively low power/control positions, such as hospital staff nurses . According to Tyler and Degoey (1996), managers play a crucial role in the development of trust since they control the flow of information by either sharing or not sharing key information . The degree of trust within an organization depends on managerial philosophy, organizational actions and structures, and employees' expectations of reciprocity . Gilbert and Tang (1998) found a strong positive relationship between organizational trust and the nature and extent of organizational communication . They suggest that formal, but even more importantly informal, access to organizational communication channels enhance organizational trust . Podsakoff et al . (1996) found that transformational leadership behaviors accounted for 28% of the variance in trust in management .

64


The impact of trust on organizational outcomes has been reported in the organizational literature . Podsakoff et al . (1996) found organizational trust to be significantly related to job satisfaction, organizational commitment, role clarity, and in-role performance . Andrews (1994) linked employee empowerment in a large manufacturing firm to an atmosphere of mutual trust . Mishra and Morrisey (1990) found that 90% of managers surveyed in their study felt that trust starts at the top of an organization and trickles down . Organizational effectiveness was perceived to depend on the level of organizational trust . Trust was associated with effective decision-making as a result of sharing ideas, information, and feelings, organizational credibility, and increased productivity . Organizational ineffectiveness was attributed to employee distrust of management by 79 .4% of those surveyed . Johns (1996) concluded that organizational empowerment and trust have a significant impact on job design, control mechanisms, extent and effectiveness of communication, relationships with other units, degree of innovation, job satisfaction, commitment, organizational citizenship behaviors, goal sharing and crisis management . There is little empirical research in the nursing literature relating to organizational trust . In a survey of staff nurses in a small U .S . hospital, Kramer and Schmalenberg (1993) concluded that trust was the best predictor of feelings of autonomy and empowerment . In another nursing study, McDaniel and Stumpf (1993) found that nurses were more empowered in health-care organizations where information is shared and trust levels are high . Kerfoot (1998) emphasized the importance of leadership behavior in developing and maintaining trust levels in nursing work settings . Finally, anecdotal accounts from nurses reflecting distrust of current management systems are prevalent in today's turbulent nursing work environments .

Nursing Work Satisfaction The study of nursing job satisfaction has focused on both outcomes and antecedents of job satisfaction/dissatisfaction . In a meta-analysis of 48 studies, Blegen (1993) identified 13 predictors of nursing satisfaction . These included personal attribute variables or personality traits such as age, education, years of experience and locus of control, and organizational variables such as supervisor communication, commitment, stress, autonomy, recognition, routinization, peer communication, fairness and professionalism . Organizational variables were more strongly related to job satisfaction, with correlations ranging from highs of -0 .61 and 0 .53 for stress and commitment respectively to a low of 0 .36 for communication with peers . Personal attribute variables had considerably


65

weaker relationships ranging from locus of control (r = -0 .28) to education (r = -0 .070) and professionalism (r = 0 .06) . Irvine and Evans (1995) observed similar findings in their meta-analyses of nursing job satisfaction studies : role conflict (r = -0 .45), head nurse leadership (r = 0 .47), supervisory relations (r = 0 .45), autonomy (r = 0 .43), and stress (r = 0 .33) . Several researchers have found significant relationships between empowerment and job satisfaction of nurses (Laschinger & Havens, 1996 ; Morrison, Jones & Fuller, 1997 ; Radice, 1994 ; Whyte, 1996) . The association between job satisfaction and turnover among nurses is well supported in the literature . Irvine and Evans (1995) found that job satisfaction was strongly related to intention to leave (r = -0 .53) in a meta-analysis of 70 studies . Opportunity to move into another job was a modifier of job satisfaction/turnover intention relationship . Few studies have linked nurse work satisfaction to client outcomes . Weissman and Nathanson (1985) found that job satisfaction of 344 registered nurses employed as primary providers in 77 Maryland family planning clinics predicted patient satisfaction which, in turn, predicted patient compliance with prescribed contraceptives . However, Tarnowski Goodell, and Van Ess Coeling (1994) could find no significant relationships between nurses' job satisfaction, quality of nursing care, and patient satisfaction in an urban Midwestern teaching hospital . Methodological constraints make it difficult to establish the nature and direction of relationships between nurses' job satisfaction and client outcomes . Organizational Commitment Organizational commitment consists of employees' attachments to their organization (Buchanan, 1974 ; Porter, Steers, Mowday & Boulian, 1974 ; Salancik, 1977) . According to Meyer and Allen (1991), there are three types of organizational commitment . Affective commitment is an individual's emotional attachment, identification with, and involvement in a particular organization . Employees with strong affective commitment work in the organization because "they want to" . Continuance commitment reflects an employee's awareness of the costs associated with leaving an organization . Individuals with high continuance commitment believe the benefits of staying with an organization outweigh the consequences of leaving and stay with the organization because "they need to ." This type of commitment is likely to be prevalent in today's downsized work environments . Normative commitment reflects an individual's sense of obligation for remaining in the organization .

66

HEATHER K . SPENCE LASCHINGER ET AL.

Affective commitment has many positive consequences for the organization . It has been found to be positively related to job satisfaction, job involvement, job performance and organizational citizenship behaviour (Allen & Meyer, 1996) . Employees with strong affective commitment contribute more to the accomplishment of organizational goals . They are also less likely to leave the organization . Although employees with high continuance commitment are also less likely to leave the organization, this lower turnover occurs at the expense of employee engagement, job satisfaction, and self-esteem (Sethi, Meinert, King & Sethi, 1996) . Employees with high continuance commitment may be motivated to do the minimal amount of work required to maintain their jobs . Thus, this type of commitment may be counterproductive to the effective accomplishment of organizational goals and objectives (Meyer & Allen, 1997 ; Sethi et al ., 1996) . This claim was corroborated by McCloskey and McCain (1987) who found that nurses who stayed in their positions because of job scarcity reported higher levels of absenteeism and were increasingly more likely to demonstrate poor work performance . Organizational commitment is of particular importance to health-care organizations . Employees in these turbulent environments are struggling to maintain high quality patient care with fewer resources . The empirical evidence suggests that employees with high affective commitment are more likely to rise to the challenges imposed by restructuring while employees with high continuance commitment may simply do the "minimum ." Moreover, Glisson and Durick (1988) found that individuals displaying higher levels of affective commitment were more resistant to job strain and burnout suggesting that affective commitment may help employees withstand the negative effects of downsizing . Clearly, it is important for health-care organizations to promote those factors that encourage affective commitment and to reduce those that encourage continuance commitment . Meyer, Irving and Allen (1998) suggest that work experiences are the strongest predictors of affective commitment . In a meta-analysis of organizational commitment research, Mathieu and Zajac (1990) found that job scope, challenge, and high levels of work autonomy were consistently related to commitment . Bateman and Strasser (1984) found higher levels of affective commitment when exceptional job performance was recognized and rewarded . Opportunity for advancement, perceptions of fairness regarding the distribution of rewards, and workplace autonomy have been found to positively influence staff nurses' organizational commitment (Curry, Wakefield, Price, Mueller & McCloskey, 1985) . These findings are consistent with Kanter's (1977) contention that structural factors of the work environment contribute to an individual's affective


67

commitment to the organization . That said, Meyer, Irving and Allen (1998) note that although such positive experiences contribute to affective commitment, these "same experiences were found to be unrelated, or negatively related, to continuance commitment" (p . 33) . Indeed, a different set of factors is likely to lead to continuance commitment . Meyer, Bobocel and Allen (1991) argued that continuance commitment was related to the perceived availability of alternatives and to the investments that would be lost if the employee left the organization . These arguments suggest that empowerment is more likely to influence affective commitment, and that its relationship with continuance commitment should be minimal at best .

MODEL TO BE TESTED IN THE STUDY This study was designed to test a model derived from Kanter's theory in which staff nurse work empowerment and organizational trust were linked to two organizationally-valued outcomes, work satisfaction and organizational commitment. An indicator of overall work empowerment was derived from measures of formal power, informal power and perceived access to the four empowerment structures (described in the earlier section on Kanter's theory) . Employee empowerment was hypothesized to influence satisfaction and affective commitment in two ways . First, we hypothesized that empowerment would have a direct effect on satisfaction and affective commitment . Empowered employees should report greater job satisfaction and affective commitment than employees who were not empowered . Second, we hypothesized that empowerment would have an indirect effect through perceived organizational trust . That is, empowerment would lead to feelings of trust which in turn would enhance job satisfaction and organizational commitment . As a competitive test of Kanter's theory, we tested the model using continuance commitment as the outcome . Neither empowerment nor trust should predict continuance commitment . Design A nonexperimental predictive survey design was used to test the proposed model . The hypothesized relationships between registered nurses' perceptions of job-related empowerment, organizational trust, work satisfaction and organizational commitment are illustrated in Fig . 2 .

68


Formal Power

Informal Power

Work Satisfaction

Workplace Empowerment

Organizational Trust

Access to

Opportunity Information Support Resources

Organizational Commitment

Fig. 2 .

Overall Model Proposed for Testing .

METHOD Setting and Sample The sampling frame consisted of 300 male and 300 female nurses who worked

in urban tertiary care hospitals . The nurses' names were randomly selected from

the College of Nurses of Ontario registry list . Although there is not commonly agreed upon method for calculating sample size for testing structural equation models, Hoyle (1995) asserts that sample sizes of 200 yield stable results for various fit indices used to determine the degree of fit between the pattern of

relationships in the data and the proposed model. Tanaka (1987) claims that sample sizes between 250 and 500 provide sufficient power to test most models

proposed in social science research . The rationale for sampling equal numbers of males and females was based on the goal of a larger study which was to

determine whether or not the models differed by gender . Since SEM requires sufficiently large subsamples to test the model adequately for each group, males are over-represented in the sample .


69

Strategies suggested by Dillman (1978) to improve return rate were used in an attempt to maximize return . Three mailings were conducted in February and March 1998 . A reminder letter was sent three weeks after the first mailing and a second questionnaire mailed three weeks later . Participants were reimbursed for their time to complete the lengthy questionnaire with a food voucher from a popular coffee shop . Of the original 600 questionnaires, 20 were returned due to change of address and 15 (2 .6%) were returned uncompleted (six males, nine females) . The final sample consisted of 412 useable questionnaires (73% overall return rate) ; 195 males (70 .1 % return rate) and 217 females (75 .6% return rate) . Nurses from all areas of Ontario were represented with the majority working in central Ontario (73%) . Nurses worked either full (58%) or part time (42%) in medical-surgical (36%), critical care (34%), maternal child (9%) and psychiatric (21%) specialty areas . Fifteen percent of the respondents had baccalaureate educational preparation ; most were diploma-prepared (85%) . Respondents averaged 40 years of age, with 16 years of nursing experience and eight years experience in their current workplace . The demographic results are presented in Table 1 . Table 1 .

Gender Male Female Work Status Full-Time Part-Time Education Diploma Degree Specialty Areas Medical-Surgical Critical Care Maternal-Child Psychiatry

Age Years of Nursing Experience Year of Unit Experiences

Demographics . n

%

195 217

47 53

239 173

58 42

350 62

85 15

148 140 37 87

36 34 9 21

Mean

SD

40 .4 15 .6 8 .0

7 .98 8 .30 5 .80

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Data Collection Instruments Five self-report scales were in this study . All employed five-point Likert scales with the exception of organizational commitment which measured responses on a seven-point Likert scale . All scales had acceptable internal consistency with reliabilities ranging from 0 .70 to 0 .93 (see Table 2) . Conditions for Work Effectiveness Questionnaire (CWEQ) - II The CWEQ-II, a modification of the original 35-item CWEQ (Chandler, 1986), was used to measure nurses' perceptions of their access to the four work empowerment structures described by Kanter : access to opportunity, information, support, and resource . These four subscales were each comprised of four items based on a confirmatory factor analysis (Laschinger, 1999) . Items were derived from Kanter's original ethnographic study of work empowerment and modified by Chandler (1986) for use in a nursing population . Mean scores for each subscale were obtained by summing and averaging items . Thus possible scores ranged from one to five with high scores indicating higher perceived access to information, support, resources and/or opportunity . An overall empowerment score was calculated by summing the means of the four subscales (possible range of 4 to 20) . A higher score indicates greater perceived workplace empowerment . Chandler (1986) conducted a factor analysis on the questionnaire items to establish construct validity with a nursing population . The CWEQ has

Table 2.

Summary of Cronbach's Reliability Coefficients for Study Instruments .

Instrument Conditions of Work Effectiveness Questionnaire Subscales Support Information Resources Opportunity Global Empowerment Scale Job Activities Scale Organizational Relationship Scale Trust and Confidence in Management Work Satisfaction Affective Commitment Continuance Commitment

Alpha Coefficients 0 .93 0 .89 0 .80 0 .84 0 .81 0 .81 0 .70 0 .87 0 .84 0 .82 0 .74 0 .75


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been used in previous studies and acceptable internal consistency for each subscale has been established ranging from 0 .73 to 0 .91 for opportunity, 0 .73 to 0 .98 for information, 0 .73 to 0 .92 for support, and 0 .66 to 0 .91 for resources (Laschinger, 1996) . The instrument has been found to discriminate meaningfully among incumbents in various levels of the organizational hierarchy . For instance, senior administrators and physicians scored higher than middle managers who, in turn, scored higher than staff professionals (Laschinger, 1996 ; Kutszcher, Nish, Laschinger & Sabiston, 1997) . Job Activities Scale (JAS)

The JAS (Laschinger, 1996) is a 12-item instrument which measures staff nurses' perceptions of formal power within the work environment . The JAS measures perceptions of job flexibility, discretion, visibility, and recognition within the work environment . Items are summed and averaged to yield a mean score ranging from one to five . Face and content validity of the instrument has been established by a panel of experts . Internal consistency for the JAS scales using Cronbach alpha coefficients has been acceptable with co-efficients ranging from 0 .69 to 0 .79 (Laschinger, 1996) . Organizational Relationships Scale (ORS)

The ORS (Laschinger, 1996) is an 18-item instrument which measures staff nurses' perceptions of informal power within the work environment . Items are designed to measure perceptions of political alliances, sponsor support, peer networking, and subordinate relationships in the work setting . Items were summed and averaged to obtain a mean score ranging from one to five . Content validity was established through pilot testing of the instrument with a convenience sample of registered nurses . Acceptable reliability coefficients, ranging from 0 .83 to 0 .89, have been reported (Laschinger, 1996) . Construct validity of the JAS and ORS has been established in several studies in which they have been found to relate to access to work empowerment structures in ways suggested in Kanter's theory (Govers, 1997 ; Laschinger, Sabiston & Kutszcher, 1997) Interpersonal Trust at Work Scale

This 12-item instrument consists of four subscales which measure faith in the intentions of and confidence in actions of : (1) peers ; and (2) managers . Items are summed and averaged to obtain scores ranging from one to five for each subscale . The scales can be combined or used as separate measures of trust and confidence in management or peers . The reliability coefficients of these measures are reported to be between 0 .70 and 0 .85 (Cook & Wall, 1980) .

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Theoretically, trust in our model has more to do with trust and confidence in management than with trust and confidence in peers . Hence we combined these two subscales to get a measure of organizational trust . Organizational Commitment Questionnaire (OCQ) Two subscales from Meyer, Allen and Smith's (1993) OCQ were used to measure affective and continuance organizational commitment . Each subscale consists of six Likert items that are summed and averaged . Scores ranged from 1 (low commitment) to 7 (high commitment) . Meyer and Allen have reported acceptable reliability across studies (range : 0 .82 to 0 .93) . Demographic Questionnaire Data were collected on respondents' gender, age, years of nursing experience, years on current unit, specialty area, educational level and work status . Data Analysis The hypothesized models were analyzed using structural equation modeling techniques (SEM) contained in the AMOS statistical package (Arbuckle, 1997) . There is little consensus in the SEM literature concerning the best index of overall fit for evaluating structural equation models (Hoyle & Panter, 1995) . Based on Hoyle and Panter's (1995) recommendations, several criteria were used to evaluate fit of the model . These included fit indices such as the Chisquare (X2 ), the Goodness of Fit Index (GFI), the Adjusted Goodness of Fit Index (AGFI) (Joreskog & Sorbom, 1996), and the Root Mean Square Error of Approximation (RMSEA) (Browne & Cudeck, 1989) . The X2 is interpreted as the test of the difference between the hypothesized model and the justidentified version of the model . Low nonsignificant values are desired (Kline, 1998) . However, the X2 is very sensitive to sample size, thus, in a model with a relatively large sample size, the null hypothesis is expected to be rejected almost all of the time . Because of this limitation, the X 2 was used only to evaluate the relative differences in fit among competing models . The GFI indicates the proportion of the observed covariances explained by the modelimplied covariances and is analogous to the R2 in multiple regression . The AGFI adjusts the GFI to taken into account the number of parameters being estimated and is analogous to the shrinkage corrected R 2 (Kline, 1998) . The RMSEA is the standardized summary of the average covariance residuals and is thus a measure of the lack of fit between the data and the model (Kline, 1998) . Low values (between 0 and 0 .06) indicate a good fitting model (Hu & Bentler, 1999) .


73

RESULTS Descriptive Statistics Descriptive statistics for all scales and subscales used in this study are presented in Table 3 . The overall work empowerment score, as measured by the CWEQII, suggests that nurses perceived their work setting to be only moderately empowering (M = 11 .04, SD = 2 .23), a finding similar to what nurses have reported in previous studies (Laschinger, 1996) . The corresponding global empowerment score was also moderate (M = 3 .02, SD = 0 .95) . All CWEQ-II subscale scores averaged around the midpoint of the scale with opportunity being the most empowering factor (M = 2 .98, SD = 0 .66) and perceived access to information, support, and resources slightly lower and of similar magnitude . Nurses in this study did not perceive their jobs to have a high degree of formal power (M = 2 .39, SD = 0.50)), but felt their job had a moderate amount of informal power (M = 3 .59, SD = 0 .64) . These findings also are consistent with results of previous research (Laschinger, 1996) . Table 3 .

Observed Means and Standard Deviations Major Study Variables .

Instrument Conditions of Work Effectiveness (CWEQ) Opportunity Subscales Support Resources Total Empowerment Scale Global Empowerment Scale Job Activities Scale (JAS) Organizational Relationship Scale (ORS) Interpersonal Trust at Work Scale Trust in Peers Confidence in Peers Trust in Management Confidence in Management Satisfaction Organizational Commitment Questionnaire" Affective Continuance Range 1-5 Range 4-20 Range 1-7

Mean

SD

2 .98 2 .67 2 .68 2 .70 11 .04 3 .02 2 .39 3 .59

066 . 0 .74 0 .72 0 .61 2 .23 0 .95 0 .50 0 .64

3 .79 3 .77 2 .66 2 .59 2 .78

0 .73 0 .81 0 .89 0 .88 0 .90

3 .77 4 .38

1 .16 1 .25

74

HEATHER K . SPENCE LASCHINGER ET AL . As Table 3 shows, nurses reported higher confidence and trust in their peers

(M = 3 .79, SD = 0 .73 ; M = 3 .77, SD = 0 .81) than in management (M = 2 .66, SD = 0 .89 ; M = 2 .59, SD = 0 .88) . Nurses in this study were not very satisfied with their jobs (M = 2 .78, SD = 0 .90 on a 5-point scale, 60% of sample below 3 .0) .

Nurses' continuance commitment was higher than their affective commitment (M = 4 .3 8, SD = 1 .25 vs . M = 3 .77 SD = 1 .16 respectively) . Testing the Model

The model proposed in this study, specifying causal links derived from Kanter's theory between employee empowerment, organizational trust, and perceptions of work satisfaction and organizational commitment, was tested using structural equation modeling (SEM) procedures with maximum likelihood estimation . Separate models were run for each of the organizational outcome measures (satisfaction, affective and continuance commitment) . SEM procedures were used in this study because this approach permits modeling of latent constructs, simultaneous estimation of all hypothesized paths and estimation of indirect effects (Hoyle, 1995) . The first statistical model tested (with job satisfaction as the outcome variable) consisted of 15 variances and covariances, 12 free parameters and 3 degrees of freedom . In accordance with our theoretical paradigm, formal power, informal power, and perceived access to work empowerment structures were modelled as indicators of the latent variable "overall empowerment ." An analysis of the reproduced covariance matrix of the variables in the proposed structural model revealed a reasonably good fit according to standards recommended by Bender and Bonett (1980) and Browne and Cudeck (1989) (X'- = 13 .8, GFI = 0 .987, AGFI = 0.934, RMSEA = 0 .095) . The interrelationships among these variables suggested that access to empowerment structures was the strongest contributor to this construct . The standardized path coefficients for the final model are presented in Fig . 3 . As hypothesized, empowerment had both a direct and indirect effect on job satisfaction . First, higher levels of empowerment were associated with increased satisfaction ((3 = 0.46) (direct effect) . Second, empowerment also influenced work satisfaction indirectly through trust in management (0 .141) . The amount of explained variance in the final model was 40% . When the model was tested using affective organizational commitment as the outcome variable, the data fit the proposed model reasonably well (X2 = 23 .6, GFI = 0 .98, AGFI = 0 .89, RMSEA = 0 .13) and the amount of variance accounted for was R 2 =28% . The pattern of relationships among the indicators to the latent variable of empowerment was similar to the satisfaction model .


75

Formal Power

0 .44

Informal Power

Access to Opportunity Information Support Reso urces

09' )

0 .25

J

R2 = 0 .40 GFI = 0 .987 AGFI = 0.934 RMSEA = 0 .095

Fig . 3 .

Satisfaction

Empowerment, Trust, Satisfaction Model .

As predicted, empowerment had a direct effect on affective commitment (0 .31),

as well as an indirect effect through its impact on trust in management (0 .16) .

The indirect path from empowerment through trust to commitment suggests that nurses' affective commitment is also mediated by the extent of their trust in

management . Since managers who create empowering work environments are

more likely to be trusted, this is not surprising . The standardized path coefficients are illustrated in Fig . 4 .

Consistent with theoretical expectations, employee empowerment and trust

in management were not strong predictors of continuance commitment . Although the data was a reasonably good fit for the model (X'- = 9 .3, GFI =

0 .99, AGFI = 0 .952, RMSEA = 0 .071), only 4% of the variance in continuance

commitment was explained by empowerment and trust in management . The

empowerment/continuance commitment path was weak and non-significant ( 3 = -0 .04) . However, empowerment was strongly associated with trust ((3 = 0 .51), and trust in turn was significantly and negatively associated with continuance

commitment ((3 = -0 .18) . This suggests that the impact of work conditions on

76

HEATHER K. SPENCE LASCHINGER ET AL .

R2 = 0 .04 GFI = 0 .99 AGFI = 0 .952 RMSEA = 0 .076 Fig . 4.

Empowerment, Trust, Affective Commitment Model .

continuance commitment is almost totally mediated by trust in management . These data support the assertion that other factors not measured in this study (e .g . security needs, availability of work alternatives) are more relevant predictors of continuance commitment . That said, it still found a significant negative relationship between trust and continuance commitment . The standardized path coefficients are illustrated in Fig . 5 . To better understand how specific aspects of empowerment related to the major study variables, the intercorrelations were examined (see Table 4) . All correlations between trust in management, satisfaction and affective commitment and the empowerment variables were significant with the strongest associations between these variables and formal power and access to empowerment structures . Correlations between continuance commitment and empowerment were low and nonsignificant . As expected, affective and continuance commitment were not significantly related to each other.

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Formal Power

Informal Power

0 .52

0 .41

Access to Opportunity Information Support Resources

Workplace Empowerment

0 .51

h

Trust

0.99 -0.18

R2 = 0.04 GFI = 0 .99 AGFI = 0 .952 RMSEA = 0 .076 Fig . 5.

Empowerment, Trust, Continuance Commitment Model .

Table 4.

*Total Empowerment Opportunity Information Support Resources Formal Power Informal Power Affective Commitment Continuance Commitment Work Satisfaction * Total Scale.

Intercorrelations Among Major Study Variables . Trust and Confidence in Management

Work Satisfaction

Affective Commitment

Continuance Commitment

0.54 0.33 0.49 0 .46 0 .33 0 .36 0 .13 0.46 -0.21 0.52

0 .56 0 .40 0 .36 0.50 0 .39 0 .41 0 .30 0 .60 -0 .03 -

0 .40 0 .32 0 .29 0 .38 0 .18 0 .38 0 .24

-0 .18 -0 .10 0 .13 -0 .21 0 .11 0 .11 -0 .06 -0 .04

0 .04 0 .61

0 .03


78

DISCUSSION The results of this study support the proposition that staff nurse empowerment

impacts on their trust in management and ultimately influences job satisfaction

and affective commitment . More specifically, staff nurses in this study felt that

their sense of workplace empowerment strongly affected their trust in

management, satisfaction with their workplace, their belief and acceptance of organizational goals and values, their willingness to exert effort in the workplace

and desire to stay in the organization (affective commitment) . These findings

highlight the importance of creating environments which provide access to structures that empower nurses to accomplish their work .

An examination of the relationships between the empowerment subscales and

trust provides insight into dynamics by which the model operates . The strongest

relationships were found between trust in management and nurses' perceived

access to information and support . The relationship between access to

information and trust is consistent with Hart et al . (1996) findings linking trust to the willingness of managers to share accurate information in a timely fashion . When this does not happen, the perception may develop that information is being hidden . At this point, the grapevine takes over . As speculation grows as to why information is not provided, feelings of safety and comfort in the

manager/staff relationship deteriorate and trust in management is destroyed . Similarly, the fact that access to support and trust were strongly related suggests

that when staff nurses are provided with helpful feedback and guidance from managers and given the flexibility to use their judgment and make discretionary

decisions, their trust in management increases . Assuming responsibility for these

actions entails a risk on the part of staff nurses . Since trust is defined as the willingness to take risks and to be vulnerable to the action of others based on

the assumption that the other will act in a manner beneficial to the trustor (Johnson-George & Swap, 1982), support from managers that leads to successful

decision-making or damage control for mistakes benefits the trustor and fosters trust in management.

The relationships between trust in management and access to resources and

opportunity were somewhat lower but significant . According to Gambetta

(1988), trusting another individual is based on the assumption that the other will act in a manner that is beneficial to the trustor, and this assumption leads

to a willingness to engage in a cooperative effort . Staff nurses and their managers must cooperate to provide care for clients . Staff nurses are responsible

for providing expertise in patient care and managers are responsible for furnishing the resources to facilitate this care . If managers cannot provide these resources due to staff shortages, fiscal restraint, breakdown of aging equipment,


79

or inadequate supplies, staff nurses may not be able to keep their side of the agreement . A weaker relationship was found between trust in management and access to opportunities to develop or advance to better jobs . Since promotion rates are largely controlled by unions in Ontario and not under the control of managers, this is not surprising . In addition, with the current cutbacks in hospital funding educational opportunities for staff have been slashed . For the few that remain, the increased workload of the reduced nursing workforce makes it virtually impossible for nurses to leave their units to attend classes . Ultimately, this may lead to negative patient care outcomes since nurses may not be able to upgrade their knowledge through continuing education . The significant effects of access to work empowerment structures on staff nurses' perceptions of trust in management is consistent with expectations of Kanter's theory and the findings of other research linking trust to open communication and information sharing, increased employee decisional involvement, and supportive leadership practices (Laschinger & Havens, 1996 ; Laschinger, Wong, McMahon & Kaufmann, 1999 ; Sabiston & Laschinger, 1995) . When staff feel they have sufficient access to support, resources, and information to get their work done, they are more likely to have faith in their managers and feel that organizational policies are intended to benefit employees . Consequently, they will be satisfied with their work and more committed to accomplishing organizational goals . Continuance commitment was only weakly related to empowerment (r = -0 .18) and trust in management (r = -0 .21) . These findings were expected given no logical or theoretical reason for strong relationships to exist . The low but significant negative correlation between continuance commitment and trust in management is reasonable since high continuance commitment individuals are often disillusioned with management and remain in the organization due to seniority and under protection of union policies . That said, the results found with respect to empowerment are consistent with Kanter's theory . That is, while Kanter's theory would predict that empowerment could predict affective commitment and job satisfaction, it really does not speak to continuance commitment . Thus, these findings provide evidence for both convergent and divergent validity of Kanter's theory .

LIMITATIONS The findings of this study must be viewed with caution given the cross-sectional nature of the design . Although the sample was representative of nurses in the province with respect to age, experience and level of education, there were

80


equal proportions of males and females which is not representative of the nursing work force . To determine whether or not this may have biased the results, the models were run on a proportionate stratified random subsample representative of the gender proportions of nursing in Ontario (88% female, 12% male) . The resulting models did not differ significantly ; they each explained similar amounts of variance and produced very similar patterns of relationships among variables thereby ruling out this source of bias .

FUTURE RESEARCH The results of the present study are consistent with Kanter's view that the "structure of empowerment" has an impact on employees . As mentioned above, because the research is cross-sectional, strong cause-and-effect statements cannot be made . That said, the data are sufficiently strong to suggest that the model should be tested in an intervention study where the conditions under which nurses work are actually changed to be more empowering . The nurses' attitudes and behaviours could then be compared to a control group that did not receive the intervention . If the attitudes and behaviour of the empowered group were better than the control group, then we can be quite confident that the changes in structure were responsible for the positive changes . In addition to an intervention study, another exciting research possibility would be to conduct a longitudinal study in which recent graduates of nursing schools are tracked for several years after graduation and their experiences with empowerment and subsequent reactions are examined . One question that future research could address is whether or not empowerment generalizes across different types of personality . According to Kanter, personality should not play a role in empowerment - all employees should benefit from empowerment. Yet, one could argue that at least some personality dimensions might be affected differentially by empowerment . For example, empowerment may be particularly important to people with a high need for achievement since it actually provides the conditions in which these people can succeed . Thus, people high in the need for achievement should benefit most when empowerment structures are provided and be disadvantaged when they are not provided . Since a person low in the need for achievement by definition is not motivated to achieve, they may not find that their behaviour is affected as greatly by the presence or absence of empowerment structures . Finally most of the research on Kanter's model have been conducted within the nursing profession . Future research could look at the impact of empowerment on other work and nonwork groups .


81

CONCLUSIONS AND IMPLICATIONS FOR NURSING ADMINISTRATORS Support for the model proposed in this study provides encouraging guidance for health care leaders interested in creating high trust work environments that benefit both nurses and ultimately the clients they care for . The creation of work environments that encourage professional nursing practice by empowering nurses to act on their expert judgment is an essential strategy for fostering trust within organizations . Moreover, both trust and empowerment will lead to increased nurse satisfaction and affective commitment ultimately ensuring high quality patient care . Although Kanter's empowerment structures provide a guide for creating effective work environments, this approach will require a transformation in the role of management . Managers traditionally have managed through control . Kanter's approach will require managers to focus less on control and more on the coordination, integration and facilitation of nurses' work . As restructured nursing work environments recover from the impact of repeated downsizing, managers must seek ways to regain the trust of employees by assuring structures are in place to allow accomplishment of meaningful goals . Both nurses and nurse managers must be willing to work together to develop a climate of mutual trust that fosters work satisfaction and genuine commitment to organizational goals to provide high quality client care .

ACKNOWLEDGMENT Funded by Social Science Humanities Research Council Extramural Grants Program #410-93-0611 .

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MANAGING ROUTINE EXCEPTIONS A MODEL OF NURSE PROBLEM SOLVING BEHAVIOR Anita L. Tucker and Amy C . Edmondson ABSTRACT This paper investigates how hospital work environments and manager behavior influence nurses' responses when faced with unexpected problems, or exceptions . Data from a qualitative study involving 239 hours of observation of 26 hospital nurses at nine hospitals suggest that exceptions occur frequently and that the work design of hospital nurses leads them to respond to exceptions through first-order problem solving, addressing only immediate symptoms without attempting to alter underlying causes . This pattern of behavior contrasts with recommended approaches found in the quality improvement literature (Ackoff, 1978 ; Deming, 1986 ; Juran, Godfrey, Hoogstoel & Schilling, 1999; Kepner & Tregoe, 1976) . An implication of our findings is that health care managers may need to tailor front line quality improvement processes to meet the demands of the health care delivery environment - in which exceptions are so frequent as to be considered virtually routine - rather than expecting health care workers to engage in quality improvement practices developed for work environments with different characteristics . Building on empirical observations from our study, we draw from two literatures - healthcare management

Advances in Health Care Management, Volume 3, pages 87-113 . Copyright © 2002 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN : 0-7623-0961-X 97

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ANITA L. TUCKER AND AMY C . EDMONDSON and organizational behavior - to develop a model of problem solving behavior by hospital nurses . The model proposes that nurse manager coaching, support, and proficiency, together with features of the organizational context - training, self management, work design, group norms, and reward interdependence - influence nurses' problem solving behavior through the mediating variable of nurse cognition (psychological safety and motivation) . The use of a problem solving coordinator moderates the problem-solving behavior's impact on performance outcomes .

INTRODUCTION Most health care managers are cognizant of the benefits that can be gained by methodically finding and removing system problems that impede worker performance (Carman, Shortell, Foster & Hughes, 1996), as evidenced by the large number of health care organizations that implement formal improvement programs (Barsness et al ., 1993) . Indeed, continuous improvement has been a key theme in health care since the mid-1980s . Interest accelerated in the early 1990s when the Joint Commission on Accreditation in Healthcare Organizations (JCAHO) made hospital-wide diffusion of learning from failures a factor in accreditation (Adler, Kwon & Signer, 2001 ; Huq & Martin, 2000 ; Levin, 2001 ; Shortell, O'Brien, Carman & Foster, 1995) . A primary feature of their interest is a focus on work systems rather than on individual performance . For instance, research on medical error shows faulty work systems, rather than incompetent or irresponsible individuals, can be implicated in most adverse drug events (Bates et al ., 1995 ; Leape et al., 1995) . Error researchers are encouraging a change in norms in health care from blaming individuals involved in a particular accident to searching for and removing work system failures . Leading thinkers in health care management (Berwick, 1991 ; Laffel & Blumenthal, 1989) have advocated a systematic approach to improving hospital work, often through the use of quality tools developed for industrial settings (Deming, 1986 ; Ishikawa, 1985 ; Juran, Godfrey, Hoogstoel & Schilling, 1999) . Researchers have found that a learning oriented organizational culture (Carman, Shortell, Foster & Hughes, 1996 ; Huq & Martin, 2000 ; Shortell, O'Brien, Carman & Foster, 1995) ; decentralized, flexible implementation (Douglas & Judge, 2001 ; Shortell, O'Brien, Carman & Foster 1995) ; training (Huq & Martin, 2000), and physician participation (Carman, Shortell, Foster & Hughes, 1996) are critical for successful implementation of quality programs . Unfortunately, even with explicit training, many such programs have proven difficult to sustain in healthcare organizations, leaving considerable variation in implementation

Managing Routine Exceptions

89

success (Douglas & Judge, 2001 ; Huq & Martin, 2000 ; Levin, 2001 ; Westphal, Gulati & Shortell, 1997) . Researchers have speculated as to why, in general, quality improvement efforts in healthcare organizations fail (Douglas & Judge, 2001 ; Levin, 2001 ; Victor, Boynton & Stephens-Jahng, 2000 ; Westphal et al ., 1997) . One reason offered is that many of these continuous improvement techniques are normative in nature and difficult to use in the hectic front line environment (Hackman & Wageman, 1995 ; Victor, Boynton & Stephens-Jahng, 2000 ; Zbaracki, 1998) . Further, few healthcare researchers have offered new tools tailored to the healthcare setting or concrete steps for accomplishing system improvement (Arndt & Bigelow, 1995) . Therefore, although continuous improvement is desirable, much remains unknown about how to successfully implement it on the front lines of healthcare . The purpose of this paper is to consider how work environment and manager behavior influence front line health care workers' responses when faced with problems . Rather than studying why continuous improvement programs such as Total Quality Management (TQM) fail, we instead sought to understand the health care delivery work environment and to investigate what caregivers actually do - in the absence of a formal quality initiative - when they encounter problems that compromise their work . By understanding how the work environment influences front line workers' natural response to problems, we hope to develop recommendations for enhancing the success of quality improvement efforts . Problems, or exceptions, signal improvement opportunities (Imai, 1986) because removing underlying causes should improve organizational effectiveness by preventing or reducing future occurrences of similar problems . We define an exception as a failure in the design or execution of the work system . The work system includes individuals' work activities, supply and communication channels, and training (Spear & Bowen, 1999) . Exceptions are similar to, but more narrowly defined than, situational constraints which are features of work that obstruct the translation of abilities and motivation into performance (Peters & O'Connor, 1980, p . 391) and are also similar to chronic problemsdaily problems that arise from the current work system design (Juran & Gyrna, 1980 ; Leonard & Miller, 1989) . We first describe our methods . We then introduce the concept of secondorder problem solving behavior, which we define as actions that attempt to remove underlying causes of problems . Third, drawing from our observational data, we develop propositions about conditions under which nurses are more likely to engage in second-order problem solving behavior . Specifically, we suggest that having a supportive nurse manager, assistance for problem solving,

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ANITA L . TUCKER AND AMY C. EDMONDSON Mechanisms for organizational improvement Worker Cognition

Nurse Manager Behaviour

Psychological Safety

Enabling behaviour Proficiency

Motivation - Feasibility - Anticipated Benefit

Organizational context

Training Reward Interdependence Self Manage lent

Problem solving coordinator Degree of 2nd order Problem Solving Behaviour Communication Effort to remove Root Causes Experimentation

Outcomes Quality of care Frequency of problems

Group Design Workload Group norms

Fig . 1 .

Model of Hospital Nurse Problem Solving .

Black type variables are suggested by our observations . Italic type variables are suggested by literature .

effective communication between groups, and a workload that allows time to engage in root cause problem solving behavior will create an environment where

nurses believe that it is worth the effort to attempt root cause removal . To develop these propositions into a formal model, we draw from relevant

literatures - health care management and organizational behavior - to identify

similar constructs examined by other researchers . Additional organizational context factors that emerge from the literature are training, self-management,

and reward interdependence . These variables collectively shape worker motivation and psychological safety, which in turn influence actual problem

solving behavior, suggesting a theoretical model, shown in Fig . 1 . We then discus implications of our model for theory and practice related to quality improvement in healthcare .

