Advances in Health Care Management, Volume 2 (Advances in Health Care Management, 2) (Advances in Health Care Management, 2)

LIST OF CONTRIBUTORS Jeffery A. Alexander Department of Health Management and Policy University of Michigan James W. ...

Author: G. Savage

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LIST OF CONTRIBUTORS Jeffery A. Alexander

Department of Health Management and Policy University of Michigan

James W. Begun

Department of Healthcare Management University of Minnesota

Diane Brannon

Department of Health Policy and Adminstration Pennsylvania State University

Norman B. Bryan

Department of Management Georgia State University

Juliet A . Davis

Management and Marketing Department University of Alabama

Dean J. Driebe

Department of Physics The University of Texas at Austin

Myron D. Fottler

Department of Health Professions University of Central Florida

John E. Gamble

Department of Management University of South Alabama

Martha Gerrity

Department of Medicine Oregon Health Sciences University

Charmine E. J. Hdrtel

Graduate School of Management The University of Queensland

Marjorie L. Icenogle

Department of Management University of South Alabama ix

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Thomas R. Konrad

Cecil G. Sheps Center for Health Services Research University of North Carolina

Christy Harris Lemak

Department of Health Services Administration University of Florida

Mark Linzer

Department of Internal Medicine University of Wisconsin

David Lorber

PCS Health Systems, Inc .

Roice D. Luke

Department of Health Administration Virginia Commonwealth University

Reuben R . McDaniel, Jr .

Graduate School of Business Administration The University of Texas at Austin

Bruce Mann

Blue Cross/Blue Shield of New Mexico

Julia E. McMurray

Department of Internal Medicine University of Wisconsin

Kathleen Montgomery

Anderson School of Management University of California

Vincent Mor

Department of Community Health Brown University School of Medicine

Matthew Neale

Human Resources Department Queensland University of Technology

Stephen J . O'Connor

Department of Health Services Administration University of Alabama at Birmingham

Donald E. Pathman

Cecil G . Sheps Centre for Health Services Research and Department of Family Medicine University of North Carolina

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Inger Johanne Pettersen

Bodo Graduate School of Business

Daniel A . Rickert

Marketing Manager Therapy Management Services

Alison M. Roboski

Cap Gemini Ernst & Young U .S . LLC

Grant T. Savage

College of Commerce and Business Administration University of Alabama

Mark Schwartz

Department of Medicine New York University

William E. Scheckler

Department of Family Medicine University of Wisconsin

Richard M. Shewchuk

Department of Health Services Administration University of Alabama at Birmingham

Howard L. Smith

Anderson School of Management University of New Mexico

Liane Soberman Ginsburg

Department of Health Administration University of Toronto

Hanh Q. Trinh

Health Information Administration Department University of Wisconsin-Milwaukee

Eric S. Williams

Department of Management and Marketing University of Alabama

Elisabeth Wilson-Evered

Queensland Health

Steven Yourstone

Anderson School of Management University of New Mexico

Jacqueline Zinn

School of Business and Management Temple University

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 Health Care Management, Carlson School of Management, University of Minnesota, Minneapolis, MN, USA

Thomas D'Aunno

School of Social Service Administration and Department of Health Studies, University of Chicago, Chicago, IL, USA

James Hoffman

Centre for Health Care Strategy, College of Business Administration, Texas Tech University, Lubbock, TX, USA

Arnold Kaluzny

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

Keith Provan

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

Howard Zuckerman

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

REVIEWERS Donde Ashmos

College of Business Administration, University of Texas

Diane Brannon

Deparrtment of Health Policy and Administration Penn State University

Kathryn Dansky

Department of Health Policy and Administration Penn State University

Eric Ford

Health Care Organization and Policy University of Alabama at Birmingham

Eric Kirlby

Department of Management and Marketing Southwest Texas State University

Beaufort Longest

Health Policy Institute University of Pittsburg

Donna Malvey

College of Public Health University of South Florida

Timothy Nix

College of Business Administration Texas Tech University

Neill Piland

Medical Group Management Association

Mary Richardson

School of Public Health and Community Medicine University of Washington

David Robinson

College of Business Administration Texas Tech University xv

xvi

Donna Slovensky

School of Health Related Professions University of Alabama at Birmingham

Jeffrey Thompson

Richard T . Farmer School of Business Administration, Miami University

Eric Williams

Department of Health Care Management University of Alabama at Tuscaloosa

ADVANCES IN HEALTH CARE MANAGEMENT: THIS VOLUME John D . Blair, Myron D . Fottler and Grant T . Savage This is the second volume in our annual research volume titled Advances in Health Care Management. Our initial volume described in detail the types of papers we publish in each volume as well as the processes we use to select the papers we publish (Blair, Fouler & Savage, 2000) . Included in this volume are invited state-of-the-art review papers by distinguished scholars, several open and special topic competitive papers, and several "best-papers" presented at the Academy of Management Health Care Management Division . The result is a mix of theoretical contributions and empirical research . The editorial approach has resulted in a rich, complex set of papers touching on many "cutting-edge" issues in health care management . The papers composing this volume may be categorized loosely into four general thematic sections : (1) (2) (3) (4)

Theoretical Perspectives on the Field of Health Care Management ; The Role and Impact of Managed Care ; Evolution of the Health Professions ; Enhancing Health Care Organizational Performance.

The papers in each of these sections are briefly described and summarized below in terms of their central questions, key contributions, and directions for future research .

Advances in Health Care Management, Volume 2, pages 1-7 . 2001 by Elsevier Science Ltd . ISBN : 0-7623-0802-8

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

THEORETICAL PERSPECTIVES ON THE FIELD OF HEALTH CARE MANAGEMENT The three papers in this first general section deal with a wide range of theoretical issues related to health care management . They range from complexity science to a theoretical comparison of integrated networks vs . systems to how health care management researchers think about the research process . In the first paper, Reuben McDaniel and Dean Driebe describe how complexity science offers new ways of thinking about health care organizations that enable one to derive new insights about their nature and functioning. Complexity science is first defined and discussed in terms of its evolution in the organizational sciences . They make the point that complexity theory is not an extension of the Newtonian model . It is a different way of looking at organizations as not just an extension of, or complement to, other perspectives . Then they discuss the characteristics of complexity science and how these characteristics manifest themselves in health care organizations . These characteristics consist of agents, interconnections, self-organization, emergence and co-evolution . When the principal characteristics of complex adaptive systems are considered (i .e, agents interconnected by self-organizing, emergent and coevolving systems), a major insight is that behaviors in these systems are fundamentally unknowable. No one is smart enough to figure out where this health care system is going at almost any level. In this circumstance, sense-making is more important than decision making and the next most appropriate management strategy is to enhance the sensemaking capabilities of the health care organization . In addition, because the future is uncertain, success comes from a capacity to learn and learning replaces control as a key management function . Finally, managers must learn to deal with surprise through improvisional behavior . The second paper by Grant Savage and Alison Roboski examines the advantages of conjoining integrated delivery systems (IDSs) with integrated delivery networks (IDNs) . The authors note the three external forces that have determined various forms of integrated delivery organizations (IDOs) are managed care penetration, legislative and reform activity and antitrust issues . They apply a strategic stakeholders analysis to both IDS and IDN forms in order to determine which array of stakeholder relationships create a beneficial or hostile environment for the organization . The analysis indicates that networks have more benevolent stakeholder relationships than systems . In order for IDNs to be effective, certain managerial competencies and organizational structures must be in place. These involve standardization, interpenetration, a shared culture, alliance management and disease management .

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In the third paper, Richard Shewchuk, Stephen O'Connor, Myron Fouler and Hanh Trinh present the results of their empirical research concerning how scholars who conduct health care management research view the research process . A nominal group technique method was employed to elicit attributes attendees at the Health Care Management Division of the Academy of Management viewed as personally salient in terms of what research meant to them . Thirty distinct attributes were eventually derived . Later 78 health care management faculty members and doctoral students completed a questionnaire and were also asked to do a card sort of the thirty research attributes to determine possible underlying dimensions and clusters . An analysis of the card-sorted data via multidimensional scaling and hierarchical cluster analysis resulted in a cognitive map of what research means to researchers in health care management . The map arranged the thirty attributes across the two dimensions of research processes/outcomes and intangible/ tangible elements of research as well as seven clusters . These seven clusters were : (1) theory ; (2) analysis ; (3) research; (4) emotional ; (5) extrinsic expectations ; (6) social interaction/self concepts ; and (7) the actualized researcher . This chapter also discusses the implications of the data for academic researchers in health care management in terms of collaboration, career paths and research orientations .

THE ROLE AND IMPACT OF MANAGED CARE The second section of this volume addresses the significant challenges faced by health care managers as they attempt to respond to the increasing impact of managed care . In the first paper, Howard Smith, Steven Yourstone, David Lorber and Bruce Mann explore the challenging issue of how managed care plans are using and could use medical practice guidelines to choose cost-effective high quality patient care . The paper notes that physician compliance with medical practice guidelines has been problematic . Several initiatives for ensuring physician compliance are reviewed including improving access to the guidelines, peer reviews, reminders and feedback, stabilization of guidelines and education of physicians concerning the use of guidelines . The paper then compares staff model vs . network models in terms of their impacts on physician autonomy and various aspects of medical practice guideline implementation . The paper concludes with a set of medical practice guidelines and research issues for the future . The second paper in this section by Christy H . Lemak and Jeffrey Alexander is an application of two organizational theory perspectives to develop a model of how managed care influences the treatment practices of two outpatient drug

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treatment providers . Resource dependence theory suggests that treatment practices will vary as a function of the organization's dependence on managed care and the scope and stringency of oversight mechanisms used by managed care firms. Institutional theory suggests that the expectations of professional staff and sources of legitimacy will also directly influence treatment practices . Research propositions derived from both resource dependence theory and institutional theory are presented . The paper concludes with a discussion of how resource dependence theory and institutional theory converge and might be integrated . Research propositions based on integration of the two theoretical perspectives are presented . The paper concludes that institutional pressures may moderate or limit relationships between managed care and treatment practices through the power of professional treatment staff and sources of organizational legitimacy . The third paper by Marjorie L . Icenogle, John Gamble, Norman Bryan and Daniel Rickert examines the variable "open access to specialists" as a determinant of HMO member satisfaction and intentions to remain enrolled in the HMO plan. This empirical study is the first test of the strategic importance of member autonomy and open access in a managed care environment . The proposed model tests the relative importance of member autonomy, service convenience, satisfaction with value/pricing and convenience of care . Results indicate that all four factors significantly influence satisfaction and that subsequently, satisfaction influences intentions to remain enrolled in the plan. In addition, the importance of autonomy is demonstrated by significant direct and indirect paths to intentions to remain in the plan. The authors conclude that high member retention rates are critical to the long-term success of managed care plans since the costs associated with losing customers and attracting new customers is very high and negatively impact company profit margins .

EVOLUTION OF THE HEALTH PROFESSIONS The third section of this volume looks at the evolving roles of the health professions . The first paper by James Begun and Roice Luke notes that the health professions are loose aggregations of practitioners and professional associations that are involved in dynamic and often conflictual relationships with buyers, regulators, teachers/researchers, substitutes and suppliers . It is through these linkages that the health professions manage their adaptation to environmental change . The authors note that as the health professions have grown in size in recent decades, they have also grown in vertical differentiation by educational level, in horizontal level by setting and by specialty . In smaller and newer health professions, internal differentiation has been less pervasive and more manage-

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able and internal cohesion has been easier to maintain . Moreover, the health profession associations have largely reacted sluggishly and defensively to the changing demands of buyers, regulatory bodies and substitutes . However, these associations have had an enormous impact on public policy formation at the state and federal levels . Since health care organizations and professions are coevolving, the authors conclude with a recommendation that researchers study the interplay between the two. The second paper by Kathleen Montgomery is a review of the literature on the role and impact of physician executives during the recent era of managed care . The conceptual framework is that of Eliot Friedson which posits that physician executives represent that segment of the profession whose role is to balance the needs of the organization with the desires of the medical profession . This paper traces the development of research on physician executives in terms of who they are, why they have chosen their career paths, what they do and how effective they are . Since there is only minimal research addressing the effectiveness of this hybrid profession, the paper focuses on the process of trust building and maintenance . A set of antecedents to trust are described followed by a discussion of the special challenges physician executives face in fostering a perception of trustworthiness among those with whom they interact . The author concludes that it behooves organizations to assure that physician executives are given meaningful responsibilities associated with merging clinical interests with managerial ones ; however, such responsibilities need to be accompanied by sufficient discretion and autonomy to enable physician executives to function as effective representatives and leaders of powerful multiple constituencies . The third paper by Eric Williams and his colleagues is an empirical study of 1735 physicians, which tests a conceptual model of the impact of physician stress on intentions to withdraw from practice . The model posits that stress impacts withdrawal behavior through global job satisfaction, mental health and physical health . Four measures of "intention to withdraw" used in the study were intention to quit, intention to decrease hours, intention to change specialty and intention to leave patient care . Structural equation analysis with latent variables was used to test the model . Results indicate that the overall fit of the model was good . Perceived stress was significant and negatively associated with job satisfaction, mental health and physical health . Job satisfaction was significantly and negatively associated with intention to leave, intention to reduce working hours, intention to change specialty and intention to leave direct patient care . Strategies for managing stress include increased physician control, more "buffering" of physicians and reduced time pressure on physicians .

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ENHANCING HEALTH CARE ORGANIZATIONAL PERFORMANCE The final section of this research volume focuses on various approaches to enhancing health care organizational performance . The first paper by Liane Soberman Ginzburg examines how implementation of total quality management (TQM) can be enhanced through a goal-setting approach . The author argues that two of the four assumptions about TQM (about people and the top-down nature of TQM) pose serious challenges to the practical implementation of TQM . Consequently, there are significant obstacles in the implementation of TQM . The author proposes a detailed process for integrating goal setting and TQM in healthcare organizations using planning goals, learning goals and doing goals . This approach should also enhance our ability to measure the effects of TQM . The second paper by Juliet A . Davis, Diane Brannon, Jacqueline Zinn and Vincent Mor examines the relationship between strategy, structure and performance in nursing facilities . The sample consisted of 308 facilities in eight states . The study tests the contingency theory proposition that a nursing facility's strategy moderated by its management structure impact performance . Strategy is defined as degree of innovation . Structure is defined as degree of organic vs . mechanistic relationships . Financial performance is defined as the payor mix, measured by the proportion of Medicaid residents . Results indicate that facilities that are both innovative and have an organic structure are more likely to have a lower proportion of Medicaid patients (i .e. stronger financial performance) . Moreover, the interaction of strategy and structure provided an overall stronger model than either alone . Implications for future research and practice are also discussed. The third paper by Elisabeth Wilson-Evered, Charmine Hartel and Matthew Neale argues for the integration of two possible improvement strategies : the use of work groups to generate and implement new ideas and the development of leadership capacity to promote innovativeness in others . The paper presents the results of a longitudinal study of 45 groups of employees at a 200-bed specialist teaching hospital in Australia . Simple regression was used to examine the effects of transformation leadership on morale . Following this analysis, hierarchical multiple regression was used to examine the effect of morale on three innovation variables : benefit to patients, benefit to staff and benefit to administration . Results showed that transformational leadership was associated with high morale . High morale, in turn, results in work group interventions having measurable benefit to patients . These

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results suggest that a leader must concentrate on developing skills to inspire, motivate, stimulate, consider and influence others . This results in enthusiasm and high morale in the workplace . Morale seems to be the key to producing an environment in which employees perceive that their ideas are supported and subsequently introduced, implemented and tested . The fourth paper by Inger Pettersen studies a national sample of 48 intensive care units (ICU's) in Norwegian hospitals in order to determine the relations between abstract and concrete measurements of unit performance . Results indicate there are no necessary conflicts between abstract perceptual measures and more concrete efficiency measures in high-reliability organizations like ICUs. Making sense of the patterns of empirically developed correlations and the patterns of overlapping elements may assist us in the effort to improve the quality of patient care .

COMPLEXITY SCIENCE AND HEALTH CARE MANAGEMENT Reuben R . McDaniel, Jr. and Dean J . Driebe

INTRODUCTION Complexity science offers new ways to think about health care organizations that enable one to have new insights about their nature and about their functioning (Begun, 1985 ; Beinhocker, 1997 ; Anderson & McDaniel, 2000 ; Arndt & Bigelow, 2000 ; Kiel, 1994 ; Lewin & Regine, 2000 ; Miller, Crabtree, McDaniel & Strange, 1998 ; Zimmerman, et al., 1998) . These new insights lead to a rethinking of managerial strategies . The purpose of this paper is to identify some of the most critical insights from complexity science that affect how we view health care organizations . Based on these insights, the paper will identify some managerial changes that are indicated and some new areas for research in health care management that are indicated . Health care organizations are, of course, members of the set of all organizations and as such share some characteristics with all organizations . However, there are some particular characteristics of health care organizations that make complexity science a particularly useful tool for studying them . For example, there is significant information asymmetry in health care organizations, particularly between professional clinician providers of services and

Advances in Health Care Management, Volume 2, pages 11-36 . Copyright 2001 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN : 0-7623-0802-8

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REUBEN R . McDANIEL, JR . AND DEAN J . DRIEBE

typical patients receiving these services and these asymmetries create unusual interdependencies . There is also a weak link between service recipients and payers for services received and the weakness of this link leads to potential distortions of system's characteristics. There is, typically, considerable technological and professional heterogeneity within any health care organization and this increases the difficulty of understanding the organization as a whole . The "mystical" nature of much of health care delivery adds another level of difficulty in understanding their management . These factors, and others like them, have made it hard to simply fit health care organizations into our general understandings of more typical organizational forms . However, complexity science offers insights that enable innovative approaches to health care management practice and research . Complexity science is the study of systems that are characterized by nonlinear dynamics and emergent properties and it is certainly true that health care organizations are such systems . One of the types of systems often studied in complexity science is Complex Adaptive Systems (CAS) . CAS are characterized by diverse agents interacting with each other and capable of undergoing spontaneous self-organization (Cilliers, 1998) . For example, the multiple professionals often required to accomplish the goals of health care organizations comprise such a system . CAS are qualitatively different from linear systems so often studied in more traditional sciences . The dynamic of CAS is nonlinear, with the state of the system at a given time being a nonlinear function of the state of the system at some previous time . The history of the system matters in a fundamental way . Existing managerial and policy issues in health care are the result of, among other things, the history of health care within the cultural milieu and this contributes to the usefulness of a complexity perspective in studying health care organizations . The state of a complex adaptive system as a whole is irreducible to a linear superposition of the states of its constituent elements . The essence of complexity science is in the study of patterns and relationships, rather than objects and substance, and in the search for characteristics of systems far from equilibrium rather than at the point of balanced stability (Capra, 1996) . Complexity science looks not at the parts, but at the wholes in an effort to gain a deeper, qualitatively different understanding of phenomenon . Complexity results from the interactions between the components of a system (Cilliers, 1998) and it is manifest at a level that transcends the local dynamics among each constituent element. Its characteristics at one level cannot be understood from knowledge of its characteristics at other levels (Holland, 1998 ; Newman, 1996). When considering issues such as the medical error rate in hospitals, it is necessary to consider these issues at the systems level rather than simply as the failure of some

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individual worker to "do his/her job" (Edmondson, 1996) . Complexity science helps in developing this perspective . Complexity science transcends traditional disciplines and has been a source of new insights in physics, biology, geology, cosmology as well as the social sciences (Fontana & Ballati, 1999) . As noted by Mainzer (1996, 272), "The crucial point of the complex systems approach is that from a macroscopic point of view the development of political, social or cultural order is not only the sum of single intentions, but the collective result of nonlinear interactions". When we look at the world through the lens of more conventional science it may seem as though order is unnatural because the orderly arrangements of elements seems so unlikely . Complexity science attempts to explain why there is, in fact, order in the universe (Johnson, 1995 ; Kauffman, 1992) . While there is certainly a relationship between complexity science and chaos theory, they should not be mistaken for each other (Morel & Rananujam, 1999, Cilliers, 1998) . James Gleick (1987), in his enormously popular book, Chaos, has contributed to a broad familiarity with many of the ideas of chaos theory and these have often been assumed to be the same as the notions that define complexity science . They are not. Chaotic behavior, in the technical sense of deterministic chaos, results from the nonlinear development of a relatively small number (as few as one) of variables and the study of chaos focuses on how complexity can arise from simplicity (Lewin, 1992; Cilliers, 1998) . Complexity science, on the other hand, focuses on how order can emerge from a complex dynamical system (Nicolis & Prigogine, 1989) . "Complexity means we have structure with variations" (Goldenfeld & Kandanoff, 1999, 87). It is probably most appropriate to say that chaos is a subset of complexity . Because we wish to reduce possible confusion, in this analysis we will be centering on complexity rather than chaos and the reader should be aware of this . CAS have been difficult to study in the past because of the mathematics associated with modeling their behavior . However, recent advances in computational power and new computational techniques used in fields such as Cellular Automata and Boolean Networks and theoretical tools such as Fractal Geometry allow complexity scientists to uncover some of the common characteristics of complex systems and to understand the spontaneous self-organizing dynamics of the world (Kaplan & Glass, 1995 ; Capra, 1996 ; Waldrop, 1992 ; Casti, 1997) . Increasingly the science of complexity is being used as a metaphor to examine the science of organizational management (Morgan, 1997) . For decades organizational scientists have labored clumsily with metaphors, myths and misunderstandings about the nature of organizations that did not fit managers' experience of organizations (Wheatley, 1992 ; Stacey, 1992, 1996 ; McDaniel,

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1997) . Rational approaches to understanding organizations have worked poorly ; at least when we think that to be rational is to be Newtonian in one's logic . There are numerous inconsistencies between traditional theoretical descriptions of organizations and what participants in those organizations experience . Evidence of the level of interest by organizational theorists in complexity science is found in the wide range of articles and books that they are writing on the subject. The May-June, 1999 edition of Organization Science dedicated to the Application of Complexity Theory to Organization Science, and the founding in 1999 of the new journal Emergence, A Journal of Complexity Issues in Organizations and Management, are but two examples . It has been difficult for managers and organizational scientists to truly incorporate insights from complexity science into their thinking . People are tempted to adopt the language of complexity science but ignore the logic ; creating a new lexicon for old ideas (Stacey, 2001) . For example, Brown and Eisenhardt (1998), in their book, Competing on the Edge, speak about complexity as associated with speed of change, but complexity science does not speak to the speed of a system's dynamics, but rather to the nonlinearity of its unfolding over time . It is difficult to break old patterns of thinking. We are constantly tempted to try to make new models fit into our old models . But complexity science is not an extension of the Newtonian model or traditional views, nor is it caught up in the notion that health care organizations are "living systems" . Complexity science is a different way of looking at the organizational world, not just an extension of, or complement to, other ways of looking at the organizational world . For managers and researchers in health care to take complexity science seriously means to accept the idea that health care organizations are complex adaptive systems and that they share the deep characteristics (properties) of complex adaptive systems . Applying a complexity framework suggests a different focus of attention for managerial analysis . Thoughtful organizational scientists are asking themselves these kinds of questions : How do we manage organizations in the face of the realization that they are complex adaptive systems? What would I think about health care management if I took complexity science seriously? How can you understand organizations better if you know complexity science? In order to avoid the trap of falling back to old models, we must be sure we thoroughly understand the characteristics of CAS and how those characteristics manifest themselves in health care organizations . The remainder of this paper is organized as follows . The characteristics of CAS are delineated . The way in which these characteristics manifest themselves in health care organizations is identified . Managerial strategies rising from complexity science are identified . Lastly, suggestions for research are given .