METHODS We conducted ethnographic research using methods similar to other researchers

interested in understanding organizational cognition and behavior (Edmondson, 1999 ; Spear & Bowen, 1999 ; Uzzi, 1997) . We chose to study hospital nurses


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because their work environment provided a context where exceptions were likely to occur because of their high task interdependence (McCloskey, Bulechek, Moorhead & Daly, 1996) . In fact, we found that exceptions were virtually routine . Moreover, these exceptions often could have a negative impact on patient safety (Tillman, Salyer, Corley & Mark, 1997), and therefore were worthy of solution . The first author, who does not have a medical background and was naive to both nursing and organizational behavior literature during the observation period, spent 239 hours shadowing 26 registered nurses at nine different hospitals in the United States and Canada . After the observation data collection period was complete, she reviewed relevant literature and conducted semi-structured interviews with thirteen nurses from seven of the hospitals . The interview protocol was designed to gather additional data on nurse cognition . We selected hospitals that varied in size (community and tertiary), location (rural and metropolitan), work force (union and non-union) and type (academic and non-academic) to insure variation . They were located in Massachusetts, Rhode Island, Minnesota, Utah, and Ontario, Canada . We purposely biased our sample towards excellence by asking industry experts for references to hospitals with "excellent nursing care ." Our goal was to find hospital units where second-order problem solving was more likely to be prevalent, to understand the conditions that enabled this behavior. We shadowed registered nurses, at least four of whom had advanced degrees . They were from a variety of units including intensive care units, maternity, pediatrics, emergency rooms, medical/surgical wards, and hematology/oncology . All units used a primary nursing model . Observations included night and weekend shifts to ensure accurate representation of the work environment . Observations ranged from two hours to thirteen hours in duration, with ten being full-shift observations with minute-by-minute recording of nurses' activities . These data were coded using an iterative, grounded theory approach (Strauss & Corbin, 1998) to develop a database of 226 exceptions and nurse response to these . Interrater reliability between the first author and an independent rater for exceptions (Kappa = 0 .81) and response type (Kappa = 0 .88) indicated substantial agreement (Landis & Koch, 1977) .

TOWARD A MODEL OF FRONT LINE PROBLEM SOLVING BEHAVIOR The nurses we shadowed faced an average of one problem per hour . Nurses viewed problems as an inevitable part of nursing . Megan from Hospital 3 commented that exceptions on her floor were routine : It is frustrating because I don't know why there can't be one day where the floor runs smoothly . Why can't the catastrophe day be unusual?

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ANITA L. TUCKER AND AMY C . EDMONDSON

The reality of routine exceptions contributes to the difficulty of engaging in second-order problem solving because dealing with exceptions becomes part of an organization's ongoing activity, creating organizational routines that reinforce the status quo (Levitt & March, 1988 ; Nelson & Winter, 1982) . Research has shown that even when faced with signals that change is needed, task-performing groups tend to adhere to routines (Gersick & Hackman, 1990; McGrath, Kelly & Machatka, 1984) . We build on this line of thinking to argue that organizational routines - rather than sporadic individual effort - for problem solving are essential for workers to develop capabilities in second-order problem solving . In fact, we observed little difference between individual nurses' desire or ability to improve the systems in which they worked, but instead identified differences in how well nurses' environments supported improvement activities by providing psychological safety for drawing attention to mistakes, communication channels for talking about difficulties, and resources to tackle cross-boundary problems . Our data thus suggest that, unless there was a supportive environment, exceptions were simply hurdles that had to be jumped over - to finish the daily course of patient care tasks - rather than improvement opportunities . As described below, the findings from our empirical study form the core of our proposed model of front line problem solving . We then turn to the literature to enhance the model with relevant additional constructs and relationships . First and Second-order Problem Solving Behavior We observed nurses engage in two types of problem solving behavior when faced with exceptions . Drawing from research on organizational learning (Argyris & Schon, 1978), we call these first-order and second-order problem solving, respectively . First-order problem solving attempts to remedy the immediate problem but does not try to change underlying conditions that created it ; second-order problem solving, in addition to remedying the immediate problem, attempts to change the system so that it does not reappear . In the health care delivery context, second-order problem solving is manifested by communication, root cause removal, and experimentation . A similar distinction has been made between reactive control and preventive control (Hayes, Wheelwright & Clark, 1988), routine action and learning action (Marcellus & Dada, 1991), and single loop and double loop learning (Argyris & Schon, 1978) . The first component of second-order problem solving is communicating about exceptions to people positioned to address underlying causes . Given the choice of only solving a situation on their own or also communicating to the source about it, nurses often chose to fix it themselves . For example, we observed nurses


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take linens and medical supplies from other units when their own supplies ran short instead of contacting central supplies . A second aspect of second-order

problem solving is effort to find and remove underlying causes of problems . For example, two nurses did not know how to operate a piece of equipment, which resulted in a requested pain medication being delayed by forty minutes for a post-

surgical patient . The nurses resolved the underlying problem of their lack of knowledge by practicing on a spare piece of equipment during a lull in the night's

activities . The third component of second order problem solving behavior is

experimentation, which involves structured trial and error episodes to test whether a potential solution produces the desired outcome (Lee, Edmondson,

Thomke & Worline, 2001) . Although we did not directly observe any experimentation to resolve exceptions, in hospital units characterized by second-order problem solving, we heard stories that indicated people had experimented with

different ways of using certain equipment, such as beepers . For example, nurses at Hospital 2 were equipped with beepers, which the secretary used to send them

coded messages that relayed basic information . For example 204-2 meant that the patient in room 204 requested pain medication . A nurse explained how this unique communication system had evolved .

We started out with beepers where you could type in messages . However, we found that by the time you typed in all the information, it was too late . So we switched to these cheaper beepers and started using codes . We assert that problem response is driven by organization factors and manage-

rial behavior rather than by individual differences . For example, Peggy,' a surgical nurse at Hospital 4, responded to a missing medication using first-order problem solving behavior . After she found what seemed to be a transcription error in the medication order, she tried to solve the situation on her own by

telling pharmacy that she needed 180 mg of Cartia - the dosage the patient's chart indicated had been ordered previously - without contacting the doctor to

let him know of his mistake . Only when she had no other choice but to call

him to change the order to a different medication (because she was later told the pharmacy did not carry Cartia), did the physician learn that there was a problem with his order .

This is not to say that Peggy was an ineffective nurse . She was highly

regarded by her peers and managers alike for her excellent nursing skills and motivation to improve her work environment . In fact, she had initiated several improvement projects for her unit and was pursuing additional education,

completing a nurse practitioner degree . However, Peggy was caught in a system that did not support second-order problem solving . First, she did not feel safe contacting the doctor about his mistake ; second, the nurse manager was not a

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ANITA L . TUCKER AND AMY C . EDMONDSON

visible presence on the floor and there was no resource person to help deal with complex issues . Third, nurses in this hospital had heavy patient loads and, fourth, lacked training on problem solving . There were no incentives for working together for the good of the patient, and little evidence of experimentation . Therefore, it is not surprising that Peggy would respond to the missing Cartia using first-order problem solving, later expressing frustration with how difficult it was to make changes, or to get other departments to respond to requests for help, or even to get nurses to take responsibility for improving their own work environment . Everyone is thinking of himself or herself . It is hard to get people to see beyond the fact that maybe they don't need the benefits from a new procedure or policy, but someone else, like the patient or a less experienced nurse, might . People need to be proactive, but I don't think you are going to see it .

Overall, we identified three other units in which nurses primarily used firstorder problem solving behavior, the oncology unit at Hospital 5, the regular ICU at Hospital 9 (designated as 9 .1 in Table 1), and the medical/surgical unit at Hospital 3 . For all of these units, the nurse manager was not present, and no resource person existed to assist nurses . In contrast, Mallory, a pediatric oncology nurse at Hospital 8, used secondorder problem solving when an ICU nurse mistakenly allowed a transfer patient to remain on his ICU bed when he should have been moved onto an oncology floor bed. Mallory communicated both to the ICU and to the charge nurse, with the intention of preventing the situation from recurring . At the same time, our data suggest that the environment at Mallory's hospital was more conducive to second-order behavior, not that Mallory was a more competent or motivated nurse than Peggy . For example, Mallory explained that it was safe to contact the other unit to talk about a problem . Her hospital had a resource person to assist nurses, a specific group that worked on improvement projects, evidence of experimentation, and a culture that encouraged efforts to understand why medication accidents occurred . Three other units in the data set also exhibited second-order problem solving behaviors - the emergency ICU at Hospital 9 (9 .2 in Table 1), a surgical unit at Hospital 2, and a cardiac unit at Hospital 6 . On these units either the nurse manager or a resource person was available to assist nurses, and there was a culture that valued improvement . Nurses communicated about exceptions to the source rather than their peers for all of the problems, and on average used second order problem solving for 79% of the exceptions, as contrasted with the units shown on the left in Table 1 . We considered the other three units in our study, the maternity unit in Hospital 4, oncology in Hospital 7, and ICU in Hospital 1 as midrange . These units had

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nurse manager support but neither a designated resource person nor an organizational culture centered around improvement . See Table 1 for a list of the hospital units characterized by first and second-order problem solving . Supportive Conditions for Second-order Problem Solving Behavior Nurse Manager Behavior At hospitals characterized by second-order problem solving, nurse managers were either a strong presence on the floor or there was a designated, available person to provide guidance and support to nurses . We argue that nurse manager behavior and support will influence the degree to which nurses engage in this behavior . For example, in Hospital 8, there was a charge nurse who did not have any patients who helped Mallory with a problem of duplicate lab orders . Tara, a nurse at Hospital 6, one of the second-order hospitals commented on the support and availability of her nurse manager, not only during working hours, but also when the manager is on vacation . My nurse manager is extremely accessible and interested in hearing about the problems that we face . In fact, I called her at home today even though she is on holiday this week and it was my day off. We had an hour-long conversation about the problems that arose this weekend . She wouldn't have wanted to hear about these things later or from a second- hand source. Hearing about issues is part of her job and role . I don't feel I was out of line in calling her because of the magnitude of issues .

Conversely, at Hospital 4, Peggy had no support either from her nurse manager or any other resource person . Susan, a medical surgical floor nurse at Hospital 3, one of the first-order units, commented on the lack of support from nursing management . They say they are interested in helping us resolve issues, but their actions don't match . I think too that they know that they can't fix the problems . They hear it day in and day out and they just kind of nod and say we are working on it .

We conducted a review of relevant literature to incorporate other researchers' findings into our model . First, research (Griffen, 1983 ; House & Dessler, 1974 ; Latham & Locke, 1991) has shown that manager behavior influences worker motivation . More specifically, we suggest that nurses are likely to engage in second-order problem solving when nurse managers exhibit : (1) enabling behavior by providing assistance and coaching to nurses and (2) proficiency at resolving exceptions . This means that managers are physically present on the nursing floor, have time to devote to resolving exceptions, and have a reputation for improving conditions on their floor .

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Group Design In our data, two aspects of group design were linked to nurses' ability to engage in second-order problem solving - workload and group norms . First, we found that nurses almost always had heavy workloads, often precluding an ability to complete their patient care responsibilities within their shift. In fact, nine of ten nurses observed for an entire shift worked an average of 42 minutes overtime at the end of their shift, indicating that time for improvement work was scarce . Of the 13 nurses interviewed, only two said they had time to follow up on issues, and one of these was an assistant nurse manager who only spent part of her time working as a bedside nurse . Second, we observed that units varied in behavioral norms related to improvement efforts and communications about problems to other groups . A lack of response from other groups also inhibited ongoing communications about exceptions . Monica, at Hospital 5, commented on nurses' reluctance to communicate about problems to other groups, like central supply . She felt that if they did call, they would not get an effective response from support groups . We complain about problems - like running out of things on our supply cart - to each other but we don't follow up on them . So that is a big problem . I think it might just be that the supply people don't know that we are having these frustrations . But, if we are missing something and call them, they are not that receptive . They just say that they have already stocked the unit, but they don't try to figure out why we don't have what we need . I think that if we invited a representative to come to one of our unit council meetings [offline problem solving sessions] they would be more helpful .

Organizational Context To build on our empirical observations, we draw from the organizational behavior literature to suggest additional factors that may explain the absence or presence of second-order problem solving behavior . Specifically, we note that training, reward interdependence, and self-management have been associated with effective improvement efforts (Huq & Martin, 2000) . We thus include these factors in our model, and subsequently used interviews to gather preliminary data about their effects from nurses whom we observed previously . Training on problem solving techniques can increase feelings of competence and help create a culture that values improvement activities . It is needed to increase knowledge of the philosophy and principles of continuous improvement and interpersonal skills to improve problem-solving abilities (Huq & Martin, 2000) . Researchers have found that insufficient training is one of the biggest obstacles to effective organizational improvement, in particular because often only managerial and support personnel who are part of an established improvement team receive it . Front line workers, such as doctors and nurses, often are not included (Huq & Martin, 2000) . We asked nurses during their interviews


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if they received any training to help resolve problems . Nurses at hospitals with high levels of second-order problem solving behavior felt that they did, while nurses at hospitals characterized by first-order problem solving did not . For example, Susan, a medicallsurgical floor nurse at Hospital 3 felt the training she had received was ineffective . No, I have not received any such training, not that I recognize . We have had some training to teach communication between different groups and it had fish bones and all that . But, it doesn't work and it doesn't last here . I think we have had three different people come in and try to improve how different entities work together and that kind of stuff . But they always get dropped halfway and there is never any follow-up.

Reward systems that focus on the performance of larger groups, such as departments or the organization, can motivate cooperative behavior (Hackman, 1987) . We use the term reward interdependence, to denote formal and informal control systems that reward cooperative efforts (Chatman & Barsade, 1995) . Some examples of reward interdependence used in the healthcare setting include matrix organizations (Bums, 1989), task teams with cross functional representation (Carman, Shortell, Foster & Hughes, 1996), and an organizational climate that values organization level outcomes rather than individual or group level performance (e .g . patient safety programs) (Shortell, O'Brien, Carman & Foster, 1995) . In addition, there is also the traditional practice of providing financial incentives based on overall organizational performance, which would be suitable for clinical and support staff employed by hospitals . Cooperative behavior is particularly important for resolving exceptions in hospitals because of the highly interdependent nature of healthcare organizations (Bums, 1989) . Reward interdependence can help create the belief that problems - even the more difficult cross-functional ones - can be resolved because the independent parts of the organization are motivated to work together (Huq & Martin, 2000) . However, the hospital setting poses a unique challenge for creating reward interdependence because physicians are usually not employees of hospitals, and therefore are not under the same reward system as hospital employees and clinicians (Adler, Kwon & Signer, 2001 ; Arndt & Bigelow, 1995 ; Carman, Shortell, Foster & Hughes, 1996) . Autonomy has received much attention in nursing literature because it has been linked to higher nurse satisfaction and productivity (Aiken & Patrician, 2000 ; Havens & Aiken, 1999 ; Scott, Sochalski & Aiken, 1999 ; Whitley & Putzier, 1994) . Autonomy is defined as the amount of job-related independence, initiative, and freedom either permitted or required in daily work activities (Slavitt, Stamps, Piedmont & Haase, 1978) . The group level analogy to autonomy is selfmanagement (Campion, Medsker & Higgs, 1993) . Researchers suggest that selfmanagement increases worker motivation by empowering them to make decisions

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that affect their productivity (Campion, Medsker & Higgs, 1993 ; Hackman, 1987 ; Janz, Colquitt & Noe, 1997) . There are two dimensions of self-management : organizational and clinical . Examples of organizational self-management include nurses being in control of their own work force scheduling and patient assignment . Clinical self management addresses decisions about nurses' clinical practice including such things as being able to make adjustments in their practice to suit patient care needs, to make autonomous care decisions, and to be fully accountable for decisions (Whitley & Putzier, 1994) . Worker Cognition We present nurse cognition as a mediator through which the supportive conditions discussed above influence actual problem solving behavior . First, there is support in the literature for the premise that worker cognition mediates antecedent conditions and behavior, in general (Argyris, 1993 ; Bern, 1981 ; Eagly & Chaiken, 1998 ; Nelson, 1981 ; Nelson, 1986) . More specifically, nurse managers, group design, and organization context are likely to affect nurse behavior through two core cognitions . First, are nurses sufficiently motivated to exert extra effort into second order problem solving activities? Prevailing conditions can indicate to nurses that such effort is desirable and worthwhile, or not . Second, even if nurses are motivated, work conditions may lead them to conclude that it is not safe interpersonally or psychologically - to engage in risky, improvement activities (Edmondson, 1999 ; Victor, Boynton & Stephen-Jahng, 2000) . To develop these ideas further, we used interview questions to assess nurses' views of and motivation for second-order problem solving behavior because interviews are a way of gaining insight into how people think about their work context . Motivation Motivation is defined here as determination to pursue activities intended to lead to root cause removal over alternative responses (Locke, Latham & Erez, 1991 ; Locke, Shaw, Saari & Latham, 1981 ; Vroom, 1995) . We identify two components of motivation in this context: feasibility and anticipated benefit . Feasibility is the worker's belief that processes and resources needed to tackle an improvement effort exist - including time to engage in second-order problem solving, mechanisms for communicating across boundaries, and access to a support person who can facilitate investigation and implementation of solution efforts . In addition to viewing these activities as feasible, nurses must believe that the potential benefits are greater than the personal costs (Fine, 1986 ; Marcellus & Dada, 1991) . Benefits stem primarily from reduced encounters with the problem, which lessens frustration, wasted time, and possibly even


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negative patient effects . Motivation will be reduced when efforts seem unlikely to result in the desired outcomes (Marcellus & Dada, 1991) and when improvement activities are interpersonally costly to those conducting them . Nurses on lower performing units were less optimistic that problem solving efforts would be successful and were less enthusiastic about engaging in this activity . For example, Monica, a medical surgical nurse from Hospital 5 commented on staff's reluctance to tackle problems . It would probably be worth it to try to resolve problems instead of just complaining about them . It is just a matter doing it and I am not sure why we haven't . I think people are overworked and when they leave here, they don't even want to think about this place . They want to go home .

Conversely, nurses on second-order units were confident that problem-solving efforts would yield the desired benefits provided the problem was one that could be resolved . Tara, a nurse at hospital 6, summarized this feeling . I am very confident that efforts to remove underlying causes will be successful . It is absolutely worth my efforts to try to resolve problems because the biggest use of nurses' time is dealing with problems . The earlier you define the problem, the sooner you get the appropriate people involved, the better the outcome will be. You have got to - it is so important .

Psychological Safety Psychological safety is the belief that the work context is safe for interpersonal risk taking (Edmondson, 1999) . We argue that psychological safety enables willingness to engage in second-order problem solving behavior because improvement efforts are inherently risky . First, highlighting a need for change often requires exposing human errors and shortcomings, which can have negative consequences for the person who raises the concerns . This is especially true if the individual has lower organizational power than the person responsible for the shortcoming, a common occurrence for nurses (Edmondson, 1996) . In addition, being associated with problems and change efforts can result in damage to one's reputation (Dutton & Ashford, 1993) . Therefore, workers will be more likely to engage in improvement efforts if they feel they have some protection from such backlash (Edmondson, 1999) . Janice, a nurse at Hospital 7, felt safe raising problems, even to the nursing executives . She also felt safe talking with her nurse manager about personal issues . Our nurse manager is very aware of our personal life in a good way - she helps her staff balance the things they have going on in their life . For example, I want to start a Master's program in the fall and she will be supportive in scheduling my time so I can attend classes .

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Unfortunately, nurses at hospitals characterized by first-order behavior did not

feel safe bringing problems to manager's attention and were concerned about the lack of support . Megan, a nurse at Hospital 3 commented about how much this shortcoming discouraged nurses on her unit .

We are frustrated because the managers don't support us or tell us we are doing a good job. There is none of that . Most of the time it is, `Why can't you get out on time? You shouldn't have a problem .' I think most of us wouldn't mind working if we had a little more support from them .

Outcomes Our model includes two performance outcomes - quality of care and the ability to reduce the occurrence of exceptions over time . First, most of the exceptions we observed had implications for quality of care because they delayed patient

care or inconvenienced patients . For example, 89 (39%) of the exceptions observed caused, on average, a 90-minute delay in patient care . Delayed tasks

included medication, treatment, food, transfer/discharge, lab results, and surgery . We observed numerous patients being inconvenienced by long waits to be trans-

ferred or by having multiple lab samples drawn because earlier samples were processed incorrectly . Research also has shown that interruptions increase the

likelihood of performing a task incorrectly (Leape et al ., 1995 ; Osbourne, Blais & Hayes, 1999 ; Reason, 1990) .

Second, first order problem solving behavior, which simply "fixes" the

immediate exception so that patient care can continue, is proposed to have no

effect on the frequency of future problems because nothing is done to ensure that similar events do not recur . In contrast, second order problem solving is predicted

to improve the system, by way of addressing root causes and making system

changes that prevent the recurrence of similar exceptions . This prediction suggests a virtuous circle, that is, a dynamic relationship between second order problem solving behavior and performance outcomes, in which the former

improves performance, which in turn motivates future second order problem solving behavior.

Moderator: Mechanism for Organizational Improvement Problem solving coordinator

Engaging in second-order problem solving does not guarantee root cause removal . For instance, we observed several examples of a nurse attempting to resolve a

problem that crossed functional boundaries but being unable to elicit participation


1 03

in the effort from the other group . Contrasting successful cross-boundary improvement efforts with unsuccessful ones led us to conclude that an explicit mechanism was needed to coordinate improvements that crossed functional or professional boundaries . In our data, three units, Hospital 8, 9 .2, and 6, had a person formally responsible for coordinating problem solving/improvement activities . These units were associated with more frequent sharing of information about exceptions, greater influence on other parts of the organization, and more time available to coordinate problem solving activities . We call this role a "problem solving coordinator" to provide a sharper focus on the formal role in transmitting information, investigating root causes, and implementing countermeasures . We found support for this observation in literature . Other researchers have called it "task coordinator" (Ancona & Caldwell, 1992), integrator (Lawrence & Lorsch, 1967), and organizational liaison (Tushman, 1977) . Researchers who study innovation adoption and diffusion within organizations - an important type of which is improvement activity - suggest that when innovations cross boundaries, boundary spanning support is needed for both influence and coordination purposes (Burns, 1989 ; Burns & Wholey, 1993 ; Kimberly & Evanisko, 1981 ; Tushman, 1977) . Researchers propose two rationales for this . First, the person who encounters the problem may not have enough influence to successfully negotiate for change when innovations affect activities of other work groups (Ancona & Caldwell, 1992) . This is especially characteristic of nurses, who struggle to obtain status within their organizations (Chambliss, 1996), as also evidenced by the emphasis on autonomy and empowerment in nursing literature (Chandler, 1991 ; Havens & Aiken, 1999 ; Upenieks, 2000) . Second, the interdependent nature of various functional and professional groups (Glouberman & Mintzberg, 2001) means that coordination is required (Burns, 1989 ; Burns & Wholey, 1993 ; Kimberly & Evanisko, 1981) . Although other researchers have emphasized informal roles (Ancona & Caldwell, 1992 ; Tushman, 1977), we argue that a formal role is important in the nursing context because it allows the slack time, organizational status, and system focus necessary for negotiating improvement activities across functional boundaries .'- Managers fulfilled this role to a degree, but interview data revealed that nurses hesitated before contacting nurse managers - even the supportive ones - with "small" problems that nurses could, and were expected to, handle on their own . See Table 2 for illustrative examples of second-order problem solving efforts with and without problem solving coordinator roles present . Our model of front line problem solving is presented in Fig . 1 . Factors that we observed directly are shown in black type and factors suggested by the literature are shown in italic type .

ANITA L. TUCKER AND AMY C . EDMONDSON

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DISCUSSION The aim in this paper is to shed light on nurse problem solving behavior and

to develop a formal model of its causes and consequences for further research . Our blend of observational data and literature review is unorthodox yet, we argue, conducive to building new insight for research in health care manage-

ment . The core insight from our integration between empirical and theoretical sources is that problem solving techniques recommended in the quality literature are unlikely to be used either often or effectively by front line caregivers - and at the same time that managerial levers exist to alter this . Our observations suggested the former insight ; the literature suggests the

latter . More precisely, we found that exceptions were such a frequent occur-

rence in this work environment as to be considered routine . This meant that workers were often overwhelmed and centrally concerned with the need to continue patient care, virtually eliminating the possibility of contributing to

system improvement . Related to this, workloads were simply too high to allow the necessary slack for "optional" activities . This reality differs from the manufacturing contexts for which most problem solving techniques were

developed, where true exceptions (missing supplies or broken equipment, for example) are a far less common occurrence, and are thus more likely to

warrant workers' and managers' interest and attention . However, despite the challenge of using second order problem solving at the front lines of health

care delivery, we can identify managerial levers to ameliorate this situation - in particular, nurse manager actions, organizational context, group design and a coordinator role .

Implications for Research This model builds on our own and others' research to suggest new directions

for research that are interdisciplinary in nature . First, the social psychology literature has commented in a general sense about work design, but has remained

largely context free and thus rarely examined workers with high task variability

and a high degree of knowledge work . These conditions are substantially

different from the repetitive production tasks often studied in work design

literature . The nature of nursing itself thus challenges some underlying

assumptions in previous work design theories . Similarly, the problem solving

literature has prescribed various tools and techniques, without testing these models against an understanding of real world conditions faced by many front line workers . This paper suggests that both literatures could benefit from

106


deliberate integration, likely to be carried out by interdisciplinary teams of researchers, bringing these different skills and ideas together . Second, the present research has the potential to contribute to organizational learning research by combining motivation (Griffin, 1983 ; House & Dessler, 1974) and work design (Hackman, 1987) theory to explain a specific behavior, such as second-order problem solving, that can directly influence system performance . The emphasis on a specific mechanism for organizational learning and improvement has yielded valuable insights in the past (e .g . Edmondson, 1996) . Third, our empirical study of how nurses respond to obstacles advances understanding of organizational conditions that foster continuous improvement in health care delivery organizations . The nursing literature has described working conditions but has not attempted to link antecedent conditions to nursing satisfaction and performance through a formal causal model . Health care researchers have examined organizational level variables to determine what predicts adoption of an administrative or technical innovation, but few researchers have looked explicitly at daily behaviors of healthcare workers as an explanatory variable in accounting for these desired innovation outcomes . In addition, we show that not all behavior is productive, even when it appears to "work," a concept that is lacking in many studies of how nurses use their time (Jinks & Hope, 2000 ; Lundgren & Segesten, 2001 ; McCloskey, Bulechek, Moorhead & Daly, 1996) . Interviews revealed that turnover and quality of workers in ancillary departments, such as food services, supplies, and laboratory might influence nurse cognition about problem solving behavior as well . Several nurses mentioned that they felt that low pay and limited opportunities for advancement in positions such as unit secretary, laboratory technician, food service worker, and supply room personnel contributed to turnover and low motivation in these important support roles . Future studies could examine the impact that stability, training, and commitment in support service groups have on improvement efforts . Implications for Health Care Educators Work systems that did not support second-order problem solving behavior prevented even nurses with advanced degrees from consistently engage in root cause problem solving, highlighting the need to incorporate work system improvement concepts into all levels of nursing education . Exposing more people to this type of thinking will help create environments where frontline workers are encouraged to raise problems and try to improve their work systems rather than blaming themselves or other individuals when problems and accidents arise .


1 07

Implications for Health Care Managers

Our analysis challenges certain assumptions that many practicing managers hold about leadership and learning in organizations . We articulate these in the form of three managerial myths that pervade health care and other industries . Myth 1 : Worker empowerment is about letting workers do their jobs . Our analysis suggests instead that nursing units need managerial support to facilitate communication and cross-boundary problem solving . We do not intend to imply that nurses are unable to do these things on their own, but rather that it is helpful to have someone do the time-consuming and difficult coordination work of communicating and implementing problem solving efforts . Myth 2 : Leadership is about finding solutions . We suggest instead that nurses have good ideas about what needs to be fixed and possible solutions to these problems . However, they need assistance getting the time and organizational resources to experiment with their solutions . Myth 3 : If quality improvement efforts fail, people need more training . Staff development in systems thinking can be helpful for creating a culture where healthcare workers feel safe to talk about problems and motivated to work together to improve the overall delivery of patient care . In fact, both Hospitals 6 and 8 had good success at creating a safety-minded, improvement-oriented culture through training, focus groups, and staff development days featuring speakers who emphasis systems thinking . However, training in and of itself is not enough . We suggest that no amount of training can overcome contextual barriers to engaging in recommended techniques and, further, that more training may in fact be counterproductive if it depletes valuable resources and time . Rather than assuming that nurses or other front line workers do not understand system improvement, we suggest that it is more likely that they are unable to enact these concepts when system conditions inhibit it and they also lack psychological safety to talk about problems . Instead, therefore, nurses need organization-wide processes to make communicating about problems and getting responses from other groups easy and effective . Limitations

This paper's limitations include gaps in the demographic data for the nurses whom we observed, such as a lack of complete data on how many years of schooling each received . It is possible that education, or other factors such as number of years nursing, or tenure on a unit could account for individual differences between nurses, a factor that our model does not consider due to a

108


lack of evidence for this . Future studies should gather basic demographic data to control for these alternative explanations . Second, we found it difficult to gather meaningful performance measures . The first complication is that performance measures, such as calls made to the pharmacy or nurse manager, are often confounded with issues of psychological safety and openness . This means that more of a measure, such as calls to pharmacy or physicians, is not necessarily undesirable . Edmondson (1996) found this in her study of error reporting, and we saw the same phenomenon in our studies . Nurses were reluctant to contact certain doctors because they were afraid of being reprimanded for bothering them . This was also a problem for measure such as overtime hours worked . Several nurses commented that they typically do not record their overtime because they don't want to have to justify to their managers why they were unable to complete their tasks during their shift. An additional complication is that inputs are confounded with outputs . For example, nursing productivity, commonly measured in nursing care hours per occupied bed varied from unit to unit based on average patient acuity and staffing decisions . Even within the same unit, daily staffing decisions can create artificial productivity gains and losses . For example, if the unit is unable to replace absent nurses, nursing care hours/ occupied bed will look "low" even though nurses are caring for more patients than they would otherwise . We also tried to gather nurse satisfaction and turnover, but these figures are influenced by many other factors about which we did not have any data including other employment opportunities available in the surrounding community, age, job security, and personal demographics . These shortcomings of single outcome measures suggest that a viable alternative would have been to ask nurses directly to what extent exceptions decrease quality of care . Given the exploratory nature of our study, we did not gather this data systematically from our research sites . Future research could address this shortcoming by developing a new outcome measure that weights self-report measures with objective data related to quality of care, such as percentage of lab tests delayed due to faulty patient preparation . Ideally, these data would be gathered longitudinally in an action research setting to assess whether quality improvement programs were effective at removing exceptions . In addition, future studies should be more systematic about choosing which units, hospitals, and nurses to study so that results are comparable across units .

CONCLUSIONS Our empirical data highlight work environment conditions that inhibit organizational learning, and we expanded on these observations by drawing on other

1 09


research to consider how nurses' jobs could be made more conducive to system improvement. Nurses are faced - on a routine basis - with exceptions that impede their effectiveness . Indeed, we found that the nurses studied were rarely even surprised by these system defects . This is an insidious situation, however . Such exceptions, no matter how routine, cause increased disruption in an already fragmented task structure . This implies that resolving exceptions to prevent recurrence is likely to be a long process rather than a rapid fix . Moreover, social relations in hospitals can inhibit effective problem solving behavior . We suggest that managers need to not only alter methods used for front line improvement but also to change the environment to leverage the knowledge and ideas of direct care providers . This will involve building a problem solving system that improves the way goods and services are requested and delivered across boundaries as well as the way goods and services flow through the organization . The hospitals we studied did not have such systems and instead designed nursing work and support systems as if nurses do not encounter problems during their daily work and yet they happen all the time . It is our fervent hope that health care researchers will take up the challenge of conducting interdisciplinary work to better understand and address these issues .

NOTES I . All names are pseudonyms to protect confidentiality . 2 . The problem solving coordinator does not have to be a full-time position or performed by a nurse . For example, at Hospital 9 the Medical Director acted as a problem solving coordinator in addition to his other responsibilities .

ACKNOWLEDGMENTS The authors wish to thank the nurses and managers who participated in this research . The valuable comments of Grant Savage and two anonymous reviewers are gratefully acknowledged .

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POPULATION HEALTH MANAGEMENT IN THEORY AND PRACTICE Ann Scheck McAlearney ABSTRACT The concepts of population health management in both theory and practice have significant implications for improving health care quality and lowering costs . I discuss the importance of defining the perspective and populations for population health management . Lifestyle management strategies emphasize health risk reduction and prevention techniques as they target a relatively healthy population. Demand management approaches extend lifestyle management strategies by concentrating on consumer demand for medical care services. Disease management techniques typically focus on individuals with chronic conditions such as diabetes, congestive heart failure, or asthma. These programs offer targeted health and care management services to help coordinate the needs and care of individuals with those specific diseases. Catastrophic care management services extend the disease management approach to provide health management services for individuals with catastrophic illnesses or injuries. Disability management approaches are designed from an employer's perspective to improve worker productivity by focusing on strategies to reduce injuries, avoid illness, and better manage employee disability. Information technologies especially are important in developing and implementing each of the above population health management strategies . A conceptual model of population health management integrates the theory and the practice of Advances in Health Care Management, Volume 3, pages 117-159 . © 2002 Published by Elsevier Science Ltd . ISBN: 0-7623-0961-X 117

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ANN SCHECK MCALEARNEY

population health management on both individual and organizational levels. Lastly, I discuss practical and research issues around developing and applying a population health management model in the U .S.

INTRODUCTION Approaches to improving individual and population health are increasing in both importance and visibility in the United States health services sector . Population health management strategies are typically designed to improve consumer health and increase quality of care with an eye towards managing medical care costs (McAlearney, 2002) . Payers and health care organizations who are financially responsible for managing defined populations of employees, members, or beneficiaries are increasingly interested in such opportunities to reduce health care costs while ensuring quality of care and health . The U .S . health care system is undeniably fragmented . As Shortell and colleagues relate, this fragmentation is present in multiple areas of the health system, including the levels of patient care, providers, organizations, financing, and overall health policy (Shortell, Gillies, Anderson, Erickson & Mitchell, 1996) . Patients may have multiple providers involved in their care, and these providers may offer specialized services in multiple settings . Organizational complexity contributes to fragmentation of the health care system, especially in cases where financial incentives conflict for different organizations and providers . Health policy issues such as access to care, insurance coverage, rapidly increasing

medical care costs, and problems surrounding the quality of medical care further complicate the management and delivery of health care services . Attempts to expand access, reduce costs, and improve the quality of health care for consumers benefit from advances in health management that address these policy issues from a management perspective . There are numerous opportunities for health and care management that can help better manage both health and financial risks to try to tackle the issues of fragmentation and complexity in the health system . Population health management strate-gies that strive to improve health and the quality of care while attempting to contain medical costs can be extremely appealing to payers and providers faced with the challenge of managing health for defined populations of individuals . Population health management initiatives include a number of approaches, five of which are discussed in this article . First, lifestyle management strategies emphasize health risk reduction and prevention techniques as they target a relatively healthy population . Demand management approaches extend lifestyle management strategies by concentrating on consumer demand for medical care services . When an individual has a health or medical problem and desires

Population Health Management in Theory and Practice attention, demand management programs provide

119 advice,

counseling,

and

referrals to appropriate providers as they address the issue of demand for medical care and services . Disease management techniques typically target individuals with chronic conditions . Focused on diseases such as diabetes, congestive heart failure, or asthma, disease management programs offer health and care management services to help coordinate the needs and care of individuals with those

specific diseases . Catastrophic care management services extend the disease management approach to provide health management services for individuals

with catastrophic illnesses or injuries . Finally, disability management strategies are designed from an employer's perspective to improve worker productivity by focusing on approaches to reduce injuries, avoid illness, and better manage employee disability .

The following article presents the concepts of population health management

in both theory and practice . First, the importance of defining perspective and

populations for population health management are discussed . Next, each of the population health management strategies presented above is described in further detail . As a special topic, the critical role of information technologies in the development of population health management strategies is also discussed . After these practical issues are presented, the article presents a conceptual model of population health management . Theoretical support for this model and the practice of population health management is then presented on both individual

and organizational levels . To conclude, practical and research issues around

developing and applying a population health management model in the present U .S . health services sector are discussed .

DEFINING PERSPECTIVE Determining the perspective of a program is very important in population health

management . Program perspective affects most aspects of program development including defining the relevant target population, structuring interventions, and specifying program goals . As shown in Table 1, defining program perspective

helps to focus the selection of alternative population health management strategies by highlighting the concerns and population of primary interest for

the program .

DEFINING THE POPULATION Developing and implementing appropriate population health management

strategies depends largely on the characteristics of the population that will be served . Population segmentation occurs along numerous lines, and in the U .S .,


120 Table 1.

Defining Perspective in Population Health Management .

Perspective

Major Program Outcomes of Interest

Target Population

Population Health Management Alternatives

Employer

• Cost • Reducing Disability • Productivity

Employees

• • • •

Society

• Cost • Health • Productivity

Citizens

• Lifestyle Management • Demand Management • Disease Management

Government as Insurer

• Cost • Health

Medicare Beneficiaries Medicaid Recipients

• • • •

Patients

• Health and Wellness • Out-of-Pocket Cost • Improved Functional Outcomes

Individuals

• Programs with self-care focus • All options may be attractive

Providers

• Improved Clinical Outcomes • Appropriate Care • Efficient Use of Time

Patients


Insurers

• Cost • Health

Covered Lives

• • • •

Lifestyle Management Demand Management Disability Management Catastrophic Care Management

Lifestyle Management Demand Management Disease Management Catastrophic Care Management

Lifestyle Management Demand Management Disease Management Catastrophic Care Management

health care services are often targeted for individuals based on their membership in different population groups . Several approaches to segmenting or defining these populations include : (1) age ; (2) geography ; (3) employer ; (4) insurance coverage ; and (5) health . Based on how individuals are targeted for health management, strategies can be developed to best meet the needs of the people in that defined population . Table 2 presents five options for defining a population for health management and explains the rationale for these approaches to segmentation . Practical examples of each population segment in practice are also described .

121

Population Health Management in Theory and Practice Table

2.

Defining Populations .

Rationale for Segmentation Factor in Population Health Management

Factor

Example Groups

Age

Permits development of age-appropriate health behavior and wellness strategies

Federal Medicare program uses age 65 as cutoff point to determine eligibility for elderly

Geography

Creates natural boundaries for defining populations

Proximity to a hospital for pregnant women ; Medicaid programs defined by state

Employer

Employers providing health insurance and disability coverage can target employee groups for population health management interventions

Employee population

Insurance Coverage

Insurance carriers are responsible for medical care costs of enrolled populations, thus their incentives are aligned with population health management goals

Enrolled population ; health plan members

Health

Targeting groups on the basis of disease or health status permits stratification into groups who will most benefit from specific population health management interventions

Groups defined by disease status such as diabetes or asthma, or other health criterion

POPULATION HEALTH MANAGEMENT APPROACHES Distinctions among population health management approaches are essentially made based on the characteristics of the defined population to be served . However, alternative approaches to defining and segmenting populations do not necessarily lead to mutually exclusive membership of individuals in one population subgroup (McAlearney, 2002), and this can complicate population health management . As an example, a 40 year-old woman employed by a utility company in a major metropolitan area that offers health insurance to all employees is a member of four different subgroups : consumers under age 65 ; employees ; citizens in the community ; and covered lives for the insurance plan .

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If this woman smokes, she may have opportunities to participate in smoking

cessation programs offered by her employer, her insurance company, and others .

For the purposes of this article, five main population health management

strategies are described : lifestyle management ; demand management ; disease

management ; catastrophic care management ; and disability management . Table 3 summarizes the key characteristics of these strategies as they are applied in

practice, including describing the target population and key elements of the approach, and providing evidence of their effectiveness in practice .

While population health management approaches are identified by distinct

labels, different strategies do overlap . As seen in Table 3, health education and a self-care focus are important in lifestyle, demand, and disease management

approaches . Coordination of care and providers are key for disease, catastrophic care, and disability management strategies . From a program perspective, a weight management program may be offered by a health plan as an independent lifestyle management strategy, by a provider as part of a disease manage-

ment initiative, or through an employer as integral to a disability management

program .

Selection of a particular population health management strategy depends

largely on the perspective of the entity developing the program, as shown in

Table 1 . In particular, this selection is based on the program outcomes of interest and the target population of concern . Resource requirements and capabilities may also influence program selection as organizations strive to implement feasible approaches to population health management for their defined populations .

The purpose of this article is not to emphasize distinctions among different

population health management approaches . Instead, this article attempts to stress the value of including population health management strategies in a comprehen-

sive and integrated approach to health care delivery . In practice, it is up to individual consumers to make choices about both their medical care and health

behavior choices . The opportunity presented by population health management

approaches is to promote healthy decisions for targeted individuals, given the

program perspective . By directing appropriate care to individuals within targeted population groups . population health management strategies attempt to increase

quality of care, lower costs, and improve health . The following sections provide further detail about each of these five approaches to population health management .

Lifestyle Management Lifestyle management strategies recognize the importance of individuals taking charge of their health and medical care decisions . This individual or self-care

Population Health Management in Theory and Practice Table 3. Population Health Management Strategy

123

Approaches to Population Health Management . Target Population

Lifestyle Management : Help individuals make good choices about health behaviours and health risks (Resource: McAlearney, 2002)

• Relatively

Demand Management : Help individual consumers take an active role in making decisions about health and medical care needs to reduce inappropriate demand for services (Resources : MacStravic & Montrose, 1998 ; Vickery, 1996 : Fries et al ., 1993 ; Fries, 1998)

• Relatively

Disease Management: Identify individuals with certain diseases and target with specific interventions (Resources : Wagner, 1995 ; Spalding, 1996 ; VonKorff et al ., 1997 ; McCulloch et al ., 1998 ; Bodenheimer, 1999)

• Individuals

healthy population groups

healthy population groups

Key Elements

Evidence of Effectivenes

• Prevention • Health risk

• Guidelines for clinical

• Telephone triage • Advice and

• Reduce variation in care

reduction • Self-care

referrals • Triaged counseling • Decision and behavioral support • Education to promote self-care

• Management of with chronic chronic diseases diseases (e .g . • Education, selfcongestive care information heart failure, • Chronic disease diabetes monitoring mellitus, Clinical oversight asthma) by care managers • Coordination of care and providers

screenings (U .S . Task Force, 1996) • Economic benefits of prevention programs (19 strategies) (HHS, 1999)

unexplained by morbidity (Andersen & Newman, 1973 ; Tanner et al ., 1983 ; Berkanovic et al ., 1991) • Improve understanding of perceived need for care (Vickery, 1996 ; Connelly et al ., 1989, 1991) • Educate individuals about treatment risks and benefits (Vickery . 1996) • Improved access, better outcomes, lower costs (Henderson & Hahn . 1996) • Reduce costs for disease

treatments (Rich et al ., 1995 ; Lucas et al ., 1995) • Decrease complications associated with chronic illness (Wasson et al ., 1992 ; Rich et al ., 1995 ; Pearson et al ., 1996 ; West et al ., 1997 ; Aubert et al ., 1998 ; DeBusk, 1999)

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Table 3. Population Health Management Approach

Target Population

Continued . Key Elements

Evidence of Effectivenes

Catastrophic Care Management: Proactive identification of cases to provide services needed for catastrophic injuries or rare or catastrophic illnesses to improve outcomes (health and cost) ; may include management of medical care, rehabilitation, and end-of-life care needs

• Individuals with catastrophic or rare illnesses, or catastrophic, injuries (e .g . cancer, renal disease, injuries, immunodeficiency diseases)

• Immediate referral to appropriate providers • Coordination of care and providers • Medical and care management by professionals with expertise with catastrophic and complex patients

• Reduce hospitalizations and total claims costs (Scott, 1999) • Reduce morbidity and hospital stays, improve quality of life (Campbell, 1996) • Realistic, patient-specific outcome goals for individuals with catastrophic diagnoses and injuries (Otway, 2000)

Disability Management : Employer-driven initiatives to reduce lost time from work, improve worker productivity, and optimize employee health and well-being (Resources : Shrey, 2000, 1998 ; Margoshes, 1998)

• Employees

• Disability prevention • Return-to-work and transitional work programs • Lifestyle management • Coordination of care and providers • Absence management • Workplace rehabilitation

• Lower worker's compensation costs and lower costs of disability benefits (Shrey, 2000 ; Gice & Tompkins, 1989 ; Bernaki & Tsai, 1996) • Reduced number of injuries, reduced lost time from work, increased productivity (Shrey, 2000, 1998 ; Carruthers, 2000)

focus acknowledges the important role of personal health choices with respect to both behavior and lifestyle . Lifestyle management approaches are designed to reduce health risks and improve health habits in order to maintain the health and wellness of the population targeted (McAlearney, 2002) . Typically, lifestyle management programs concentrate on a relatively healthy population and focus on maintaining and improving health for those individuals using prevention techniques and specific risk reduction strategies . Prevention and risk reduction are interrelated concepts in the promotion of better health and improved lifestyles . Specifically, risk reduction strategies attempt to modify identifiable risk factors for illness or injury . These approaches

Population Health Management in Theory and Practice

1 25

are inherent in primary prevention initiatives that attempt to prevent the occurrence of illness or disease, and secondary prevention strategies that focus on early detection of disease to facilitate better treatment and slow or prevent symptom appearance (Schmidt, 1994 ; Suber, 2001) . Lifestyle management programs typically focus on primary and secondary prevention activities to reduce the likelihood of future symptomatic and costly diseases . An employer-based lifestyle management program may target overweight individuals and include weight management and stress reduction programs to help improve employee health and wellness . Concentrating on modifiable risks such as weight and stress, programs attempt to reduce the risk of adverse medical events due to the identified health risks . These lifestyle management strategies have demonstrated both economic and clinical benefits that support their inclusion in guidelines for clinical screenings and prevention programs nationwide (Force, 1996 ; HHS, 1999) . Demand Management

Demand management is a common approach to population health management that helps individual consumers take an active role in making decisions about their health and medical care needs . The term demand management has actually been trademarked to reflect a product that combines self-care and triaged counseling designed to help consumers manage their medical symptoms (MacStravic & Montrose, 1998) . Generically, the concept of demand management or demand improvement is derived from the idea that when people are involved in health care decisions, the demand of these individuals for medical care services can be guided and therefore managed (MacStravic et al ., 1998) . The premise of demand management as a health management strategy is that individuals may demand medical care that is inappropriate or unnecessary because of factors such as self-care, doctor-seeking, and technology-seeking practices that are not tied to actual needs for medical care . Unnecessary demand, as described by James Fries, reflects the notion that while medical care services may be demanded at the margin, the addition of these services may not be associated with health benefits that are measurable (Fries, 1998 ; Fries et al ., 1993) . Behavioral constructs such as personal self-efficacy and learned helplessness may also affect demand for services when individuals lack confidence in their ability to manage their own health, or when they overestimate the potential value of medical services in health improvement (Connelly, Smith, Philbrick & Kaiser, 1991 ; Fries, 1998 ; Kaplan & Camacho, 1983 ; O'Leary, 1985) . Using a demand management approach, decision and behavioral support tools encourage individuals to use health care services that are appropriate for their

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needs . Modifiable factors such as types of services, location of services, and timing of services are addressed in the attempt to guide demand for medical care . A key figure in demand management, Donald Vickery, helped establish a model of demand management in 1992 that recognizes four different factors in individual health that can influence demand for medical services : morbidity, perceived need, patient preferences, and nonhealth motives (Vickery, 1996 ; Vickery & Lynch, 1995) . Tools and interventions including education, health promotion, and interventions directed at patient self-care (Vickery, 1996) attempt to help health care consumers maintain health and seek appropriate care in the context of cost containment (Mohler & Harris, 1998) . Programs such as telephone triage, decision support, advice and referrals, access to an information library of health care and wellness topics, wellness classes, and even appointment scheduling comprise some of the specific tactics used by demand management strategies . Similar to lifestyle management approaches, demand management programs usually target a relatively healthy population . However, moving beyond lifestyle management information, demand management services are directed towards providing specific health information to guide decisions about utilization of medical services . Research has provided estimates that up to one-quarter of visits to physicians are for conditions that patients could be trained to assess and self-treat (Vickery, 1983), providing evidence for the value of health education in self-care . This combined focus on improving health status for a defined population while attempting to reduce utilization of costly and potentially unnecessary health care services (Montrose, 1995) may be seen in health management tactics such as searching for therapeutic alternatives to expensive surgery, promoting self-care options, and encouraging lifestyle management (McAlearney, 2002) . Demand management program outcomes including reducing variation in care, improving perceptions about need for care, and increasing access to care while lowering costs have all been demonstrated (Andersen & Newman, 1973 ; Berkanovic, Telesky & Reeder, 1991 ; Connelly, Philbrick, Smith, Kaiser & Wymer, 1989 ; Connelly et al ., 1991 ; Henderson & Hahn, 1996 ; Tanner, Cockerham & Speth, 1983 ; Vickery, 1983, 1996) . By leveraging the opportunities presented by the concept of teaching individuals how to manage their own demand for medical care, demand management and demand improvement strategies can be a valuable component of a health management approach to delivering medical care . Disease Management Disease management is a classic health management strategy that is widely used in different health care settings . Ideally, disease management initiatives are


1 27

established to identify individuals at risk within a population and then target those individuals with specific interventions designed to address disease risk . This approach works best when it is multidisciplinary, using the continuum of medical care services available to treat targeted individuals . The emergence of disease management programs in the U .S . reflects the recognition that beyond acute care needs, chronic illness represents a substantial burden for the health care system . An Institute for the Future report noted that by 2000, 105 million people in the U .S . would have one or more chronic illness, and numbers were projected to increase by 2010 to 120 million persons, or 40% of the U .S . population (Future, 2000) . Disease management initiatives address this prevalent problem by attempting to better manage care for individuals with chronic diseases . Considering that congestive heart failure, diabetes mellitus, and asthma are the three largest contributors to health care utilization and medical expenses, better managing the care for these conditions on a disease-specific basis represents a tremendous opportunity to both save money and improve health care service quality . A key element of the disease management strategy is the notion that this population-based approach proactively identifies individuals who will benefit from intervention attention . Largely focused on behavior change methodologies, disease management programs provide education, self-care information, and chronic disease monitoring in order to optimize patientfocused management of these illnesses . Programs rely upon patients to take considerable initiative in monitoring their own health, but use care managers such as health educators and nurses to provide information and clinical oversight (Bodenheimer, 1999 ; McCulloch, Price, Hindmarsh & Wagner, 1998 ; Spalding, 1996 ; VonKorff, Gruman, Schaefer, Curry & Wagner, 1997 ; Wagner, 1995) . Disease management programs have been developed by a number of entities including pharmaceutical firms and pharmacy benefits managers, managed care organizations, provider organizations, health plans, employers, Medicaid agencies, and independent vendors (McAlearney, 2002 ; Lucas, Gunter, Byrnes, Coyle & Friedman, 1995 ; Sadur, Moline, Costa et al ., 1997) . Risk bearing entities have particular interest in disease management strategies because they are liable for the cost of care for such illnesses . Evidence supporting the effectiveness of disease management programs (Aubert et al ., 1998 ; DeBusk, 1999 ; Lucas et al ., 1995 ; Pearson, McBride, Miller & Smith, 1996 ; Rich et al ., 1995 ; Wasson et al ., 1992 ; West, Miller, Parker et al ., 1997) reflects the recognized potential of this approach to reduce health care costs by improving management of chronic illness .

1 28


Catastrophic Care Management Catastrophic care management is an approach to population health management that specifically focuses on catastrophic injuries or rare or catastrophic illnesses . Catastrophic events in the U .S . account for approximately $30 billion in medical care expenses every year, even though the prevalence of such conditions is not very high within most defined populations . In practice, the rarity of some diseases diminishes their attractiveness to traditional disease management programs which may rely on patient volume to justify program expenses . Rare and catastrophic conditions can be characterized both by their low prevalence in a defined population and their requirements for specialized and complex clinical management . Typically, health management of these conditions involves multiple providers at multiple sites of care . Approaches to catastrophic care management capitalize on the notion that the occurrence of such conditions is unpredictable but the costs and care needs can be extremely high. Correspondingly, population health management services are designed to provide the spectrum of services needed in the context of these rare or catastrophic conditions . Three major characteristics of the catastrophic care management approach include immediate referral, care plan development, and medical management by professionals with experience managing catastrophic and complex patients (Anonymous, 1998) . As a proactive approach to care delivery and service coordination, this health management strategy can help reduce costs and improve outcomes for involved patients . The catastrophic care management model includes two main component health management programs : rare and catastrophic illness management and catastrophic injury management . Rare and catastrophic illnesses such as cancers, major organ system diseases, and immunodeficiency diseases present opportunities to manage the complex medical care, rehabilitation, and, unfortunately, end of life care needs associated with such conditions . Cancer care alone is associated with $120 billion of direct and indirect costs in the U .S . market, thus the financial risk to payers associated with different cancers can be substantial . Catastrophic injury management programs focus on major accidents and injuries associated with catastrophic diagnoses and large medical claims . One model for a catastrophic injury management program assumes all risk for expenses associated with carved out catastrophic claims until established outcomes are reached (Cowans, 1996) . For individual patients with the same catastrophic diagnosis resulting from an injury, final outcomes may range from minimal psysiological stability to full reintegration of that individual into the community (Otway, 2000) . Offering care coordination and case oversight can


1 29

help each injured patient reach the best outcome possible given individual circumstances . Evidence that a catastrophic care management approach works is growing . One company that focuses on managing rare conditions reports substantial reductions in the number of hospitalizations and in total claims costs to produce savings for the program (Scott, 1999) . A cancer-focused company has shown similar success with reduced morbidity, hospital stays, and improvements in quality of life for surveyed patients (Campbell, 1996) . By focusing on a proactive approach to rapidly identify cases that can benefit from health management oversight while providing the necessary care and services to optimize outcomes and lower costs for affected patients and families, a catastrophic care management program can be a very valuable population health management approach . Disability Management

Disability management is a population health management strategy that primarily considers the employer perspective when attempting to manage health and disability . The defined population of employees is targeted for initiatives that are designed to reduce lost time from work, improve worker productivity, and optimize employee health and wellness (Margoshes, 1998 ; Shrey, 1998, 2000) . With a focus on reducing the economic and personal costs associated with workplace injuries and disabilities, strategies such as early intervention, Employee Assistance Programs, transitional work, and ergonomics can all be included in a disability management program . Ideally, a disability management approach is a comprehensive strategy that includes disability prevention initiatives, return-to-work programs, and rehabilitation treatment efforts (Fitzpatrick & King, 2001) in order to address issues surrounding both the incidence and impact of employee disability . Work-related injuries and disability are a major economic cost to employers . The Census Bureau predicted that costs due to disability in 2000 could top $340 billion, reportedly double their cost level a decade earlier (Hellwig, 1999) . The costs associated with workplace accidents and injuries alone were reported to exceed $80 billion in 1996, and employers reportedly spend an average of 10% of their payroll on direct and indirect costs associated with employee disability (Fitzpatrick et al ., 2001 ; Johnson & Strosahl, 1999) . For the defined employee population, developing a disability management program has tremendous potential to improve health and health management for involved individuals . Programs are associated with savings to employers reflected in both lower workers' compensation costs and lower costs for disability benefits

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(Bernacki & Tsai, 1996 ; Gice & Tompkins, 1989 ; Shrey, 2000) . Improvements in productivity are another valued benefit for employers (Carruthers, 2000 ; Shrey, 1998, 2000), and factors such as higher employee morale, improvements in employee health and wellness, and a greater ability for employers to recruit and retain qualified employees have also been associated with disability management programs (Carruthers, 2000) . By focusing on reducing work-related illnesses and injuries while maintaining an overall perspective on increasing employee wellness and productivity, such an approach can benefit both employers and their employees who are typically more interested in working than remaining off of work (Lerner, 1998) due to disability .

ROLE OF INFORMATION SYSTEMS AND TECHNOLOGIES Information technologies are vitally important to the effective implementation of any population health management approach . In practice, a variety of information technologies help facilitate health and care management processes by organizing data, monitoring information, and enabling coordination and communication . From computer databases to telemedicine opportunities to sophisticated electronic communications using handheld devices or the Internet, information technologies and systems can improve clinical decision making, increase worker productivity, improve quality of care, reduce medical errors, streamline operations, and increase participant satisfaction for physicians, patients, and employees (McAlearney, 2002) . Figure 1 illustrates some of the multiple benefits of incorporating information technology in population health management. In addition, Table 4 highlights some of the specific roles for information technology in different population health management approaches . Data Collection, Organization, and Analysis

One of the main roles of information systems in population health management programs is in collecting, organizing, and analyzing data . Potential program participants are typically screened by reviewing existing sources of data including demographic, clinical, and financial information . Sources such as hospital claims, ambulatory visits, employee databases, health plan member surveys, and so forth can be assessed to identify individuals who are members of defined populations that could benefit from health and care management strategies . To the extent that such databases are integrated, searching for patients who would benefit from program participation is streamlined, making the targeting process both easier and more accurate .


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Table 4.

Lifestyle Management

Information Technology Applications in Population Health Management .

Demand Management

Disease Management

Catastrophic Care Management

Disability Management

• Tailored Messages

• Computer-driven Algorithms

• Automation of Guidelines, Care Pathways

• Web-based Support Groups

• Coordination of Benefits

• Dynamic Health Assessments

• Telephonic Decision Support

• Remote Care Management/ Disease Monitoring

• Automation of Care Guidelines

• Integrated Benefits Administration

• Web-based Self-Care Education

• Dynamic Health Assessments

• Coordination of Care Providers

• Coordination of Care Providers

• Ability to Integrate Absence Management Programs

Remote Care Management and Monitoring Ongoing patient monitoring within health management programs also relies heavily on information technologies . Tracking participant progress through steps such as telephone contacts, visits to providers, and educational interventions

can create opportunities for intensified intervention when progress is not

proceeding as expected . Similarly, ongoing monitoring of clinical data using information technologies such as electronic scales or blood pressure cuffs connected to information systems can notify program personnel if clinical measurements cause alarm and can stimulate immediate intervention .

As an example, disease management programs for congestive heart failure

generally rely on patients to record their weights daily in order to identify any clinically important changes . Incorporating an electronic scale which

instantaneously transmits patients' weights to clinical personnel can eliminate a crucial step whereby patients are required to make a call to report their

weight fluctuation . Using information technologies can thus facilitate accurate communication between the patient and the program and can also speed intervention response time, especially when alarming clinical information can

be communicated to program personnel immediately using pagers or other electronic communication methods .


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Decision Support Tools Information technologies are also very important when they serve as decision support tools . While patient care guidelines, pathways, and protocols may exist

on paper, consistent and appropriate use of such decision support aids is facilitated by their automation . Automation of patient care guidelines and proto-

cols can help sort through multiple issues and decision rules in a reasonable time frame . While patient care decisions are still made by physicians and other providers, automated pathways can reduce the number of available treatment

options to a reasonable and appropriate list of alternatives . In addition, by automating patient care logic using computer-driven algorithms, programs can leverage the opportunities created by decision rules to more appropriately

respond to individual patient differences and treatment needs . Making these guidelines available at the patient's bedside through a movable computer

terminal or on a handheld device such as a personal data assistant (PDA) can promote the use of information-based treatment strategies in real-time .

Computer-driven algorithms can also be used to identify individuals for health

management program participation or for particular interventions . This type of

information systems application can permit the use of multiple patient selection

criteria, optimally obtained from multiple data sources . As an example, decision

rules based upon disease presence, risk status, or a claim for a medical event can be defined to screen individuals into a particular health or care management

program . The breadth of additional information available from sources such as

health assessment tools, claims data, pharmacy data, laboratory data, and so

forth can then specifically identify individuals who will benefit most from different intervention options .

Health assessments and health surveys also benefit from the use of informa-

tion systems . Rather than relying on paper survey tools, computerized surveys can include branching logic to ask responders different questions based on

answers to previous questions and make these assessments dynamic . For example, if an individual responds affirmatively to a question about having diabetes, following questions may be included that delve deeper and assess the diabetes . While such logic can be built into paper surveys, speed and

accuracy of survey completion can be compromised . New electronic options such as web-based assessment tools can incorporate dynamic features that

present assessment questions in an order that is tailored appropriately for each respondent .

The power of these decision support tools is multiplied when information

systems are integrated or interconnectivity (Reese & Majzun, 2000) exists among

systems and sites . When multiple systems are accessible at the same time,

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algorithms that are developed can be more complex and responsive to individual participant needs and conditions . Integrated databases can permit incorporation of more sophisticated screening criteria for program participation and establish parameters for health management interventions based on changes over time . As an example, the combination of laboratory data with pharmacy data in a disease management program would permit identification of those patients who have received a drug such as Coumadin but who have not had appropriate followup laboratory tests such as pro-times . These patients could then be targeted for a simple communication intervention to remind them to get their test and thereby potentially avoid unnecessary clinical and financial risks . Use of the Internet Another information technology that has great potential to improve population health management strategies is the Internet . Whether providing access to health education information, developing program-specific web pages to present health and wellness content, or leveraging the potential of web-based algorithms and dynamic web pages to facilitate health assessment and health monitoring, the Internet can play a major role in many population health management programs . The Internet can also be used to improve coordination and communication among different participants in health management programs . Internet access to chat rooms, program-specific bulletin boards, and support groups can facilitate communications about health and diseases that may be very valuable to individual participants . Similarly, communication and coordination among those involved in providing health management and clinical care services can be enhanced by using tools such as electronic mail, messaging, or streaming video . With proper security ensured, the Internet can also facilitate access to medical records, patient progress notes, and other available data using protected web pages .

PART II: A MODEL FOR POPULATION HEALTH MANAGEMENT While population health management strategies have been developed in a variety of settings, most share similar characteristics that can be described in a model for population health management . Fundamentally, the population health management approach to providing services is structured whereby some type of Influencing Entity attempts to act upon a Target Population, as illustrated in Fig . 2 . The Influencing Entity, whether payer or provider, has an interest in

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Influencing Entity

I

Entity

Population Health Management Approach

Population Health Management Strategy

Payers • Employer • Government • Health Plan • Insurance Company

Lifestyle Management Demand Management Disease Management Catastrophic Care Management Disability Management

Providers • Physician • Hospital • Clinic

Target Population

I

Defined Population Individuals • Patient • Employee • Member • Covered Life • Beneficiary • Recipient • Patient Surrogate • Citizen

n

n

Theoretical Support for Population Health Management Approaches

• Individual Behavior Change Theories • Integration Theories • Organizational Change Theories

U Care Goals of Population Health Management

• • • •

Fig. 2.

Individualized Appropriate Coordinated Population-Based

Population Health Management Model .

helping the Target Population of individuals make appropriate choices and decisions about their health and medical care in order to reduce unnecessary medical expenses and keep healthy . Population health management strategies, specifically, lifestyle, demand, disease, catastrophic care, and disability

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management, provide the means by which Influencing Entities attempt to change the behavior of their targets . This influence model draws heavily from behavior change theories as population health management strategies try to help individual targets make better decisions about their health behaviors and utilization of medical care services . Integration theory is also applicable because of the importance of coordination of care and services among involved entities and target individuals . Finally, organizational change theories are important because of the organizational implications that adopting a population health management approach has for changing the behavior of Influencing Entities . In this population health management model, Influencing Entities can be either payers or providers . Payers such as employers, health plans, other insurers, Federal or State governments, or any entity at risk for medical care costs for a defined population of individuals are considered Influencing Entities because of their interest in protecting and promoting the health of this population . Similarly, both individual and institutional providers such as physicians, hospitals, and clinics are considered Influencing Entities because of their concern and financial risk for the cost of medical care . Even when financial risk is not assumed by providers or provider entities, their professional and institutional commitments to improve health and care delivery permit their categorization as influencing entities . These Influencing Entities provide the perspective for the population health management programs, as previously shown in Table 1, that frames program design and defines desired program outcomes . Target populations are those individuals included in the population defined for service . These groups may include people with labels including employees, patients, members, beneficiaries, citizens, or consumers . Furthermore, for individuals who are unable to make their own medical decisions such as children or those deemed incompetent, patient surrogates may be identified as the actual targets of population health management interventions . Using this classification scheme, uninsured and underinsured individuals are also included as intervention target populations because, as citizens, their medical care expenditures are ultimately the responsibility of some type of payer or provider entity that would like to influence and optimize health and medical care for those individuals . Population health management approaches provide the tools and personnel for Influencing Entities to affect their Target Populations of individual consumers . As tools, population health management strategies help teach target individuals and groups how to care for themselves and how to appropriately access the medical care system . Program personnel including physicians, nurses,


137

educators, telephone counselors, and other care managers deliver population health management services on an individual or group basis for members of the target populations . Using techniques derived from behavior change theories, these professionals attempt to persuade individuals to make choices to improve their health and optimize their use of medical care services . Additional personnel responsible for designing, implementing, and overseeing population health management programs provide necessary infrastructure and organizational commitment to facilitate the delivery of appropriate and coordinated health and care management services . Theories of integration and organizational change support the modification of organizational operations, strategy, and culture required by the adoption of a population health management approach . Underlying this model of population health management is a common set of care goals that these approaches share : that provision of health and care management be individualized, appropriate, and coordinated for defined populations . Providing care and health behavioral support for individuals is by its very nature individual- or patient focused . The tension between focusing on defined populations versus the individuals within those populations is resolved in the practice of population health management . While target populations are segmented as groups, health and care management services are delivered to individual people . Maintaining a program focus on individuals as well as target populations can help population health management programs achieve their health improvement and patient care goals and provide services that are appropriate for the target individual . Coordination becomes important when appropriate, patient-focused services are delivered by multiple providers in multiple care sites . Given that there is overlap among many health management approaches, coordination is especially critical . Program personnel must be cognizant of the opportunities and limitations of the different strategies in practice and work to reduce duplication while best meeting the needs of their target populations of individuals . In practice, integration of population health management activities within either a single Influencing Entity or across multiple entities requires the use of sophisticated information technologies and the participation of knowledgeable program personnel . Institutionalizing the care goals of health management as organizational values can help cultivate organizational support for this conceptual model and encourage resource allocation to support health and care management activities . By promoting the organizational changes necessary to incorporate the goals and philosophies of a population health management model into the strategies and cultures of the Influencing Entities, it is possible to create organizational environments truly focused on health and wellness .

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PART III: THEORETICAL SUPPORT FOR POPULATION HEALTH MANAGEMENT APPROACHES Approaches to population management have strong theoretical bases from both individual and organizational perspectives . As described above, from the perspective of individuals participating in population health management programs, such approaches rely heavily upon behavior change theories in order to improve health . Similarly, an organizational perspective must acknowledge the importance of theory in areas such as integration and organizational change in order to support the development of health and care management programs and an integrated population health management model overall . Table 5 describes the relationship between the Population Health Management Model and Supporting Theory, presenting both the rationale for this linkage and examples of how the theories support population health management practice . The following sections of this article discuss the theoretical underpinnings of population health management approaches using these different theoretical perspectives .

INDIVIDUALS : BEHAVIOR CHANGE THEORIES The ability to change individual health behavior using various population health management strategies rests solidly upon the foundations of behavior change theories . When influencing entities are interested in changing unhealthy behaviors and the health risks of individuals within target populations, individual behavior change theories are valuable techniques to encourage appropriate habits, self-care, and informed demand for medical services . This theoretical support is also consistent with the care goals of population health management, especially those of providing individualized, appropriate care that is both directed to populations and tailored to target individuals . Several main theories heavily support health behavior change and health promotion (Elder, Geller, Hovell & Mayer, 1994), and these theories are important in a model of population health management : (1) Health Belief Model ; (2) Theory of Reasoned Action ; (3) Communications-Persuasion Model; (4) Social Learning Theory ; and (5) Field Theory . In addition, the relatively new Transtheoretical Model of Health Behavior Change contributes a temporal dimension to health behavior change models that provides an example of how theory is integrated with practice . These models and their links to population health management approaches are shown in Table 6 and described further below .

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Relationship Between Population Health Management Model, Supporting Theory, and the Role of Information Technology .

Table 5.

Theory Individual Behavior Change Theory:

-Health Belief Model (Becker, 1974 ; Janz & Becker, 1984 ; Rosenstock, 1966, 1974) -Theory of Reasoned Action (Fishbein & Ajzen, 1974) • CommunicationsPersuasion Model (MacGuire, 1964) • Social Learning Theory (Bandura, 1977 ; Elder et al., 1994) -Field Theory (Lewin, 1935, 1951 ; DeRivera, 1976) • Transtheoretical Model of Health Behavior Change (Prochaska et al ., 1992, 1994 ; Prochaska & Velicer. 1997) Integration Theory :

-Differentiation and Integration (Lawrence & Lorsch, 1967) -Vertical and Virtual Integration (Goldsmith, 1994 ; Robinson & Casalino, 1996 ; Robinson, 1997 ; Williamson, 1981)

Rationale for Link to Population Health Management Model

Example Applications

Influencing Entities • Lifestyle Management interested in changing programs such as behaviors and smoking cessation and modifying health risks of weight management to individuals in the Target modify behavioral Population can use risks intervention techniques Demand Management in Population Health interventions to inform Management approaches and improve demand that are supported by for medical care individual behavior services change theories . • Disease Management techniques to encourage appropriate self care and management of chronic illness

Role of Information Technology Information technologies are used to facilitate behavior change by targeting populations and individuals within those populations, tailoring behavior change interventions to individuals, and facilitating communications with the target population .

• Disability Management

programs that use the employer context to develop behavior change interventions

Integration is required • Management of in Population Health complex cases in Management approaches Catastrophic Care to bring together Management that different components of require coordination of medical care services activities among across the continuum of different organizations care and address the cost and care providers of payer and provider though contract-based Influencing Entities and or virtual integration individuals in the Target • Developing a Disease Populations . Management approach for defined populations

Information technologies and information systems play a role in promoting both vertical and virtual integration in population health management practice . Interconnectivity and integrated


1 40

Table 5.

Theory


Continued . Example Applications involves integration of data and information systems to identify target individuals and refer them for needed services .

• Population Health Management programs must create mechanisms for integration so that care is coordinated and appropriate, avoiding redundancy and waste . Organizational Change Theory :

• Classifying • Organizational Change (Kaluzny & Vency, 1997) -Stages of Organizational Change (Smith & Kaluzny, 1986) Enabling Factors for Implementing Change (Kanter et al ., 1992)

Organizational change theories promote the ability of Influencing Entities to make changes in their operations and care processes necessary to incorporate Population Health Management strategies. Theory also supports changes in organizational strategy and culture that are needed when organizations adopt the Population, and Health Management Care Goals of appropriate, individualized and coordinated care for defined populations .

• Delivery of Disease

Role of Information Technology information systems can help facilitate data collection and analysis, coordinate the activities of care management, and help with outcomes measurement.

Information technologies may interventions may be integral parts involve technical of technical changes to use change, can interdisciplinary teams, facilitate integrate information transformational systems, or accomodate change that new information requires monitortechnologies . ing progress • For provider toward Population Influencing Entities, Health transitional change Management Care may be necessary Goals, and play to incorporate an important role approaches such as as enabling factors (supporting Lifestyle Management or Disease Management, structures) in the and to include Care change Goals of Population implementation Health Management . process as • Organizations impleorganizations menting a Demand move towards Management program institutionalization of a Population Management

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Population Health Management in Theory and Practice Table 5.

Theory


Continued. Example Applications will require consideration of the enabling factors for implementing change • In order to institutionalize a Population Health Management approach such as Disability Management, employer organizations must progress through the four Stages of Organizational Change and realize this transformational change .

Role of Information Technology Health Management Model .

The Health Belief Model, developed by theorists such as Becker (Becker,

1974 ; Janz & Becker, 1984) and Rosenstock (Rosenstock, 1966, 1974), rests

on the notion that health behavior is dependent on both individual knowledge

and motivation . In deciding whether to seek care for a medical problem, an

individual's perception of vulnerability to that illness and evaluation of the possible effectiveness of that care become very important. If individuals perceive that they are vulnerable or susceptible to an illness or medical problem, if they

assess this problem as serious, if they believe that the treatment will be effective and not too expensive, and if they interpret some type of cue to act, such persons will act to seek medical care (Elder et al ., 1994) .

The demand management approach to health management relies heavily upon

this Health Belief Model . Specifically, demand management strategies attempt to influence consumer demand for medical care by addressing issues such

as perceptions of the seriousness of a condition . By providing advice and counseling to consumers who are contemplating the decision to seek medical

assistance, demand management programs help direct consumers to the most appropriate level of care that will be both effective and economical .

The Theory of Reasoned Action set forth by Fishbein and Ajzen (Fishbein

& Ajzen, 1975) emphasizes the importance of personal intention to determine

142 Table 6.


Relationship Between Individual Behavor Change Theories and Population Health Management Approaches .

Theory

Population Health Management Approaches Supported

Rationale

Health Belief Model : Health behavior is dependent on individual knowledge and motivation (Becker, 1974 ; Janz & Becker, 1984 ; Rosenstock, 1966, 1974)

• Demand Management

Demand management strategies attempt to influence consumer demand by addressing issues such as perceptions of the seriousness of a condition

Theory of Reasoned Action : Importance of personal intention to determine individual behavior (Fishbein & Ajzen, 1975)

• Lifestyle Management • Disease Management

Lifestyle and disease management approaches provide education about health conditions to influence individual expectations about the consequences of their health behaviors

Communications-Persuasion Model : Public communication is important to support attitudinal and behavioral change (McGuire, 1964)

• Lifestyle Management • Disability Management

Lifestyle and demand management strategies often emphasize communications as an intervention strategy to influence behavior change

Social Learning Theory : Interrelationships among individuals, behavior, and the environment are all important ; self-efficacy and expectations about outcomes affect behavior change (Bandura, 1977 ; Elder et al ., 1994)


Lifestyle, demand, and disease management approaches stress the importance of self-efficacy to promote behavioral changes

Field Theory : Behavior change is considered in the context of an individual's present situation and that individual's needs (Lewin, 1935, 1951 ; DeRivera, 1976)

• Disability Management

Disability management programs start with the employer context as the relevant field from which to understand and change health behaviors

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Table 6.

Theory

Transtheoretical Model of Health Behavior Change :

Six stages of change mark the progress of individual health behavior change : precontemplation, contemplation, preparation, action, maintenance, and termination (Prochaska & Velicer, 1997)

Continued .