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CHARACTERISTICS OF COMPLEX ADAPTIVE SYSTEMS Agents

Complex adaptive systems are made up of a large number of agents that are information processors (Zimmerman, Lindberg & Plsek, 1998 ; Cilliers, 1998 ; Waldrop, 1992; Holland, 1998 ; Casti, 1997) . These agents may be nerve cells, computer programs, individuals, or firms . In a health care system agents might include individual people such as clinicians, patients and administrators . Agents might also include processes such as nursing processes and medical processes, functional units such as nursing, accounting and marketing and entire organizations such as insurance companies and regulatory agencies . The one characteristic that these agents all share is that they can process information and react to changes in that information (Casti, 1997) . Agents have the capacity to exchange information among themselves and with their environment and to adjust their own behavior as a function of information they process . Agents are constantly acting and reacting to what other agents are doing (Holland, 1995) . It is important when thinking about health care organizations not to simply consider them as the people in the organization but to recognize the wide variety of kinds of agents in the system . CAS agents are diverse from each other (Kauffman, 1995 ; Coleman, 1999). This diversity is critical to the ability of the CAS to function because diversity is a source of novelty and adaptability . If all of the agents were the same, and all processed information in the same way, there would be no potential for change and/or growth. Agents have different information about the system and none understand the system in its entirety (Casti, 1997) . As noted by Cilliers, "If each element `knew' what was happening to the system as a whole, all the complexity would have to be present in that element" (Cilliers, 1998, 5, italics in original) . Each individual agent pays attention to its local environment ; it is ignorant of the system as a whole and some central agent with responsibility for overall system behavior does not control it (Casti, 1997) . This very diversity among agents can be a source of significant frustration . The different structure and goals of accounting processes in health care often come into conflict with the structure and goals of healing processes . Yet diversity is also the source of invention and improvisation . Although agents are elements in their own right, and are often CAS themselves, it is also true that agents at any one level in a CAS serve as building blocks for agents at a higher level (Waldrop, 1992) . Different agents take different roles as the dynamic of the system unfolds . "CAS are constantly revising and rearranging their building blocks as they gain

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REUBEN R. McDANIEL, JR. AND DEAN J . DRIEBE

experience" (Waldrop, 1992, 146) . The health care organization as a whole consists of functional units each of which is a CAS . At the same time, each is a building block for a CAS, the health care organization itself. As these building blocks change over time, the whole organization changes . Interconnections

While a diverse set of agents is necessary for a CAS, it is not sufficient . In fact, the essence of a CAS is captured in the relationships among agents, rather than in the agents themselves . Recently, as scientists have begun to approach questions about organizations, they have noted that their questions tend to refer to systems where there are a great many interdependent agents interacting with each other in a great many ways (Waldrop, 1992) . The dynamics of these interactions makes these systems qualitatively different from static systems that may be complicated, but not complex adaptive systems . The environment for agents in a CAS is a function of the interconnections that agent has with other agents in the system and with agents in the system's environment. Therefore, understanding a CAS requires understanding patterns of relationships among agents rather than simply understanding the nature of agents . In family medicine, it has become clear that the management of many illnesses requires attention to the relationship of the patient to others in the family, but health care organizations are ill equipped to treat the family rather than the patient . As we look at the incidence of litigation in health care, we note that the relationship of the patient and the physician may be a significant moderating factor in whether or not the patient sues the health care organization over an alleged error. And clearly, the relationship among the clinical staff of a health care organization is critical to the overall performance of the organization. We speak of well functioning surgical teams and recognize that the relationships among team members is important . Some attempts have been to manage relationship systems in health care through the adoption of increasingly sophisticated information systems . These have not been very successful . For example, computerized patient information systems have not been widely adopted in health care despite over a decade of effort (Dick, Steen & Detmer, 1997) . Telemedicine has been seen as a major potential strategy for increasing the quality and access to health care and to lower costs and yet it has been disappointing in its impact (Office of Technology Assessment, 1995) . In both cases, failure to resolve relationship problems, rather than failure to resolve information technology issues, seems to be the major cause of difficulty (Paul, Pearlson & McDaniel, 1999 ; Seligman, 1999) . When treated from the


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perspective of complexity science these difficulties are easier to understand and alternative approaches to resolving them emerge . The relationships among agents in a CAS are nonlinear in nature . Inputs are not proportional to outputs . Small changes can lead to big effects and big changes can lead to small effects. A general system has both positive and negative feedback loops and the effect of any one agent's activity can feed back on itself as well as influence other agents . In the world of linear equations we thought we knew that systems described by simple equations behaved in simple ways, while those described by complicated equations behaved in complicated ways . In the nonlinear world - which includes most of the real world, as we begin to discover - simple deterministic equations may produce an unsuspected richness and variety of behavior . On the other hand, complex and seemingly chaotic behavior can give rise to ordered structures, to subtle and beautiful patterns . . . Another important property of nonlinear equations that has been disturbing to scientists is that exact prediction is often impossible, even though the equations may be strictly deterministic (Capra, 1996, 123) .

One characteristic of CAS is that each agent is generally connected to local agents, and the nature of these connections among diverse agents can lead to complex behavior . However, it is not simply the number of connections in a CAS that determines its character ; it is also the richness of these connections . Any element in the system influences and is influenced by, quite a few other ones (Cilliers, 1998) . Even though an agent's range of interaction may be short, its range of influence is often wide. Information is carried throughout the system through feedback (Kauffman, 1995 ; Eisenhardt & Brown, 1999), creating patterns of interaction. "Such interactions are typically associated with the presence of feedback mechanisms in the system. These interactions in turn introduce nonlinearities in the dynamics of the system" (Morel & Ramanujam, 1999, 279) . These patterns of interconnections can follow fairly simple rules and complex behavior can emerge from these rules . Order is created through the patterns of interconnections, not complicated controls and rules . A large number of connections between agents is not required, and in fact can lead to random behavior (Kauffman, 1995 ; McKelvey, 1999). In many ways this flies in the face of conventional wisdom that suggests that everyone should participate in all activities . Sometimes, programs such as shared governance programs for nursing fail because of too much connectivity rather than too little . Research on participation in decision making in health care organizations suggests that attention must be paid to patterns of participation, not just amount or frequency of participation (Anderson & McDaniel, 1999 ; Ashmos & McDaniel, 1991) . Adaptability is reflected in the ability of the CAS and its agents to change the rules through their interactions, thus changing the system . Interactions can take many forms . For example, Thompson (1979) describes interactions in terms of

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pooled, sequential, and reciprocal interactions. More recently, Dooley and Van de Ven (1999) have discussed the dynamic interactions among agents in terms of Chaos, Colored Noise, Periodic, and White Noise . Dooley and Van de Ven (1999) have identified appropriate mathematical techniques for distinguishing among these dynamic interactions . They suggest that complexity scientists studying organizations carefully utilize appropriate models when attempting to describe the interconnections among agents in a CAS . Self-Organization "Self-organization is the spontaneous emergence of new structures and new forms of behavior in open systems far from equilibrium, characterized by internal feedback loops and described mathematically by nonlinear equations" (Capra, 1996, 85) . Self-organization arises from the changing patterns of relationships in CAS . When diagnostic related groups became the standard for prospective payment in health care, then health care organizations began to develop entire work units devoted to redefining physician's diagnosis of illnesses in such a way as to maximize payments to the organization. This was not the intent of those who implemented drgs but it was an organizational form that emerged from changing patterns of relationships . The structure and form of CAS is not simply externally imposed from some hierarchical controller . Rather, structure and form are a function of patterns of relationships among agents and interactions of these agents with their environment (Cilliers, 1998 ; Mainzer, 1996) . As noted by Zimmerman, Lindberg and Plsek (1998, 10), "CAS have distributed control rather than centralized control" . Many health care policy makers and managers have learned, to their dismay, that their control over the organizational patterns in health care can be minimal . Two examples that have been often used for illustrating the self-organizing properties of CAS are the flocking of birds and the schooling of fish . In neither case is there some "smart" bird or fish that "gets things organized" (Callen & Shapero, 1974) . Rather the pattern of organization develops from local interactions among agents, apparently following very simple rules . This phenomenon of self-organization has been used to better understand how colonies of ants seek food and organize their living arrangements (Deneubourg, Pasteels & Verhaege, 1983 ; Bossomaier & Green, 1998) . "The crucial point of the complex systems approach is that from a macroscopic point of view the development of political, social, or cultural order is not only the sum of individual intentions, but the collective result of nonlinear interactions" (Mainzer, 1996, 272) . When one observes order in a system, one is tempted to assert that the order must come from some intentionally on the part of some


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external controller . Complexity science teaches us that order in a system may well be a result of the properties of the system itself (Nicolis & Prigogine, 1989 ; Kauffman, 1993) . Order is a result of nonlinear interactions and the capacity for self-organization is a function of (among other things) the number of connections among agents and the intensity of these connections . It is not true that the more connections the better. Too many connections may lead to behavior that never settles into any recognizable pattern of self-organization . On the other hand, too few connections may lead to frozen behavior rather than dynamical self-organization. Kauffman (1995, 84) expresses the importance of this observation as follows, "Our intuitions about the requirements for order have, I contend, been wrong for millennia . We do not need careful construction ; we do not require crafting . We require only that extremely complex webs of interacting elements are sparsely coupled" . CAS consist of agents, interconnected, generating order . Emergence

"Emergence is above all a product of coupled, context-dependent interactions. Technically these interactions and the resulting system are nonlinear: The behavior of the overall system cannot be obtained by summing the behaviors of the constituent parts" (Holland, 1998, 122, italics in original) . Agents interacting in a nonlinear fashion may self organize and cause system properties to emerge . We see units in integrated health care systems developing patterns of behavior that make it difficult, if not impossible, for the integrated system to achieve anticipated synergies . Organizational mergers and the issues,created by these mergers need to be viewed from a complexity science viewpoint in order to detect their emerging properties (Baskin, Goldstein & Lindberg, 2000) Because individual agents are ignorant of the behavior of the whole system of which they are a part, they cannot control emergence of the system . Rather emergence is a result of the pattern of connections among diverse agents . But it is more than connectivity alone that leads to complexity arising from emergence . The nature of the interactions among agents is critical (Casti, 1997) . The global characteristics of the CAS arise from characteristics of agents and their relationships but are not reducible to these characteristics . The properties of the whole are distinctly different from the properties of the parts . The quality of a surgical team arises from the properties of the individual physicians, nurses and surgical technicians but is not reducible to these properties . A medical unit in a hospital is more than the sum of the talents of individual workers but is an emergent property of the whole unit . This means that the managerial task goes beyond getting the best employees but to facilitating the emergence of the