Population Health Management Approaches Supported • Lifestyle Management • Disease Management

Rationale Lifestyle and disease management strategies that can match interventions to individual participants' willingness and readiness to change behaviors have demonstrated improvements in health outcomes

Acknowledgement: Thank you to the anonymous reviewer who suggested the format for this table .

whether or not a person will behave a certain way . Here, personal volition, or behavioral intent, depends upon factors such as an individual's expectancies about behavioral outcomes, additional attitudes towards that behavior, and beliefs that individual may hold regarding what peers or others might choose to do in a similar situation (Elder et al ., 1994) . Lifestyle and disease management approaches often use tenets of the Theory of Reasoned Action to support health management strategies . By providing education about health conditions, lifestyle management and disease management programs attempt to influence individual expectations about the consequences of their health behaviors . In addition, by including program elements such as group sessions or videotapes emphasizing peer experiences, the link to this theory is strengthened as such strategies try to change behavioral intent . The third model, the Communications-Persuasion Model, was developed by McGuire (McGuire, 1964) and colleagues and emphasizes the role of public communication such as mass media in attitudinal and behavior change . In this model, the combination of input factors including the source of the message, the message, the message channel, characteristics of the receiver, and the destination of the message can all affect the effectiveness of any communication . Similarly, output factors including the changes an individual is expected to experience upon receiving the communication such as in knowledge, attitude, decision-making, and behavior also affect the results of any efforts at health communication (Elder et al ., 1994) . Many public health promotion strategies rely upon the theoretical foundation of the Communications-Persuasion Model . Population health management

144


approaches such as lifestyle and disability management programs that emphasize communications as an intervention strategy are good examples of this model in practice . Specifically, programs such as smoking cessation or injury prevention that rely on health communications to influence behavior change rest upon the Communications-Persuasion Model . Albert Bandura's Social Learning Theory (Bandura, 1977) emphasizes the importance of interrelationships among individuals, behavior, and the environment. The process of "reciprocal determinism" reflects the influence of both the environment on individual behavior and of the individual person who can act and change that environment (Bandura, 1977) . In addition, concepts such as self-efficacy and expectations about outcome all affect the likelihood of individual behavior change (Elder et al ., 1994) . Many population health management techniques rely upon the foundations of social learning theory in practice . In particular, lifestyle management programs, demand management programs, and disease management programs all stress the importance of self-efficacy as they promote behavioral changes and approaches to self-care that will reduce individual need and demand for medical care services . Field Theory, introduced by Kurt Lewin and colleagues, (DeRivera, 1976 ; Lewin, 1935, 1951) considers behavior in the context of an individual's present situation and that individual's needs . This context is described as the field surrounding the individual, and this field contains different forces that can influence behavior (Elder et al ., 1994) . In population health management, disability management programs are arguably based upon field theory . Given the employer context as the relevant field, programs attempt to understand and change health behaviors within this field . In addition to the strong influence of these main behavior change theories in population health management practice, Prochaska and colleagues Transtheoretical Model of Health Behavior Change (Prochaska, DiClemente & Norcross, 1992 ; Prochaska, Norcross & DiClemente, 1994 ; Prochaska & Velicer, 1997) has received considerable recent attention . In this model, six stages of change are posited that mark the progress of health behavior change : precontemplation, contemplation, preparation, action, maintenance, and termination (Prochaska et al ., 1997) . While criticized because the model is not a true stage theory and seemingly fails to recognize the complexity of human behaviors when it segregates individuals into discrete stages, (Bandura, 1997) this model has nevertheless been widely applied in health practice . Population health management strategies including a health promotion component such as lifestyle management or disease management programs have demonstrated improvements in health outcomes when interventions are


1 45

matched to individual participants' willingness and readiness to change behaviors . The transtheoretical model encourages program developers to distinguish among those participants in the precontemplative stage (40%), those in the contemplative stage (40%), and those in the preparation stage (20%) (Prochaska et al ., 1997) when approaching a behavior change challenge . Smoking cessation programs, as an example, are believed to benefit from delivering different messages about quitting based on participants' stages of willingness and readiness to change . The transtheoretical model has received substantial interest as new information systems and technologies permit the incorporation of branching decision logic into health and care management tools . The combination of such theoretical and technological innovations enables a form of mass customization (Davis, 1996) of communications in the form of tailored messages that can be transmitted via telephone or the Internet, based on individual participant responses to questions about willingness and readiness to change health behaviors .

ORGANIZATIONS : INTEGRATION AND ORGANIZATIONAL CHANGE Population health management approaches are also well supported by organization theory . Integration theory emphasizes the importance of coordination which is critical in population health management . When multiple influencing entities are attempting to improve health and lower costs for differently defined target populations, coordination of the efforts of these multiple payers and providers through care managers is very important . Integration of services and systems establishes a solid basis upon which to provide appropriate care to individual participants, avoiding duplication of services, miscommunications, and medical errors . Organizational change theories are similarly consistent with population health management approaches as they promote the ability of influencing entities to adopt changes in their operations and care processes . Striving towards the population health management goals of appropriate, individualized, and coordinated care for defined populations may require substantial changes in organizational strategy and culture which can be facilitated by the application of these theories . Integration

Organizations such as payer and provider entities face multiple competing challenges to ensure their survival . As described by Lawrence and Lorsch

146


(Lawrence & Lorsch, 1967), two of these central issues are differentiation and integration . Differentiation involves the challenge of an organization or unit within an organization to be distinct from another organization or unit . In contrast, integration involves a level of collaboration among organizations or units, "required to achieve unity of effort by the demands of the environment" (Lawrence et al ., 1967) . Given the differentiation that exists with the multitude of services and programs available to provide patient care, integration within the health care system is frequently absent. However, an ideal approach to population health management requires integration . Collaboration among different organizations and care providers is critical in order to best serve patients in need of population health management services . Integration describes the capacity to bring different components of medical care services together across the continuum of care to improve care and service to patients, and to reduce costs for payers as the value of those care services is maximized (Bazzoli, Shortell, Dubbs, Chan & Kralovec, 1999) . By pursuing the goal of integration in the practice of population health management, care provided is more likely to be both coordinated and appropriate, with less redundancy and waste in treatments . Integration of population health management services within a single organization may be complicated by the presence of multiple clinical units, professional boundaries, and even physical distance . Integration of population health management functions across organizations or across institutions that comprise a multiorganizational entity is even more complex . Accomplishment of such integration across organizations has been described by Goldsmith (Goldsmith, 1994) and Robinson and Casalino (Robinson & Casalino, 1996) as possible through either ownership of the different component services and programs across the continuum or care or through contract-based relationships among organizations . These different alternatives for integration have been described as being ownership-based (Bazzoli et al ., 1999) or vertical (Goldsmith, 1994 ; Robinson et al ., 1996) in contrast to contract-based (Bazzoli et al ., 1999) or virtual (Goldsmith, 1994 ; Robinson, 1997 ; Robinson et al ., 1996) . The benefits of different approaches to integration have been debated with respect to both their cost-effectiveness and financial viability (Bazzoli et al ., 1999) . As described by Williamson, vertical or ownership integration may have fewer transaction costs resulting in lower production costs (Williamson, 1981) . In addition, vertical or ownership integration may have the possibility of achieving economies of scope and scale (Bazzoli et al ., 1999 ; Conrad & Shortell, 1996) that may also reduce business costs . The alternative model of virtual or contractual integration offers the potential for more flexibility


147

in the marketplace as well as increased opportunities to promote learning and build trust among involved entities (Bazzoli et al ., 1999 ; Goldsmith, 1994 ; Kaluzny, Zuckerman & Ricketts, 1995 ; Luke & Begun, 1996 ; Robinson et al ., 1996) . Within a population health management model, both vertical and virtual integration are important . From the perspective of patients, who actually owns the component of the care continuum they need is less important than whether the services they receive are appropriate, individualized, and coordinated . This fundamental need for coordination of services exists whether such services are provided within a single organization or across multiple entities . Requirements for coordination and communication among different care providers recognize that integration, while necessary, may not be contractually or organizationally guaranteed . Instead, virtual integration or the development of a virtual population health management organization to provide oversight for such services, especially when supported by a strong information systems infrastructure, may help patients receive seamless, coordinated care when necessary and appropriate . In practice, integration is critical to ensure proper coordination of services and communications whenever and wherever possible . Fig . 3 illustrates the important role of integration in disease management for diabetics . In this example, multiple influencing entities, multiple sources of information, and multiple sites of care are all important and involved in providing care and service for diabetic patients . Population health management personnel, whether offering lifestyle, demand, or disease management programs to this target population, must coordinate and integrate these multiple factors, supported by information technology, and guided by clear care goals . Theories of integration provide context and guidelines for how integration may be achieved in organizations committed to offering population health management programs and adopting a population health management approach . Organizational Change

Organizational change theories become important when organizations must adapt their standard operating practices to accommodate a population health management approach . Payer organizations who adopt a population health management model may be faced with the challenge of organizing themselves to achieve new goals including improved health, lower medical care costs, and better quality of care for the populations they serve . Provider organizations may already have similar health-related goals, but they may face challenges to orient themselves

148


Target Population : Diabetics

Population Health Management Personnel Work to Coordinate Care and Services Care Manager Diabetes Health Educator • Social Worker Counselor Medical Director

v

Multiple Sites of Care • Physician Office • Diabetes Clinic • Hospital

Program Option :

Lifestyle Management

Program Option :

Disease Management

Program Option :


Multiple Influencing Entities • Payers • Employer • Health Plan • Government • Providers • Primary Care Physician • Endocrinologist • Cardiologist

Multiple Sources of Information and Requirements for Information Technologies • Patient Identification

•

Fig . 3 .

Data Collection and Analysis Remote Care Management and Monitoring Web-based Services and Information Tracking Clinical and Non-Clinical Metrics Provider Communication and Coordination

Integration Facilitates Population Health Management of Diabetes .

towards providing better coordinated, appropriate care to target populations of individuals . A first step in moving organizations towards this population health management model involves classifying the types of change needed for those organizations . Kaluzny and Vency developed a classification scheme for three


1 49

different types of organizational change based upon the different means and ends associated with organizational change : technical change, transitional change, and transformational change (Kaluzny & Vency, 1977) . Using this model, technical change is described as emphasizing change of the means, or the typical activities of an organization, without changing the ends such as the mission or goals of an organization . In this sense, technical change involves changing the workings of structure or process of an organization in order to improve operations or enhance performance . Transitional change concentrates on changes to the ends of an organization rather than changing the means . By changing an organization's goals or products and keeping the structure and process of the organization relatively constant, an organization may attempt to respond to changes in the environment such as consumer expectations or increased competition . Last, transformational change involves changing both the means and ends within and organization . This dramatic type of change affects the entire organization as structure and process are modified in addition to goals and organizational products (Hernandez, Kaluzny & Haddock, 2000) . Organizational adoption of population health management methods may involve all three of these types of change . When organizations attempt to improve operations in ways that include the use of interdisciplinary teams or integration of management information systems to support health management approaches, these changes are mainly technical . However, adoption of a population health management model for a health care organization interested in developing or emphasizing population health management functions may instead involve a transitional change with a redefined mission and goals for the organization . Similarly, a payer entity interested in promoting the value of health and care management for its defined population may require transitional change to reflect new organizational values . Finally, transformational change is also possibly necessary for both payer and provider entities . If hospitals or other health care organizations redesign themselves to operate as health care systems (Shortell, Gillies & Devers, 1995) and adopt a patientcentered population health management model, this reorientation will likely involve transformational change . Similarly, for employers who sincerely adopt a disability management approach, this process will likely involve transformational change . After classifying the type of organizational change required to accommodate a population health management approach, the process of change for that organization is typically complex . Smith and Kaluzny have described a model of change or innovation that involves four distinct stages (Smith & Kaluzny, 1986) : awareness ; identification ; implementation ; and institutionalization .

150


Ideally, this change model is applied sequentially with a change or innovation proceeding from one stage to the next in the process. Bypassing steps such as moving immediately to implementation of an organizational change without first developing awareness of an opportunity or need for change and then identifying the solutions this change represents can lead to problems with institutionalization and integration of the change into the organization (Smith et al ., 1986) . Figure 4 shows how a population management strategy can be institutionalized in a health care organization to attain the care goals of population health management . In practice, implementation of an organizational change such as adoption of a population health management approach can be very difficult. Kanter and colleagues describe six factors that can enable change in their discussion of the change implementation process : pace ; scope ; depth ; publicity ; supporting structures ; and who will be driving the change process (Kanter, Stein & Jick, 1992) . Table 7 highlights some of the crucial questions to consider in this implementation process . Effective implementation of organizational change will be reflected in institutionalization of a population health management model that supports the goals of individualized, appropriate, and coordinated care for the defined populations served by that organization .

Table 7.

Enabling Factors to Support Implementation of a Population Health Management Model .

Pace • How quickly can this model be implemented? • How quickly have other programs been implemented in the past? Scope • How broadly will this change affect the organization? • Is change technical, transitional, or transformational? Depth • What changes will be required in operations? Clinical practice? • How will this change affect professional turf? Publicity • How will this change be communicated? Publicized? Marketed? Supporting Structures • What information systems and information technologies are needed? • How are resources going to be allocated or reallocated? Change Drivers • Who is driving this new program and organizational change? • At what level are these individuals in the organization? Source: Adapted from Kanter et al ., 1992 .


151

Identification Awareness

• Opportunity for a population health management approach

• Fragmentation of the health care system • Focus on acute care • Bias toward treatment based on organ systems • Problems resulting from lack of coordination

I

• Perspective • Defined Population • Options available : • Lifestyle Management • Demand Management • Disease Management • Catastrophic Care Management • Disability Management

v

Institutionalization

• Coordinated, seamless system of care • Focus on individual needs within population groups • Appropriate care provided : • At right time • At right level • By right people • At right place • To right patients

Fig . 4.

Implementation

• Align financial incentives • Determine reimbursement • Develop/enhance information system capabilities • Design evaluation metrics • Improve communications • Resolve professional turf issues • Reallocate organizational resources

Institutionalization of a Population Health Management Model .

Source : Adapted from Smith and Kaluzny's Four-Stage Model of Organizational Change, 1986 .

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CONCLUSION : PROMOTING A POPULATION HEALTH MANAGEMENT MODEL Population health management approaches such as those described in this article can play an important role in the health services sector . Properly designed and implemented, these strategies can help to improve health and quality of care while reducing medical expenses for defined populations of individuals . Optimally, population health management approaches can be applied in the context of a model that encourages consideration of the needs of individuals to receive appropriate and coordinated care from the health care system overall . In practice, an integrated population health management model is difficult to implement . Traditionally, health services have focused on providing acute care, and hospital organizations play a central organizational role . This traditional medical care delivery approach is also reflected by the organization of health services, largely along the lines of individual organ systems . Patients with heart problems see a cardiologist while patients with lung problems see a pulmonologist . Internists, pediatricians, and general surgeons may address a wider range of care needs, but diagnosis and treatment of disease still typically progresses by organ system . A population health management model of service delivery requires a holistic focus on patients and their health and medical care needs . Patients with heart problems may, indeed, need attention from cardiologists, but their problems may be due to lifestyle issues such as poor eating habits, and their specific heart problems may be more due to comorbid conditions such as diabetes that also need to be addressed . Moving beyond an acute care focus on individual organ systems to a population-based health management approach that tailors its focus for individuals may require major organizational changes . Developing and implementing population health management programs can be extremely complicated . Challenges such as ensuring physician involvement, mastering organizational politics, and resolving financial and regulatory issues affecting incentives and reimbursement are considerable. Defining target populations for focus may involve issues of professional turf and questions of resource allocation amongst competing programs that could serve this group of individuals . Within a well-defined population, selecting among alternate population health management strategies may be difficult . However, even with an identified target population and selected strategy, operational issues such as cooperation, communication, and coordination can be problematic . Fig . 5 highlights some of the key success factors involved in defining, designing, implementing, and evaluating a population health management approach .


Definition • • • •

Perspective Target Population Population Health Management Approach Program Goals

U

Design

• • • • •

Key Change Drivers Physician Involvement Reimbursement Strategies Aligned Financial Incentives Integration Strategies and Structures

• • •

Resource Allocation Communication Strategies Information Technology Investment, Enhancement Professional Cooperation Population Health Management Strategies Organizational Change Management Processes

Implementation

• • •

v

Evaluation • • •

Fig . 5.

Appropriate Functional, Parameters whom?) Continuous

Metrics (Financial, Clinical, etc .) of Evaluation (How often? By Quality Improvement Process

Success Factors for Population Health Management Program Development .

153

1 54


Demand Management

Disease Management

Lifestyle Management Catastrophic Care Management


Coordination of Care and Providers

Individualized Care and Services

Appropriate Care : • Demand • Referrals • Treatment

Population-Based Health Care

Quality of Care

Clinical Outcomes Fig . 6. Population Health Management Strategies Promote Quality of Care .


155

Evidence is established and growing to support the multiple component parts of a population health management model . However, research opportunities abound to determine how to best implement this model . Is integration of health management programs operationally and clinically possible? Assuming clinical integration of services is possible, how is it best achieved? How can organizations design open architectures for information systems that permit interconnectivity and integration of multiple data sources on different information system platforms? When population health management initiatives are extra-organizational, how can they best promote change within provider and payer entities? What types of influencing entities are most successful at promoting what types of individual health behavior change`? How are population health management programs best managed to enhance participation and coordination among both influencing entities and target populations of individuals? Answering these questions and many others can help promote the design, development, and implementation of a practical health management model that is both managerially feasible and clinically appropriate . Concentrating on the care goals of population health management helps programs to truly improve quality of care, as illustrated in Fig . 6 . Integrated service provision helps ensure continuity of care, reduces waste and duplication, and improves service quality . Information technologies help operationalize strategies by supporting data analysis, patient monitoring, and outcome measurement . Ideally, population health management approaches can be implemented to promote improvements in both clinical and financial outcomes while reducing inappropriate variation and medical errors . The ultimate goals of better individual and population health and wellness can then be achieved .

ACKNOWLEDGMENTS The author sincerely appreciates the dedicated support of the co-editors of this volume, Grant T . Savage, Ph .D ., Myron D . Fouler, Ph .D ., and John D . Blair, Ph .D ., as well as the enthusiastic encouragement of her colleague, Stephen Strasser, Ph .D . She is especially grateful to the editors and to two anonymous reviewers who provided invaluable suggestions to improve this article .

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EMOTIONS, THE NEGLECTED SIDE OF PATIENT CENTERED HEALTH CARE MANAGEMENT: THE CASE OF EMERGENCY DEPARTMENT PATIENTS WAITING TO SEE A PHYSICIAN Laurette Dube, Lefa Teng, Josiah Hawkins and Marilyn Kaplow

ABSTRACT The thesis of this paper is that patient emotions have not been sufficiently integrated into patient-centeredness, a well-established organizing principle of health care management . We first review the scientific knowledge on emotions that is of relevance to support their being a core component of patient-centeredness . We then report afield study designed to investigate the mechanisms by which emotions influence care outcomes (specifically, patient satisfaction) . Structural analyses performed on self-reports by 283 minor care patients in an Emergency Department revealed that both positive and negative emotions influence satisfaction indirectly by biasing patient perceptions of quality of care in a valence-congruent direction .


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Negative emotions have an additional direct effect on satisfaction . Patients who were made to wait longer to see the physician not only manifested a progressive deterioration of their emotional states (i.e. decrease in positive affects and increase in negative affects) but their satisfaction judgments became more importantly formed on the basis of emotions . Implications of the research for healthcare management are discussed.

INTRODUCTION Patient-centeredness as a basic organizing principle for care and health care management has steadily gained a broader acceptance over the last couple of decades . Clinicians have adopted a style of interaction that take into account the patients' preferences and perceptions, encouraging shared decision making and participation in their own care . There are also new models of care that explicitly place patients at the center of complex evaluation and specialized treatment plans . On the health care management side, number of managers and policy makers from the public and private sectors have given themselves the challenges of redesigning processes and delivery systems to provide a seamless, patientcentered continuum of care that integrates generalist and specialist cares to family and community support when appropriate (see Institute of Medicine, 2000, 2001) . Finally, accreditation criteria and quality management programs call for the solicitation of consumer feedback in terms of their expectations and perceptions of quality on various dimensions of care like reliability, responsiveness, assurance, or empathy (Safran et al ., 1998 ; Sower et al ., 2001) . Typically, the contribution of these dimensions to the overall perception of quality of care and satisfaction is estimated and satisfaction serves as a key patient outcome in quality management (Bowers, Swan & Koehler, 1994 ; O'Connor, Trinh & Shewchuk, 2000 ; Ford, Bach & Fouler, 1997 ; Sower et al ., 2001) . These relative great strides made in centering health care and its management on the patient, albeit far from having become routine practice (Holman, 2000 ; Laine & Davidoff, 1996), have paid off in several ways . Studies have demonstrated that clinicians who enroll patients in their care decisions and management, in particular in the context of chronic diseases - compared to those who don't - have better outcomes in terms of patient satisfaction, health status, as well as service utilization (Barry et al ., 1995 ; Greenfield et al ., 1985, 1988 ; Lorrig et al ., 1999 ; Wagner et al ., 1999 ; Wagner et al ., 2001) . Moreover, the degree of trust a primary care physician succeeds in inspiring in patients has been found significantly predictive of individuals' willingness to attempt necessary lifestyle changes (Cooper-Patrick et al ., 1999 ; Safran et al ., 1998) .

Emotions, The Neglected Side of Patient-Centered Health Care Management

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Positive effects of patient-centeredness can also be cited for quality management . Research has shown that more positive patient perceptions of quality of care are related to higher satisfaction and intention to use the service again in the future if necessary (Bowers, Swan & Koehler, 1994 ; O'Conneor, Schewchuck & Bowers, 1992 ; Taylor & Baker, 1994 ; Woodside, Frey & Daly, 1989) . Perceptions of high quality of care and high patient satisfaction have also been found predictive of compliance with advice and treatment regimens (Hulka et al ., 1976), choice of provider plan and malpractice law suits (Brown, Bronkesh, Nelson & Wook, 1993), as well as health outcomes (Elbeck, 1987) . A limited number of studies that have focused on the for profit sector of the industry have found that high levels of patients' perceived quality of care are positively related to an organization's financial performance (Koska, 1990 ; Nelson et al ., 1992 ; Press, Ganey & Malone, 1991) . What is striking in reviewing prior research and practice on patientcenteredness in the provision of health care and its management, is the exclusive focus on the cognitive, rational side of the patient, be it in the various models of care that posit a highly involved, information-thirsty, and rational consumer, or in quality management programs that rely on dimension-specific or overall quality perceptions, all cognitive judgments . This focus on the rational is evidenced in two recent reports from Institute of Medicine (2000, 2001), which underscore the need to apply patient-centered care more broadly . When the various dimensions of patient-centeredness are addressed, these include customized information, coordination and integration of care across conditions and settings and over time, shared decision-making of clinicians with patients and families, self-management skills, etc . No mention is made that patient-centeredness may entail the patient's emotional side, which potentially could also be assessed and integrated when care is designed and delivered, or health care processes and systems are managed . Yet, we all know that the rational side accounts for only part of a person's decisions and behavior . Viewed from the rational perspective, a person's decisions and actions are based primarily on logic applied to the deliberative consideration of relevant information and potential outcomes of the various options . In other words, from this perspective, patients make judgments and behave on the basis of their conceptual understanding of their health problem and its solution(s), consciously using information provided by the clinician, in conjunction with knowledge of themselves and their environment, to make judgments and behave in the most effective way to manage their health . However, in many instances, judgments, choices, and behaviors do not rely on a conceptual understanding of a situation, but are instead based on the emotions it arises . Emotions are positive and negative feeling states that signal the

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occurrence of events that are relevant to important goals (for a review see Oatley & Jenkins, 1992), motivating those who feel them to act in a certain manner and others to respond in a given way (Carstensen & Turk-Charles, 1994) . If emotions are fundamentally about motivation and actions, i .e . positive and negative feelings, readiness or tendency to cope, and cues for cognition and behaviors (Izard, 1993), it is urgent that they be considered if the focus of care organization and management is actually to influence individuals' decisions and actions . Thus, for the patient-centered approach to become more complete, it is important to understand better how the rational, cognitive side of the patient is complemented, sometime substituted for, even competed with on certain occasions, by the experience of a variety of positive and negative feelings . In fact, the necessity of systematically building patient emotions into the design and delivery of care may become highly pressing since much of health care demand is getting driven by an aging clientele suffering from chronic diseases, with the performance of appropriate health-maintaining or healthrestoring behaviors being performed by the patient (or his/her social support environment), outside of traditional health care institutions . There is now robust evidence showing that with increasing age, emotions may become more powerful than rational knowledge as a motivator to act (Carstensen & TurkCharles, 1994 ; Gross et al ., 1997 ; Labouvie-Vief, De Voe & Bulka, 1989 ; Levenson et al ., 1991 ; Leventhal, 2000) . Until now, formal consideration of patient emotions in the delivery of care has consisted primarily of formal psychotherapeutic interventions prescribed when negative emotions are felt at a clinical level . As part of the "art of care," health professionals also apply some general display rules to help patients cope with negative emotions in the course of severe diseases (Frazier, 2000 ; Holahan et al ., 1997) or highly stressful medical interventions or diagnostic procedures (Anderson, 1987 ; Anderson & Masur, 1983 ; Devine, 1992 ; Suls & Wan, 1989) . Yet, numerous health conditions, medical procedures, or diagnostic tests, which would not necessarily qualify as sufficiently severe or stressful to require formal psychological or psychiatric interventions, are often perceived by the person as threatening, and therefore induce negative emotions (Lykouras et al ., 1989 ; Markel, 2000) . Research shows that such negative emotions not only impair a person's subjective well-being, but most importantly may have deleterious consequences on health and the outcomes of healthcare (Dracup et al ., 1995 ; Everson, 1997) . Therefore, there is a need to expand the organizing concept of patientcenteredness, beyond its current view of the patient as a uniquely rational, cognitive being, to include emotions and their impact . In the context of health care services which require the presence of the patients on premises for care


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to be provided, an in-depth understanding of how positive and negative emotions arises as the process unfolds, be it during waiting times or during service delivery proper, could be highly useful . Research suggests that providers can pick up cues from patient emotions and use these to fine tune the quality of their care, in a way that helps patients deal successfully with their negative feelings, thereby inducing higher satisfaction (for a review, see Dube, in press) . In service industries like healthcare, the engineering of provider responses to the client's emotions is important because what is being "produced" has an intrinsic human component and, being produced at the same time as it is consumed, post-hoc quality control on this aspect of the client's experience are relatively useless (Dube, Johnson & Renaghan, 1999) . Thus, understanding, measuring and monitoring patient emotions may be necessary to support the design of new care processes or the reassessment of existing ones, in a manner that is fully patient-centered and operationally effective as well . The contribution of this paper is twofold . First we review the scientific knowledge on emotions that is of relevance to the understanding of what patientcenteredness may mean if one focuses on the emotional side of the patient . Second, we report a study designed to investigate the mechanisms by which emotions influence care outcomes (specifically, patient satisfaction) . We investigated emotions experienced by minor care patients who had waited different lengths of time before seeing the physician in an Emergency Department (ED hereafter) . In addition to their emotions, patients reported their perception of the overall quality of care and satisfaction with the services they had received during their visit to the ED . Research propositions are made for the direct and indirect ways in which patient emotions influence satisfaction, and for an increase in the strength of this impact as waiting time increases . The remaining of the paper is organized as follows : We first review the existing literature about patient emotions and their impact on health-related information processing, decision making and behaviors, as well as on other care outcomes . We then present the research propositions as to the influence of patient emotions on satisfaction . Finally, we discuss how the results contribute to a patientcentered approach to health care management research and practice .

PATIENT EMOTIONS AND EVERYDAY DELIVERY OF CARE The Nature of Patient Emotions

In the literature, emotions have been conceptualized and operationally defined in two ways, i .e . either by a taxonomy of discrete primary emotions, such as

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joy, sadness, and fear (e .g . Izard, 1977), or as a limited number of basic dimensions such as pleasure/arousal (e .g. Russell, 1980) or positive/negative affects (e .g . Watson & Tellegen, 1988) . Both approaches to emotions can be found in research within the specific context of health and healthcare services : Considerable amount of health research has been directed at specific emotions like depression (e .g . Meeks, Murrell & Mehl, 2000 ; Spencer, Tompkins & Schulz, 1997) and anxiety (e .g . Calvo & Miguel-Tobal, 1998 ; Martelli et al ., 1987) as being both potential contributors to health, and potential outcomes of various pathologies and health care interventions . Work along the second view of emotions, i .e . the dimensional approach, has focused primarily on the positive/negative affect representation such as the assessment of the structure and variation of the emotional experience attached to specific diseases (e .g . Shifren et al ., 1997), or the estimation of the relationship between positive and negative affects and the experience and reporting of physical symptoms (Brown & Moskowitz, 1997 ; Diefenbach et al ., 1996 ; Watson & Pennebaker, 1989) . There is direct and indirect evidence showing the impact of emotions on a person's health-related information processing, decisions and behaviors, as well as on other outcomes of care . When individuals are emotional, they do not attend to and remember the same dimensions of external stimuli as they do in more neutral states (Brett-Halberstadt & Niedenthal, 1997 ; Dube & Morgan, 1996 ; Metcalfe, 1998 ; Niedenthal & Brett-Halberstadt, 1995) . For instances, research has shown that anxiety impairs processing efficiency in general (for a review, see Eysenck & Calvo, 1992), and that individuals experiencing anxiety (Byrne & Eysenck, 1995), anger (Averill, 1980), or depression (Dalgleish & Watts, 1990) at non-clinical level detect the negative dimensions of a stimulus more quickly and remember more of them than its neutral or positive content . Normal elderly seem to be more vulnerable than the normal young to the adverse effects of negative emotional states on memory processes (Backman & Molander, 1986 ; Deptula, Singh & Pomara, 1993) . Turning to the impact of emotions on decision making and behaviors, it is also supported by abundant research . For instances, research shows that anxiety and fear that arise at the onset of certain diseases (see Dracup et al ., 1995 for the case of heart attack) may cause patients to delay seeking treatment, even when it is known that optimal efficacy of care is related to earlier intervention (Cooper et al ., 1986 ; Maynard et al., 1989) . Negative emotions in general have been found to be related to negative outcomes like poorer health status (Croyle & Uretsky, 1987 ; Hemenover & Dienstbier, 1998 ; Salovey & Birnbaum, 1989) and more symptom reporting (Brown & Moskowitz, 1997 ; Diefenbach et al ., 1996 ; Costa & McCrae, 1987 ; Watson & Pennebaker, 1989) . Researchers have also found that the experience of anger, whether silently suppressed or expressed


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blatantly, is generally accompanied by potentially harmful physiological responses, such as increased blood pressure (Dembroski et al ., 1985 ; Everson, 1987) . In sum, the research reviewed above show that positive and negative emotions bias perception, memory, and judgment in a valence-congruent direction and significantly impact various objective indicators of disease morbidity and mortality as well as health status . Thus, patient emotions clearly present a considerable potential for interference - or for synergy - at various points in the normal flow of the everyday delivery of health care, and not just within the limited context of psychotherapeutic interventions in extremely severe and highly stressful medical conditions . Moreover, patient emotions may have even stronger effects on more subjective indicators of outcome quality of care, like satisfaction . In the next section, we present a model for the mechanism by which patient emotions influence satisfaction, the focal care outcome in the present study .

A MODEL OF THE ROLE OF EMOTIONS IN SATISFACTION Satisfaction reflects the evaluative summary of one's experience with the services received (Oliver, 1997) . Of all measures of outcome quality of care (Donabedian, 1988), patient satisfaction is the most immediate channel through which patients can express their appreciation of the services they receive (Weisman & Koch, 1989) . In addition, there is robust evidence that patient satisfaction is a predictor of health-related behaviors like compliance and continuity of care (Pascoe, 1983 ; Pascoe, Atkinson & Roberts, 1983) . In Fig . 1, we present the structural model we used for mapping the direct and indirect ways in which patient emotions influence satisfaction, and how these are sensitive to the time spent waiting to see the physician . Before addressing the mechanisms of influence of patient emotions on satisfaction judgments proper, it is important to note that in the present research, we adopt the positive/negative dimensional approach to represent patient emotions . In this approach, patients provide self-reports of intensity or frequency of experience of a set of positive and negative emotions that are submitted to data reduction techniques, generally unravelling two weakly correlated, valencebased factors (e .g . Dube & Morgan, 1996, 1998 ; Brown & Moskowitz, 1997 ; Watson, Clark & Tellegen, 1988) . In Western countries, reports of negative emotions tend to be less intense than those of positive emotions, even within the health care context . For instance, in their monitoring of emotions for acute-care patients, Dube and Morgan (1996, 1998) observed on the first day

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w O A

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b


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of hospitalisation an average of 3 .97 (out of a 7-point scale) for positive

emotions compared to 1 .94 for negative emotions . A similar make-up of emotional experience, with natural dominance of positive over negative affect,

and relative independence of the two dimensions, has been found in other aver-

sive contexts, such as suffering from chronic diseases with disability (Shifren

et al ., 1997) or waiting in an airport (Taylor, 1994), as well as in the course of daily life (Brown & Moskowitz, 1997) .

Direct and Indirect Effects of Patient Emotions on Satisfaction Prior research in the health domain has shown that patient satisfaction stems primarily from one's perception of the quality of care being received, with

higher quality leading to higher satisfaction (Donabedian, 1988 ; Pascoe, 1983 ; Pascoe, Atkinson & Roberts, 1983) . This relationship is formalized in the QS link in Fig . 1 . The model posits that a first, indirect manner in which positive

and negative emotions influence satisfaction, is by coloring the patient's percep-

tion of quality of care in a valence-congruent direction, i .e . as more intense

positive (negative) emotions are experienced, one perceives higher (lower)

quality of care, which in turn influences satisfaction . These relationships are

represented in Fig . I by the NQ and PQ links . In addition to the studies cited earlier showing that emotions bias perception, memory, and judgment in a

valence-congruent direction, such biasing effects have also been demonstrated for general positive and negative affective states in a diversity of contexts (Bradley & Lang, 1999 ; Mano, 1992 ; Ottati & Isbell, 1996) . Moreover, because research has shown that positive emotions, more so than negative emotions, trigger non-differentiated, heuristic processing of information, we expect that this indirect influence on satisfaction will be particular strong for positive

emotions . Biasing effects are especially likely under heuristic processing (for a review, see Schwarz, 1990) .

If positive and negative emotions are likely to influence satisfaction through

the indirect route described above, research also suggests that, in addition,

negative emotions may have a direct effect on satisfaction (NS link) . Research in the consumer domain (for a review, see Oliver, 1997) has shown that satisfaction does not only stem from one's perception of the quality of perfor-

mance, but also from various aspects of one's experience, such as prior expectations and the degree to which they are fulfilled by the performance, the

sense of equity and, of interest here, causal attributions . Negative emotions are associated with detailed, analytical processing, with a spontaneous focus on searching for the causes underlying the negative emotions and its corresponding

implications (Peeters & Czapinski, 1990) . Research has shown that individuals

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are not always perfectly accurate in their assesment of causal attributions for various dimensions of their subjective experience, in particular emotions (Ottati & Isbell, 1996 ; Schwartz & Clore, 1988 ; Weiner, 1985) . Therefore, even if the negative emotions that accompany an actual or prospective illness may have nothing to do with the provision of healthcare, when these are experienced in the service facility, these, rightly or wrongly, may be attributed in part to the provider and thereby, inversely and directly influence satisfaction . This relationship is represented in Fig . 1 by the NS link . Waiting Time Effects Because many healthcare services are produced and delivered in presence of the patient, it is important to better understand how the make up of patient emotions and their relationships to satisfaction evolve as time elapses in the actual delivery of care . In this regard, variations in the amount of time patients had to wait to see the physician (i .e . to receive the core of the health service) is of particular relevance because it enables the development and testing of predictions that can be based on theoretical grounds . Building on Kurt Lewin's (1943) field theory, researchers in the area of services management (Hui, Thakor & Gill, 1998 ; Dube, Schmitt & Leclerc, 1991) have suggested that waiting at an early stage of the process, before the core of the service has been delivered, is a particularly aversive event because it blocks one's movement toward the achievement of the goal of the service transaction . The longer the barrier on the way towards the goal, the more frustration and other negative emotions arise and the more one's attention is focused on this aversive experience . Similar inference on the sensitivity of the emotional experience to the duration of aversive conditions can be made from results of research on escalation in response to persistent annoyance (Berkowitz, 1989 ; Mikolic, Parker & Pruitt, 1997) . Therefore, as the length of time spent waiting to see a physician increases, the patient's emotional experience will deteriorate in terms of less intense positive emotions and more intense negative emotions and will also result in more negative perception of quality of care and lesser satisfaction . These are represented in Fig . 1 by the links WN, WP, WQ, and WS . Moreover, it is also likely that the contribution of emotions as a predictor of satisfaction judgments will increase significantly over time . Research in social psychology (Brett-Halberstadt & Niedenthal, 1997 ; Epstein, 1994 ; Epstein et al ., 1992 ; Kirkpatrick & Epstein, 1992) and neuroscience (Bechara et al ., 1997 ; Damasio, 1996) suggests that as subjective experience becomes highly emotion-laden, conscious and unconscious processes may be operating in shifting one's judgments, decisions, or behaviors away from being based on


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rational processing of information to, what has been called, experiential processing, i .e . less reflective decisions and actions based on gut feelings and emotions . In other words, the more intense the emotions become, the more the judgments become made on an emotional basis, with lesser exclusive consideration of the declarative information (e .g . perception of quality of care in the present case) . This suggests that with an increase in the waiting time to see the physician, the proposed relationships between positive (indirect) and negative (direct and indirect) emotions and patient satisfaction should all become stronger than those observed with a shorter waiting time .

METHODS Study Population

The study population consisted of minor care patients in ED . In most ED in North America, minor care patients are those patients considered as not having critical, life-threatening injuries . A normally healthy person with an upper respiratory tract infection, or a person who cut his/her finger and needs some stitches, are examples of minor care patients . Minor care patients are generally discharged after having seen the physician . Considering the objective of the present study, this population presents numerous advantages : (1) emergency care is intrinsically emotion-laden ; (2) minor care patients are given relatively low priority compared to critically ill or injured ED patients, and therefore are susceptible to significant and variable waiting time, during which emotional states are likely to change over time ; (3) the whole care episode (i .e . the visit at ED) is relatively constrained in time and space, thereby providing a relatively controlled environment for the study of emotions and their impact on satisfaction . Study Setting

The study was conducted at two sites of the ED of a major university health care center located in down town Montreal, Canada .' Only patients assigned to the minor care category were eligible to the present study . Upon arrival through the walk-in entrance or via ambulance, a triage process determines the level of medical priority of a patient . Patients are broadly triaged in three categories : advanced care, minor care or psychiatric care . Minor care patients then sit in the waiting area specifically assigned to minor care until they see the physician . The focus of the present research is on the time spent into the emergency department, up to the point when they get to see the physician . Research has shown

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the length of this waiting time, more so than the overall duration of the visit, is critical to patient satisfaction (Yarnold et al ., 1998 ; Thompson & Yarnold, 1995 ; Thompson et al ., 1996a, b) . In fact, Bursch, Beezy, and Shaw (1993) found that the length of waiting time before receiving medical care be the factor that matters most in accounting for variability in patient satisfaction with ED . Patient Selection, Sample Description, Procedure, and Survey Instrument Patient Selection and Sample Description The study was conducted over a 4-week period, and was presented to the ED patients as "Patient Satisfaction Month ." Posters were drawn up in various areas of the ED, announcing the study . Eligible patients were those assigned by the triage nurse to the minor care category having to see a physician . Minors less than 14 were excluded, as were advanced care patients, patients who would be admitted to the hospital, and psychiatric care patients . A total of 283 patients completed the survey . The profile of the respondents is presented in Table 1 . As can be seen, women were present in a larger proportion than men (58% versus 42%), while the sample spreaded itself relatively evenly across all age categories . The sample was well balanced in terms of the day of the week and the time within a day that patients had been visiting the ED . The profile of the sample was reflective of that of the ED clientele . Table 1 . Variavble

Sample Description .

N (Total Sample = 283)

% Frequency

Age

14-30 31-45 46-60 61+

90 92 48 53

32% 33% 17% 18%

Gender

Male Female

119 164

42% 58%

34 31 95 37 86

12% 11% 34% 13% 30%

99 115 69

35% 41% 24%

Day of Arrival at ER Monday Tuesday Wed/Thurs Friday Sat/Sun Time of arrival at ER 4 p.m .-8 a.m . >8 a .m .-Noon >Noon-4 p .m.


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Procedure The questionnaire, presented with a cover letter, was attached to the patient's paperwork by the triage nurse and transmitted to the minor care nurses in the minor care area of the ED . These distributed the questionnaires to the patients in the examination rooms and patient completed the questionnaire after they saw the physician . The questionnaire took an average of 10 minutes to complete, and patients deposited their questionnaire in clearly identified boxes on their way out. Survey Instrument In addition to personal and contextual information presented in the sample description, the variables measured in this study fall into four categories : emotions, patient satisfaction, perceived quality of care, as well as perceived waiting time before seeing the physician . Patient emotions were measured using a 5-point scale to indicate to what extent they had felt each of a set of emotions during their visit at the ED (anchored by "not at all" to "extremely so") . Scale items were selected from prior studies on patient emotions in the health care service systems (Dube et al ., 1996) and their appropriateness to an ED setting was validated in a pre-test . A larger list of items (14 in total) was included in the questionnaire to ensure that a sufficient number of items would be used to operationalize the constructs after the purification of unreliable items (Anderson & Gerbing, 1988) . Principal Component Analysis revealed a two-factor structure that accounted for 56 .51 % of the variance . Negative emotions emerged as the most salient factor (eigenvalue = 3 .94) with a second factor of positive emotions (eigenvalue = 1 .72) . Only items with high loading on one factor and low loading on others were kept for subsequent analyses . The final sample of items was composed of 10 items (loadings ranged between 0 .62 and 0 .81 and between 0 .75 and 0 .83 respectively for negative and positive emotions) . Items for negative emotions were: feelings of depression, worry, anxiety, discouragement, distress, tension and suspicion . Positive items were : optimist feeling, feeling of comfort, and feeling of being respected as a person . The multi-item scales of negative emotions (alpha = 0 .85), positive emotions (alpha = 0 .68) and patient satisfaction (alpha = 0 .85) presented good reliability (Nunally, 1977) thus individual average scores were computed for descriptive analysis and original items were entered as indicators in structural analyses . Patient satisfaction was assessed at the overall level, by a 2-item 5-point scale . Patients indicated how satisfied they were with (scale anchored by "very dissatisfied"-"very satisfied") and how they felt about (scale anchored by "terrible"-"delighted") the services they received in the visit at the ED (Oliver, 1997 ; Pascoe, 1983) . Perceived quality of care was assessed on a 5-point single

1 74


item scale anchored by low/high quality (Donabedian, 1988) . Such measures of perceived quality of care and patient satisfaction at the overall level and using single-item scales or scales with a limited number of items is frequently used in field study in various healthcare services to provide valid assessment of patient judgments while reducing patient burden to its minimum (for reviews see Pascoe, 1983 ; Pascoe, Atkisson & Roberts, 1983 ; for studies in ED, see Krishel & Baraff, 1983 ; Yarnold et al ., 1998) . Perceived waiting time before seeing the physician was measured on a 5point scale anchored by 0-1 hour and > 5, with reference times being provided for intermediary points of the scale . Perceived waiting time before seeing the physician was used in two ways in data analyses . The original 5-point scale was used as a continuous ordinal variable in the aggregate structural analysis . It was transformed in a 3-level categorical variable reflecting the length of waiting time (short, 0-1 hour, N = 118 ; moderate, > 1-3, N = 129 ; long, > 3, N = 36) for analysis of variance in mean comparisons, and for the multi-sample and group-level structural analyses .

RESULTS Descriptive Statistics

For the sample as a whole, patients reported negative emotions at a relatively low intensity (M = 2 .05) and positive emotions at a moderate intensity (M = 3 .29) . Consistent with prior research (Dubr & Morgan, 1996, 1998 ; Warr, Barter & Brownbridge, 1983 ; Watson & Tellegen, 1988), positive and negative emotions were significantly but weakly correlated (r = - 0 .23, p < 0.01) . Perceived quality of care (M = 4 .02) and patient satisfaction (M = 4 .25) were reasonably high . Analyses of variance revealed no significant effects on any of the four patient responses for gender and age (all p-values > 0 .13) . As contextual variables, both time of arrival and day of the visit significantly influenced perceived quality of care and patient satisfaction (time of arrival: F[4, 278] _ 2 .83, p < 0 .05 and F[4, 278] = 3 .22, p < 0 .05 respectively for quality of care and satisfaction ; day of the visit : F[4, 278] = 2 .94, p < 0 .05 and F[4, 278] = 2 .88, p < 0 .05 respectively for quality of care and satisfaction) . However, a-posteriori Sheffe's comparisons failed to find any significant difference at the p < 0 .05 level in pairwise comparisons between periods of arrival . For differences by day of the week, for both measures, Monday was the day of the week with the lowest evaluative rating (M = 3 .68 and M = 3 .96 respectively for quality of care and satisfaction), reaching significance on a pair wise basis in a posteriori comparison to Friday, when patients reported the highest perception of quality


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of care and satisfaction of the whole week (M = 3 .98, and M = 4 .26, respectively for quality of care and satisfaction) . Interestingly, these differences in patient responses as a function of the day of the visit were observed even though the amount of time people reported having waited for the physician did not vary across days (p > 0 .60) . Albeit not reaching standard statistical threshold of significance, the pattern of variation in positive and negative emotions was valence-congruent with that observed at a significant level for perceived quality of care and satisfaction, i .e . more intense positive emotions and less intense negative emotions tended to be reported by patient in these contexts in which perceived quality of care and patient satisfaction were higher . The Relationships Between Emotions and Patient Satisfaction Predictions bearing on the direct and indirect (via perceived quality of care) effects of emotions on patient satisfaction were tested in a structural analysis conducted at the aggregate level (see Fig . 1) . In addition to the theoretical predictions, we also included a direct link between positive emotions and satisfaction to validate our assumption that this relationship would be non significant . This analysis also included waiting time as a continuous measure to test first the proposed relationships while controlling for the effect of waiting time . Analyses were performed using the maximum likelihood method, with EQS software (Bentler, 1992 ; Barbara, 1994) . Assessment of overall model fit was based on : (1) comparison of fit with reference indices which for the present sample size consisted of Bentler-Bonett non-normed fit index, NNFI, and the comparative fit index, CFI, (Bentler, 1990 ; Hu & Bentler, 1995) ; and (2) on acceptability criterion for chi-square (less than three times the number of degree of freedom, Carmines & McIver, 1981) . Results of the aggregate-level structural analysis showed a very good performance of the model (NNFI = 0 .91 ; CFI = 0 .93), with a chi-square of 185 .87 (df = 68, p < 0 .001) . These results suggest that the observed structure is consistent with the proposed network of relationships between emotions and satisfaction . Table 2 presents the standardized parameters of the relationships included in the structural model with their corresponding t-values . The examination of the standardized loadings of the variables to their respective constructs revealed an appropriate dimensionality of all multiple-indicator constructs included in the model . All hypothesized paths were significant with standardized loadings ranging from 0 .57 to 0 .91 and t-test values far above 1 .96 (Anderson & Gerbing, 1988) . Standardized parameters presented in Table 2 further show that after having controlled for the significant impact of waiting time on the two dimensions of

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LAURETTE DUB$ ET AL.

Table 2. Standardized Estimates and t-values for Specific Relationships of the Structural Model of Patient Emotions and Their Relationship with Perceived Quality of Care and Satisfaction . Standardized Estimates

t-values

0 .579 0 .750 0 .749 0 .683 0 .569 0 .616 0 .665 0 .651 0 .571 0 .712 1 .00 0 .912 0 .812

8 .70 10.964 10 .969 fixed parameter 8 .571 9 .449 9 .875 fixed parameter 7 .052 7 .717 fixed parameter fixed parameter 17 .119

Waiting Negative emotion Waiting - Positive emotion Waiting Perception of quality of care Waiting Satisfaction

0 .246 -0 .337 -0 .294 -0 .124

3 .7898 -4.601 -5 .388 -2 .781

Negative emotion - Perception of quality of care Positive emotion Perception of quality of care Negative emotion Satisfaction Positive emotion Satisfaction Perception of quality of care - Satisfaction

-0 .215 0 .339 -0 .109

-3 .861 5 .584 -2.408 NS 13 .465

Links Yl Negative emotion Negative emotion Y2 Negative emotion Y3 Negative emotion Y4 Negative emotion Y5 Negative emotion Y6 Negative emotion - Y7 Positive emotion Y8 Positive emotion Y9 Positive emotion Y10 Perception of quality of care -i Y 11 Satisfaction Y12 Satisfaction - Y 13

0 .731

patient emotions and on perceived quality of care, both positive and negative emotions influenced patient's perceptions of the quality of care in a valencecongruent direction . As expected, positive emotions had no direct influence on satisfaction whereas negative emotions, in addition to their indirect effect on satisfaction through their deleterious impact on perceptions of quality of care, also had a significant and reverse impact on patient satisfaction . Finally, perception of quality of care had a strong and direct effect on patient satisfaction . The Effects of Waiting to See the Physician The effects of waiting time on the patient's self reports of emotions, perceived quality of care and satisfaction were first tested in separate analysis of variance


177

(ANOVAs) with waiting time sub-groups as a 3-level (short, moderate, long), between-subjects factor . As expected, the length of time patients reported having had to wait before seeing the physician significantly influenced all four measures (negative emotions, F[2, 280] = 10 .60, P < 0 .01 ; positive emotions, F[2, 280] = 11 .458, P

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Managers' Perceptions of Hospital Capabilities

245

executive directors discussed the tremendous strategic implications of change between capitation and fee for service . They discussed how this change is "turning around everyone at the hospital," as well as anyone associated with the hospital, including physicians' practices . The tight coupling of financial management and "managing" managed care was reinforced in executive director interviews . Deep understanding of costs, and of cost-quality trade-offs, appeared to be essential to all the capabilities that loaded on this factor. The embedded nature of this critical knowledge is best explained by one executive's comment that, "To succeed [with managed care and capitation] requires a set of complementary knowledge skills, including financial, underwriting, and risk management knowledge ." (4) Capabilities in managing external stakeholders . The fourth factor is fundamental to the strategic success of a wide range of organizations (Andrews, 1980), and particularly to health care (Blair & Fouler, 1990) . As one hospital executive director explained, "Managing external relationships is very important to a hospital like ours . [For example], our skills in public issues management - in constructively managing our relationship with [the local newspaper] and other media - allow us to build our constituency in the area ." Given the high level of public sector involvement in all facets of health care, and reinforced by the fact that all hospitals in this study were community-based, it is not surprising that these capabilities emerged . Key stakeholders with ongoing oversight capacity (such as third party payers or JCAHO) do not explicitly monitor these capabilities . These capabilities, therefore, may need to be reinforced by top managers to ensure that the hospital builds this knowledge effectively, rather than exercising it reactively . (5) Information systems capabilities . The fifth factor focused on the information systems that facilitate integration within the hospital and with physicians associated with the hospital . Interestingly, these two capabilities emerged as two areas of greatest challenge in Gillies et al .'s (1993) study of health systems integration . In the face of sometimes overwhelming changes in technology, managers must remember that information technology is not simply the purchase of new technology resources ; rather, it includes processes that integrate disparate areas of the hospital, and changes in organizational values that facilitate and accommodate technological efforts . Research analysts recently criticized the health care industry for slow adoption of information technology (Anonymous, 1998) . The capabilities that emerged from this study reinforce the challenge of managing the processes, and values necessary to strategically integrate information systems .

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ADELAIDE WILCOX KING AND CARL P . ZEITHAML

(6) Capabilities that facilitate innovative market extensions . Interviews with hospital executives and industry experts highlight the increasing (and often belated) recognition of the importance of the sixth knowledge factor, knowledge that facilitates innovative market extension . Fundamental shifts in the nature of heath care services,' as well as the nature of competition,' contributed to the rising cost of health care and dramatically increased the risks associated in running health care organizations . Entrance of private competitors significantly altered the conservative norms of the hospital industry, raising the level of advertising and dispelling the stigma associated with marketing hospital services . The rapid nature of change in the competitive environment also led many managers to consider developing capabilities in creating non-traditional partnerships to gain either skills (such as computer technology) or access to markets (such as direct agreements with employers) . This factor offers significant opportunity for future growth, and it is a capability that top managers may wish to consider as they compete in the increasingly complex and changing health care market . (7) Capabilities that contributes to patient perceptions of care . Responsiveness to patients as stakeholders is recognized as critical to success in the health care literature (Blair & Fottler, 1990) . All three capabilities that load on this factor (a) tracking patient satisfaction over time, (b) maintaining a patient-friendly environment and (c) maintaining a business-driven environment - indicate whether the human resources, processes, and values in a hospital create satisfactory stakeholder outcomes . In addition, the following quote illustrates one hospital executive's beliefs about the importance of managing stakeholder perceptions . Quality in our business is basically defined from a patient's standpoint, and is defined by responsiveness. A patient trusts that his doctor knows what he is doing . His next questions are, "How nice were they? When I got there, did he know whom I was? Did the hospital staff treat me nicely and did I get out in a timely fashion?" This all has little to do with the scientific nature of the quality of the product .

In sum, seven different capability factors emerged from this study . They provide valuable insights into the types of capabilities that hospital managers believe contribute to competitive advantage . They represent a timely and detailed survey of a range of managers' perspectives that that can add insights to guide hospitals in their own capability identification process . While identifying these capabilities overcomes an important challenge in describing capabilities, additional analysis is required because successful organizations cannot afford to become complacent about key capabilities' long-term competitive advantage . Assuming that any capability continues yielding competitive advantage is risky .


247

Capabilities have limited lives and earn only temporary profits, as they are vulnerable to imitation, substitution, and environmental change (Barney, 1995 ; Collis, 1994 ; Collis & Montgomery, 1995) . In the next section, we suggest three characteristics that managers can use to assess capabilities in ways that may add important insights into their strategic advantage . Based on knowledge and cognitive theories, we further explore whether managers' perceptions of capabilities relate to an objective measure of hospital success .

ARE MANAGERS' PERCEPTIONS OF CAPABILITIES RELATED TO OBJECTIVE MEASURES OF HOSPITAL SUCCESS? Articulating the capabilities that managers believe lead to organizational success is an important first step . However, additional analysis of specific characteristics of capabilities may add further insight into the strategic value of these capabilities . Knowledge and cognitive theories highlight three characteristics that may help explain capabilities' strategic value : agreement, tacitness and robustness . In the following sections, we define these characteristics and present hypotheses that relate these characteristics to hospital performance . Management Agreement Weick and his colleagues (e .g . Weick, 1979 ; Daft & Weick, 1984) view organizations as social systems that must process and interpret uncertain and ambiguous information for action . At the individual level, managers' perceptions configure information in ways that reduce information-processing demands and facilitate complex decision-making (Walsh, 1988 ; Walsh, 1995) . These filters can increase the efficiency of problem solving by providing a structure for evaluating complex, ambiguous information . At a group level, decision makers' perceptions can be aggregated through measures of consensus or agreement, which reflect the level of similarity among the group members' individual perceptions (Walsh, 1988) . In our study, high agreement indicates that group members share similar perceptions regarding organizational capabilities . Capabilities are ambiguous and complex . If an organization does not specify capabilities and managers' assessment of capabilities, misunderstandings and confusion may remain hidden . In addition, shared understandings play essential roles in framing interpretations of ambiguous events, which include almost all strategic issues (Daft & Weick, 1984) . Groups that interact in "heedful" and "careful" ways act with a "collective mind" that can increase organizational effectiveness (Weick & Roberts, 1993) . Similarly, Grant (1995) argues that the competitive advantage of a capability depends on the efficiency of knowledge integration, which is a function of "the

248


extent of common knowledge among organizational members" (p . 12) . Managers who agree may be more likely to make consistent decisions and actions in allocating scarce firm resources (Wooldridge & Floyd, 1989) . These groups can often make decisions more quickly because they do not need to spend as much time clarifying assumptions or supporting their conclusions . While high levels of agreement may present risks (e .g . Levitt & March's (1988) competency traps, Leonard-Barton's (1992) core rigidities, and Janis' (1972) group-think), we believe that the benefits outweigh the risks . A shared understanding of the hospital's most important capabilities helps focus the hospital's efforts, and may increase the likelihood of implementation success . Conversely, when managers do not agree on the firm's most important capabilities, employees and other stakeholders are likely to receive mixed messages and different organizational units may pursue conflicting agendas . We therefore present the following hypothesis : HI : Management agreement on capabilities is positively associated with

hospital performance .

Tacitness

At any point in time, knowledge can be based upon a tacit-articulated continuum (Nelson & Winter, 1982 ; Nonaka & Takeuchi, 1995 ; Polanyi, 1969) . Articulated knowledge is also known as expressed knowledge (Nonaka, 1988), or knowledge that can be communicated either verbally or in writing (Hedlund & Nonaka, 1993 ; Nelson & Winter, 1982) . Articulated knowledge is objective knowledge that can be codified "into a set of identifiable rules and relationships that can be easily communicated, . . . alienable from the individual who wrote the code" (Kogut & Zander, 1992) . In contrast, tacit knowledge is "intuitive, non-verbalized and yet unarticulated ;" (Hedlund & Nonaka, 1993 ; Polanyi, 1969) interpretation requires experience and is context-specific . For example, tacit knowledge is the skill that professional tennis doubles players possess to correctly move in anticipation of a partner's shot or to execute a flawless lob during critical points . Articulated knowledge is the knowledge passed on by the teaching professional to a beginning team, such as how to keep score or where to stand when your partner is receiving serve . Articulated knowledge can be divided into a series of steps or codified into a set of rules that can be communicated either orally or in writing . Managers can evaluate capabilities on a continuum of articulated to tacit . Articulated knowledge is independent of context and therefore can more easily be transferred to competitors . Tacit knowledge is more opaque and inherently more difficult to imitate than articulated knowledge (Kogut et al ., 1992 ; Reed &


249

DeFillippi, 1990 ; Winter, 1987 ; Zander & Kogut, 1995) ; increased tacitness may increase firm specificity, decreasing the value of knowledge outside the context of the organization (Spender, 1993 ; Grant, 1991) . Tacit knowledge, therefore, may be more valuable inside the firm than it is to competitors . When hospital managers assess key capabilities as more tacit, this hospital may be better able to apply, extend, and protect these capabilities in ways that create and sustain competitive advantage . We suggest, therefore, that : H2 : Managers' perceptions of the tacitness of key capabilities are positively associated with hospital performance . Robustness Robustness reflects managers' perceptions of a capability's ability to sustain value in face of environmental change . Capabilities are valuable when they contribute to a hospital's ability to take strategic actions that neutralize environmental threats or exploit opportunities . Given the tumultuous health care environment, this dimension provides an important measure that can capture managers' beliefs regarding the future value of given capabilities . Robust capabilities are likely to retain their value in the future because they are more flexible and are not tied to a particular set of circumstances outside the control of the organization . Robustness can be evaluated along a continuum from robust to vulnerable . Vulnerable capabilities are more likely to lose their value due to environmental change, such as technological, economic, or political changes . In contrast, robust capabilities are more likely to hold their value in the face of changes outside the control of the organization . For example, since the mid-1990s, the capability in managing the knowledge and skills necessary to succeed in an environment of capitation was not robust; it did not maintain value due to changes in the competitive environment . In contrast, a capability in cost containment may be very robust because it is valuable regardless of environmental changes . Assessing managers' perceptions of a capability's robustness, therefore, can provide valuable strategic information . Therefore, H3 : Managers' perceptions of the robustness of key capabilities are positively associated with hospital performance . Methodology Following the identification of capabilities and analysis of knowledge factors, correlation tests were conducted to assess the relationship between managers' perceptions of capabilities and objective performance outcomes .

250


Independent Variables Managerial agreement . The seven factors were used to assess managerial agreement on the capabilities . Factor scores were assigned to each respondent . A factor score measured each respondent's perception of the importance of each factor in contributing to the relative competitive advantage of his or her organization . Average Euclidean squared distance (henceforth called Euclidean distance) among a group of decision makers is an accepted measure of agreement in the literature (Houghton, Zeithaml & Bateman, 1994 ; Walsh, 1988) . Euclidean distance begins with the calculation of distances between each pair of individuals within a designated group . For a dyad, distance is measured by summing the squared differences between individual responses to an identified set of questions . A high distance score, therefore, implies lack of agreement between that dyad . An organizational score is then derived by summing the distances between each unique dyad within an organization and dividing the sum by the number of unique dyads . Agreement was measured based on distances derived from all factor scores . The level of agreement was assessed relative to other hospitals . Agreement scores were multiplied by -1, so that an organization with a relatively high Euclidean distance would have a high level of agreement . Tacitness and robustness . To measure tacitness and robustness, managers were asked questions about two capabilities . Each manager answered questions regarding the capability that he or she considered most important to the firm's current success . In addition, each manager answered the same set of questions regarding the capability of "cost containment ." To measure the tacitness of a capability, managers were asked to assess four statements, modified from Kogut and Zander (1992) on a seven-point scale . Principal component analysis was then conducted on these four items, revealing two stable two-item factors that were consistent with Winter's dimensions of tacitness (Winter, 1987) . The first factor represents managers' perceptions that the capability has been articulated . The second factor represents managers' perceptions that the capability is articulable . Robustness was measured based on a factor score derived from responses to an original scale . This scale was designed to measure a capability's insensitivity to environmental variation . Daft et al . (1988) provided guidance for key sources of environmental variation . Once again, with regard to the capability in question, managers were asked to rate their agreement with the statements on a seven-point scale . Factor analysis revealed that all statements in each administration loaded on a single item . Coefficient alphas for all administrations exceeded the level for minimal acceptability (0 .65) (DeVellis, 1991) . The


251

factor score was reverse scored so that high numeric responses indicated high robustness . Tables 2 and 3 present the questions and full-study analyses for the tacitness and robustness measures . Dependent Variable - Financial Performance The dependent variable was return on assets (ROA) to capture profitability of a hospital (Zeller et al ., 1997) . While the performance of community hospitals is judged by multiple non-financial criteria (e .g . mortality rates, patient satisfaction, relations with third party payers, community health, and community relations), financial performance remains a critical gauge of success . ROA continues to be accepted in the strategic management and health care literatures (Baliga et al ., 1996 ; Judge & Zeithaml, 1992 ; Wiersema & Bantel, 1993) . ROA provides superior relative year-to-year stability vis-a-vis other financial measures (Hill et al ., 1992) . Control Variable The number of managers who participate is relevant when considering managers' perceptions at the organization level . Large management teams may be able to manage a wider variety of capabilities and tolerate a wider range of viewpoints . Larger numbers of managers may impede communication of capabilities . The number of managers per organization, therefore, was included as the control variable . Results and Implications for Hospital Managers Results Table 4 presents the research results .' The results are consistent with the perspective that managers' perceptions regarding capabilities relate to objective measures of organizational outcomes . Specifically, hospitals with higher financial performance tended to have managers who agree on their capabilities and who describe key capabilities as tacit and robust . The correlation between firm performance and management agreement is logical given the complex nature of capabilities . Creation and implementation of capabilities require participation and involvement of a number of individuals throughout an organization . Management agreement on the key capabilities that distinguish a hospital implies a less arduous coordination effort within a hospital . Agreement among managers may be associated with collaboration and less associated with political schism . Managers' shared views of the value of capabilities in a hospital's competitive environment also may provide a valuable platform for recognizing,

252


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MANAGEMENT OF ACADEMIC HEALTH CENTERS : THE PAST, PRESENT, AND FUTURE Sharon Topping and Donna Malvey ABSTRACT There are approximately 120 academic health centers (AHC) in the U .S. today whose mission is to deliver critical, tertiary care while also providing graduate medical education and conducting cutting-edge medical research . This traditional mission is overlaid by the social mission or the provision of highly specialized, complex or innovative care not readily available from other community providers to those who need it, including the poor . These missions make AHCs unique ; however, they also are the focus of much controversy surrounding the management of AHCs . On one hand, there are those who advocate that AHCs operate similar to business organizations, thereby adapting strategies accordingly and revising their missions as necessary . On the other hand, there are those who believe in the uniqueness of AHCs and the necessity of upholding their traditional missions . Following from this, this paper presents a review of the literature that focuses on the changing environment facing AHCs and their strategic responses . In doing this, we argue that many are "copy cat" strategies that may have been successful for community hospitals and general business organizations but may not necessarily be appropriate for


268

SHARON TOPPING AND DONNA MALVEY

AHCs . At the end, this paper provides a debate on the mission and strategic direction of AHCs, particularly in light of the business or enterprise model and raises questions about the future management of these institutions .

INTRODUCTION In 1996, the President and CEO of Allegheny Health, Education, and Research Foundation (AHERF) explained in Academic Medicine how the strategic success of his academic health center (AHC) was achieved (Abdelhak, 1996) . Four short years later, Burns and colleagues described the AHERF bankruptcy (Burns, Cacciamani, Clement & Aqino, 2000) . Similarly, Van Etten wrote in Health Affairs about the 1997 merger of UCSF/Stanford describing it as being a "common sense" strategy (Van Etten, 1999) . Yet in Fall 1999, Hospitals & Health Systems described the AHC break-up (Kirchheimer, 1999) . Similar scenarios have taken place around the country . Given the changes in the health care environment over the past two decades, researchers, practitioners, and policy-makers alike have tried to determine how to manage AHCs successfully . This has led to a plethora of publications, prescriptive and descriptive, focusing on various AHC strategies . While benefits were attributed to each strategy, many were untried and new to AHCs ; therefore, little evidence exists to substantiate their value. It is important to note that when catastrophes occurred, the strategies failed, not the AHCs . Much has been written over the past ten years predicting the demise of AHCs if they do not adapt to the changing health care environment . Yet, none have expired . In fact, available data suggest that, on average, they have been financially healthy in the 1990s (Anderson, Greenberg & Lisk, 1999) . Much also has been written about how different AHCs are from other organizations especially community hospitals . Nevertheless, many researchers have advocated that AHCs operate like business organizations (Iglehart, 1997) . As a result, many have implemented "me too" strategies as fast as possible (Krauss & Smith, 1997 ; Topping, Hyde, Barker & Woodrell, 1999) . Furthermore, many of the strategies being advocated, such as mergers or downsizing, have not been evaluated after implementation by community hospitals, or have never proven successful in the business world (Bazzoli, Losasso, Arnould & Shalowitz, 2002 ; Bland, 1997) . Following from this, the overall intent of this paper is to review and assess the literature on AHCs in order to provide a better understanding of the changing environment facing AHCs and the management responses that have followed . In so doing, we, first, provide background information pointing out not only the commonalities but also the differences found among AHCs . Included in this is also an historical perspective that looks at the changing environment and its

Management of Academic Health Centres

2 69

impact . Both AHC uniqueness and environment play a crucial role in setting the strategic direction and initiating change. As part of that, we present an overview of the AHC missions : teaching, research, and clinical service . Although the missions seem rather straightforward, they are the focus of much of the controversy surrounding the management of AHCs . In addition, we use the literature to identify strategies that have either been prescribed for or implemented by AHCs . In doing this, we argue that many are "copy cat" strategies that may have been successful for community hospitals and general business organizations but may not necessarily be appropriate for AHCs . At the end, this paper provides a debate on the mission and strategic direction of AHCs, particularly in light of the business or enterprise model and raises questions about the future management of these institutions .

ACADEMIC HEALTH CENTERS : AN OVERVIEW The definition of an AHC used in this paper was derived from a 1983 article in the New England Journal of Medicine (Ebert & Brown, 1983) and is very similar to the one used by the Association of Academic Health Centers (AAHC) . First, to be an AHC, the organization must be either owned by or closely affiliated with a university or medical school . Second, the AHC must have at least one other graduate health professional program, and lastly, be actively engaged in undergraduate medical education, biomedical research, and delivery of patient care . To be a member of AAHC, the institution must meet all three requirements . Commonalities and Dissimilarities of AHCs

The similarity stops with the definition, for it has been rightfully said, that if you have seen one AHC, you have seen one AHC . Organizationally, they may share certain features such as missions and governance structures, and most of their CEOs, about 80%, tend to be physicians (Critical Data Survey Report, 1994) . Yet, they are dissimilar in many areas of strategic importance . Primarily, they are located in diverse markets with unique resources and opportunities . For instance, a number of AHCs are located in rural states, while others are in large metropolitan areas characterized by intense competition with other AHCs and community hospitals . The majority of AHCs have components such as hospitals and teaching facilities that are contiguous or at least located on the same campus, but some have great distances, more than 300 miles, between these components (Critical Data Survey Report, 1994) . Size variation exists as well . AHCs can consist of a few small hospitals totaling just over a hundred beds, while others have 10 or more affiliated hospitals with beds numbering

270


over a thousand . Although some teaching hospitals have revenues exceeding $500 million annually, there are others with more modest budgets (Dranove, 2000) . Even though there are approximately 120 AHCs in the U .S ., the exact number is somewhat elusive, as evidenced by different numbers appearing in various reports . The numerical changes most likely reflect the recent impact of consolidation and integration that has occurred . While the number of AHCs is often inexact because of strategic activity, there is little evidence of AHC closures (Mission Management, 1999) . However, to better differentiate, three dichotomous classifications exist to describe AHCs . First, they are classified according to public or private status, which is established by charter and is based on reporting relationships with the governing board . Second, AHCs can be viewed as systems such as California, Texas, or New York consisting of at least an individual office concerned solely with health professions education . All system academic health centers are public . Third, AHCs can be differentiated as free-standing or university based (Critical Data Survey Report, 1994) . Historical Perspective Medicine and medical training through universities have existed for centuries, but it is the AHC, which represents the nexus of a hospital combined with university training that is more recent . Although there is no agreement about the date of origin of the AHC, the organizational form is thought to have evolved following World War II with federal funding for investment in university-based science programs . In addition to this funding stream, Medicare/Medicaid legislation in the mid-1960s contributed explicit support for graduate medical education and delivery of medical services to specific populations . The Department of Veterans Affairs (VA) medical system also made important financial, as well as educational, contributions to AHCs (Korn, 1996 ; Shapiro, 1994 ; Starr, 1982) . All of these developments assisted in fueling the growth of AHCs that emphasized highly specialized tertiary care, specialty graduate medical training, and ultimately resulted in fragmentation in the health care industry (Scott, Ruef, Mendel & Coronna, 2000 ; Starr, 1982) . Scott and colleagues (2000) also have suggested that most of the change occurring in the health care environment has been incremental, with few instances of discontinuous change occurring in the previous century, 1900-2000 . Discontinuous - radical or revolutionary - change is by its very nature rare, and its occurrence leads to profound institutional change . Each instance of discontinuous change, however, has been marked by significant variations in the behavior of health care organizations, such as AHCs . For example, Medicaid and


271

Medicare represent the first source of discontinuous change in the health care industry . This change marked the entry of the federal government as a major purchaser of health services . With new funding sources, AHCs grew, especially in terms of manpower and expansion of access to care for the poor and the elderly, and access to remuneration for faculty physicians and practice plans (Korn, 1996) . A second source of discontinuous change occurred early in the 1980s with federal legislation, including the Tax Equity and Fiscal Responsibility Act (TEFRA) and the Prospective Payment System (PPS), both of which were aimed at controlling costs and encouraging competitive processes in health care (Scott et al ., 2000) . As such, a more business like approach was advocated in which managers focused on the bottom line and profitability . The growth of managed care in the 1990s also emphasized business principles and behaviors in managing health care organizations (Bigelow & Ardnt, 2000 ; Dranove, 2000) . During this period, AHCs underwent radical transformation as they integrated, merged, and partnered in response to rapid, unprecedented pressures of both private markets and governmental policy (Managing Academic Health Centers, 2000) . The AHC's Missions AHCs underpin the U .S . health care system by providing critical, tertiary care that has saved thousands of lives . George Lundberg, former editor of the Journal of the American Medical Association, predicted that managed care would put a "real squeeze" on AHCs in the future because they are inefficient . However, he is quick to add that he received his medical education and training in an AHC . More importantly, if he gets sick, he wants to be cared for in an AHC (Mullan & Lundberg, 2000) . Lundberg's sentiments are not unusual because when individuals are confronted by serious life-threatening situations such as burns, complicated heart disease, or other complex pathologies, most end up being cared for in an AHC (Pardes, 2000) . Thus, while AHCs produce goods and services that typically do not pay for themselves and have slight chance of profitability, they are essential to society and the public good . Figure 1 demonstrates AHCs multiple conjoint missions . In fact, the tri-partite missions of research, education, and clinical service are a distinguishing characteristic of the AHC . Moreover, these missions are interconnected because their union is necessary to produce the particular goods and services of an AHC . Figure 1 also illustrates the social mission, which overlays the traditional AHC missions of teaching, research, and service . This social mission has been defined in various ways, but essentially it refers to the poor and those needing highly specialized, complex or innovative care that may not be readily available from other community providers (Health Care at the Cutting Edge,

272


2000) . The social mission further differentiates the AHC from the community hospital, for unlike the community hospital, AHCs produce two distinct types of goods and services : private and public . Private goods include the services and products that are derived from teaching, research, and clinical care and for which there is a private market . For example, providing clinical care for an insured patient or performing a research study for a drug company (i .e . applied research) represents a private good . Public goods are similarly derived, but the market for these goods is determined by the needs and expectations of society . Thus, providing care for an uninsured patient or performing basic research are examples of a public good (Blumenthal & Meyer, 1996) . Because the missions of teaching, research, and clinical service are interrelated or conjoint (see shaded area in Fig . 1), it is difficult to understand them as s eparate entities . Thus, what follows is a discussion of each of the three traditional AHC missions of teaching, research, and clinical service ; yet, the social mission permeates the mission environment and affects the performance of all AHCs . RESEARCH MISSION

TEACHING MISSION

CLINICAL SERVICE MISSION

Fig . 1 .

Traditional AHC Missions .


273

The Teaching Mission AHCs train our future physicians and provide graduate medical education for residents who are training in specialty care areas . In many instances, they are training their own competition since many community hospitals are staffed by physicians who were trained at AHCs (Blumenthal & Meyer, 1995 ; Starr, 1982). AHCs are more expensive primarily due to teaching intensity . Teaching hospitals, in particular, incur tremendous costs in order to develop the ability to treat difficult and complex illnesses . Teaching also reduces clinical productivity, especially when tests and treatments are ordered for didactic purposes . In addition, in order to fulfill its teaching mission, the AHC must offer a broad range of services even though these services may not be profitable (Fox & Wasserman, 1993 ; Mechanic, Coleman & Dobson, 1998) . For instance, the nation's AHCs represent approximately a third of all trauma centers providing complex trauma care and 46% of all transplant centers . Furthermore, about 31% of dedicated AIDS inpatient units are located in AHCs (Biles, 1997 ; Blumenthal, Campbell & Weissman, 1997) . Because high costs are inconsistent with principles of managed care, teaching hospitals are especially pressured to behave competitively and use strategic options to maximize financial effectiveness . Paradoxically, although AHCs are considered inefficient because of their high cost teaching mission, recent studies have shown teaching hospitals provide superior quality care compared with other hospitals (Culbertson, 1996 ; Kassirer, 1999 ; Langabeer, 1998 ; Taylor, Whellan & Sloan, 1999) . The pressure to reduce educational costs and increase productivity is so intense that AHCs worry about faculty having less time for teaching and the consequent negative impact on residents' training . For example, if a faculty member wants to remain competitive for research grants, he or she will have less time to spend teaching and seeing patients . As a result, finding faculty to teach has become increasingly difficult . The time available for teaching is also affected by the complex documentation regulations required of physicians that supervise residents providing services to Medicare patients (Griner & Danoff, 2000) . Case study research also has demonstrated that increasingly AHCs appear to be dc-emphasizing teaching and research and pressuring faculty to treat more patients in order to generate more clinical revenues (Blumenthal & Meyer, 1996 ; Korn, 1996 ; Mechanic & Dobson, 1996) . Clinical Service Mission AHCs depend on indirect mechanisms to fund mission activities ; historically, they have used revenues from clinical services to subsidize them . Fulfilling the AHC mission is costly and until the introduction of managed care and competition, was primarily subsidized through clinical services . Thus, a complex web of cross subsidies of clinical services is necessary because AHC other

274


mission-related activities do not pay for themselves . Very few of the missionrelated activities are financed through explicit sources of funds, such as tuition or government grants and, instead, reflect co-mingling of funds (Iglehart, 1995) . Ironically, overall pressures to reduce health care expenditures have resulted in a decline in clinical revenues available to subsidize mission activities such as training physicians (Griner & Danoff, 2000) . Yet, the clinical service missions is critical because physicians cannot be adequately trained without being exposed to the latest advances in technology and treatments . Specialty clinical services, in particular, are essential to the education and training of physicians regardless of their relative profitability . Because funding for the research and teaching missions relies on external federal and state subsidies in addition to internal cross subsidies from clinical services, cutbacks in clinical service obviously will impact research and teaching budgets . Reductions in clinical programs or divestiture of clinical services may jeopardize other mission components . Conversely, success in clinical service markets is critical . Thus, it is not unusual to find that AHCs are devoting most of their time and energy in attempts to increase clinical market share while reducing costs (Managing Academic Health Centers, 2000) . Research Mission Historically, the research mission has required less intensive management than clinical services because fewer resources were involved and research was typically viewed as a creative endeavor overseen by AHC faculty . Managed care has changed this position . Increasingly AHCs are recognizing the need to develop a research infrastructure and decision-making capacity because of the increase in competition for research dollars (Weissman, Saglam, Campbell, Causino & Blumenthal, 1999) . Thus, nearly all AHCs are involved in expanding their research activities (From Bench to Bedside, 1999) . Federal and state funding, especially funding from NIH, and local or regional economic development efforts are the major factors underlying this expansion . Industry funding, initiatives, or partnerships represent significant sources of non-governmental funding . In addition, new faculty recruitment, expanded research budgets, and promotion policies that reward researchers for collaboration with industries are expanding AHC research activities . Yet, many AHCs are unable to offer competitive compensation packages with private, nonacademic research groups (Campbell, Weissman, Moy & Blumenthal, 2000) . Although in the past AHCs have served as business incubators for the development of new ventures, they face competition from established offices of research aimed at developing and managing these new relationships with industry (Ball & Rubin, 1994 ; Basinger, 2001 ; Rubin & Lindemann, 2001) . The research mission of


275

AHCs also faces competition from non-academic research organizations such as clinical research organizations (CROs) many of which are for-profit . CROs are private, nonacademic research groups that can perform clinical research for less money because they are not encumbered with bureaucratic red tape associated with universities and academic research . Academic researchers have reported as much as 25% higher costs in enrolling patients in studies than their nonacademic counterparts (University HealthSystem Consortium, 1995) . The Emergence Of New Models

AHCs have not escaped the business metamorphosis, despite their public service agendas . Declining clinical revenues and research dollars resulting from increased competition and managed care as well as diminishing federal subsidies for graduate medical education have challenged them to operate more like a business and eliminate functions that contribute to inefficiency and cost (Blumenthal & Meyer, 1996 ; Mechanic et al ., 1998) . In particular, the AHC mission has been placed at serious risk because of its incompatibility with managed care and competitive pressures (Shortell, Gillies, Anderson, Erickson & Mitchell, 1996) . Although earlier studies have shown that AHCs are surviving, there is concern that competitive forces may compromise their missions (Anderson et al ., 1999 ; Gold, 1996 ; Hadley & Gaskin, 1995) . In response, several new models have been suggested in which missions are split, thereby, allowing the larger AHCs to specialize as regional centers providing tertiary care and specialty training while others function at a more limited or primary care level . In addition these models tend to be more compatible with managed care requirements for organizing around patient care (Blumenthal & Meyer, 1993 ; Capper & Fargason, 1996 ; Epstein, 1995) . Alternatively, AHC missions are increasingly being characterized as "enterprises ." The literature refers to the "academic enterprise", or the "research enterprise", or the "social enterprise" where once the term mission was used . This transformation is significant because it conveys new meaning, scope, and boundaries to the purposes or missions of AHCs and ultimately affects future goals and direction of these institutions . Suggestions to modify or "reshape" missions to increase profitability are prevalent in the literature as are strategies to disentangle conjoint missions so that research or educational activities essentially become a separate business line, which must be managed separately under the rubric of mission management (see Fig . 2) . Some AHCs have created separate, parallel tracks for clinicians and researchers so that research and patient care become distinct byproducts instead of related endeavors (Anderson et al ., 1999 ; Blumenthal et al ., 1997 ; Griner & Danoff, 2000 ; Korn, 1996) .