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unit itself. For example one might call into question existing human resource practices in health care that focus on individual workers and suggest more focus is needed on the emergent system of workers . Continuing education programs for clinicians might well concern themselves with the education of emergent systems as well as education of individual members of systems . Emergence is the source of novelty and surprise in CAS (Goldstein, 1999) and the properties of the emergent system cannot be ascertained by observing the properties of lower level agents or subsystems . Complexity science focuses on dynamic states that emerge in far from equilibrium systems (Goldstein, 1999 ; Holland, 1998). Emergence is not a provisional construct that will succumb to more powerful analytical techniques or a better theory . Rather the unpredictability of emergent systems is fundamental . What is the outcome of emergence in CAS? There are emergent structures and organizations but perhaps most importantly, there are new patterns of relationships among agents and these modify the self-organizing characteristics of CAS . These new patterns emerge from the nonlinear relationships among agents and the rules that constrain agents . Emergence is a continuous property of CAS and emergent order is always changing in unpredictable ways . "A small set of well-chosen building blocks, when constrained by simple rules, can generate an unbounded stream of complex patterns . . . The most lucid examples of emergence arise when these persistent patterns obey macrolaws that do not make direct reference to the underlying generators and constraints" (Holland, 1998, 238-239) . Emergence is not the same as serendipitous novelty such as patterns of raindrops on a window pane but is the result of nonlinear dynamics generating new properties at the macro level of analysis (Goldstein, 1999 ; Holland, 1998) Coevolution CAS consist of agents interacting in a nonlinear fashion such that the system self-organizes and emerges in a dynamic fashion . But the CAS does not simply change ; it changes the world around it . There is coevolution of the CAS and its environment such that each fundamentally influences the development of the other (Kauffman, 1993, 1995 ; McKelvey, 1999) . When a major hospital system develops and implements a new pharmaceutical control system, this will change the hospital's relationship with pharmaceutical suppliers including, possibly, changing their source of competitive advantage . Agents do not simply adapt to the environment and each other. They coevolve with each other and with the environment in a constant dance of change . A physician changes her practice pattern and nurses, therapists and clerks are affected . A new process for managing pharmacy supplies is put in place and the relative competitive


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advantage of pharmacy suppliers is changed . The installation of a computer system makes some processes for assuring patient safety obsolete and demands that new, unanticipated ones be put in place. The organization acts and others react, in unexpected and unpredictable ways . Kauffman (1993, 1995) has suggested that CAS exist in "fitness landscapes" and that each seeks a point of maximum fitness with its environment. Managers have often considered the need for their organizations to adapt to the environment but when they consider that every adaptive move creates another move by another organization or set of organizations, they then can see that adaptation is not sufficient . A new hospital computer system creates new tasks for the training department as well as new functions for the purchasing department. Each of these must now rethink how it responds to its environment because the fitness landscape for each has changed . But the hospital itself has changed the environment in which other hospitals operate and they must seek to reestablish their position in the competitive field . Health care systems are constantly attempting to improve their functioning through seeking new peaks of fitness, or new places of competitive advantage on their fitness landscapes. They seek new ways to achieve better results given the circumstances in which they find themselves . But landscapes vary in their ruggedness and, therefore, there are significant differences in the efficiency with which an agent can achieve some point of improved fitness . Some health care systems exist in a milieu where there are few health care options for their clients and others exist in a milieu where there are many such options . No agent has some global view of the world and thereby, the capacity to see the "total picture" (Cilliers, 1998) . Rather each agent acts based on local information, seeking to continuously improve its fit with its environment and, therefore, usually can only achieve some local optimum. In the process of achieving this position, each agent changes the landscape for itself and for all other agents in the system . As explained by Kauffman (1993, 243) "In a coevolutionary system, we need to represent the fact that both the fitness and the fitness landscape of each species are a function of the other species . Thus, in general, it is necessary to couple the rugged fitness landscape for each species, such that an adaptive move by one species projects onto the fitness landscapes of the other species and alters those fitness landscapes more or less profoundly" . For CAS, the property of coevolution signals limits in their developmental processes . Agents posses conflicting constraints within themselves and among neighboring agents and because so many of the constraints are in conflict, compromise and cooperation lead to workable solutions rather than to some grand, superb solution (Kauffman, 1995) . The dynamics of the situation mean that you can't "get it right" in some global sense . Rather, because of the

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REUBEN R . McDANIEL, JR. AND DEAN J . DRIEBE

emerging properties of each agent and of each CAS, the "goodness" of CAS adaptation to its environment is a moving target . An effective and efficient hospitall at one moment may turn into a dinosaur of a hospital in the next moment . "The structure of the system is not the result of an a priori design nor is it determined directly by external conditions . It is the result of interaction between the system and its environment" (Cilliers, 1998, 91, italics in original) . "Real organisms constantly circle and chase each other in an infinitely complex dance of coevolution" (Waldrop, 1992, 259). Summary of CAS Characteristics When the principal characteristics of complex adaptive systems - agents interconnected in self-organizing, emergent, and coevolving systems - are considered, a major insight is that the behaviors of these systems are fundamentally unknowable . No one is smart enough to figure out where the health care system is going at any level . People continue to probe for the "simple" solution but neither investors nor practitioners have been successful in predicting the future of the health care system or even which of the system's components are likely to prosper in the future . Agents processing local information in response to simple rules can generate unpredictable behavior, even if the system is deterministic (Gleick, 1987, Prigogine & Stengers, 1984) . Patterns of interconnections in CAS are nonlinear and dynamic . CAS self-organize independently of any controlling hand, but as a function of non-linear interactions among agents and patterns of self-organizations are unknowable from any analysis of present system states . Yet, the system emerges in complex and unknowable ways as a function of the self-organization that is taking place . Complexity science and the study of CAS leads us to a deeper understanding of that portion of the universe that is not linear and additive . Health care systems are certainly in that class of things . Understanding the characteristics of CAS leads to the understanding that they are unpredictable in their trajectory but can be understood in terms of their patterns of behavior and their probabilistic nature (Waldrop, 1992 ; Prigogine, 1996) . Agents cannot forecast total system response to their actions and, therefore, agents attempt to improve their own payoffs or fitness, not that of the system as a whole (Kauffman, 1995) . Health Care Organizations as CAS Typically, when we have thought of health care organizations we have thought of them as machines that should be well run (Harris, 1997 ; Blair & Fottler, 1990) . We have relied on Newtonian perspectives of organizations to guide our


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thinking (Zimmerman et al ., 1998 ; McDaniel, 1998 ; Wheatley, 1992) . These perspectives have led to a focus on getting pieces to fit together, on predicting future outcomes of managerial behavior and on controlling behavior of workers to get them to do what we want them to do . The Newtonian perspective is a reductionist perspective where understanding the whole of a system is dependent on understanding its parts . Things must be broken down into their constituent elements in order to understand them . Clockwork is the dominant metaphor and an organization that "ran like a clock' is the desired condition . The more we explored the mechanistic view of health care organizations the more we came to realize that our experiences of health care organizations did not meet our expectations of the machine-like systems we had come to define as the well run organization (Zimmerman et al., 1998 ; McDaniel, 1997 ; Stacey, 1992 ; Anderson & McDaniel, 2000 ; Chirikos, 1998) . One example of attempts to apply reductionist, Newtonian thinking to health care has been in widespread efforts to apply total quality management or continuous quality improvement to improve clinical practice . In particular, it has been used to attempt to improve the delivery of preventive services . This seems like a very straightforward objective but success has not been achieved (Solberg et al., 2000) . In fact a review of efforts to apply continuous quality improvements to clinical practice has generally been unsuccessful (Shortell, Bennett & Byck, 1998) . These efforts all have assumed a machine-like health care system with the key issue in the failures being an inability to move the right levers to effect change. However, this may not be the real issue. The real issue may be a mis-specification of the nature of the system . A review of the characteristics of complex adaptive systems as outlined above, suggests that health care organizations are, in fact, complex adaptive systems rather than machine bureaucracies . There are many, diverse agents (Blair & Fouler, 1990) and the ability to manage these systems of agents creates major concerns (Alexander & Morrisey, 1988 ; Alexander, Fennell & Halpren, 1993 ; Begun, 1985 ; Bloche, 1999) . Relationships and interconnections are critically important (Alexander & Morrisey, 1988 ; Ashmos & McDaniel, 1991 ; Ashmos, Huonker & McDaniel, 1998 ; Thomas & McDaniel, 1990) . Health care organizations have the capacity for self-organization and emergence and they are coevolving (Zimmerman, Lindberg & Plsek, 1998 ; Lewin & Regine, 2000; Anderson & McDaniel, 2000; Kiel, 1994) . As executives seek new insights for managing health care organizations in these troubled times, complexity science offers a way to re-focus attention from creating a better run organization to maximizing the potential for the organization to co-evolve in ways that increase organizational fitness . As managers take complexity science seriously, they discover new strategies for action .

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The health care manager is an agent in the health care organization and not an observer (Stacey, Griffin & Shaw, 2000) . Traditional views of health care administration see the manager as an external controller who manipulates the system in accordance with some well thought out logic . Complexity science teaches us that the manager must first and foremost recognize him/herself as an agent of the system whose patterns of interaction with other agents is part of the overall set of factors that is leading to the dynamic behavior of the system. The manager is within the system and his/her behavior is one of the factors leading to systems behavior but it is only one of the factors . There is nothing the manager can do to manipulate the system in a certain, explainable, predictable way . The manager can act, and his/her actions will affect the organization, but there is no guarantee of what that effect will be . Once begun, the action will be carried through the organization in a way that has no predictable outcome . After all is said and done, the art and science of traditional health care administration has been about control . Improvement efforts in health care management have been focused on better regulation, financial restrictions and punishment of offenders . Traditional views of health care managerial theory have been focused on organizational control and the goal of the management system was to ensure that the organization and its workers did what they were supposed to do. What they were supposed to do was determined by the manager. Complexity science suggests that it is impossible to control, in the traditional sense, health care organizations or the people that work in them because of the self-organizing and emergent properties of CAS and the unknowability resulting from these properties . You cannot control that which you cannot know and you cannot know the form and direction of a CAS because these are always changing . They exist only in the moment and as potentialities, and the manager does not have control over them . This unknowability is fundamental and is not simply a lack of information . With an understanding of the unknowability of the system, the goal of management is to enable the health care organization to emerge and self-organize . The manager cannot know the entire system because the information in the system is dispersed . The whole cannot be captured in any one agent, not even the top executive, as it is impossible for any one agent to see the entire system . Instead, managers must become adept at encouraging things to happen everywhere in the system and to allow these small, local happenings to be dispersed throughout the system . When one understands that health care organizations are complex adaptive systems and that they share the characteristics of these systems then managerial focus shifts . The manager's focus shifts from knowing the world to making sense of the world ; from forecasting the future to preparing the organization to meet an unknowable


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future and from controlling the system to unleashing the system's potential . The next section of this paper details some of the managerial strategies that arise when we take complexity science seriously .