2 76


TEACHING

RESEARCH

CLINICAL SERVICE Fig . 2.

AHC Enterprise Model .

AHCs are often regarded as over-serving the health care needs of a much larger patient population whose illnesses and disease have become more routine and increasingly are treatable in physician offices and even in the home . Ironically, AHCs successes have become their problems . They are responsible, in large part, for the capability to provide treatment outside the hospital in less costly settings . The diffusion of high technology services into nearby community hospitals actually represents AHC success as educators and in helping to assure access to services . Furthermore, the diffusion of technology and development of drugs also allow patients to administer care in the home and less-skilled and less expensive practitioners to take on more complex cases (Christensen, Bohmer & Kenagy, 2000; Health Care at the Cutting Edge, 2000) .

LITERATURE REVIEW : IDENTIFICATION OF STRATEGIES The literature review involved a MEDLINE search covering a ten-year period ending 2001 and using the key words "academic medical center" or academic health center" . To further identify the literature, the reference lists of all


277

publications from the search were checked for additional citations as well . In total, 142 articles, reports, and books were reviewed . To identify strategies, we independently reviewed each article looking for AHCs identified by name (e .g . Oregon Health Sciences University) and upon finding, extracted information describing the specific strategies . The data from the two separate reviews were combined to be used to identify major strategy categories according to three criteria . First, we focused on strategies that had received considerably attention in the literature, and second, had been implemented in AHCs over a long enough period of time that successes and failures were being reported . Third, we included strategies that were both strategic and operational in our review . In this way, linkage strategies such as mergers and alliances would be included along with managerial strategies such as governance and structural reforms . Using this criteria, we identified four major strategies : linkage strategies (e.g . mergers and referral networks) ; product/market strategies ; structure and governance strategies ; and, operating efficiency strategies . Linkage Strategies Due to changes in the AHC environment, much has been written about the need to develop integrated delivery systems (IDS) in order to negotiate with managed care organizations from a position of power . Following from this, AHCs implemented linkage strategies involving mergers of hospitals and medical schools along with alliances, partnerships, and acquisitions to build referral networks . Mergers : Hospitals and Medical Schools One strategy receiving considerable attention over the past decade involves mergers between AHC teaching hospitals, medical schools, or a combination thereof (Abdelhak, 1996 ; Barnett, 1995 ; Bums et al ., 2000 ; Devers et al ., 2001 ; Goldsmith, 1999 ; Serb, 1997) . Mergers are purported in the literature to neutralize or decrease the threat of managed care (Andreopoulos, 1997 ; Barnett, 1995 ; Van Etten, 1999) . Through mergers, AHCs can build integrated delivery systems, ensure economies of scale, and consolidate the market, thereby decreasing competition and increasing market share . It appears to be the strategy of choice in urban areas where an oversupply of health care resources can create pressures to change (Blumenthal & Edwards, 2000) . This is particularly true when competition involves not only community hospitals but also other AHCs . According to Blumenthal and Edwards, mergers should " . . . provide the critical mass needed to sustain world-class research and educational activities,

278


to create new opportunities for cost reduction and improved efficiencies, and to develop the market power necessary to deal with local competitive pressures" (2000, p . 98) . Several AHC mergers are noteworthy for the considerable attention in the literature and the value gained from their experiences . See Table 1 for selected high profile mergers along with the current status of each . For example, when

two large AHCs in Boston (Beth Israel and New England Deaconess) merged in the 1990s, the aftermath of the merger was a highly publicized disappointment . The merger failed to achieve operational or cultural integration and resulted in huge financial losses (Devers et al ., 2001) . In particular, an attempt

to integrate the anesthesiology departments subsequently failed, resulting in the loss of medical staff and programs to other institutions . The merger of the two AHCs had not anticipated the cultural problems associated with getting two medical staffs to work together . Instead of achieving economies of scale, the merger resulted in at least a $215 million loss during 2000 and 2001 as well as a loss of market share (Lagnado, 1999 ; Devers, et al ., 2001) .

Table 1 .

Selected High Profile AHC Mergers .

Date

AHC

Current Status

References

1996

New York University/ Mount Sinai Medical Centers

• Merger called off before completed • Complexity of combining two medical schools

Batouli and Gottlieb, 1996 ; Serb, 1997

1994

Partners : Mass, General/ Brigham and Women's Hospital (affiliated with Harvard Medical School)

• Developed IDS • Strong market presence • MGH & Brigham independently managed • Some administrative integration • Little reduction in scope and size

Barnett, 1995 ; Blumenthal and Edwards . 2000 : Devers et al ., 2001 ; Kastor, 2000; Serb, 1997

1997

UCSF/Stanford

• • • • •

Merger dissolved in 1999 Financial losses Governed by new private corporation No clinical integration Extremely different cultures

Andreopoulos, 1997 : Dranove, 2000 : Goldsmith, 1999 ; Kastor, 2000 ; Lagnado. 1999 : Van Etten, 1999

1996

CareGroup: Beth Israel/ New England Deaconess

• • • •

Operating losses Members threatening to drop-out Little clinical integration Strong individual cultures

Devers et al ., 2000 : Lagnado, 1999

1993

Allegheny Health Education & Research Foundation : Medical College of Pen nsylvania/Hahnemann Graduate Health Systems

• • • •

Bankruptcy in 1998 Financial losses Complexity of 2 medical schools Little clinical integration

Abdelhak, 1996 ; Burns et al ., 2000 ; Dranove, 2000: Goldsmith, 1999 ; Kastor, 2000 .


27 9

Other high profile failures include University of California, San Francisco and Stanford Health Services ; Medical College of Pennsylvania and Hahnemann Graduate Health Systems ; and New York University and Mount Sinai Medical Centers . For the most part, the merger strategy appears unlikely to realize financial benefits unless operations are integrated . All too often, merging hospitals remain operationally independent with the exception of one or two departments (Dranove, 2000) . In part, this is due to the organizational and cultural complexity of the organizations, particularly in the merger of two medical schools (Andreopoulos, 1997 ; Serb, 1997) . The Stanford/UCSF merger, for instance, involved a private hospital in a wealthy community serving well-insured patients with a state owned hospital with many underinsured patients often having complicated illnesses (Kastor, 2000) . One merger that is pointed to as a success is that of Massachusetts General and Brigham and Women's hospitals - both affiliates of Harvard Medical School . In a market known for cutthroat competition and managed care, the two hospitals have become the linchpins of an integrated delivery system, Partners Healthcare System, that includes 4,000 affiliated physicians and a number of community hospitals and outpatient sites (Barnett, 1995 ; Devers et al ., 2001) . However, little has been done to reduce scope or size . For example, Massachusetts General recently opened a new obstetrics unit, yet this is one of Brigham's centers of excellence . Although some administrative consolidation has occurred (e .g . finance, budgeting, information systems, legal, marketing, and purchasing), the hospitals still remain physician-driven and decentralized (Barnett, 1995 ; Kastor, 2000) . Because of size and brand name, Partners has leveraged these advantages into an aggressive and successful negotiating position, thereby being able to shift power from managed care organizations (Devers et al ., 2001) . Much of the early literature identifies numerous benefits associated with AHC mergers ; however, recently, it appears that these mergers are not producing the promised market leverage or earnings (Goldsmith, 1999) . One reason may be the enormous investment of time needed from senior leaders, or the distraction taking academicians from the daily work of patient care, teaching, and research (Blumenthal & Edwards, 2000) . It also is not clear that AHCs have the managerial talent or the management information systems necessary to run such large institutions . Furthermore, mergers are complicated arrangements that are hindered by the different cultural attributes of the AHCs . Cultural reconstruction of organizations of this complexity simply cannot be achieved rapidly, and, therefore, it becomes a long process of relearning and adjustment (Denis, Lamothe & Langley, 1999) . Lastly, mergers frequently are used to decrease costs, but few show any reductions because they maintain separate facilities and duplication of programs (Andreopoulos, 1997) .

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Referral Networks Another linkage strategy, the development of referral networks, was designed to turn an AHC into an extensive community-based health care system (Alpert, Flanagan & Bostford, 2001) . By acquiring or aligning with community hospitals and/or primary care practices (PCPs), this strategy was purported to guarantee AHCs all tertiary care referrals generated by the affiliated practitioners . In many cases, this strategy has been a financial disaster . Referral patterns did not change, and often, if the practitioner became a salaried employee, productivity decreased (Alpert et al ., 2001) . Moreover, the implementation of this strategy is difficult because of the AHC's traditional, acute care, specialty oriented culture and the fragmented departments and fiefdoms (Epstein, 1995 ; Shortell et al ., 1996) . Overall, the major lesson learned from this strategy is that network agreements do not produce community physician referrals (Van Etten, 1999) . For example, the AHERF collapse is attributed, in part, to network development (Goldsmith, 1999) . The expansion of the large network of primary care providers was used to secure the revenue base for the system (Abdelhak, 1996) . Declining earnings at the BJC Health System in St . Louis and unrealized referral projections at the University of Chicago Hospitals and Health System appear to be linked to AHC community network development as well (Goldsmith, 1999 ; Van Etten, 1999) . On the other hand, by focusing on the medically underserved populations, the University Medical Center in Mississippi implemented linkage strategies that target both inner city and rural underserved populations while simultaneously providing venues for primary care training and educational programs . This successful use of a linkage strategy for growth may be a good fit in resource-poor states or areas of the country (Malvey, Hyde, Topping & Woodrell, 2000) . Nevertheless, this AHC strategy, development of referral networks, is on the decline (Managing Academic Health Centers, 2000) . It should be noted that the high failure rate of AHC linkage or integration strategies is tied to both the fit and implementation of these strategies . The merger strategy is recommended when size and brand name serve as a leveraging tool in the market (Goldsmith, 1999) . Thus, the market is generally characterized by a high concentration of managed care in a highly competitive urban area where consolidation would lead to increased power and market share . At the same time, to implement the strategy successfully, the AHCs must have brand recognition while also being able to achieve economies of scale . The latter, in particular, has been difficult to achieve due to the cultural and organizational complexity that typifies AHCs . In most of the merger examples, few AHCs have been able to truly integrate operations and eliminate duplication, thereby, failing to reduce size and scope . The referral or integrated network


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strategy is also used to achieve leverage in the market by focusing on the AHC as the linchpin of a community-based system that guarantees tertiary care referrals . This, too, is difficult to implement since it involves the linkage between PCPs and/or community hospitals, each with cultures vastly different from the AHC . Furthermore, successful implementation is usually associated with planned change that includes a vision of the future, communication of mutual benefits, identification of change champions, and training and incentive systems that reflect the change (Woodard, Fottler & Kilpatrick, 1999) . Few AHC linkages have developed such a plan . Product/Market Strategies Clinical Services Product/Market Strategies

An early strategy used by the AHCs was to establish and fund their own managed care insurance operations, but this failed largely due to the lack of finances and business skills (Alpert et al ., 2001) . The insurance packages were subject to severe adverse selection, thereby increasing losses as well . In addition, if AHCs establish an HMO, they also must consider the enrollment necessary to support the level of professional revenue and to maintain the number of faculty members . For example, Billi and colleagues (1995) determined by estimating utilization rates that the University of Michigan Medical Center could not create an HMO or network large enough to support the specialty practice of the current number of members at the 1992 financing level . A more recent development is the successful exploitation of market niches by AHCs . One example is Oregon Health Sciences University (OHSU), which has focused on mostly rural areas (Blumenthal, Weissman & Griner, 1999) . In this case, OHSU is the only AHC in a state with a large rural population . Given the highly competitive Portland market, OHSU was unable to compete effectively in primary care there . In another example, the University of California at Davis (UCD) has been able to focus on level I trauma due to its isolated location in Sacramento and the unfortunate, yet insured traveler passing through on the major highway system . In other examples, the community is viewed as a source of opportunity or a niche (Calleson et al ., 2002 ; Ross, 1995) . The University of New Mexico Health Sciences Center takes a population perspective by focusing its mission on the identified health and service needs of communities in its state and aligning with public health (Kaufman et al ., 1996) . Differentiation plays an important role in the success of the niche strategy (Epstein, 1995) . Although many AHCs have been involved in cost reduction, findings indicate that financially effective hospitals do not use the low cost

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producer strategy but are able to differentiate themselves in the market (Langabeer, 1998) . Higher quality, higher perceived value, better reputation, or organizational differentiation allows AHCs hospitals to charge incrementally higher prices for their services . It also has been found that when health care becomes a commodity purchased mainly on the basis of price, it is difficult for AHCs to remain financially secure (Blumenthal et al ., 1999) . Research Product/Market Strategies Recently, AHCs have devoted much attention to the threats and opportunities associated with their research mission . Due to managed care, funds to crosssubsidize research have been declining, while faculty has been finding it more difficult to both do research and provide clinical services (Blumenthal et al ., 1999 ; Hudson, 1997 ; Rettig, 2000) . As a result, more and more AHCs are trying to attract alternative sources of research funds, while also competing with nonacademic institutions (Managing Academic Health Centers, 2000) . However, given that research product/market strategies are fairly recent, judgment is still out as to their value . Many AHCs are developing innovative ways of enhancing the research component of their mission . The University of New York Upstate Medical Center has developed an incentive system encouraging faculty research grants, while the University of Maryland at Baltimore has developed an aggressive technology development and transfer program (Fiocchi & Osterweis, 2000) . Another example is the joint venture between Columbia University, Cornell University, and New York Presbyterian Hospital to create a Clinical Trials Network (Bodenheimer, 2000). The network brings together academic researchers and community-based physicians in cardiology, hepatology, neurology and oncology, while providing training and centralized contracting, budgeting and reimbursement systems . In 1997, the University of Pittsburgh Medical Center Health System chartered the Pittsburgh Clinical Research Network, a single point of contact between industry and clinical researchers . In essence, the structure and organization of AHCs are changing to accommodate a renewed emphasis on research in ways such as the addition of an office of research, support for patents, partnerships with research parks, and the development of incubators and centers of excellence (Rubin & Lindeman, 2001) . Governance and Structure Strategies Traditional AHC organizational structures are continually challenged by the need for operational and entrepreneurial flexibility to survive in competitive markets . These structures must allow for rapid decision making as well as

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mobilization of the organizational resources necessary for implementing strate-

gies (Griner & Blumental, 1998) . The traditional AHC governance structure relies on a central figure, such as a vice president, dean, or university

president to integrate clinical services and medical education (Blumenthal et al ., 1999) . Texas Tech and Texas A&M Universities have each organizationally relocated their health activities, placing them within a separate university

administrative unit that is directed by its own president . This effort was intended to consolidate research, education, and service missions under one authority

position (Mission Management, 1999) . However, it still leaves the role and

authority structure between the hospital and the medical school unclear . Furthermore because public AHCs are legally restricted in Texas from

ownership of affiliated hospitals, their ability to address governance problems is necessarily limited . However, this situation could change, especially with states' recent interest in commercializing research and expediting technology

transfers . For example, the Texas legislature recently enacted a law that essentially limits lawmakers from intruding on the process of promoting

collaboration between universities and businesses that is crucial in transferring technology (Schmidt, 2002) .

Concerns over financial liability have led some universities to spin off their

clinical enterprises despite the fact that such a move may reduce the influence of the medical school over the teaching mission and decrease the availability

of both physicians and patients to meet the needs of the clinical curricula (Griner & Danoff, 2000) . While decreasing control, this new strategy allows increased autonomy and flexibility especially when it involves reduced oversight by the

state (Managing Academic Health Centers, 2000) . For example, Oregon Health Sciences University reinvented itself as an independent public corporation by

removing itself from the control of the state's system of higher education (Alexander, Davis & Kohler, 1997) . The University of Maryland's AHC

removed itself from the university's governance structure by becoming a

not-for-profit corporation (Schimpff & Rapoport, 1997) .

Other AHCs report similar separations from university control, including

Creighton University, St . Louis University, Tulane University, and George Washington University

(Mission Management,

1999) . In the case of the

George Washington University, the hospital is separately owned by a partnership

between Universal Health Services, Inc., a large for-profit hospital management

company, and the university (Hospital News, 2002) . Others such as Tulane Medical Center sold controlling interest to Columbia/HCA, St. Louis University sold controlling interest in the hospital to Tenet Hospital System, and Creighton University

sold its major teaching hospital to Tenet Hospital System (Managing Academic Health Centers, 2000) . Although this strategy was a response to the increasing

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complexity and competitiveness of the health care industry, its success is still to be determined . A Commonwealth Fund report that looked at three examples in detail (i.e . Creighton, George Washington, and Tulane) found no short-term adverse effects on the academic missions (Blumenthal & Weissman, 2000) . In no case did the for-profit partners try to affect the content of medical education or did the level of indigent care decline . Financial performance improved under the for-profit management as well ; however, at this time, the long-term impact of this strategy has not been evaluated . Operating Efficiency Strategies As part of decreasing reimbursement rates, AHCs have taken steps to improve financial efficiency and increase clinical productivity . Some of these have been positives moves such as the revamping of the University of Arizona Health Sciences Center's business practices by hiring business people to run the group practice and hospital, eliminating most capitated contracts while focusing on discounted FFS, and building up billing and collection (Alpert et al ., 2001) . Alternatively, Duke Children's Hospital implemented the balanced scorecard, a management approach used to align the goals of financial health, customer satisfaction, internal business procedures, and employee satisfaction (Meliones, 2000) . In addition, AHCs are experimenting with new information systems, such as funds flow accounting and physician order entry, in order to improve accountability and quality (Managing Academic Health Centers, 2000) . On the other hand, a number of AHCs have implemented downsizing strategies (Bland, 1997) . For instance, downsizing of AHCs such as Duke University Hospitals and Medical University of South Carolina have been described in the literature (Woodard, Fottler & Kilpatrick, 1999 ; Zimmer, 1997) . Although this strategy demonstrates short-term results, there is doubt as to its long-run ability to lower the operating budget and increase productivity (Bland, 1997) . In summary, AHCs are adapting new strategies by looking at their clinical and research operations for innovative solutions . They are beginning to look at the long-term implications of their strategies and make decisions based on the results . However, this has been long in coming . Before, AHCs played "copy cat" in their strategy development, particularly involving strategic decisions and considerable change. For instance, note the similarity between many AHC strategies (e.g . mergers, network development, and PCP acquisitions) and those of community hospitals and other AHCs (Krauss & Smith, 1997 ; Topping et al, 1999) . The AHCs were admonished to become more business-like and, in so doing, have adapted business strategies that often are questionable . Furthermore, the early AHC literature is replete with articles describing the need to develop


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integrated delivery systems in order to increase market share, thereby, improving power to negotiate with managed care organizations . Following from that, AHCs implemented these strategies, sometimes much to their regret .

FUTURE STRATEGIES : WHERE DO AHCS GO FROM HERE? The future of AHCs is a matter of debate . On one hand exist those who advocate that the AHCs change their missions and evolve into organizations that do not resemble the institutions of today . On the other hand are those who believe that the mission defines the AHC and by adapting incrementally, AHCs can adjust to the environment and succeed . To illustrate the debate, Epstein (1995) likens AHCs to the role of locomotives in the evolution of the transportation industry . Over a century ago, the steam-driven locomotive was the dominant form of long distance transportation, yet over time, it had to give way to the diesel-driven locomotive and, then, to other new technologies . Although still important, locomotives had to redefine their function and role in transportation . Reasoning from this analogy, AHCs, like the locomotives, may have to redefine their role and function in the evolving health care system . Conversely, Muller (2001) suggests the image of the four-chambered heart to represent the traditional three missions of the AHC plus the overlaying mission of community service . According to Muller, this biologic model symbolizes the dynamic relationship that exists between the missions . More importantly, it captures the centrality of the AHC to keeping alive the greater body of the health care system . Without any one of the four chambers, the heart cannot function ; without the heart, the body cannot survive . In essence, the missions are essential because without them, there is no AHC . Similarly, the AHC with its long-standing mission plays a central role in the health care system ; without the AHC, the system will die . There are many who agree with Muller, calling AHCs the "intellectual backbone" of the health care system (Iglehart, 1997 ; Langabeer, 1998 ; Saxton, Blake, Fox & Johns, 2000) . However, the management philosophy in vogue today seems to be more in agreement with Epstein . For instance, AHCs are beginning to implement "mission management" which involves separating the missions so that each one can be managed in terms of specific resources and expectations . A matrix organizational structure supports mission management in that individuals at multiple levels of the organization are assigned primary responsibility for each mission, but retain dual accountabilities for the organizational unit in which they are based as well as the mission for which they have assigned responsibility . The goal of mission management is to create a

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group of managers who pay attention to the unique needs of each mission without neglecting the needs of the AHC as a whole and without contributing to increased bureaucracy (Managing Academic Health Centers, 2000) . The move toward unbundling or spinning-off missions, which traditionally have been conjoined, is an untested strategy . Although researchers and practitioners alike are advocating for disconnecting the AHC's missions, there is little evidence to support such activity . Furthermore, there is almost no indication that serious thought or consideration has been given to the implications for such changes to the traditional, interconnected missions . Reconfiguring mission functions as unconnected business lines, with each one having a bottom line, a separate funding source, and no linkage with another function is a radical step for AHCs and the U .S . health care system as a whole (Korn, 1996) . Additionally, the shift from mission to enterprise comes with enormous consequences . Enterprise, unlike mission, connotes a business venture or project and typically represents a degree of risk and a potential for loss . If the tripartite missions become speculative projects for the AHC instead of the reasons for the organization's existence, differentiating AHCs from other organizations becomes questionable . According to the AAHC definition, the missions define the AHC . If AHC missions are translated into special projects or business lines of the AHC, it may become easier, at least psychologically, to dispense with unfunded or underfunded services and activities such as teaching and indigent care . Clearly, great care should be given to changes in the mission of AHCs because of their impact on the core values and culture of these institutions and the expectations of society relative to social goods . Since Epstein and Muller represent each end of a continuum, it may be a better alternative to find a middle ground . Drucker (1995) has suggested that many organizations are in trouble because their theory of the business is obsolete, invalid, or in need of revising . That is, the assumptions on which the organization was built no longer fit reality and are no longer congruent . Given the point of view of the AHC, these assumptions would include those about the mission and core competencies as well as assumptions about the environment, including markets, customers, technology, and society . These should fit together, and if they do not, AHCs should be encouraged to question the validity of their assumptions . Based on Drucker (1995), Table 2 provides an example of a checklist for an urban AHC examining its assumptions . In this case, the urban AHC finds that, indeed, the assumptions have changed, and as a result, will have to decide whether to follow, say, Partners' example and merge or remain independent . The decision may rest on the identification of core competencies, for one of the reasons that Partners has been so successful is because of the reputation of the two merged AHCs .

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Table 2.

Example of a Checklist of Assumptions for an Urban AHC .

Item

Possible Responses

Have assumptions about the environment changed?

Yes, AHCs are no longer assured the central position in the health care system ; therefore, they cannot sit back and wait for referrals .

• Markets

Competition is intense with unprecedented consolidation occurring in response to managed cared as well as substantial restructuring with development of IDSs . Gains in market power are being achieved through mergers . Competition is once again occurring in local markets .

• Customers

Competition is no longer patient driven . Managed care has led to payer-driven competition . MCOs focus on price of services rather than quality .

• Technology

Advances allow community hospitals to provide some tertiary services that previously were only available at AHCs .

• Social

Managed care has shifted focus from access, quality and cost to cost, access and quality . Business principles infuse AHCs and community hospitals .

Has AHC mission and/or strategies changed?

No mission change ; strategy change includes emphasis on efficiency through cost-cutting measures and market share by identifying centers of excellence.

Are they still the right mission and/or strategies?

Mission is still right, but strategies must continue to change to accommodate the increasingly competitive environment .

Is it still worth doing?

Yes, due to the mission and the contribution to society .

Are AHC core competencies Core competencies are well-renown reputation, innovative appropriate given the environmental, culture, and cutting-edge research ; therefore, it makes sense mission, and strategic changes? to merge with another AHC with like culture located in the city to decrease competition . The intent would be to find a I partner having similar reputation with complementary centers of excellence. Source: Checklist derived from Drucker . P . F . (1995) . Managing in a time of great change . New

York : Truman Talley Books/Plume .

Clearly, it is not sufficient to ask, "What is our mission and is it appropriate"? AHCs must also question the core competencies of the organization and if they lead to a competitive advantage . When considering mission change, it is important to note that AHCs have not been effective in defining their unique contributions to the health care system (Iglehart, 1997) . Solomon (1995) believes that AHCs, more than any other entity, are responsible for the technological advances in modern medicine . He believes that AHCs " . . . have

288


revolutionized the practice of medicine, that their teaching hospitals are a laboratory, and that their health professionals provide the scholarship supporting technological advances" (p . 97) . Blumenthal and Meyer (1995) support this contention, for they believe that AHCs have a unique advantage in their position in the technology transfer process . "Their competitive advantage is the ability to `marry new knowledge' to practice ; they add value to the health care system by the production of knowledge-based products and services" (p . 189) . Thus, this is their market niche . However, we cannot lose sight of the fact that although AHCs' multiple missions appear to provide competitive advantage in terms of niche markets, they have greater financial burdens that diminish these advantages. The teaching mission of AHCs is a competitive disadvantage in the market for privately insured patients . Similarly, providing care for the uninsured continues to be a financial burden for AHCs because MCOs are unwilling to cross-subsidize such care . More recently, the research mission of AHCs has been challenged by forprofit CROs that are not subject to lengthy reviews by IRBs, which must approve and monitor every clinical trial (Hundley, 2002) . Thus, it is impossible to describe AHCs as either advantaged or disadvantaged by their tripartite missions . The reality is that some aspects of their missions are beneficial strategically such as the status and prestige of a teaching hospital while others are detriments such as the cost of teaching . One important opportunity that can be derived from the AHC mission is the enhancement of reputation or image . The findings of a survey of PCPs in two markets, Philadelphia and Atlanta, supported the notion that the image of the AHC is its strongest asset (Culbertson, 1996) . Another study (Ayanian et al ., 1998), examining outcomes in congestive heart failure and pneumonia in the Medicare population, found that overall quality of care was rated better in major and other teaching hospitals than in non teaching . Although AHCs may be recognized for treating rare and severe diseases, these findings and others support the notion that AHCs provide better care for common illnesses as well (Taylor et al ., 1999) . As a result, Pardes (1997) recommends that AHCs communicate frequently and loudly to all stakeholders their importance in the health care system . For example, although the specialty care mission puts financial burden on AHCs, they are the major providers and initial developers of rare procedures and treatments . These services may be a source of competitive advantage since AHCs can market their unique capability to deliver high technology and specialized services such as cardiac care, burn units, and transplant services (Managing Academic Health Centers, 2000) . In considering the image and reputation of AHCs, an important caveat is necessary . That is, AHCs must pay close attention to the demands of the


289

marketplace in developing innovative strategies and defining core competencies that ultimately will enhance reputation and image . For instance, the University of California, San Francisco Medical Center (UCSFMC), relying heavily on its outstanding reputation, has developed tertiary and quaternary product lines and marketed these aggressively on a regional and national basis . This strategy, marketing expertise in highly specialized areas, was in response to a high penetration of managed care that existed in the area making UCSFMC unable to compete in primary care (Blumenthal & Meyer, 1996) . The University of Chicago Medical Center (UCMC) has been able to turn its location in the inner city to its competitive advantage . Since it has become the sole provider to the vulnerable populations located there, the AHC was able to lobby state legislators for a favorable Medicaid reimbursement rate, which has resulted in improved financial conditions (Blumenthal & Meyer, 1995) . In both these cases, the AHCs have responded to the market, thereby making it easier to identify and, therefore, communicate directly with key stakeholders . Although the examples above pertain to clinical services, it has been recommended that value enhancement be extended to teaching and research . One example, the West Virginia University Health Sciences Center (WVUHSC), which is located in a largely rural state, has placed special emphasis on education products by offering mini-residencies with specialty services and traveling specialists to conduct continuing medical education programs in isolated areas (Blumenthal & Meyer, 1995) . Others have opened internal offices for licensing and technology transfer, increased involvement with industrial organizations, and development of incubators and centers of excellence (Robin & Lindeman, 2001) - all with the goal of communicating the value added to key constituents . Broadly speaking, this means that AHC managers must be not only attuned to the specific environment or market but also able to communicate and influence targeted stakeholders (Guo, 1999, 2001) . Arguments against the mission driven approach usually focus on financial concerns and managed care, but the evidence does not clearly support this reasoning . First, results from studies of the financial experiences of AHCs have shown that AHC hospitals actually have performed better than other hospitals . In an early study showing the impact of DRGs and PPS, AHC hospital margins increased, even though margins of other large hospitals decreased (Hadley & Gaskin, 1995) . A more recent analysis reported that AHCs experienced healthy financial performance during the 1990s despite the higher costs of their education, research, and social missions such as indigent care (Anderson et al ., 1999) . Thus, even with substantial mission commitments AHCs have somehow managed to survive and prosper, but the future is less certain . According to Anderson and colleagues (1999), AHCs are subsidizing much of their

290


mission-related work from one source - Medicare . Whether AHCs will be able to rely on Medicare in the long run to provide the extra funding for their missions and assure their continued viability is questionable. Although researchers have proposed a variety of strategies to assist AHCs in generating revenues and efficiencies, most are in agreement that AHCs cannot in the long-term sustain their traditional missions and remain competitive without finding additional sources of funding, either public or private support . In 1997, the Commonwealth Fund's Task Force on Academic Health Centers recommended creating a special trust fund, the Academic Health Services Trust Fund, to finance the missions of AHCs (Leveling the Playing Field, 1997) . Established as a broadly financed pool combining explicitly designated payments from Medicare, some Medicaid programs, and state and local government contributions, the trust fund would provide AHCs with a stable and adequate source of funding . Assessments or taxes on private health plans for their fair share of supporting AHC mission costs could also be included . In an address to the plenary session of the 107th Annual Meeting of the Association of American Medical Colleges, Pardes (1996) called for increased governmental support of AHCs, but with separate revenue streams for research, education, and care for the poor . Pardes also advocated for expanded communication with a variety of stakeholders, especially the American people, who are averse to more taxation, but for whom the future of AHCs is critical to the health of their families . There are also arguments for securing a stable funding source outside government . In particular, Anderson and colleagues (1999) have described the need to explore private funding sources so that AHCs will not be subject to the vicissitudes and politics of the governmental appropriations processes . Blumenthal and Meyer (1996) suggested that AHCs were neglecting opportunities to find private customers for their training functions and also the possibilities for alliances with MCOs to train health care professionals, including nurses and allied health professionals . Such action would enable AHCs to more fully exploit their training mission while contributing to quality clinical and service outcomes in a relatively efficient manner . Ultimately, as long as the public sector continues to pay a large proportion of the incremental costs, and the private sector is willing to pay some increment, the long-term viability of AHCs is good . Of course, this will be predicated on the public's image of AHCs and the belief that they add value .

CONCLUSIONS Blumenthal and Meyer (1996) assert that "at no time in the past 75 years, however, since the publication of the Flexner report, have AHCs experienced


29 1

such threats" (p .173) . From past experience, AHCs know that decision-making is difficult in such a dynamic environment ; however, the decisions made today are crucial to their future . For this reason, we have tried in this paper to analyze and ultimately understand the past mistakes and successes of AHCs, while also translating those outcomes into implications for the future . In so doing, we have focused on the tripartite missions and strategic direction of AHCs emphasizing both their uniqueness and commonalities . This has allowed us to explore current and future issues while questioning the conventional wisdom concerning AHCs . The value of this approach is that its allows us to think outside of the constraints of the business or enterprise models and to envision the synergistic potential that can result from the traditional missions of AHCs . Based on this, we focus on the question : "What was learned that managers, policymakers, and researchers can carry forth into the future`?" First, it is important to note that AHC uniqueness is an issue that carries through much of the previous discussion . Although similarities exist, most AHCs have their own distinct characteristics and personality . Some are public ; others are private . Some face intensely competitive markets ; others have little competition . Some are large and urban with powerful images and considerable financial slack ; others are small and rural with little reputation and many problems surviving . Because of this, individual differences are an important consideration in decisions about mission and strategy . An AHC located in a highly competitive, urban market will consider and execute a very different strategy than the AHC located in a resource starved rural area of the country . The AHC that competes directly against other AHCs will develop its mission and vision differently than the sole one in the state . The AHC that is dependent largely on state and federal support will shape its mission and strategy very differently from one that has large endowments . Thus, AHC uniqueness influences the need for context-specific solutions while also lending support to the dangers of the "me too" and "copy cat" strategies of the past . In addition to individual differences, AHCs share a commonality with all AHCs . That is, the unique role that they play in the health care system - the tripartite missions of teaching, research and service . It is important to note that the unique role, defined by the missions, is what differentiates AHCs ; therefore, it may be that there is no AHC without the tripartite missions . Given this condition, it seems that the business or enterprise model can be taken only so far . AHCs can function as a business as long as they remember what business they are in . In shifting their attention to the bottom line, they are making decisions based on the "means" and not the "end ." However, profitability is not the goal or "end," but the "means" to ensure survival of the AHC . Krauss and Smith (1997) wisely advocate that AHCs stop following the money because this leads

29 2


to unrelated research and programs and will jeopardize the public service mission for the sake of the bottom line . Hence, AHCs should focus on the synergy that comes from the missions in developing core competencies and gaining a competitive advantage . According to Pardes (1997), AHCs are the backbone of innovation due to medical research, which, in turn, is transferred to patients through teaching and clinical practice . Therefore, the real opportunity that faces AHCs is how to translate the source and amount of synergy from the tripartite missions into core competencies for the individual AHC . A third point coming out of the previous discussion is that AHCs have a dismal past record when it comes to revolutionary change . Although some of the failures are attributable to the wrong fit between the market and AHC strategy, much of it is due to implementation problems . Drastic change is generally met with considerable resistance from stakeholders, particularly those directly involved such as the medical staff . Because of this, large changes such as mergers or acquisitions should be accompanied by an implementation plan that involves developing a change vision, communicating with stakeholders, and training of staff and administrators . This last point is particularly important since it keeps surfacing as a significant weakness . That is, AHC's lack the managerial talent to deal with the complexities that arise with change. This, in part, can be dealt with through education and training which, ultimately, will filter down to the hiring process . In addition, the new development of evidencebased management in health care may be of benefit (Walshe & Rundall, 2001) . On the other hand, most everyone agrees that the AHC environment will continue to change resulting in numerous solutions and strategies being purposed . Instead of taking the lead, however, AHCs may be better off following Mintzberg's (1978) advice to use a "testing the waters" strategy . In essence, when drastic changes occur in the environment, those affected lose all sense of what will work and what will not . As a result, it is better to change incrementally or in small steps . Given the complexity of AHCs, the practical problems arising from the implementation of revolutionary changes are formidable, and in some cases, insurmountable . For example, the creation of an IDS has been a costly and difficult challenge for AHCs and other hospitals, as well . The strategy has resulted in cultural clashes between academic physicians and their community partners, and in reaction, the IDS strategy is in retreat among AHCs and other health care providers . Given these failures, it may be wise for AHCs to play it safe using incremental changes particularly since a number of incremental strategies adapted by AHCs have been fairly successful . Moreover, while the environment is changing, researchers and practitioners alike will continue to search for some perfect model that will allow AHCs to prosper and succeed in turbulent environments . In reality, there will be no


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permanent fix or perfect model to secure prosperity and success . In truth, AHCs, as with other health care organizations, have little alternative, but to change . However, AHCs would be wise to remember the past and the lessons that come from failure . Falling for every fad because it supposedly succeeded in business or some other community hospital is a denial of the vital missions of the AHCs and the ensuing competencies and capabilities . This puts AHCs in a reactive mode, susceptible to every change in the environment regardless of how small . Traditionally, their role has been training highly qualified physicians and other health professionals, conducting cutting-edge biomedical research, providing specialized services, putting technological innovations into medical practice, and providing care for the poor and uninsured (Leveling the Playing Field, 1997) . AHCs must apply this role to their own individual situation and develop a clear vision of what they aspire to be . As Krauss and Smith point out, for success they need "to acquire the requisite insight and understanding of the individual AMC, its distinctive competencies and capabilities, its value-creation processes, and the particular features and attributes of the markets the AMC serves or desires to serve" (1997, p . 575) .

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A STRATEGIC CHANGE/

ORGANIZATIONAL ECOLOGY BASED THEORY OF POST BANKRUPTCY PERFORMANCE IN HEALTHCARE FIRMS David D . Dawley, James J. Hoffman and Mark Hoelscher ABSTRACT This paper develops a theory regarding the determinants of postbankruptcy performance of healthcare firms. Specifically examined are the potential effects of strategic change (i.e. refocusing), organizational size, slack and munificence on post-bankruptcy performance. It is theorized that bankrupt healthcare firms that refocus have greater post-bankruptcy performance than all other firms . It is also theorized that greater organizational size, slack, and munificence enhance post-bankruptcy erformance . The theory developed in this paper highlights the benefits of refocusing the diversified healthcare firm, the liabilities associated with diversification in the healthcare industry, and organizational ecology theories and perspectives regarding organizational size, slack, and munificence . In addition, this paper aims to provide richer insight into our understanding of the post-bankruptcy performance of healthcare firms . Advances in Health Care Management, Volume 3, pages 299-318. Copyright (D 2002 by Elsevier Science Ltd. All rights of reproduction in any form reserved . ISBN : 0-7623-0961-X 299

300

DAVID D . DAWLEY, JAMES J . HOFFMAN AND MARK HOELSCHER

INTRODUCTION Over the past few years, there has been a dramatic increase in corporate Chapter 11 bankruptcy filings . During this time, healthcare organizations have not been

immune to bankruptcy . In January 2001, five of the ten largest national nursing

home chains were in bankruptcy court (Piotrowski, 2002) . After pursuing bold acquisition strategies in the 1990s, many post-acute providers are slowing down

and regrouping (Piotrowski, 2002) . During the 1990s, health systems and physician practice management companies (PPMCs) across the U .S . also pursued bold acquisition strategies by competing with one another to buy physician practices and hire doctors as employees (Burns, Degraaf & Singh, 1999 ; Steever, 2000) .

In the healthcare industry the conventional wisdom has been that healthcare

systems could strengthen market position by integrating, thereby consolidating

hospitals, ancillary services, physician practices and other services, even health

insurance, into large entities . In some cases, the purchases were one of the cornerstones of a proactive strategy to build integrated delivery systems and

prepare for future risk-based contracting (Collins, 1999) . However, according to the Medical Group Management Association, many of these new partnerships have evolved into "distressed marriages" that may be heading towards

divorce (Medical Group Management Association, 1999) . Unfortunately, many of these healthcare organizations (i .e . integrated delivery systems, hospitals, and

physician groups) are now facing financial difficulties that could lead to additional bankruptcy activity in the healthcare industry .

Particularly troublesome about the prospects of an increase in Chapter 11

filings are the costs to society . In the case of healthcare firms, bankruptcies have the potential to drain valuable resources from an already financially

strapped U .S . healthcare system . Researchers have cited several financial and non-financial costs associated with corporate bankruptcy that could drain

valuable resources from the U .S . healthcare system . Moulton and Thomas (1993) found that the direct costs (e .g . attorney's fees, loss from disrupted operations)

of bankruptcy may approach 20% of the firm's total liabilities . Although more difficult to estimate, indirect costs such as higher interest rates for lines of

credit, reduced bargaining power with suppliers, and difficulty in entering into long-term commitments (e .g . joint ventures, strategic alliances) may

exceed direct costs (Moulton & Thomas, 1993) . Non-financial costs include the stigma associated with being a bankrupt firm (Sutton & Callahan, 1987),

managerial displacement and/or underutilization (Gilson, 1989), the general loss of employment (Lynn & Neyland, 1992), and an overall reduction in access to healthcare .

A Strategic Change/Organizational Ecology Based Theory

301

The existing research in bankruptcy has been examined from the financial

and accounting perspective (e .g . Altman, Haldeman & Narayan, 1977), the legal

perspective of asset distribution and venue (e .g . Bradley & Rosenzweig, 1992),

the environmental perspective of corporate legitimacy and prestige (e .g . Aldrich, 1979 ; Pfeffer & Salancik, 1978 ; Selznik, 1949 ; Thompson, 1967), and the behavioral perspective of the board of directors (BOD) and top management

team (TMT) (e .g . Daily & Dalton, 1993, 1994a, b ; Gilson, 1990; Hambrick & D'Aveni, 1992 ; Miller & Friesen, 1977) . However, minimal research has exam-

ined the fate of firms once bankruptcy has been declared (see Hotchkiss, 1995 ; Moulton & Thomas, 1993) . This is especially true for firms in the healthcare industry .

Although a few studies have examined organizations that have emerged from

bankruptcy, none have examined the effects of strategic change or organizational ecology on post-bankruptcy outcomes . Consideration of these effects

seems important given that poorly performing firms which engage in specific types of strategic change are theorized to have better chances of recovery than

those which undertake less such strategic activity (Hall, 1980 ; Bibeault, 1982 ; Pearce & Robbins, 1993) . Additionally, a wealth of prior research suggests that

selection (i .e. organizational ecology) processes affect survival and failure rates (Hannan & Freeman, 1977, 1984 ; Sharfman et al ., 1988 ; Baum, 1996 ; Aldrich, 1979 ; Aldrich & Auster, 1986 ; Stinchcombe, 1965 ; Carroll, 1985 ; Delacroix &

Carroll, 1983 ; Bourgeois, 1981 ; Porter, 1980) .

Given the potential drain on the U .S . healthcare system when healthcare firms

go bankrupt, and the fact that the healthcare industry has been classified as a , non-munificent' industry that has been associated with abnormally high bankruptcy filings (New Generation Research, 1998), a logical extension of prior

bankruptcy research is to theorize about the effects of strategic change and organizational ecology on post-bankruptcy performance . This paper draws upon research that has examined bankruptcy in all types of firms/industries, and then applies it to healthcare firms . Specifically, this paper develops a theory

pertaining to the effects of refocusing and organizational ecology on the postbankruptcy performance of healthcare firms .

LITERATURE REVIEW Prior literature examining the post-bankruptcy performance of firms both inside

and outside the healthcare industry is minimal (see Brockmann, 1997 ; Daily, 1995, 1996 ; Hotchkiss, 1995 ; Moulton & Thomas, 1993 ; Flynn & Farid, 1991

for exceptions) . Research in post-bankruptcy performance includes voluntary

versus involuntary bankruptcy filing (e .g . Moulton & Thomas, 1993), BOD

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composition (e.g . Daily, 1995), and executive turnover (Hotchkiss, 1995) . A review of this literature is given below .

Voluntary versus Involuntary Choice of Chapter 11 Some research has examined Chapter 11 filings as being either voluntary (strategic) or involuntary (Flynn & Farid, 1991) . Voluntary choice of Chapter I 1 filing is thought to occur sooner than an involuntary choice, and is invoked with the intent of providing the bankrupt organization "a period of insulation from its creditors to assess its strengths, locate slack resources, and identify those products/ businesses that can be nurtured, scaled-down (shrunk selectively) or divested" (Flynn & Farid, 1991, p . 63) . These firms are believed to have greater chances of recovery than those firms forced into an involuntary declaration of Chapter I1 (Moulton & Thomas, 1993) . Flynn and Farid (1991) argue that in the period prior to the declaration of bankruptcy, management becomes increasingly aware of potentially devastating threats in their external environment . Additionally, Sutton and Callahan (1987) suggest that an organization's external constituencies may contribute to the focal company's demise . Examples include suppliers that become more focused on collecting past debts than pursuing future business, and a trend of customers not paying their debts . The key to surviving bankruptcy might be for the focal organization to remain cognizant of such trends and file for bankruptcy before

necessary resources are depleted . Perhaps a key outcome in selecting either voluntary or involuntary Chapter 11 filing is the resulting organization's viability . Flynn and Farid suggest that there is a critical level below which the "level of dysfunctional attributes begins to exceed the amount of functional attributes" (1991, p . 68) . The implication is that it may be critical to file Chapter 11 (voluntarily) before this critical level is reached and some level of viability remains . Before the critical point is reached, the organization is thought to retain some functional level of manage-

rial prestige (D'Aveni, 1989), technostructure and strategic apex (Mintzberg, 1983), employee morale (Cameron et al ., 1988), and communication technology (Huber, 1984) . After the critical point for Chapter 11 filing has passed, dysfunctional organizational attributes are thought to emerge such as high turnover (Flynn & Farid, 1991), intra-organizational conflict (Cameron et al ., 1988), dysfunctional managerial attributes (Whetton, 1980), and negative constituent reactions (Sutton & Callahan, 1987) . Thus, a voluntary Chapter 11 filing occurring before this critical point is reached affords the firm more functional attributes, and an involuntary Chapter 11 filing occurring after the critical point affords more dysfunctional attributes .


3 03

BOD Composition

A widely held belief in strategic management is that "board composition matters, and in a particular manner" (Baysinger & Butler, 1985, p . 103) . Most BOD composition research focuses on potential opportunistic behavior by management (Eisenhardt, 1989) . Perhaps the most powerful governance mechanism of the BOD is the audit committee (Kesner, 1988) . The audit committee is created to ensure the financial health of the firm, and monitor the integrity of the firm's financial reports (Daily, 1996) . In examinations of organizational failure, Daily (1996) suggests that the audit committee is particularly relevant . The Securities and Exchange Commission (SEC), the New York Stock Exchange (NYSE), American Stock Exchange (AMEX), and the National Association of Securities Dealers (NASD) mandate that all audit committees be composed exclusively of BOD outsiders (Kesner et al ., 1986) . A major function of the audit committee is to safeguard shareholder's interests against opportunistic behavior (Daily, 1996) . The focus on the audit committee's use of BOD outsiders ensures that committee members do not become "too cozy with management, either because of personal loyalties or their reliance on company-related business, to be independent" (Himelstein, 1994, p . 113) . While theoretically appealing, Daily (1996) found no empirical support for the efficacy of an outsider-dominated audit committee in reviving bankrupt organizations . Hambrick and D'Aveni (1988) argue that outside board members are typically the first to leave a failing firm . This exodus can be explained from the resource-dependency view that BOD outsiders typically have linkages to third party organizations allowing their departure (Daily, 1996) . Further, this departure may be explained by the human resource perspective that suggests BOD outsiders are often the most talented and thus the most mobile members of an organization (D'Aveni, 1989b) . It has also been suggested that BOD outsiders are more concerned with the stigma of being associated with a bankrupt firm . That is, BOD outsiders will disassociate themselves with the bankrupt firm to avoid media sensationalism and becoming scapegoats (Daily, 1996) . Consistent with resource-dependency theory, Brockmann (1997) found that board size was directly associated with post-bankruptcy performance . That is, as board size decreases, post-bankruptcy performance is likely to suffer . In addition to changes in the BOD, the composition of the BOD has also been found to affect post-bankruptcy performance (Daily, 1995) . That is, Daily found that the greater the proportion of BOD outsiders, the greater postbankruptcy performance . There may be a number of explanations why an outsider-dominated BOD might influence post-bankruptcy performance . From

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a resource dependence perspective, BOD outsiders often have greater access to external resources than BOD insiders (Hambrick & D'Aveni, 1992 ; Steams & Mizurchi, 1993) . Further, BOD outsiders with contacts to financial institutions may facilitate the bankruptcy negotiation process (LoPucki & Whitford, 1993) . Consistent with the threat-rigidity perspective, BOD composition may also affect post-bankruptcy performance . For example, Daily (1995) suggests that an insider-dominated BOD is more reliant on the CEO for their jobs than an outsider-dominated BOD . Therefore, an insider-dominated BOD has a greater centralization of authority than an outsider-dominated BOD and thus is more prone to threat-rigidity . Threat-rigidity is associated with managerial `paralysis' and hinders managerial ability to affect change (Staw et al ., 1981) . An inability to affect change will impede post-bankruptcy recovery (Hambrick & D'Aveni, 1988) . Executive Turnover CEO Replacement . CEO replacement is also associated with post-bankruptcy performance . Since the CEO is the individual held accountable for firm performance, it should not be surprising that CEO turnover often follows organizational failure (Hotchkiss, 1995) . For example, the average annual CEO turnover rate in "healthy" companies is 8%, whereas that for bankrupt firms approaches 50% (Gilson, 1990) . Additionally, Boeker (1992) found that more powerful CEOs (i .e, CEOs who also serve as chairman of the BOD) are less likely to be replaced than less powerful CEOs (Boeker, 1992) . That is, CEO duality moderates the relationship between bankruptcy and CEO replacement . Accordingly, other researchers argue that a change in CEO aids the recovery process of the failing organization (Hotchkiss, 1995 ; Datta & Iskandar-Datta, 1995) . For example, it is argued that simply the mere symbol of a new and purportedly different CEO sends a signal to stakeholders that an effective new leadership style will be implemented (Hambrick & Fukutomi, 1991) . Further, it has been argued that a replacement CEO (usually an outsider) affords the bankrupt firm new latitude for change that may break existing threat-rigidity (Staw et al ., 1981) . TMT turnover. Analogous to a newly (and externally) hired college or professional football coach bringing in a new staff, the CEO is likely to replace the existing TMT with managers of his/ her own choosing . Accordingly, Boeker (1992) found that while a CEO outsider is associated with greater TMT change, an internally promoted CEO is associated with less TMT change . Additionally, a powerful CEO is more likely to replace TMT members than a less powerful


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CEO (Boeker, 1992) . Hotchkiss found that "retaining pre-bankruptcy management is strongly related to worse post-bankruptcy performance" (1995, p . 8) . Similarly, Brockmann (1997) found that TMT turnover was positively associated with post-bankruptcy performance .

A STRATEGIC CHANGE/ORGANIZATIONAL ECOLOGY BASED THEORY OF POST-BANKRUPTCY PERFORMANCE IN HEALTHCARE FIRMS In short, prior post-bankruptcy research has been associated with voluntary Chapter 11-filing, BOD composition, and executive turnover with postbankruptcy performance . The relationship between these change agents and post-bankruptcy performance is shown in Fig . 1 . Implicit in the prior literature regarding change agents affecting postbankruptcy performance is that the aforementioned change agents will directly affect post-bankruptcy performance . However, merely enacting these change agents does not guarantee strategic change . In reality, it is more likely that strategic change directly affects post-bankruptcy performance (e .g . Rumelt, 1974 ; Hoskisson & Hitt, 1994 ; Miles & Snow, 1994) . Therefore an important extension to prior research is to develop a theory regarding the relationship between strategic change and post-bankruptcy performance . Recent research also suggests that certain organization ecology variables could also affect the strategic change and post-bankruptcy performance relationship (McGahan & Porter, 1997 ; Goll & Rasheed, 1997 ; Hrebeniak & Joyce, 1985) . Therefore a theory of how both strategic change and ecological factors (i .e . organizational size, slack and environment) affect the post-bankruptcy performance of healthcare is developed in this paper . A strategic change/organizational ecology based model of post-bankruptcy performance for healthcare firms is shown in Fig . 2 . In the following pages, propositions will be developed which examine the impact of strategic change,

• • •

Change Agents BOD composition Executive turnover Voluntary filing

Fig . 1 .

r Post-bankruptcy performance

Prior Research of the Antecedents to Post-bankruptcy Performance .

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I I Strategic Change

Fig . 2 .

A Strategic Change Based Model of Post-banruptcy Performance in Healthcare Firms .

organizational size, slack, and environment in order to extend the postbankruptcy literature as it pertains to integrated delivery systems that may be disintegrating and/or other healthcare organizations faced with the prospect of bankruptcy . Propositions

A wealth of research suggests that a key to initiating successful turnaround includes reductions in business segments, assets, product lines, and overhead (Hall, 1980; Bibeault, 1982; Pearce & Robbins, 1993) . Such strategic change is facilitated by high levels of diversification (Pearce & Robins, 1993 ; Barker & Duhaime, 1997) . That is, more diversified firms typically possess a greater number of business lines (or segments) that can be emphasized or de-emphasized thereby affording the firm more latitude to enact strategic change . De-emphasizing business segments or reducing diversification levels is the heart of refocusing . Refocusing is the process of contraction through reducing levels of diversification and/or segment divestitures (Markides, 1992, Hoskisson & Hitt, 1994) . In many ways, refocusing is an action taken to "tame the diversified firm" (Hitt & Hoskisson, 1994, p . 5) . Hotchkiss (1995) argues that the more business segments a bankrupt firm owns (i .e . the higher the diversification) the


3 07

greater the options of divesting unprofitable (or non-core) business segments . That is the higher the diversification level, the greater the chances of refocusing the firm's activities . Accordingly, Bibeault (1982) suggests that by divesting unprofitable business segments and focusing on more profitable segments (i .e . refocusing), the distressed firm should be able to improve cash flow and help keep the company afloat. However, some diversified bankrupt firms do not reduce their levels of diversification (i .e . refocus) (New Generation Research, 1998) . That is some bankrupt firms will maintain their diversification level and seek performance enhancement through other means (e .g . cost-cutting and financial restructuring strategies) (e .g . Pearce & Robbins, 1993) . Nonetheless, refocusing activity typically enhances post-turnaround performance (e .g . Barker & Duhaime, 1997) . In the present context, it has been suggested that some refocusing activity is better than no refocusing activity (e .g . Datta & Iskandar-Datta, 1995) . For example, Hoskisson and Turk argue that an over-diversified firm that refocuses "provides the firm with a number of opportunities to restore value that has been dissipated through excess diversification" (1990, p . 469) . Additionally, Montgomery and Thomas (1988) found that industry-adjusted ROA improved for refocusing companies in the three years following segment divestiture activity . Further, refocusing activity in over-diversified firms has been associated with profitability improvements (Markides, 1995) . If refocusing is successful in restoring value and profitability to the diversified firm, the diversified (and refocusing) bankrupt organization stands a better chance of recovering than either a diversified firm that does not refocus or a nondiversified (and stable) firm . (The remainder of this paper will simply refer to these firms as non-diversified firms .) Therefore, Proposition 1 : After filing for Chapter 11, diversified healthcare firms that refocus have a higher chance of recovery than diversified healthcare firms that do not refocus . Proposition 2 : After filing for Chapter 11, diversified healthcare firms that refocus have a higher chance of recovery than non-diversified healthcare firms .

Thus far it has been argued that healthcare firms that are diversified entering bankruptcy have greater tools with which to affect post-bankruptcy performance than firms that do not (or cannot) refocus . However this may not be the case for diversified healthcare firms that do not refocus . That is, distressed, diversified healthcare firms that do not refocus may have worse post-bankruptcy performance than non-diversified healthcare firms .

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Remaining diversified has its costs . These costs include information processing (e .g . Hoskisson & Hitt, 1988 ; Williamson, 1967), employee shirking (e .g . Calvo & Wellisz, 1978), coordination costs (e .g . Keren & Levahari, 1983), dilution of "dominant logic" (e .g . Prahalad & Bettis, 1986), and inefficiencies in governance and control of internal capital markets (e .g . Hoskisson & Turk, 1990) . Hoskisson and Hitt suggest that "when firms exceed certain diversification limits, they suffer reduced performance because ineffective strategic control or overemphasis on financial controls produce poor managerial decisions" (1994, p . 127) . As levels of diversification increase, the organization's (i.e. management's) capacity to make efficient resource allocations among the business units diminishes (Williamson, 1985) . Inefficient resource allocations are endogenously initiated and are argued to impede performance . This inefficiency is the result of diversification "beyond the limits of managerial know-how" (Miles & Snow, 1994, p . 67) . That is, diversification may exceed the limit of managerial competence and violate the organization's operating logic . In short, diversification can impair management's "dominant logic" in effectively managing the firm's business portfolio (Prahlad & Bettis, 1986 ; Grant, 1988) . Further, product diversification is associated with inadequate governance (Williamson, 1985) . That is, it has been theorized that diversification may shift the governance focus from strategic to financial controls (Hoskisson et al ., 1991) . A preponderance of the literature suggests that financial controls are a

less effective form of governance than strategic controls (e .g . Hoskisson & Hitt, 1988) . That is, strategic controls are believed to lead to better strategic choices (and hence profits) than financial controls (e .g . Hoskisson & Hitt, 1994) . Any of the above-mentioned consequences of diversification suggests that a bankrupt firm remaining diversified may impede its recovery process . In the present context, diversified firms that do not refocus carry a "liability of diversification" not present in non-diversified (and stable) firms . Therefore,

Proposition 3 : After filing for Chapter 11, non-diversified healthcare firms have a higher chance of recovery than diversified healthcare do not refocus .

firms that

Baum (1996) notes that "until the mid-1970s, the prominent approach in organization and management theory emphasized adaptive change in organizations" (1996, p . 77) . A more current approach for studying organizational change emphasizes evolution and environmental selection (e .g. Hannan & Freeman, 1977 ; Aldrich, 1979) . The field of studying organizations in this context is referred to as organization ecology .


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Organization ecology does not totally discount the strategic choice perspective (Hrebeniak & Joyce, 1985) . However, organization ecology views strategic choice as constrained and offers ecological approaches to studying organizational foundings and failures (Baum, 1996) . Organizational ecology includes consideration of demographic processes (e .g . age and size) (e .g . Stinchcombe, 1965 ; Aldrich & Auster, 1986 ; Hannan & Freeman, 1984), niche-width dynamics (Hannan & Freeman, 1977 ; Carroll, 1985), population dynamics (Delacroix & Carroll, 1983), density dependence (Hannan & Carroll, 1992), institutional processes (e .g. Meyer & Zucker, 1989), competitive processes (Hannan & Freeman, 1977), community interdependendence (Brittain, 1994), environmental processes (e.g . Delacroix & Carroll, 1983 ; Hannan & Freeman, 1977, 1984), technological processes (e .g . Tushman & Anderson, 1986), and structural inertia theory (Hannan & Freeman, 1977) . Specifically, this paper examines the demographic and environmental processes of organization ecology . Demographic processes include organizational size and slack (Hannan & Freeman, 1977 ; Baum, 1996) . Environmental dimensions include munificence (Aldrich, 1979) . In this context munificence viewed as the extent to which a given task environment is capable of sustained growth (Starbuck, 1976) These demographic and environmental processes will be discussed in the paragraphs that follow . Organizational Size . Organizational size is a key influence on survival rates in the organizational ecology literature (Hannan & Freeman, 1977, 1984 ; Baum, 1996) . Larger organizations are thought to be less likely to fail, because they are seen as more legitimate and possess greater structural inertia which the selection process favors (Hannan & Freeman, 1984) . Smaller organizations are thought to be more likely to fail due to the liability of smallness discussed in the previous section . Additionally, it has been suggested that smaller organizations are associated with higher death rates (Hannan & Freeman, 1977 ; Baum, 1996) . This may be due to the lack of resources (compared to larger organizations) that could be applied to the task of survival (Hannan & Freeman, 1984) . In short, organization ecology favors larger firms . In the case of bankrupt healthcare firms it is likely that size may also play an important role in affecting post-bankruptcy performance . This assertion is supported by Sharfman et al . (1988) argue that larger firms have a greater physical capacity to hold excess resources which enable firms to be more resilient to environmental shocks . Further, Moulton and Thomas (1993) found that organizational size is positively associated with reorganization success . From an organizational ecology perspective, it can be theorized that as firm size increases so would the firm's chances of recovery . Therefore,

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Proposition 4 : As organizational size increases, the chances of a health-

care firm's post-bankruptcy recovery increases .

Organizational Slack. While organizational slack does not appear in most organizational ecology literature, it does seem to affect ecological processes . Organizational slack is a synonym for "excess capacity" (e .g . Hannan & Freeman, 1989) . For example, Hannan and Freeman (1989) argue that organizations may posses a reduced sensitivity to ecological forces "by maintaining (sic) excess capacity" (1989, p . 314) . Additionally, Hannan and Freeman suggest that "organizational slack provides an evolutionary advantage" (1989, p . 106) to changes in the environment . Organizational slack has been dichotomized into two categories, absorbed and unabsorbed slack (Bourgeois, 1981 ; Singh, 1986) . Researchers generally define absorbed slack as costs inherent in the organizations (e .g . selling and administrative, overhead, working capital), and unabsorbed slack as uncommitted liquid resources (e .g . cash and marketable securities) . Organizational slack has been argued to be the greatest resource for implementing strategic change (Grinyer et al ., 1988 ; Barker & Duhaime, 1997) . Because organizational slack can be conceptualized as the cushion of resources which allows an organization to successfully adapt to changes (Bourgeois, 1981), firms with more slack resources at the time of bankruptcy filing should have a greater chance of surviving and recovering from bankruptcy (Flynn & Farid, 1991 ; Moulton & Thomas, 1993) . Therefore, Proposition 5 : As organizational slack increases, the chances of a health-

care firm's post-bankruptcy recovery increase .

The relationship between an organization and its environment is argued to be a relatively unexplored but potentially fruitful area in post-bankruptcy research (Daily, 1994) . A wealth of researchers argue that the firm's external environment is theoretically and empirically linked to performance (Porter, 1980 ; Scherer, 1980 ; Prescott, 1986 ; McGahan & Porter, 1997) . For example, Pfeffer and Salancik suggest that "one would expect that as the potential environmental pressures confronting the organization increase, the need for outside support would increase as well" (1978, p . 168) . This statement implies that failing healthcare firms may fair better in an environment rich with critical resources . Particularly important during organizational crisis (e .g . bankruptcy) is the organization's continued exchange with its critical constituents (Sutton & Callahan, 1987) . Consistent with the population ecology variables discussed in the sections above (i .e . organizational size and slack) is the view that recovery (or survival)


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is affected by the ability of the operating environment to support a population of firms (Hannan & Freeman, 1977) . Aldrich notes that "environments affect organizations through the process of making available or withholding resources and organizational forms can be ranked in terms of their efficacy in obtaining

resources" (1979, p . 61) .

Munificence . Consistent with the notion that environmental munificence is

associated with firm performance is that bankruptcies have been typically concentrated in industries which are experiencing adverse economic conditions

(e .g . low munificence) . For example, since 1980 thirteen 'non-munificent' indus-

tries have been identified with abnormally high bankruptcy filings (New Generation Research, 1998) . These industries (and examples) include health

care (e .g . Charter Medical, 1992, Unison Healthcare, 1998), airlines (e.g . Continental, 1990), information processing (e .g . Wang, 1992), real estate and

construction (e .g . Olympia & York, 1992), entertainment (e .g . Orion Pictures,

1991), restaurant chains (e .g . Flagstar, 1997), apparel manufacturing (e .g . Farley

Inc ., 1991), coal mining (e .g . Westmoreland Coal, 1994 & 1996), paging services (e .g. MobileMedia Corp ., 1997), casino hotels (e .g . Trump Taj Mahal, 1991), retail department stores (e .g .

Federated Department Stores, 1990),

convenience stores (e .g . Southland Corporation, 1990), and automobile financing (e .g . Jayhawk Acceptance, 1997) .

Accordingly, Goll and Rasheed (1997) recently found that munificence affects

firm performance . Similarly, McGahan and Porter (1997) found that an

organization's industry membership accounted for nearly 19% of the variance

in profitability, whereas business segment-specific membership accounted for nearly 32% of the variance in profitability . In short prior research provides strong support that munificence (by industry and business segment) affects organizational performance. Thus,

Proposition 6 : As environmental munificence increases, the chances of a healthcare firm's post-bankruptcy recovery increase.

DISCUSSION The Strategic Change/Organizational Ecology Based Theory of Post-bankruptcy Performance developed in this paper makes three important contributions to the

healthcare literature and specifically to research regarding the post-bankruptcy

performance of healthcare organizations . Each of these contributions is discussed below . First, this paper draws on the management literature and puts forth the idea

that refocusing can enhance post-bankruptcy performance in healthcare firms .

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DAVID D. DAWLEY, JAMES J . HOFFMAN AND MARK HOELSCHER

It is theorized that it is best to enter bankruptcy as a diversified firm as suggested

by Hotchkiss (1995) . This paper extends Hotchkiss' (1995) work by suggesting that post-bankruptcy performance can be enhanced by refocusing the diversi-

fied healthcare firm . Specifically, it is theorized that after filing for Chapter 11 : (1) diversified healthcare firms which refocus have a higher chance of recovery

than diversified healthcare firms which do not refocus, and (2) diversified healthcare firms which refocus have a higher chance of recovery than non-diversified healthcare firms .

Second, from a broader managerial perspective the theory developed in this

paper has implications for diversification theory as it pertains to healthcare

firms . Although prior research has shown some level of diversification to be

beneficial in healthy firms, the current paper highlights the liabilities of diversification in bankrupt healthcare firms and the need for managers to divest

non-critical business segments and refocus on business segments that maximize the opportunity to restore profitability .

Third, the theory developed in this paper extends the healthcare literature by

highlighting the positive effect of organizational size, slack, and munificence on

the post-bankruptcy performance of healthcare firms . Specifically, our theory builds on the population ecologists' theory that greater firm size leads to greater

survival rates (Hannan & Freeman, 1977, 1984 ; Sharfman, 1988 ; Aldrich &

Auster, 1986), and also proposes that smaller healthcare firms are likely to be at a relative disadvantage regarding constituency support, raising capital, and attract-

ing and maintaining human assets (Hannan & Freeman, 1984 ; Baum 1996) . Our theory also proposes that appreciable levels of absorbed slack reduce sensitivity

to adversity and provide healthcare firms with an evolutionary advantage over

their counterparts (Hannan & Freeman, 1989 ; Bourgeois, 1981) . Additionally, our

theory extends the healthcare literature by highlighting the positive effect of organizational slack on the post-bankruptcy performance of healthcare firms .

The theory developed in this paper has several managerial implications . Since

healthcare organizations that file for bankruptcy protection have met the ultimate measure of organizational failure (liquidation notwithstanding) (Daily,

1995), it is crucial that management refocus operations in an attempt to recover and recover quickly before all critical resources are depleted . It is theorized that there are specific actions that managers can take which can improve the bankrupt firm's chances of recovery and decrease recovery time . These actions include strategic change, location and utilization of absorbed slack, the management of

long-term debt, and asset reduction . It should be stressed that if a firm enters bankruptcy as an undiversified organization (like many healthcare organizations do), that post-bankruptcy performance can still be enhanced if managers of bankrupt firms are open to the idea of divesting as many non-critical assets as possible .


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The theory developed in this paper puts forth several determinants of post-bankruptcy performance that were hitherto absent in the literature . The theory also provides a foundation for several future research directions . In addition to testing the propositions put forth in this paper, one logical extension to the current literature would be to examine other forms of strategic change . While this paper focused on refocusing activity, other types of strategic change by healthcare firms could also be considered . Of particular interest in the recent strategic management literature are strategies involving downsizing . Moreover, strategic change determined by Rumelt's (1974) categorizations could also provide insight into other desired types of strategic change that healthcare firms could undertake . Finally, the inclusion of other facets of organizational ecology could extend the current study . Given the scope of this paper, organization size, slack and munificence appeared to be three of the most relevant ecological constructs in current strategic management literature . However, expanding the propositions developed in this paper to include niche-width and population dynamics, density dependence, community interdependence, and institutional and technological processes (Baum, 1996) could provide additional insights in the area of postbankruptcy performance .

CONCLUSIONS As mentioned in this paper's introduction, during the 1990s, health systems and physician practice management companies (PPMCs) across the U .S . competed with one another to buy physician practices and hire doctors as employees . Specifically, an industry consulting firm found that publicly reported merger activity in medical groups rose sharply from 205 groups in 1995 to 265 groups in 1996, peaking in 1997 with 511 groups merging (Steever, 2000) . Unfortunately, many of these new partnerships have evolved into "distressed marriages" that may be heading towards divorce (Medical Group Management Association, 1999), and thus could put a strain on the U .S . healthcare system . The fact that some of these physician group acquisitions are eventually divested and the fact that some integrated delivery systems are disintegrating is consistent with the more general business or corporate merger and acquisition literature . Although acquisitions are a popular means of diversifying, many are eventually divested (Porter, 1987 ; Ravenscraft & Scherer, 1987 ; Medical Group Management Association, 1999) . Various researchers suggest that the rate of failure exceeds 50% (Porter, 1987 ; Montgomery & Wilson, 1986) . Thus, the process of diversifying through acquisition is both a risky and expensive

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proposition . The costs associated with acquisitions and their divestiture leave managers wondering why some succeed and others fail .

There is an increasing body of anecdotal and empirical evidence that

difficulties in integration of physicians from medical groups into acquiring

hospitals and other healthcare organizations may in part lead to the break-up

of the combined organizations (Kirchheimer, 2000) . Disagreement of physicians over the groups day-to-day management combined with falling income has caused a great deal of conflict in many medical groups . These group conflicts led to loss of physicians who preferred to return to smaller, more independent

group practices even though the exiting physicians would face greater financial risk (Walter & Barney, 1990) . Dissatisfaction among physicians has led to experimentation with unionization by doctors . Fear of the consequences of owning unionized physician medical groups is likely to be an impetus to sell

medical groups and avoid future management/union conflict (Johnson, 1999) . There has also been difficulty in formerly independent physician-owners making

the transition into larger organizations where they are treated as employees with employment contracts to fulfill (Holm, 2000) .

These observations indicate that many post-merger integration problems could

lead to financial trouble for healthcare firms or worse yet bankruptcy . The

purpose of this article has been to examine the possibility of healthcare firms

declaring bankruptcy and offer steps that can be taken to increase their chances

of post-bankruptcy recovery . Whereas the current healthcare literature has dealt with acquisitions and divestitures as part of a diversification strategy, limited

research has dealt with the consequences of a diversification strategy failing to

the point that it puts the healthcare firm at risk of having to file bankruptcy .

Although this paper does not completely resolve all of the issues surrounding post-bankruptcy recovery by healthcare firms, it does furnish a broader perspec-

tive from where we can analyze the problem . It also establishes a new theoretical foundation from which bankruptcy in the healthcare industry should be studied . Overall, it hoped that the new theoretical foundation developed in this paper

aids managers of bankrupt healthcare firms in restoring their organizations to

financial health . It is also hoped that this paper will serve as a foundation for future research in the area of the determinants of post-bankruptcy performance for healthcare firms .

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FROM STAKEHOLDER MANAGEMENT STRATEGIES TO STAKEHOLDER MANAGEMENT STYLES : SERENDIPITOUS RESEARCH ON ORGANIZATIONAL CONFIGURATIONS John D . Blair, Staff A . Blair, Myron D . Fottler, Timothy W . Nix, G . Tyge Payne and Grant T . Savage ABSTRACT How health care managers make sense of stakeholders and act strategically within these inter-organizational relationships has significant impact on organizational survival and performance . Existing research on stakeholder management has focused on managing dyadic relationships with individual stakeholders. We propose, based on serendipitous findings from a prior reseach study, that organizations exhibit distinct configurations -

stakeholder management styles - in the ways in which they manage their key stakeholders. To explicate this notion, we review potential theoretical configurations of stakeholder management styles, including a well-known stakeholder typology, which focuses on the concepts of threat and cooperation . Based on this review, we develop a typology that shifts the focus from individual stakeholdrs to a focus on the organizations and their orientation toward managing a portfolio of stakeholders . We use secondary

Advances in Health Care Management, Volume 3, pages 319-346. Copyright © 2002 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN : 0-7623-0961-X 319

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JOHN D . BLAIR ET AL.

data analyses of a national sample of 686 medical group executives to conduct an exploratory study of how and whether stakeholder management styles are likely to impact multiple indicators of organizational performance. We conclude with propositions for future research, as well as implications for managerial practice .

INTRODUCTION All organizations have stakeholders (Mason & Mitroff, 1981) . Stakeholders are any individuals, groups or organizations which have a stake in the decisions and actions of an organization, and which attempt to influence those decisions and actions (Freeman, 1984) . Stakeholders exert a potential influence on every issue (Mason & Mitroff, 1981) and should be recognized and evaluated for their potential to support or threaten the organization and its competitive goals (Freeman, 1984) . Stakeholders are likely to attempt to affect organizational decisions and actions in order to influence the direction of the organization so that it is consistent with the needs and priorities of the stakeholders . In line with this reasoning, early conceptions of effective stakeholder management focused explicitly on strategically managing relationships with individual stakeholders (Blair & Whitehead, 1988 ; Blair & Fottler, 1990 ; Savage, Nix, Whitehead & Blair, 1991) . More recently, the focus on managing dyadic relationships to achieve strategic success for an organization has been questioned, and organization-stakeholder relationships have been characterized as networks (Rowley, 1997) or strategic webs (Blair & Fottler, 1998 ; Savage & Roboski, 2001) . Arguably, within the healthcare industry, the strategic web of relationships with key stakeholders is becoming more threatening and uncertain for a variety of health care organizations (Blair & Fottler, 1998 ; Savage, Campbell, Patman & Nunnelley, 2000) . For an organization, the "stakeholder bottom line" is the aggregate potential to threaten the organization and/or the potential to cooperate with it found within the set of key stakeholder relationships that make up its strategic web (Blair & Fottler, 1998) . The supportiveness - or lack of supportiveness - of the key stakeholders in this strategic web of relationships affects how and whether those stakeholders use their power and resources to support or thwart the organization's attempts to achieve its strategic objectives . Focusing on stakeholder supportiveness within the strategic web is an alternative way to look at traditional concepts of environmental threat and munificence (Blair & Whitehead, 1988 ; Whitehead, Blair, Smith, Nix & Savage, 1989) . Conceptually, the level of stakeholder supportiveness partially determines the strategic capabilities and vulnerability of an organization, i .e . its range of

From Stakeholder Management Strategies to Stakeholder Management Styles

32 1

strategic options and room to maneuver . Hence, we address two interrelated research questions in this paper . First, do organizations, in a generalized response to stakeholder supportiveness, adopt certain configurations for managing stakeholders? And, second, do stakeholder management configurations have strategic implications for organizations? To address these questions, we review potential theoretical configurations of stakeholder management styles, including a well-known stakeholder typology, which focuses on the concepts of threat and cooperation . Second, based on this review, we develop a new typology that shifts the focus from individual stakeholders to a focus on the organizations and their fundamental orientation toward managing a portfolio of stakeholders . Lastly, we use secondary data analyses of a national sample of 686 medical group executives to examine how and whether stakeholder management styles are likely to impact multiple indicators of organizational performance .