MANAGERIAL STRATEGIES RISING FROM COMPLEXITY SCIENCE Making Sense In complex adaptive systems the problem is not the bounded rationality of decision-makers but the fundamental unknowability of the unfolding dynamic of the system over time. In this circumstance, sensemaking is more important than decision-making and the appropriate managerial strategy is to enhance the sensemaking capabilities of the health care organization (Thomas, Clark & Gioia, 1993) . When faced with nonlinear connections and with emergent properties, people in organizations must develop a collective mind about what the situation is, who we are, why we are here and what is going on around us (Weick, 1995) . Sense making is a social act that requires interaction among agents . But these very interactions create new uncertainties and ambiguities . Sensemaking is enhanced through paying attention and organizational survival is often a struggle for alertness in the face of dynamic co-evolutionary events (Weick & Roberts, 1993) . Because the world is unknowable, meaning comes, not through knowing what is going on but through making sense of what is going on . Agent characteristics of information processing ability, rule following ability and, particularly, ability to connect with other agents, increases organizational capabilities for sensemaking . Managers must create time for agents to pay attention and to interpret the events around them . Managers must also create more different ways of paying attention and interpretation . This means that they must exploit the diversity of agents in the CAS to tease out variety of ways of experiencing and interpreting events (McDaniel & Walls, 1997) . Some ways of thinking about the world see homogeneity as desirable and others see heterogeneity as desirable (Glick, Miller & Huber, 1993) . The characteristics of CAS suggest heterogeneity as the most fruitful managerial strategy for enriching sensemaking in the organization . When homogeneity is the focus then group think and decreased effectiveness result . In an unknowable world, sensemaking is not a matter of doing the best we can because we are limited ; rather it is the best we can do because we are smart. In a world that is constantly emerging, we cannot know the world through planning and predicting ; therefore, the importance of these activities is less than

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we once thought (McDaniel, 1997) . Managers help order emerge in CAS through sensemaking but this order is not a stable equilibrium . Agents continuously create and reenact sense and meaning because the patterns and order in CAS are always changing . Remembering (and Forgetting) History

As health care managers think about the characteristics of CAS they may conclude that the history of the system is unimportant . On the contrary, the arrow of time is a key factor and the nonlinear trajectory of the system is often a function of the time dependent events that occur . Predisposition is a key factor in both enabling and inhibiting health care organizational behavior (Ashmos, Duchon & McDaniel, 1998) . Because the futures of CAS are uncertain (Prigogine, 1997) success comes from capacity to learn and learning replaces control as a key managerial function (Stacey, 1995 ; Senge, 1990) . Critical remembering of history is not in order to know what to do before we take action. Rather we must treat the unfolding of events in real time . As noted by Stacey (1995, 17) "The most important learning we do flows from the trial-and-error action we take in real time and especially from the way we reflect on those actions as we take them" . CAS need to engage in learning processes that enable a pattern of action to emerge as the organization interacts with its environment (Wheatley, 1992 ; Kiel, 1994 ; Bettis & Prahalad, 1995) . Because things in organizations do not recur in repetitive fashion agents must develop skills at learning from samples of one (March, Sproull & Tamuz, 1991) . Included among activities necessary for such careful attention to a history that is unlikely to repeat itself are experiencing events richly and interpreting events broadly . The diversity of agents in the system enhances the system's ability to do these things and organizations need a diverse set of stakeholders to enhance the probability that framebreaking learning will occur (Argyris, 1992) . History is not important because CAS will know what to do next time but so that they will continuously enhance their capabilities to act in the face of an uncertain unfolding of its co-evolutionary space . History informs capabilities . CAS mangers are not expected to know what is going on and then to tell others what to do. Rather the manager develops an environment where people listen to each other and value each other's insights . It is the capacity to learn rather that the capacity to know that enhances CAS functioning (McDaniel, 1997). "Sometimes learning requires courage. It can be difficult for experts, especially, to admit candidly that they could be better at what they do if only they knew more . To become a learner is to become vulnerable . The dilemma is painful" (Berwick, 1991, 841) .


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Thinking about the Future Traditional planning based on feedforward modeling and predictions of future states is not useful in CAS where the dynamic unfolding of the system is uncertain . Because of the emergent nature of CAS, reliance on forecasting and modeling of cause-effect relationships is an inappropriate managerial strategy . This does not mean that managers should not think about the future . But they must think about it in new ways . Scenario planning helps organizations to deal with surprise and it is a technique that has been widely used . The effectiveness of scenario planning in CAS is not a function of how well the manger maps the future or how likely a given scenario is . Rather, the effectiveness of scenario planning is in developing organizational capabilities for dealing with uncertainty . Bricolage, the ability to create what is needed at the moment out of the materials at hand (Weick, 1993), is a valuable way for CAS to think about the future . Traditional managers ask the question, "What do I need to do what I want to do?" while bricoleurs ask the question, "What can I create from what I have?" Bricolage requires knowing existing situations intimately so that new and creative ways to deal with confused and mixed up situations can be invented . In CAS no one knows what is going to happen but some people are better able to create positive outcomes from what emerges . Managers of CAS pay attention to the role of enactment and interpretation in thinking about the future (Thomas & McDaniel, 1990) . CAS are systems of interconnections and they produce or construct through co-evolutionary social processes, a significant part of the environment they face (Weick, 1995) . These choices are often reflected in how agents frame the world as they enact reality through patterns of action (Anderson & McDaniel, 2000) . People call things problems or opportunities, sick people are patients or clients, payers are customers or stakeholders . In each case the CAS maintains capacity to think about the future through framing the future by social interaction . Dealing with Surprise "Uncertainty is an essential ingredient of progress . Surprise drives progress because innovation depends on the sort of knowledge no one can gather in a central place" (Postrel, 2000, 1-3) . The source of surprise in a CAS can be the nonlinear trajectory of the system (Prigogine, 1996), bifurcations, or qualitative changes in behavior resulting from parameter changes (Kaplan & Glass, 1995) or sensitivity to initial conditions (Gleick, 1987) . Mangers of CAS recognize that the self-organization, emergent and coevolutionary properties of CAS ensure that surprise will be a constant companion and the ability to deal with surprise will

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be a key source of competitive advantage . Dealing with surprise requires improvisational behavior. Crossan and Sorrenti (1997, 156) define improvisation as "intuition guiding action in a spontaneous way" . Action is in the moment rather than the future and there is a high use of intuition rather than reliance on detailed analysis or routine habit . As surprise emerges in a CAS managers must encourage agents to respond to unanticipated circumstances through a balance of structure with flexibility (Brown & Eisenhardt, 1998) . Loose-tight coupling and order-chaos-order enable the achievement of temporary advantage in a world characterized by surprise . Dealing with surprise requires innovation and creativity at all levels and in all segments of the organization . Because we cannot always know what resources we have to work with, or what resources we will have to work with tomorrow, we must become good improvisers . There are some trades, jobs, professions, and tasks whose workers come to be good at working with ambiguity . Good scientists are always working just beyond the edge of what they know. They feel their way, trust their instincts, and make frequent leaps of faith . Instead of assuring the workers that the ambiguity and uncertainty will go away once we "get things under control", managers in CAS must teach them to live with ambiguity and embrace surprise. Jazz players are another example of people who are used to living with surprise and they are often seen as role models of improvisational behavior. They know a general musical form or structure and within that they create constant surprise and very complex stuff comes out of a very simple standard form . Bad jazz occurs because one person played something that the others couldn't build on . Note that both the player and the builder have responsibility to create good jazz . It is the responsibility of the whole system not the individual agent - it's about the connections that lead to self-organization . Good jazz players, when they hear a surprise, don't ask, what did you intend to do? They act on what they heard and they create . The surprising note (or phrase or passage) wasn't the right note or the wrong one . It is right if we can use it and the central question is what can I do with what happened? Dealing with surprise involves thinking in terms of how to use whatever happens to further the development of the system . It involves building on emergent characteristics of the CAS to develop patterns of social interaction among agents that gives them confidence in each other, that leads to small wins and that enhance the capacity to learn from surprising events (McDaniel, 1997) . Taking Action When health care managers have traditional beliefs about their systems they are likely to focus on "getting ready to do it right" . However, if they recognize


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the dynamic, nonlinear nature of organizational evolution, they will understand that they need to focus on "taking action as circumstances unfold" (Eisenhardt, 1989 ; Brown & Eisenhardt, 1998) . Action leads to learning and learning leads to the ability to cope with the unpredictable nature of CAS . Action should be focused on small changes that can provide positive feedback to the system . The effects of both small and large inputs can be unpredictable but small inputs provide more room for learning and organizational development (McDaniel & Walls, 1998) . A major component of action in CAS is the creation of connections and relationships (Casti, 1997) . A lot of traditional managerial behaviors have been about reducing connections . Getting everyone in their place, doing their own thing, staying on task . Even typical organizational charts tend to fragment organizations rather than focus on the interdependencies . Managerial practices that isolate workers from each other and attempt to constrain behavior and events through rules and policies will not encourage the self-organization needed to create order. In CAS, the essence of the system is in relationships, not pieces and, therefore, the quality of connections in a CAS is more important than the quality of any one agent. Dialog, then, becomes a major mechanism for collective thinking and organizational learning (Isaacs, 1993) . "Dialog can be initially defined as a sustained collective inquiry into the processes, assumptions and certainties that compose everyday experience" (Isaacs, 1993, 25) . It is not simply a matter of more connections . Increases in complexity are the result of increases in interdependencies rather than increases in number and differentiation . The kinds of relationships that develop are important . Managers of CAS must be careful not to simply focus on tight connections or ties, as these may often be the source of failure (Weick, Sutcliffe & Obstfeld, 1999, 87) . There is, in fact, often strength in weak ties (Granvovetter, 1973) particularly when operating in an environment of uncertainty and surprise . In general, in CAS, agents are guided by information flows in local connections and managers must act to enhance local connections as well as some highly centralized, systems-wide set of connections . Mangers need to develop an understanding that a person's range of influence is very wide even though their range of interactions is small and this influence occurs through overlaps in information domains (Kauffman, 1995) . Structure and form are a function of the patterns of relationships among agents in CAS and interactions of agents with their environment . This suggests that health care managers must pay attention to processes in CASs . When we focus on process rather than simply on form and structure, we reorient the level of analysis for action and there is nothing sacred about the organizational level of analysis (Weick, Sutcliffe & Obstfeld, 1999) . Managers must help agents

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develop skills at paying attention to actions in their local environment. They can not simply look at the environment to see how they should adapt to it, because CAS co-evolve with their environments and the environment will change as a result of actions taken by agents in CAS and vice versa . Participation in decision making is an action tactic that can be effectively used by managers to enhance system functioning in health care organizations (Ashmos, Duchon & McDaniel, 2000 ; Anderson & McDaniel, 1999 ; Ashmos, Huonker & McDaniel, 1998) . When participation is used as a complicating mechanism in CAS, the amount on information brought to the decision table is increased and the sensemaking capacity of the system is increased . Therefore, managers in CAS should be seeking ways to involve a broad range of organizational actors in many kinds of situations . But much of the traditional management analysis has too narrow a view of who should be involved in what activities (Harris, 1997) . CAS can be moved from state to state by the manipulation of control parameters (Mainzer, 1996) and velocity of information flow, connectivity of agents and diversity of information models are three key parameters (Stacey, 1996) . Participation in decision-making is a strategy for managing the control parameters of an organization and, thereby, moving the organization to new states (Anderson & McDaniel, 1999) . Note that imposed teams as a strategy for participation are not the same as emergent networks (Goldstein, 1999) and it is the latter which are most likely to lead to organizational creativity and imaginative problem solving . Developing Mindfulness

Traditional organizational analysis focuses on routines and embedded processes . The belief is that if health care managers can "get it right", develop information systems that reveal the future state of critical variables, and understand critical cause-effect relationships then organizations will function in an efficient and effective manner (Griffith, 1994) . Our understanding of health care organizations as complex adaptive systems suggests that such an outcome is hardly to be expected (Stacey, 1992 ; Wheatley, 1992 ; McDaniel, 1997 ; Miller, Crabtree, McDaniel & Strange, 1998) . Rather the system should be understood in terms of nonlinear dynamics, self-organization, emergence and coevolution . Under these conditions, one can't know what to do, regardless of the amount of previous understandings one has . Organizations must handle unforeseen situations in ways that work. We want them to be reliable and "reliable outcomes now become the result of stable processes of cognition directed at varying processes of production that uncover and correct unintended consequences" (Weick, Sutcliffe & Obstfeld, 1999, 87) .


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The achievement of a stable cognitive process that can enable CAS to operate in a reliable manner and achieve high quality performance requires mindfulness . Mindfulness is the "capability to induce a rich awareness of discriminatory detail and a capacity for action" (Weick, Sutcliffe & Obstfeld, 1999, 88) . Processes that lead to mindfulness include a preoccupation with failure, reluctance to simplify interpretations, sensitivity to operations, commitment to resilience and underspecification of structures (Weick, Sutcliffe & Obstfeld, 1999, 89) . Health care organizations that develop these processes are more likely to be able to deal with the uncertainty inherent in complex adaptive systems . A mindful organization is one that pays attention and managers in CAS must be careful observers of the world as it unfolds (McDaniel, 1997) . Organizational survival is often a struggle for alertness (Weick& Roberts, 1993) . What is needed is, often, not information but attention (Simon, 1994) . Managers often feel that they do not have time to pay close attention to the world around them so they can notice, in a mindful way, important changes that are occurring in their worlds (Senge, 1990 ; Argyris, 1992) . CAS also need more diversity in the way they see and interpret the world (McDaniel & Walls, 1997) . They also need the ability to sense danger at local levels while maintaining the ability to coordinate action (Weick, Sutcliffe & Obstfeld, 1999) . Thus CAS managers must be mindful, and pay attention in real time to the unfolding and coevolving worlds in which they must function . They must do this while keeping in the front of their consciousness the understanding that they are not external observers of the system but are, themselves, agents in the system whose behavior is a fundamental part of the pattern of nonlinear interactions that is causing emergent behavior (Stacey, Griffin & Shaw, 2000) .

RESEARCH QUESTIONS SUGGESTED BY COMPLEXITY SCIENCE Complexity science is offering a host of new ideas for research in organizational science (Anderson, 1999) . Likewise, new research questions arise that are likely to be of particular interest to students of health care administration . Listed below are a few of these. In no way is this list intended to be exhaustive but simply to suggest the range of research questions that emerge when one takes complexity science seriously . (1) How can we maintain trust in health care organizations when the fundamental behaviors of the organization itself are unpredictable? (2) What patterns of interactions among health care professionals is most likely to result in positive self-organization?

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(3) How can health care managers make sense of the constant change implied by complexity science? (4) What are the barriers to rich connections among agents in health care organizations and how can these barriers be reduced? (5) How can health care organizations, which by their very nature want to be high reliability organizations, manage highly uncertain emergent properties in highly reliable ways? (6) What is the appropriate level of interconnections for a well-functioning health care organization? (7) Can stakeholder analysis be used to shed light on the relevant agent population of a health care organization as a CAS? (8) What are the key sources of surprise when one examines health care organizations as CASs?

CONCLUSIONS Issues in the administration of health care are becoming more and more difficult . Traditional views of organizational analysis often seem to have run their course and new ways of thinking about health care systems are constantly being sought. Complexity science is offering new ways of thinking about natural phenomenon as well as artificial systems . Increases in computer power and new computational techniques have opened the door to a richer study of all kinds of systems from genetic to political to economic . These approaches can enrich our understanding of health care organizations as we realize that they are complex adaptive systems and that they share characteristics with other complex adaptive systems . In particular, understanding the agent-based nature of systems, the role of interconnections and the self-organizing, emergent and coevolving dynamics of complex adaptive systems can lead to new insights . We have suggested five specific managerial strategies that seem to rise from complexity science . They are, making sense, remembering (and forgetting) history, thinking about the future, dealing with surprise and taking action . When complexity science is taken seriously, these managerial strategies become the focus of attention . One must offer a word of caution . There is to date no well-developed theory of the complex (Casti, 1997 ; Anderson, 1999 ; Cohen, 1999) . We are just beginning to scratch the surface of the study of complex adaptive systems and research methods are in their infancy . Managerial inferences from current information on general characteristics of complex adaptive systems are coarse at best but they do represent a new point of view that deserves serious attention as we attempt to unravel the nature of health care systems (Begun, 1994) .


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INTEGRATION AS NETWORKS AND SYSTEMS : A STRATEGIC STAKEHOLDER ANALYSIS Grant T. Savage and Alison M . Roboski ABSTRACT Vertical and horizontal integration has transformed the organization and delivery of health services, with hundreds of systems or networks providing a range of services to regional populations by the late 1990s . The advantages and disadvantages of vertical integration are well known in other industries, with most strategists suggesting that it is inherently less competitive than virtual and other arrangements . This paper explores the advantages of conjoining integrated delivery systems (IDSs) with integrated delivery networks (IDNs) . An historical overview of health delivery organization integration illustrates how three external forces - managed care penetration and competitiveness, legislative and reform activity, and anti-trust issues - have determined the various forms of integrated delivery organizations (IDOs) . Empirical research comparing the financial performance of hospitals in system versus network organizations generally favors systems over networks. A strategic stakeholder analysis of both IDN and IDS forms of organizations identifies key stakeholders and their interests ; classifies the relationships of these stakeholders with the IDO ; and assesses the extent to which the array of stakeholder relationships create a benevolent or hostile environment for the IDO . This strategic Advances in Health Care Management, Volume 2, pages 37-62 . Copyright 2001 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN: 0-7623-0802-8

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analysis indicates that networks have more benevolent stakeholder relationships than systems . We discuss the environmental conditions favoring, and the managerial challenges facing, IDOs that embody both systems and networks.

INTRODUCTION An integrated delivery organization (IDO), either in the form of a network or system, may be defined as "an organization that provides or arranges to provide a coordinated continuum of services to a defined population and is willing to be held clinically and fiscally accountable for the outcomes and the health status of the population served" (Shortell, Gillies, Anderson, Erickson & Mitchell, 1996, 7). During the, 1990s, IDOs had remarkable growth . The Managed Care Information Center listed over 850 systems throughout the U .S . in 1999, while the American Hospital Association (AHA) reported in 1999 about 2,238 community hospitals belonged to a health system and 1,310 hospitals belonged to a health network (AHA, 2001) . 1 Policy experts and researchers view IDOs as decreasing health service fragmentation (Ginsburg, 1997 ; Savage et al ., 2000) and better meeting the healthcare needs of targeted populations (Berman, 1999 ; Shortell et al ., 1996 ; Tompkins et al ., 1999) . They also agree that fiscal and clinical accountability is shifting toward healthcare providers (Bazzoli, Chan, Shortell & D'Aunno, 2000a ; Bazzoli, Dynan, Burns & Lindrooth, 2000b ; Bazzoli, Shortell, Dubbs, Chan & Kralovec, 1999b ; Boult & Pacala, 1999 ; Perkins, 1999) . With this shift, IDOs have been urged to focus on the wellness of communities rather than curing individual illnesses (Toomey, 2000 ; Weil, 2000b) . Organizational forms for delivery depend upon the breadth, depth, and alignment of health services (Bazzoli et al ., 1999b), as well as the extent to which IDOs are integrated functionally, clinically, and financially (Shortell et al ., 1996) . On the one hand, recent studies indicate that healthcare providers may be pursuing integration in order to increase their bargaining power with managed care organizations (Bazzoli et al., 2000b ; Bums, Bazzoli, Dynan & Wholey, 2000 ; Kohn, 2000; Okunade & Aronoff, 2000) . On the other hand, they may see integration as a means to add value to patient services (Morrisey, Alexander, Burns & Johnson, 1999 ; Thompson, Sirio & Holt, 2000 ; Weil, 2000a) . Adding value occurs when a fixed quality unit of service is delivered at a lower cost, or when a fixed cost unit of service is delivered with higher quality . Value is a major concern to both internal and external stakeholders of IDOs (Curtright, Stolp-Smith & Edell, 2000) . Both types of stakeholders seek

Integration as Networks and Systems

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advantages from different IDO formations . From an ideal type perspective, IDOs may opt to organize in two different ways : (1) develop a system under unitary ownership, or (2) create a network through strategic alliances with multiple ownership . The Veterans Affairs (VA) Healthcare System exemplifies the strategic alliances inherent in a healthcare network . These alliances allowed better access to scarce resources (Carey, 2000) ; centralized group purchasing power ; provided functional integration in quality management (Kizer, Demakis & Feussner, 2000), information technology (Charles, 2000), and research (Hynes, 2000) ; and reduced service duplication (Biro, 1999 ; Carey, 2000). In addition to these amenities, the 22 VA networks, now referred to as Veterans Integrated Service Networks (VISNs), allow autonomy that strengthens local care delivery . An individual VISN may form stakeholder alliances with non-veteran local stakeholders to improve referral systems, clinical pathways, and outcomes assessment reviews (Halverson, Kaluzny & Young, 1997) . As a result, the VA has been able to rapidly develop its preventive and primary care delivery by forming strategic alliances with other providers (Beason, 2000 ; Robinson, 2000 ; Therien, 2000) . In contrast, Intermountain Health Care is a recognized industry leader in vertically integrating within a multi-hospital system (Bellandi, 2000 ; Lisonbee, 2000) . Like the Veterans Administration, IHC has had a long tradition of non-profit, hospital-based care (Wirthlin, 1990) . This tradition was transformed through strategic visioning and management during the early 1990s (Parker, 1990) . IHC was an early innovator, using smaller hospitals as primary and secondary care centers (Wirthlin, 1990) that feed into tertiary care facilities, providing opportunities for specialized care of pediatric patients (Smith, Price, Stevens, Masters & Young, 1999) . Its centralized operations (Welch, 1999), administration, and information technology infrastructure (Gardner, Pryor & Warner, 1999 ; Peck et al ., 1997) allow IHC to dominate managed care negotiations (1997) . Moreover, IHC has been a leader in viewing both continuous quality improvement (Haug, Farrell, Frear, Blatter & Frederick, 1997 ; Richards, 1994 ; Shaha, 1995 ; Shaha & Bush, 1996) and outcomes-based research (Thompson et al ., 2000) as a strategic investment . These two exemplars combine features of both systems and networks . The VA Health System is the largest system in the U .S . Its movement toward network-based relationships has provided it with a means to address inherent weaknesses while expanding services and improving outcomes (Biro, 1999) . At the same time, IHC coalesced into a system by drawing upon a network of preexisting affiliations (Parker, 1990; Wirthlin, 1990), many of which still remain independent, strategic allies (Lisonbee, 2000) . As these two cases

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illustrate, it may be advantageous for IDOs to merge both system and network forms. Exploring this thesis is the purpose of this paper . The manuscript is divided into three sections . Section 1 provides an historical and evolutionary overview of health delivery organizations integration . It addresses how three external forces - managed care penetration and competitiveness, legislative and reform activity, and anti-trust issues - have determined the organizational forms of IDOs . The section concludes by comparing the financial performance of hospitals in system versus network organizations . Section 2 presents a strategic stakeholder analysis of both IDN and IDS forms of organizations . This analysis identifies key stakeholders and their interests ; classifies the relationships of these stakeholders with the IDO ; and assesses the extent to which the array of stakeholder relationships create a benevolent or hostile environment for the IDO . Section 3 speculates on the trend toward merged forms . We discuss the environmental conditions favoring, and the managerial challenges facing, IDOs that embody both systems and networks, and the implications both for health care executives and policy makers .