FROM TYPOLOGIES TO ORGANIZATIONAL CONFIGURATIONS Although typologies of stakeholders have been developed (Freeman, 1984 ; Blair & Whitehead, 1988 ; Blair & Fottler, 1990 ; Mitchell, Agle & Wood, 1997 ; Savage, Nix, Whitehead & Blair, 1991), no typology of organizations themselves - focusing on how they approach managing relationships with a set of their key stakeholders - has been proposed . Thus, the first issue to be addressed in this paper deals with whether organizations have distinct, recognizable styles for managing sets of stakeholder relationships . Blair and Fottler (1998) report evidence for the existence of a stakeholder management configuration . In the process of analyzing their research data, they initially discovered and reported a typology of "web navigation types" from an organizational perspective (Blair & Fottler, 1998, p . 90) . They had set out to look for individual strategies used by organizations with individual stakeholders, and had serendipitously discovered that organizations managed their stakeholders with what we, in this paper, call a consistent "stakeholder management style" which cuts across all stakeholders . Stakeholder management style parallels for relationship management the notion of strategic orientations for overall organizational strategy . For example, the strategic orientation typology developed by Miles and Snow (1978) and used effectively to study healthcare organizations by Zajac and Shortell (1989) is, as we explain below, an attempt to identify organizational configurations . Many classifications of organizations exist that are based around the strategy and/or structure configuration concept . They have been labeled typologies

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JOHN D . BLAIR ET AL .

(Galbraith & Schendel, 1983), gestalts (Miller, 1981), modes (Mintzberg, 1973), archetypes (Miller & Friesen, 1978, 1984) or taxonomies (Hambrick, 1984) . Whichever term is used, the grouping of organizations based on configurations assumes that individual members of each group have similar elements, characteristics, or themes . In this paper, we will use the concept of "styles" to reflect the same kinds of configurations . Configurations are typically proposed as useful to strategy research because of their ability to predict the performance of the organization, usually given certain environmental conditions (Miles & Snow, 1978 ; Dess, Newport & Rasheed, 1993 ; Miller, 1986, 1996a ; Ketchen, Combs, Russell, Shook, Dean, Runge, Lohrke, Naumann, Haptonstahl, Baker, Beckstein, Handler, Honig & Lamoureux, 1997) . The central idea of configurations lies in configurations themselves - as an independent quality (Miller, 1996a) . Configurations can be a source of competitive advantage for a firm because that advantage resides in the interaction of many elements centered and coordinated along a pivotal theme (Black & Boal, 1991) . In other words, competitive advantage for any organization may not be based on specific resources or abilities per se, but rather those integrated mechanisms or relationships between or among organizational components (Black & Boal, 1991) . It is the uniqueness of any organization - the configuration - that is the essence of an organization and has a central impact on performance . Despite a long history of configuration research and its relative intuitive appeal, the area of study as a whole has met with much scrutiny and has demonstrated mixed empirical results . Some scholars have questioned the validity or usefulness of configurations and the need for further study (Barney & Hoskisson, 1990 ; Hatten & Hatten, 1987), while others have called for more configuration research (Miller, 1996b) . Although distinct organizational configurations which appear as different stakeholder management styles by different clusters of organizations probably matter to the representatives of their key stakeholders, the question of whether different styles of stakeholder management matter to the organizations themselves is unclear. This issue involves both a descriptive and an instrumental question that has not been adequately addressed in the stakeholder literature (Donaldson & Preston, 1995) . There are three distinguishing characteristics of most stakeholder research in management . First, stakeholder research focuses primarily on dyadic ties between a stakeholder and the focal firm - often the shareholders or the employees (Rowley, 1997 ; Kochan & Rubinstein, 2000) . Second, stakeholder research generally takes the perspective that stakeholder groups put demands, make claims, or pressure the firm, and the firm must respond or otherwise


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"placate" the stakeholders . Thus, there is a premise of either an adversarial

relationship or a dependency . Finally, stakeholder research has mostly focused on public policy issues such as ethical controversies and social responsibility . Hence, one reason that stakeholder management styles have not been explored

is that much of the stakeholder theory has been directed toward addressing

issues of its normative adequacy, while ignoring the instrumental linkages to

strategy that Freeman (1984) first articulated . Clarkson (1995) suggested another reason for this gap in the literature . He argued that most empirical efforts have

sought to link organizational performance with highly abstract notions of corporate social responsibility and ethics . These empirical efforts have not approached the organizational performance issues by looking at organizational configurations, as we are doing in this paper .

Indeed, the need for understanding how to manage relationships in a system-

atic and strategic manner is crucial since the nature of those relationships is

changing . These challenges and issues are relevant for all healthcare organizations and for most other industries . All organizations face challenging strategic

issues, and their leaders must navigate their way around the obstacles of building a supportive strategic web in an emerging environment .

The question raised is whether following an identifiable organizational config-

uration across stakeholders will be successful . This question runs counter to much of the strategic stakeholder management literature that recommends

treating each stakeholder as an entity to be assessed and for which an

appropriate matching strategy should be developed and implemented . To address this question and its logical implications, we review potential theoretical configurations of stakeholder management styles .

EXPLORING STAKEHOLDER MANAGEMENT STYLES CONCEPTUALLY For strategic purposes, the stakeholder typology that has been most frequently

used in the health care and management literature is one developed by Blair

and his colleagues (Blair & Whitehead, 1988 ; Blair & Fouler, 1990 ; Savage,

Nix, Whitehead & Blair, 1991) . This typology is based on two dimensions :

potential for threat and potential for cooperation . Figure 1 illustrates how the these two dimensions may be used to characterize four distinct types of stake-

holders - Mixed-blessing, Supportive, Nonsupportive, and Marginal - along with specific, matching strategies for the organization . These matching

strategies, arguably, are the optimal way to manage each of the four types of stakeholders . I

3 24

JOHN D . BLAIR ET AL . Stakeholder's Potential For Threat to Organization High Strategy I

High

Strategy 2

Collaborate With

Stakeholder's Potential For Cooperation With Organization

Mixed-Blessing Stakeholder Strategy 3

Defend Against

Low

Low

Nonsupportive Stakeholder

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Strategy 4

Monitor Marginal Stakeholder

"Based on the typology originally developed by Bla r and Whitehead (1987) and presented also in Blair and Fouler (1990 and 1998) as well as in Savage, Nix, Blair and Whitehead (1991) .

Fig. 1 .

Stakeholder Management Strategies - Organizational Strategies Based on Different Diagnoses of Individual Stakeholder Relationships .

Significantly, achieving optimal results with these stakeholder management strategies both imply and impose certain conditions . First, since executives continually manage a wide variety of stakeholders in terms of their potential

for cooperation and threat, executives need to use a combination of strategies

at any one time . Second, for optimal impact, each strategy should be consis-

tent with (or match) the diagnosis of each distinct stakeholder . Third, since the stakeholder diagnoses are very likely to change from issue to issue, the matching strategies also should change .

Changing the Focus to Types of Organizational Configurations The conditions noted above potentially are beyond the resource and cognitive

constraints of organizational executives . Executives may not individually diagnose and manage all of their stakeholders in terms of their potential for cooperation and threat, using a combination of strategies at any one time as the


325

diagnoses changes from stakeholder to stakeholder and from issue to issue . To conserve resources and reduce cognitive dissonance, executives may use a

consistent pattern of actions that reflects a specific stakeholder management strategic configuration for their organization - a style, across all stakeholders

regardless of the diagnosis of the individual stakeholders or the issues involved . The well-known Miles and Snow (1978) approach to strategy focused on four

different types of organizational configurations (the Defender, the Analyzer, the

Prospector, and the Reactor) . In a similar fashion, we propose four types of

configurations, or styles, that top managers' use for managing stakeholder relation-

ships . Instead of focusing only on the stakeholder or the stakeholder relationship

itself, as stakeholder researchers have in the past, we examine how an organization

approaches the wide-ranging web of relationships with its key stakeholders . For

executives, this means taking a hard look at how they think about relationships . Do they primarily focus on opportunities (potential for cooperation) or on hazards (potential for threat) when viewing their strategic web of relationships? Stakeholder Management Style Our aim is to develop a useful typology of organizations in terms of differ-

ences in stakeholder management styles . These styles should reflect differences in the levels of organizational priorities to reduce threat and/or to enhance

cooperation across multiple stakeholder relationships . Stakeholder management style is our term that defines the relationship management "intentions" of a

specific organization . To the extent that there are identifiable groupings of

organizations that use the same fundamental style, one can characterize these styles which represent distinct organizational configurations in terms of fundamental approaches to managing key organizational stakeholders .

Stakeholder management styles should describe overall patterns of actions

rather than specific actions . These stakeholder management styles can be used

to type or classify organizations and to represent the underlying propensity of an organization's leaders to approach stakeholder relationships concerned with

the potential for threat and/or the potential for cooperation - or to ignore both . Modern healthcare and other organizations face relationships with a multi-

tude of stakeholders . In other words, executives manage a portfolio of stakeholder relationships . Because of the complexity of these relationships and

the large number of diverse stakeholders, managers may seek shortcuts in the

stakeholder management process . Or, they may face an industry that is overwhelmed by one type of stakeholder, so they fail to recognize that others still

exist . Hence, an organization may adopt one type of stakeholder management strategy as dominant .

326

JOHN D . BLAIR ET AL . Stakeholder Management Styles as Organizational Configurations

Drawing upon the earlier efforts by Blair and Fouler (1998), we identify four types of stakeholder management styles, i .e . organizational configurations for managing stakeholders . The classification is based on two priorities that we argue are most important in effectively managing relationships with key stakeholders : the priority on enhancing cooperation and the priority on reducing threat. Four different combinations of dichotomous versions of the two dimensions - threat reducing and cooperation enhancing - allow one to assign each organization to one of four types, which are shown conceptually in Fig . 2 and discussed below . Stakeholder Management Style 1 : Relationship Eagle Relationship Eagle organizations have a high priority both on reducing stakeholder threat and on enhancing cooperation in web relationships . This style reflects the most sophisticated view of the organization-stakeholder web of relationships . It recognizes that most relationships are a mixed blessing, i .e. they will contain both opportunities, as well as threats . Organization's Priority on Reducing Stakeholder Threat Across Multiple Relationships Low

High

Style 1

High

Relationship Eagle

Organization's Priority on Enhancing Stakeholder Cooperation Across Multiple Relationships

Style 3

Relationship Pessimist

Low

Style 2

Relationship Optimist

Style 4

Relationship Ostrich

"Extension and modification of earlier typology developed by Blair and Fouler and presented as Figure 5 .1 on page 80 in Strategic Leadership for Medical Groups : Navigating Your Strategic Web (San Francisco : Jossey-Bass, 1998) .

Fig . 2 .

Proposed Stakeholder Management Styles - Organizational Configurations Based on Different Priorities in Managing Stakeholder Relationships .*


327

Stakeholder Management Style 2: Relationship Optimist Relationship Optimist organizations place a high priority on enhancing cooperation among the stakeholders in their of web relationships . They are optimistic about what they can do together, focusing primarily on the potential for cooperation . This focus is paired with a disregard for the potential dark side of stakeholder relationships . Relationship Optimists act as if every relationship can be made into a "win/win" for both parties . While these organizations certainly do not miss opportunities that other organizations might forgo, Relationship Optimists can assume unreasonable risks by ignoring or downplaying the implications, for example, of growing dependence on a strategic partner . Stakeholder Management Style 3 : Relationship Pessimist Relationship Pessimists place a high emphasis on reducing threat in their web of stakeholder relationships ; that is, they believe that all stakeholder relationships are risk-laden . Hence, these organizations view relationships primarily in terms of their potential for threat . As the mirror image of the Relationship Optimist, these organizations have little regard for the positive side of stakeholder relationships . Leaders of these organizations certainly do not put their organizations at risk through ignoring or downplaying the implications, for example, of growing dependence . However, they may be reluctant to explore key opportunities for what can, in fact, be win/win relationships . Relationship Pessimists are at risk primarily in producing negative self-fulfilling prophecies (Merton, 1957) . That is, because of distrust of the motives or trustworthiness of others, they either do not seek to form useful strategic relationships or put excessively burdensome restrictions and contractual guarantees on potential partners . Stakeholder Management Style 4: Relationship Ostrich Most organizations that are relationship ostriches are probably unintended ostriches . These organizations' leaders appear unwilling or unable to think systematically about the potential threat and cooperation inherent in the web of stakeholder relationships surrounding them . Therefore, these organizations cannot establish a pattern of prioirities to reduce threats and/or enhance cooperation within their stakeholder relationships .

RESEARCH QUESTIONS ABOUT STAKEHOLDER MANAGEMENT STYLES AS ORGANIZATIONAL CONFIGURATIONS We developed four research questions (see Fig . 3) to explore in detail some of the implications of the conceptual discussion of stakeholder management styles .

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These questions focus on whether stakeholder management styles exist, are a separate phenomenon, affect performance, and adhere to the conceptual framework articulated above . Research Question 1 Will organizations within the same industry segment empirically cluster into identifiable configurations consistent with the proposed stakeholder management, i.e. based on their levels of organizational priorities to reduce threat and/or to enhance cooperation across multiple key stakeholder relationships? Research Question 2 Will configurations of distinct stakeholder management styles be separate phenomena, which are independent of other expected factors (such as organizational structure or environmental context) which are also likely to impact organizational performance and which could provide an alternative explanation of the findings? Research Question 3 Will the stakeholder management style, which emphasizes both action-oriented priorities to reduce threat or to enhance cooperation (Relationship Eagles), show higher levels of organizational performance than single-priority style organizations (Relationship Optimists or Relationship Pessimists)? Research Question 4 Will the stakeholder management styles, which emphasize either action-oriented priority to reduce threat or to enhance cooperation (Relationship Optimists or Relationship Pessimists), show higher levels of organizational performance than the style with neither action-oriented priority (Relationship Ostriches)?

EXPLORING STAKEHOLDER MANAGEMENT STYLES EMPIRICALLY The quantitative data used in this study are a subset of data obtained from a national survey of medical group physician and administrative executives, entitled Facing the Uncertain Future . 2 This paper presents a secondary analysis of these cross-sectional survey data from the 686 medical group executive respondents in this study . The multiple item scales used have already been established by Blair and Fottler (1998) using factor and item analysis . However, Blair and Fouler did not specifically address the research questions posed in this paper, including whether stakeholder management styles exist empirically or how they impact multiple indicators of performance .

330


Use of Organizational Informants Respondents were requested to be informants about their own organizations, rather than to supply answers to questions about themselves . They followed an approach used by Tan and Litchert (1994) to look at managers' perceptions of their organization's relative performance compared to their competitors . Starbuck and Mezias (1996) note that managerial perceptions may be inaccurate and call for more research on the issue . However, they also note that perceptual errors may be smaller if the manager's functional area is related to the perceived variables of interest (in our case, stakeholder management styles and organizational performance), if the manager has more work and industry specific experience, and if the firm plans more frequently . In a related study, McCracken, Mcllwain and Fouler (2001) had managers compare themselves to their peer group concerning financial and profitability performance . Results showed that these comparisons had a high correlation and very high significance to actual financial performance measures . Although the issue may be moot in an exploratory rather than explanatory study, overall this research indicates that subjective comparisons to peers by organizational managers are acceptable indicators of performance . Moreover, as in this study, this method is acceptable for determining levels of organizational performance as compared to others in the same industry . Dependent Variables Organizational performance can appear in many forms . In this paper we will use five different indicators of such performance : 3 Performance Indicator 1 : Performance Indicator 2:

Relative Stakeholder Management Ability Relative Ability to Collaborate with Other Organizations Performance Indicator 3 : Relative Skills for Horizontal and Vertical Integration Performance Indicator 4 : Relative Achievement of Organizational Goals Performance Indicator 5: Relative Information System Capabilities for DecisionMaking. Independent Variable As argued earlier and illustrated in Fig . 3, the key independent variable in this study is stakeholder management style . This variable was derived in two steps, using two sets of questions about six key stakeholders . The first set of six


331

questions asked about the organization's priorities on reducing threat with each stakeholder; the other set of questions asked about the organization's priorities on enhancing cooperation with those same stakeholders . The question regarding priorities on reducing threat asked, "What priority does your organization put on reducing the level of actual and potential threat from each stakeholder?" Respondents then evaluated six stakeholders (physicians, patients, hospitals, competitors, managed care organizations, and integrated delivery system/network) according to a Likert scale ranging from one (very low) to five (very high) . Similarly, the priorities on enhancing cooperation question asked, "What priority does your organization put on enhancing the level of actual or potential cooperation from each stakeholder?" It also asked for responses on the six stakeholders according to the same Likert scaling . To derive the actual stakeholder management styles, two scales were created from these sets of questions . Then, a cluster analysis based on these scales was used to form four sets of organizations corresponding to the four ideal style types (Relationship Eagles, Relationship Optimists, Relationship Pessimists, and Relationship Ostriches) illustrated in Fig . 2 . Control Variables We controlled for the impact of two structural variables (organizational size and complexity) and two context variables (industry segment and environmental munificence) in these analyses . These four variables consistently demonstrated a high level of influence in studies by Blair and Fouler (1998) using these data and firm resource variables . Therefore, they are included here to ensure that any relationship found between stakeholder management style and the performance indicators is not spurious and simply a reflection of some contingency variable . Analysis Due to the large sample size, both hierarchical and non-hierarchical clustering techniques were chosen (Norusis, 1994) . K-means cluster analysis is used here as the primary, multivariate cluster analysis technique . However, this technique was followed only after a series of hierarchical clustering analyses were conducted based on random sub-samples of the entire data set . This process follows Ketchen and Shook's (1996) recommendations concerning clustering techniques in strategic management . Their suggestions

332


include using multiple techniques, multiple representative samples from the data, and visual examination of dendograms and other graphical displays to first determine the number of clusters that are appropriate for the study . Our analysis found that four clusters seemed to be the most common and relevant number upon which to base the final K-means cluster analysis . Then we used the K-means clustering procedure, which is a non-hierarchical clustering technique . This particular technique requires knowledge as to the number of clusters prior to running the procedure, which may be preferable to strictly allowing empirical clusters to form (Dowling & Midgley, 1988 ; Kabanoff, Waldersee & Cohen, 1995) . The empirical taxonomy found in our exploratory study is considered theory-driven because the variables utilized in the clustering were selected based on the explicit theoretical arguments presented earlier in the paper, as well as having support from the earlier hierarchical clustering of subsets of the data . Punj and Steward (1983) determined that the K-means approach is superior to other clustering techniques due to its relative robustness . Note that as in any classification, the higher the level of aggregation, the less similar the members in the respective class . Therefore limitations arise because of the restriction of the number of clusters . Moreover, cluster analysis does not take into account statistical significance testing because it is not as much a statistical test as it is a collection of different algorithms that categorize cases or variables . This point, therefore, requires cluster analysis to be often used in an exploratory way to determine if cluster findings match closely with theorized dimensions . Therefore, statistical significance testing is not appropriate even though p-levels are often reported when using K-means clustering techniques . This suggests that the cluster findings will only resemble reality if the theoretical components behind the variables themselves are representative of reality . Clustering techniques statistically create mutually exclusive categorizations of data based on multiple indicants . These techniques simultaneously seek to maximize within-group similarity and maximize between-group differences . However, cluster analysis is often criticized because it breaks the data into categories regardless of the strength of the data points . Therefore, since criticism of previous taxonomies has come for being too narrow in scope, the broad set of variables discussed previously and utilized in this study should nullify the influence of any one variable . To mitigate the effects of skewed distributions, all data were standardized with a mean of zero and a standard deviation of one . Because of the strong theoretical conclusions presented in earlier portions of this paper, the cluster analysis was performed using the individual survey items from the two scales


333

measuring the dimensions of stakeholder management style, with a four-cluster solution .

RESULTS Although theory-driven, our analysis is not a theory-testing activity . It is a theory-building effort to explore the conceptual and empirical probability of organizational configurations for managing stakeholders, and an exploratory attempt to see if they could be interpreted using the conceptual model presented earlier in this paper . The model itself reflects serendipity in research (Merton, 1957), since it was not anticipated when the original study was designed . The original study focused on organizations' stakeholder assessment, diagnosis and strategies . Organizational configurations, which reflect identifiable, cross cutting styles across multiple stakeholders, were not anticipated . The four empirically generated clusters were plotted to see if they, in fact, represented the four stakeholder management styles that were proposed in Fig . 2 . As Fig . 4 illustrates, the clusters fit the expected model quite well . An ideal model would have the four clusters located in each corner of the model . Although no cluster fit exactly, Cluster 1, representing the Relationship Ostrichs, is very close . Cluster 3, representing the Relationship Eagles, was also close to the theoretically expected position on the grid . It is interesting to note that these two management styles represent the extremes . Cluster 4 represents the Relationship Optimists reasonably well . Cluster 2 is identified with the Relationship Pessimists . Even though it is not on the extreme corner of the grid, it does locate in the expected quadrant . A new variable was then created that assigned one of the four styles to each organizational respondent . Utilizing Pearson's Chi-square statistic in a contingency analysis, the independent variable (categorizing the four stakeholder management styles) was determined to be not statistically significantly related (p < 0 .05) to the four potential control variables (organization size, organizational complexity, industry segment, and environmental munificence) discussed above . This indicates that, although Blair and Fottler (1998) found the four control variables to be highly related to many of the capabilities as key performance variables, these four control variables are unnecessary in the current analysis of stakeholder management styles . Thus, no multivariate technique was needed to examine any linkages between the styles and firm resource measures . Subsequently, one-way analysis of variance was used to measure the linkages of the stakeholder management styles to multiple indicators of organizational performance (see Table 1) . The overall results showed a remarkable level of

334

JOHN D . BLAIR ET AL . Organization's Priority on Reducing Stakeholder Threat Across Multiple Relationships High

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support for the four research questions associated with stakeholder management styles .

Research Question 1 : Do Stakeholder Management Styles Really Exist?

The first question asks whether organizations within the same industry segment

will empirically cluster into identifiable groups, and whether these groups will be consistent with expected stakeholder management styles based on the organizations levels of priorities to reduce threat and/or to enhance cooperation

across multiple key stakeholder relationships . The cluster analysis found four

From Stakeholder Management Strategies to Stakeholder Management Styles Table 1.

335

Exploring the Impact of Stakeholder Management Styles on Multiple

Indicators of Relative Organizational Performance (Compared to Competitors) . Performance Indicator

Eagle

Stakeholder Management Ability Standardized Scale Mean

0 .127

0.102

-0 .036

-0 .320

Collaborative Ability Standardized Scale Mean

0 .110

0.167

-0.064

-0 .287

Integrative Skills Standardized Scale Mean

0.158

0 .041

-0 .068

-0 .281

Competitive Capabilities Standardized Scale Mean

0 .056

0.071

-0 .054

-0 .152

Eagle (Compared to . . . ) Optimist Pessimist




Information System Capabilities Standardized Scale Mean

Optimist Pessimist Ostrich

X

X X

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F Ratio

F Prob

12 .096

0 .000

8 .697

0 .000

6 .782

0 .000

3 .105

0 .026

1 .162

0 .324

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X = Indicated statistically significant difference between the means of these two groups using a LSD test with significance level of 0 .05 .

distinct clusters of organizations based on their two key priorities in managing

stakeholder relationships . Further, the four empirically generated clusters clearly

represent the four proposed stakeholder management styles as shown in Fig . 2 . Research Question 2 : Are Stakeholder Management Styles a Separate Phenomenon?

This proposition argued that exhibiting a particular stakeholder management

style is independent of organizational structure (i .e . size, complexity) or context

33 6


(i .e . industry segment and environmental munificence) . Each potential control

variable was found to be not statistically significant (p > 0 .05) when analyzed using a Pearson chi-square statistic in a contingency table with each stakeholder management style . Hence, stakeholder management styles seem to be a separate phenomenon, independent of other plausible factors . Research Question 3 and 4 : Which Stakeholder Management Styles are Most Effective? Our tentative answer to Questions 3 and 4 is that stakeholder management style appears to be related to multiple areas of organizational performance . However, one area (information systems capabilities) was not related to style . Table 1 provides an overall assessment of the relationship between stakeholder management styles and the five firm resource indicators discussed previously . This table also will be used to examine Questions 3 and 4 in more detail . From the results presented in Table 1, it appears that the stakeholder management style, which emphasizes both action-oriented priorities to reduce threat and to enhance cooperation (Relationship Eagles), leads to higher levels of key areas of performance than the styles with one action-oriented priority (Relationship Optimists or Relationship Pessimists) . The results for the Relationship Eagle are clear for three of the five measures of performance indicators when compared to the Relationship Pessimist . There are clear relative differences for stakeholder management ability, collaborative ability and integrative skills (see Table 1) . However, Relationship Eagles did not demonstrate superiority in competitive capabilities or information system capabilities . In fact, in the most unrelated performance indicators (information system capabilities), Relationship Eagles show no statistically significant differences with any of the other three styles . The tentative results for the Relationship Eagle are not clear across all five measures of performance indicators when compared to the Relationship Optimist . There are no clear relative differences for any of the relative performance indicators between these two styles (see Table 1), but there are differences in how they relate to the Relationship Pessimist . However, although Table 1 shows only significant differences, examination of the patterns of mean score differences are consistent with the prior conceptualization of stakeholder management styles . It appears that stakeholder management styles, which emphasize either actionoriented priority to reduce threat or to enhance cooperation (Relationship Optimists or Relationship Pessimists), have higher levels of performance than the style with neither action-oriented priority (Relationship Ostriches) . Also,


337

Relationship Ostriches, when compared to the other three stakeholder management styles, had the lowest capability levels in four of the five key performance areas (all except information systems capabilities in which no significant differences were found) . Interestingly, the results in Table 1 indicate that stakeholder management style is most related to those areas of organizational performance which would be most impacted by high levels of relationship management analysis and actions. The largest F-ratio was found for the scale measuring the performance indicator, "relative stakeholder management ability," while each of the other performance indicators have progressively lower F-ratios (from top to bottom in Table 1) . As these performance indicators get less connected to what an organization does in terms of analyzing relationships or actions, the relationship with stakeholder management style becomes weaker . For example, in Table 1 "relative information system capabilities for decision-making" is not linked to stakeholder management style, nor should we expect it to be . This serendipitous finding is an important reminder that stakeholder management styles have impact within certain parameters . PROPOSITIONS FOR FUTURE RESEARCH The first four of the key propositions to be examined for future research are relatively straightforward, drawing from both the theoretical and empirical study of stakeholder management styles and organization performance . The fifth proposition, however, is based on the serendipitous finding noted above, and not included in our original conceptualizations about stakeholder management styles . Our overall model, including the propositions listed below, is presented in Fig . 5 . Proposition 1 Organizations within the same industry segment will empirically cluster into identifiable configurations consistent with expected stakeholder management styles, i .e . based on their levels of organizational priorities to reduce threat and/or to enhance cooperation across multiple key stakeholder relationships . Proposition 2 Configurations of distinct stakeholder management styles are separate phenomena and will be independent of other expected factors (such as organizational structure or environmental context) which are also likely to impact organizational performance and which could provide an alternative explanation of expected findings .

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Proposition 3

The stakeholder management style that emphasizes dual action-oriented priorities to reduce threat or to enhance cooperation (Relationship Eagles) will have higher levels of organizational performance than single-priority style organizations (Relationship Optimists or Relationship Pessimists) . Proposition 4

The stakeholder management style that emphasizes either action-oriented priority to reduce threat or to enhance cooperation (Relationship Optimists or Relationship Pessimists) will have higher levels of organizational performance than the style with neither action-oriented priority (Relationship Ostriches) . Proposition 5

Stakeholder management styles will have a greater impact on those types of organizational performance that need high levels of stakeholder management analysis and action, and will have a less impact on those types of organizational performance that need low levels of such activities .

CONCLUSIONS In this paper, we have attempted to raise some key questions and provide some tentative answers to some parts of them . Further we have articulated a series of propositions consistent with the model presented and the tentative findings of our re-exploration of the Facing the Uncertain Future data . We challenge other researchers to seek to both improve the theory and to make it as useful as possible to those looking over the ramparts of the organization's administrative offices . We even challenge them to apply these conceptual and methodological approaches to industries outside the healthcare industry . In addition, we have several suggestions for future researchers so they recognize the limits to this study, including suggestions for additional statistical analysis and research design . We then discuss the theoretical and practical implications of this work . Limitations

One of the limitations of this paper is the use of same source data for development of the stakeholder management styles and the performance measures . Certainly future research should include additional standard performance measures such revenues, growth, various measures of profitability, and market share .

340


Another problem with this study is its cross-sectional nature . On one hand, this cross-sectional view of stakeholder management styles over a number of organizations allows us to develop propositions about these styles . On the other hand, although this study's intent is exploratory and focuses on theoretical correlations and explanations, the element of time should also be taken into consideration when evaluating stakeholder management styles against performance . If the management style has changed over time due to environmental pressures or top management turnover, then performance should be evaluated after those changes have had time to have an effect . Since this was a secondary analysis, scales were utilized as they were drawn from the survey instrument . This data focused on a single respondent's descriptions of how their organizations responded to stakeholders . Multiple sources identifying the stakeholder management styles should be gathered for each organization in future research . In addition to some omitted variables of interest, some variables and constructs used in this study may be limited in their ability to capture the necessary measurement constructs. Future research should re-evaluate the stakeholder managerial style constructs, their measurement and the dependent variables described above . Future analysis should go beyond comparisons of groups through ANCOVA and MANCOVA analysis and look at regression models to determine the variance in performance that can be attributed to the four stakeholder management styles . The different constructs should be examined individually as well as together to look for any interaction affects that might be present . Implications for Theory This paper has moved stakeholder management beyond prescriptive management strategies to explore the possibility that we can identify a manager's style, which is applied regardless of the specific industry context of the stakeholder . In addition to the propositions developed here, future research should also ask how managers develop and apply stakeholder management styles . Example questions are listed below . (1) Do organizations recognize the different types of stakeholders? (2) Do organizations recognize that the classification of stakeholders may change as the environment of the industry changes? (3) If not, how do managers learn to recognize the different types of stakeholders?


341

(4) Does the same configuration of stakeholder management styles (i .e . relationship eagle, relationship optimist, relationship pessimist, and relationship ostrich) exist in other industries? (5) Do stakeholder managerial styles change with the different stakeholders, or do managers apply their particular style regardless of the characteristics of the stakeholder? (6) Are there differences between organizations in their ability to adapt to the appropriate stakeholder management style? (7) Can organizations learn to apply the appropriate stakeholder management style? If so, through what means? Implications for Practice

The four stakeholder management styles presented above lead to several overall implications for executives . These implications indicate the importance of relationship assessment techniques and imply that a high level of effort (including human and other resources) should be spent on relationship assessment . Accurate measures of the organization's reliance upon the resources from various stakeholders should be developed and periodically evaluated . Due to the turbulence in the health care market, key relationships should be continually assessed for their potential to threaten or cooperate with the Organization . These ongoing assessments should allow executives to seek fruitful coalitions and avoid or reduce threatening dependencies . This should result in better overall management of their relationships . Executives need to do more than merely identify stakeholders or react to stakeholder demands . They must proactively develop or enhance their organization's capacity for strategic relationship management rather than concentrating only on effectively dealing with a particular stakeholder on a specific issue . This means they need to anticipate the goals of their key stakeholders and then satisfy their key stakeholders by offering appropriate inducements in exchange for essential contributions . Even with effective strategic relationship management activities, many challenges will exist for health care executives . Turbulence will continue within the U .S . health care industry . Government reforms, especially at the state level, will continue to be proffered . Employer coalitions will gain in strength and demand concessions from health care providers and administrators . MCOs and IDS/Ns will become a stronger force, even as their organizational forms change . Those health care organizations, which take an active lead in assessing their stakeholders and following an optimal style, are more likely to be among the winners . In most cases, an optimal stakeholder management style will include both defending against threats from each particular stakeholder and stakeholders in

342


general while simultaneously enhancing cooperation with each stakeholder and stakeholders in general . In other words, the "relationship eagle" style, which simultaneously address threat and cooperation is the optimum relationship style in most cases . A close second is the relationship optimist, which focuses on enhancing cooperation . Of course, a potential downside of the "relationship optimist" style is a failure to address threats from a "mixed blessing" or "nonsupportive" stakeholder . The management of both threats and cooperation does not necessarily need to be done by one manager . Indeed, some managers may focus on threat (i .e . lawyers) while others may focus on opportunities (i .e . marketing managers) . As long as both threats and opportunities are addressed for mixed-blessing and non-supportive stakeholders, organizational performance should be enhanced . The goal should be to move mixed-blessing stakeholders to supportive stakeholders and non-supportive stakeholders to mixed-blessing stakeholders . In addition, executives must continue to develop their skills in identifying, assessing, and diagnosing their key relationships . Executives also must continue to learn how to formulate and successfully implement strategies that will effectively manage their group's important, but often unclear, relationships with these key stakeholders . Strategic and operational actions consistent with our findings are :

• Executives need to develop a vision of how they would like to relate to key stakeholders in the future, for example, what should be the nature of their contractual relationships? • Executives need to identify who within their organizations will be able to effectively "manage" the set of relationships and to provide these persons the resources necessary to ensure that the organization's "priorities" become its "realities ." • Organizational leaders must develop evaluation and analysis skills so they can understand contracts and cooperative agreements in order to protect their organizations from financial risk . • Health care executives must develop tools and techniques to assess which resources are vital to them and which resources have substitutes available . • Executives should reduce the health care organization's dependence on those stakeholders who will control key resources, but who will likely threaten rather than cooperate, with the organization . To survive the turbulent and revolutionary changes facing the health care industry, executives must better understand their internal and external relationships . In addition, they need to develop appropriate organizational priorities for


343

these many different types of relationships - and implement these priorities to both reduce threat across many types of relationships and also to enhance cooperation where it is appropriate . The final serendipitous finding of our research is that even if the organization adopts a "relationship eagle" stakeholder management style, certain dimensions of performance will be significantly and positively impacted while others will not be so impacted . More specifically, those elements of performance that need high levels of stakeholder management analysis and action in order to be achieved will be positively and significantly impacted by the "relationship eagle" style while technical aspects of performance (i .e . information systems performance) will not be so impacted . Competitive dimensions of performance (which are impacted by both relationship and technical competence) should be moderately and positively impacted by adoption of a "relationship eagle" strategy .

NOTES 1 . The following descriptions of the four strategies draw upon the writings of Blair and Whitehead (1988), Blair and Fottler (1990), and Savage, Nix . Whitehead, and Blair (1991) : Stakeholder management strategy 1 : Collaborate with the mixed-blessing stakeholder . The mixed blessing stakeholder, high on the dimensions of potential threat and potential cooperation should be best managed through collaboration . If executives seek to maximize their potential for cooperation, these potentially threatening stakeholders will find their supportive endeavors make it more difficult for them to oppose the organization . However, executives need to always be careful to focus on reducing threat as much as possible while they are working to enhance cooperation . Collaboration involves much give-and-take on the parts of the organization and the stakeholder . Collaboration may require the organization to give up or expend certain key resources or change important policies to gain stakeholder support by either lowering threat and/or increasing cooperation . Stakeholder management strategy 2 : Involve the supportive stakeholder . By involving supportive stakeholders in relevant issues, healthcare executives can maximally capitalize on these stakeholders' cooperative potential . Because these stakeholders pose a low threat potential, they are likely to be ignored as stakeholders to be managed, and their cooperative potential may therefore be ignored as well . Involvement differs from collaboration in that involvement further activates or enhances the supportive capability of an already supportive stakeholder. The emphasis here is not on reducing threat, since its potential is low . Instead, the strategy attempts to capitalize on the already existing potential for cooperation by converting even more of the potential into actuality . Stakeholder management strategy 3 : Defend against the nonsupportive stakeholder . Stakeholders who pose high threat but whose potential for cooperation is low are best managed using a defensive strategy . In terms of external dependence, the defense strategy tries to reduce the dependence that forms the basis for the stakeholder's interest in the organization . A defensive strategy involves preventing the stakeholder from imposing

344


costs - or other disincentives - on the organization . However, healthcare executives should not attempt to totally eliminate their dependence on nonsupportive stakeholders . Such efforts either are doomed to failure or may result in a negative image for the organization . Defensive strategies may be (and probably should be) proactive in order to anticipate nonsupportive stakeholders . This generic strategy can also take the form of either driving out or reducing competition, since most competitors are nonsupportive stakeholders most of the time . Stakeholder management strategy 4 : Monitor the marginal stakeholder. Monitoring helps manage those marginal stakeholders whose potential for both threat and cooperation is low . The underlying philosophy for managing these marginal stakeholders is proactively maintaining the status quo, but with finances and management time kept to a minimum . Executives address issues on an ad hoc basis . The general thrust of this approach is to "let the sleeping dogs lie ." Keeping them asleep, however, may require an organization to engage in an on-going public-relations activities and to be sensitive to issues that could activate these groups to become an actual threat . Marginal stakeholders should - in general - be minimally satisfied . What it takes to keep a particular marginal stakeholder minimally satisfied may increase over time, thus necessitating greater involvement of managerial time and other organizational resources . Managers must monitor such expenditures of inducements or disinducements to determine whether they have become excessive or are perhaps inadequate before the marginal stakeholder has become a key stakeholder, either in general or on a particular issue that impacts the stake held by that individual, group or organization . 2 . The Facing the Uncertain Future study was conducted jointly by the research unit of the Medical Group Management Association (MGMA) and the former Institute for Management and Leadership Research (now the Center for Healthcare Leadership and Strategy) in the Rawls College of Business at Texas Tech University and funded by Abbott Laboratories . Collaborators included the American College of Medical Practice Executives (ACMPE) and faculty from Texas Tech University and from the University of Alabama at Birmingham . 3 . These multiple indicators were measured in the Facing the Uncertain Future (FUF) study (Blair et al ., 1995 ; also see Blair & Fottler, 1998) . An overview of the research design of the FUF study is found in Blair et al . (1995) . Detailed accounts of the measurement techniques used in this paper are available from the authors at <j blair@ba .ttu .ed u> in the form of a methods appendix .

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