AN OVERVIEW OF INTEGRATED DELIVERY ORGANIZATIONS Vertical integration via unitary or multiple ownership may assist health care organizations (HCOs) in achieving major efficiencies . For example, vertical integration may provide a seamless continuum of care, leading to disease management and patient outcome benchmarks that increase the overall wellness of a population (Berman, 1999 ; Boult et al., 1999 ; Lynch, Forman, Graff & Gunby, 2000; Toomey, 2000) and reduce acute care admissions (Baseman & Truxell, 2000) . Via unitary ownership, integrated delivery systems (IDSs) may create economies of scale and scope for applying technologies, deploying human resources, and delivering health services (Ginsburg, 1997 ; Weil, 2000a) . In comparison, integrated delivery networks (IDNs) are IDOs with two or more owners linked through contractual agreements and strategic alliances (Bazzoli et al ., 2000a) . They exhibit fluidity in membership and rapid response to market changes, with key internal stakeholders experiencing high levels of economic mobility and autonomy within the IDNs (Bazzoli et al ., 2000a ; Bazzoli et al ., 1999b ; Bums, 1999) . There is also some evidence to suggest that integrated delivery networks may enhance service provider innovations (Bogue & Hall, 1997a; Bogue, Antia, Harmata & Hall, 1997b) . From an evolutionary perspective, health care organizations may be clustered into four distinct forms or ideal types : cottage, multi-institutional system with


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horizontal integration, multi-institutional system with vertical integration, and community healthcare management system with clinical integration (Charns, 1997) . Additionally, each ideal type may be delineated from the historical perspective of legislative and regulatory changes within the health industry . Although HCOs may be typified by any of the first three types, we focus on multi-institutional systems (or networks) with horizontal and/or vertical integration. Moreover, arguably, the continual evolution of each type seems to have clinical integration as its ultimate goal . Cottage Forms of Organization The cottage type of HCO consists of freestanding hospitals and independent physicians without any formalized lines of group decision-making . In other words, each affiliate manages its own affairs to maximize its own goals (Chams, 1997) . Historically, this type of HCO arose because providers were reimbursed on a cost-plus basis via fee-for-service payments (Robinson, 1999) . The independent hospital is there to serve the needs of the community, and it competes against other hospitals on the basis of reputation and attractiveness to physicians . For this cottage type of HCO, the physicians' role in hospital strategic decision making is not central to its operation nor is the influence of other stakeholders (Chams, 1997 ; Lister, 2000) . Multi-Institutional Organizations with Horizontal Integration Multi-institutional systems made use of horizontal integration techniques in response, first, to the cost containment pressures during the mid-1970s and, second, to the prospective payment system imposed by Medicare in the early 1980s (Robinson, 1999) . Hospitals could no longer prosper with the inefficiencies and duplication of services inherent in their organizations . The multi-institutional system pools interdependence with only minimal functional integration of system-wide rules, procedures, and reporting practices that assist the hospitals' financial standing . Otherwise, the institutions' operation is no different than the cottage type institution . This minimal level of functional integration limits further attempts at clinical integration since financial and clinical issues are separated; moreover, clinical integration is hampered by the lack of a formalized physician organization (Charns, 1997) . However, further clinical integration can be achieved if this horizontal integration assumes a disease rather than institutional focus . One way that has emerged is to create a focused factory (Herzlinger, 1998).

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Focused health care factories exhibit high levels of horizontal integration inherent in multi-institutional systems, but have varied levels of centralization, and low levels of differentiation (Bazzoli et al., 2000a) . This organizational form changes the provider-based structure to a disease-based structure . Supporting this structural change are studies showing that most medical expenditures are spent on a relatively small portion of the population at high risk for chronic diseases and disabilities (Baseman et al ., 2000; Lynch et al ., 2000 ; Tompkins et al., 1999) . The focused factory relies on a multidisciplinary team of healthcare providers who coordinate their services (Herzlinger, 1998) . The multidisciplinary sets of care providers address complex medical problems such as diabetes management . As a team, the care provided is subject to those professionals who focus on this one aspect of the healthcare disease continuum . They become experts in that field, thus encouraging continuous quality improvement of the disease management process (Joshi & Bernard, 1999) . Multi-Institutional Forms with Vertical Integration In response to greater cost control and competitiveness from government programs, i.e. Medicare, and from employers and insurance companies, hospitals began the process of vertical integration because the pooled interdependence of horizontal integration limited cost savings (Nooteboom, 1999a ; Robinson, 1999). This type of integration began to emerge as a trend during the mid-1980s, and it is characterized by greater physician collaboration via medical group practices and through hospital governance structures (Charns, 1997) . Integrated delivery organizations have been and are experimenting with system, network, and hybrid formations in hopes of developing sustainable competitive advantages (Engert & Emery, 1999 ; Etchen & Bouton, 2000 ; Ginsburg, 1997 ; Kohn, 2000 ; Savage et al ., 2000) . Recent studies have found that IDOs show high levels of vertical integration but vary in terms of their centralization and differentiation of hospital services, medical group practices, and insurance products (Bazzoli et al ., 1999b). At the same time, the health care market is providing organizational rewards to those who find cost efficient practice measures, rather than cost inhibitive ones (Robinson, 1999) . External forces shaping IDOs include managed care penetration and competitiveness, legislative and reform activity, and antitrust measures . MCO Penetration and Competitiveness . Recent theorizing (Ginsburg, 1997) and empirical research (Bazzoli et al ., 2000b ; Morrisey et al ., 1999 ; Okunade et al ., 2000) suggests that the market structures for managed care and health care services affect IDO formation.


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Findings from a series of studies by Burns and his colleagues indicate that the intensity of MCO competition has a greater impact on the structure of an IDO than the degree of managed care penetration . Within markets with high degrees of MCO penetration, IDS formation is more likely in highly competitive markets with multiple MCOs than in less competitive markets with a few dominant MCOs (Burns, 1998 ; Bums et al ., 2000) . A straightforward interpretation of these results is that IDS formation serves to increase health care providers' bargaining power when contracting in a markets with multiple MCOs, especially as the MCOs start to consolidate (Burns et al ., 2000) . As a large entity encompassing a continuum from primary through tertiary to post-acute care, an IDS may negotiate greater reimbursement for certain provider services and increase its profitability (Greenberg, 1998) . While IDNs also attempt to negotiate for a wide range of services with MCOs, IDSs have an advantage in the transfer pricing - internal subsidizing - of their bundle of services (Safran et al ., 2000) . For example, IDSs can break even in areas such as primary care, i .e . treat the unit as a loss leader, while seeking profits in higher margin areas such as tertiary care (Christianson, Wellever, Radcliff & Knutson, 2000). The primary care organizations in an IDN, in contrast, cannot remain in business without obtaining a profit . On the one hand, it is difficult for an IDN to compete with an IDS for MCO contracts across a range of health services . In other words, to match the internal subsidizing advantage of the IDS, the IDN's primary care units must be more efficient than the subsidized (loss leader) units within the IDS . On the other hand, there is some evidence that IDSs resist lowering costs enough to thwart competition from highly efficient IDNs (Bazzoli et al ., 2000b), especially if the IDS owns a managed care product or health plan (Bums & Thorpe, 2001 ; Engert et al ., 1999 ; Weil, 2000a) . Legislative and Reform Activity

At the same time, legislative and reform activities are imposing fiscal concerns on all health care providers . The trend towards government imposed cost reductions on health providers is manifested in such legislation as the Health Insurance Portability and Accountability Act (HIPAA) of 1996 and the Balanced Budget Act (BBA) of 1997 . Since the adverse impact of the BBA of 1997 on health providers has been acknowledged and somewhat mitigated by the Balanced Budget Refinement Act of, 1999 and the Benefit Improvement and Protection Act of 2000, we focus on HIPAA . The HIPAA is a wide-ranging piece of legislation that has had a profound impact on fraud and abuse detection and prevention (2000a, b ; Tomes, 1998), electronic communication standards (Anspaugh, 1998), and health information

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security (Hellerstein, 1999). As a result of the HIPAA fraud and abuse regulations, health care providers have had to develop compliance plans for Medicare and Medicaid (Tomes, 1998), imposing new costs on IDOs and their partners (Coles & Babb, 1999 ; Saum & Byassee, 2000) . The administrative simplification portion of the HIPAA, involving electronic communication standards and health information security, also impose substantial costs . On one hand, electronic standards should drastically reduce the cost of paper-driven transactions, improve accuracy, speed the process, and increases the quality of patient services . On the other hand, the initial cost of compliance with these standards will be high for both managed care organizations and health care providers (Moynihan & McLure, 2000 ; Shinkman & Gardner, 2000 ; Tennant, 1999). The Health Care Financing Administration and the Washington, D .C .-based National Committee for Quality Assurance (NCQA) regulate both provider and health plan quality . Their shared goal is to expand care specific data elements of the Health Plan Employer Data and Information Set (HEDIS) . In addition, consortiums of public and private purchasers, for example, the Oregon-based Foundation for Accountability, are joining government actions to release performance measurement sets requiring HCOs to gather and disseminate specific quality-driven data . Moreover, the Institute of Medicine released a report to the nation in December, 1999, claiming that about 100,000 people per year die due to preventable medical errors . These concerns have only increased IDS stakeholders' urgency about health service quality and the accountability of these organizations (Griffith, 2000) . Public disclosure, government reporting, and clinical standardization comes at a cost for both MCOs (Epstein, 1999) and HCOs (Hosler & Nadle, 2000) . In comparison to an IDN, an IDS can obtain economies of scale through administrative centralization and access to capital . Both for physician practices and hospitals, centralization within an IDS decreases the costs associated with governmental legislation, permitting consolidated reporting and standardization (Conrad, Koos, Harney & Haase, 1999), as well as information technology enhancements (Neumann, Blouin & Byrne, 1999) . Antitrust Measures As IDSs integrate in response to regulatory and market pressures, they must carefully navigate the shoals of antitrust stipulations . Vertical integration and provider consolidation is a means of achieving economic efficiencies ; however, the Federal Trade Commission and Department of Justice are more and more likely to view such actions as anti-competitive and monopolistic in nature (Gifford, 1999). Emerging IDSs fit the definition of a monopoly in the following manner : their market share increases, they have superior technology, they have larger size relative to their competitors, they create barriers to entry, their pricing


45

trends change, and they decrease diversity in the marketplace (Heightchew, 1997) . As a monopoly, an IDS would experience fewer constraints from pricing pressures, thus allowing an increase in patient care prices to third party payers (Savage, Taylor, Rotarius & Buesseler, 1997) . In addition, the monopolistic IDS, in contracting or competing with MCOs, may exhibit unfair advantages in negotiations (Greenberg, 1998) .2 Blocking further the growth of some systems and networks are the Stark Laws (I and II) and the Health Care Financing Administration's interpretation of these regulations (Dubow et al ., 1998) . Existing IDSs that have already passed antitrust scrutiny are at an advantage versus IDNs in securing "safe harbor" under both Stark I and II (Johnson, Niederman, Bowman & McCullough, 1998) . Community Healthcare Management Systems The most extensive form of vertical integration is the community healthcare management system that emphasizes clinical integration (Charms, 1997) . Although IDOs may state that they are seeking to achieve this status (Griffith, 2000), few have achieved this level of integration (DeBusk, West, Miller & Taylor, 1999 ; Engert et al ., 1999 ; Weil, 2000a) . This organizational type coordinates the care to any given person over time, and emphasizes the aggregation of this coordinated care to a population (Charms, 1997) . This emphasis is consistent with the trend toward greater accountability of healthcare providers and health plans (Bazzoli et al ., 2000a ; Christianson et al ., 2000; Shortell et al ., 1996) . The key factors that determine the extent of clinical integration include development of physician-system collaboration (Bazzoli et al., 2000b ; Bums et al ., 2000 ; Morrisey et al ., 1999), ambulatory and preventive services paradigm shift (Beason, 2000 ; Berman, 1999 ; Harvey & DePue, 1997b), internal care management strategies (Curtright et al ., 2000 ; DeBusk et al ., 1999 ; Welch, 1999), and a greater integration of financial management and strategic planning (Benoff & Harris, 2000 ; Campobasso, 2000a, b ; Charms, 1997) . Ideally, this organizational form exhibits high levels of integration and differentiation of physician services and insurance products, as well as highly differentiated hospital services, and variable levels of centralization (Bazzoli et al ., 1999b ; Whitelaw & Warden, 1999) . Performance Comparisons among IDS and IDN Forms Bazzoli and her colleagues have developed a taxonomy for IDOs based on the level of their organizational differentiation, centralization, and integration (Bazzoli et al ., 1999b) . IDOs exhibit a range of both contractual (network) and

46


ownership-based (system) integration . For example, IDO-based physicians may achieve economic integration ranging from loosely to tightly coupled (e.g . salary or contractual arrangements) within either , an IDS or an IDN (Bazzoli et al ., 2000a ; Bazzoli et al ., 1999b ; Burns, 1999) . A number of studies indicate that this variation occurs as a response to environmental pressures from managed care organizations, other third-party payers, and competing provider organizations (Bazzoli et al., 2000b ; Burns et al ., 2000 ; Byrne & Ashton, 1999 ; Kohn, 2000 ; Morrisey et al ., 1999 ; Nauenberg, Brewer, Basu, Bliss & Osborne, 1999). Studies by Bazzoli and her colleagues have found that hospitals in IDSs generally have better financial performance than hospitals in IDNs (Bazzoli, Chan & Shortell, 1999a ; Bazzoli et al ., 2000a) . On the one hand, hospitals in highly centralized IDNs had better financial performance than those belonging to more decentralized IDNs . On the other hand, hospitals in moderately centralized IDSs performed better than highly centralized IDSs . Finally, hospitals in IDNs or IDSs with little differentiation or centralization experienced the poorest financial performance (Bazzoli et al ., 2000a) . The lower financial performance of hospitals in highly centralized IDSs may be attributed to reduced market response flexibility, high administrative operating costs, and diminished incentives for key internal stakeholders (Byrne et al ., 1999 ; Weil, 2000a) . Nonetheless, hospitals in IDSs tend to be more leveraged than IDNs, with more current physical plants and infrastructures (Bazzoli et al., 2000a) . To summarize, IDOs have developed in response to market and regulatory pressures from managed care organizations, accrediting bodies, and federal agencies . Both network and system approaches to IDOs are evident, but hospitals in systems with moderate centralization have had the best financial outcomes . Clearly, there are other ways to assess the performance of systems and networks . One fairly comprehensive alternative is to examine the degree of stakeholder support for an organizational form . Stakeholder theory (Freeman, 1984) - or thinking (Nasi, 1995) - focuses on describing and understanding the relationships between business organizations and society (Carroll, 1994) . Stakeholder management attempts to acquire knowledge about stakeholder interests so organizations can anticipate and handle stakeholder actions in a way that satisfies the needs of the organization and the claims of the stakeholders . A primary tenet of stakeholder theory is that an organization cannot continue its existence unless it satisfies the needs of its stakeholders in the long run (Clarkson, 1995 ; Donaldson & Preston, 1995) . This stakeholder approach is explored in the next section .


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A STRATEGIC STAKEHOLDER ANALYSIS Understanding the interests that key stakeholders have in either the system or network form of integration provides yet another lens for discerning their advantages and disadvantages (Fottler, Savage & Blair, 2000) . From a strategic stakeholder management perspective, IDOs should adopt organizational forms that benefit, or do the least harm, to their key stakeholders' interests (Goodpaster, 1991 ; Harrison & Freeman, 1999 ; Savage et al ., 2000 ; Savage et al ., 1997) . In the following discussion, we conduct a strategic stakeholder analysis by : (1) Identifying key stakeholders and their interests (Agle, Mitchell & Sonnenfeld, 1999; Fottler, Blair, Whitehead, Laus & Savage, 1989; Mitchell, Agle & Wood, 1997) ; (2) Classifying the relationships of these stakeholders with the organization (Blair & Fouler, 1990 ; Savage, Nix, Whitehead & Blair, 1991) ; and (3) Assessing the extent to which the array of stakeholder relationships creates a beneficial or hostile environment for the organization (Savage et al ., 2000; Whitehead, Blair, Smith, Nix & Savage, 1989) . Identifying Key Stakeholders and Their Interests

The trend toward integrated delivery organizations affects internal, interface, and external stakeholders (Savage et al ., 1991). Embodying an IDO are its internal and interface stakeholders . For example, internal stakeholders include affiliated hospitals, affiliated medical group practices and physicians, and affiliated health plans (Savage et al ., 1997) . Interface stakeholders, which have stakes in both the IDO and another organization, include physician, nursing and other health service employee unions, as well as governing boards for the IDO (Savage et al ., 1997) . While both internal and interface stakeholders hold a general interest in the profitable operation of the IDO, their major concern will be whether the IDO's strategic outcomes are congruent with the stakeholders' primary and secondary goals . External stakeholders for IDOs include the consumer as advocate, patient, and taxpayer ; employers as third-party payers ; state and federal governments as purchaser, regulator, and legislator ; durable medical equipment, medical supply companies and pharmaceutical companies ; and local communities (Savage et al., 2000; Savage et al., 1997) . Typically, external stakeholders purchasing from IDOs want health care services that are accessible, affordable,

48


and of high quality ; those stakeholders that are regulating IDOs want accountability ; and those stakeholders supplying IDOs want competitive market forces (Griffith, 2000 ; Savage et al., 1997) . Table 1 provides a more detailed breakout of key stakeholders for IDOs, specifying the nature of their relationship, the resources they offer, and their primary and secondary interests . Classifying Stakeholder Relationships In addition to their institutional relationship with the IDO, stakeholders can also be classified according to their potential to cooperate with or threaten an organization . On one hand, the potential to cooperate represents the level of interdependence between the stakeholder and the DO, as well as the stakeholder's capacity to expand this interdependence . On the other hand, the ability to threaten captures the stakeholder's relative power and its relevance to the IDO . For this analysis, we use an established diagnostic typology (Blair et al ., 1990; Savage et al., 1991) and modify it so that it classifies stakeholder relationships into four types based on these two dimensions . 3 Supportive stakeholder relationships are high on potential for cooperation but low on threat . Non-supportive stakeholder relationships have high potential to threaten but low potential for cooperation with the IDO . Marginal stakeholder relationships are neither threatening nor cooperative . The last type of stakeholder relationship, a mixed blessing, is the most challenging for DOs . These stakeholder relationships have high potential for both cooperation and threat . Figure 1 shows key stakeholders' potential to cooperate with or threaten an IDN, while Fig . 2 displays their potential to cooperate with or threaten an IDS . Assessing the Array of Stakeholder Relationships The array of stakeholder relationships faced by integrated networks and systems vary most dramatically along the dimension of potential to cooperate, resulting in IDSs facing more hostile environments than IDNs . The specific configurations of stakeholder relationships for both IDNs and IDSs are discussed below . Key Stakeholder Relationships for an IDN As illustrated in Fig 1, IDNs deal with a fairly benevolent array of stakeholder relationships, with most stakeholders relationships classified as either supportive or mixed blessing. The consumer as patient and taxpayer, consumer advocacy groups, the local community, affiliated medical group practices, aligned hospitals, and employers are all likely to have supportive relationships with an IDN . These stakeholders can also influence the large number of mixed blessing


Table 1 .

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Key Stakeholders for Integrated Delivery Organizations : Relationships, Resources, and Interests .

EXTERNAL STAKEHOLDERS

Nature of Relationship

Resource Offered

Primary Interest

Secondary Interest

Consumer Advocacy Groups

Tax Payers/ Voters

Legitimacy

Cost/ Access

Quality

Consumers

Patients/ Payers

Purchase Compensation

Access Quality

Quality Cost

Durable Medical Equipment & Medical Supply Companies

Suppliers

Equipment Supplies

Profit

Market Share

Employers & Governments

Third Party Payers

Compensation

Cost

Quality

Government : State & Federal

Legislators/ Regulators

Institutional Framework

Access Cost

Quality Quality

Local Communities

Consumers/ Payers

Legitimacy Compensation

Access Cost

Quality Quality

Pharmaceutical Companies

Suppliers

Pharmaceutical Supplies

Profit

Market Share

Unaffiliated Managed Care Organizations

Brokers

Contracted Compensation

Cost

Quality

Unaffiliated Physicians & Medical Group Practices

Competitor/ Contractors

Health Services

Profit

Market Share

Unaligned Hospitals: Acute & Long Term

Competitors/ Contractors

Health Services

Market Share

Profit

INTERFACE STAKEHOLDERS Nursing & Healthcare Professional Unions

Employment Contract

Labor & Knowledge

Salary

Benefits

Physician Unions

Employment Contract

Labor & Knowledge

Salary

Autonomy

INTERNAL STAKEHOLDERS Affiliated Managed Care Organizations

Partner/ Brokers

Payer Contracts

Shared Profit

Sustained Relationship

Affiliated Physicians & Medical Group Practices

Partners

Health Services

Shared Profit


Aligned Hospitals : Acute & Long Term

Partners

Health Services

Shared Profit



50

StakehoMar's Potential to Threaten IDN Hi h Affiliated MCO Government as Legislator/Purchaser/Regulator Nursing &

High

Stakeholder's Potential to

Low Affiliated Physicians &

Medical Group Practices Aligned Hospitals

HC Professional Unions

Consumers

Physician Unions

Consumer Advocacy Groups

Unaffiliated Physicians & Medical Group Practices

Employers

Unaligned Hospitals

Local Community

Mixed Blessing Stakeholds s

Cooperate

Supportive Staksholdsrs

with IDN DME & Other Suppliers

Low

Pharmaceutical Suppliers

Unaffiliated MCOs

Non-supportive Stakeholders

Fig 1 .

Marginal Stakslmidsrs

Stakeholder Potential to Cooperate with or Threaten IDN .

stakeholders with relationships high in potential both to cooperate with and threaten the IDN . For example, supportive stakeholders may lobby and otherwise influence the government as regulator, legislator, and purchaser to cooperate with IDNs. Similarly, while unaligned hospitals and unaffiliated medical group practices may threaten the IDN through direct competition, they also have high potential to cooperate through strategic alliances with the IDN . Stakeholders with non-supportive relationships with the IDN (low potential to cooperate with but high potential to threaten) include unaffiliated MCOs, durable medical equipment and medical suppliers, and pharmaceutical companies . MCOs attempt to dictate reimbursement rates and access to health care providers . The pharmaceutical suppliers, as large consolidated entities, exert their market power as both large suppliers and by convincing consumers to demand their products directly from physicians, thus implementing a "pull strategy ." In addition, IDNs lose economies of scale if they cannot enter into consolidated purchasing agreements, a pitfall of more decentralized


51

Stakeholdees Potential to Threaten IDS High

Affiliated MCO

Low

Consumers Consumer Advocacy Groups Employers

High

Stakeholder's Potential to Cooperate with IDS

Government as Purchaser Local Community Nursing & HC Professional Unions

Affiliated Physicians & Medical Group Practices Aligned Hospitals

Physician Unions

Mixed Blessing Stakeholders Government as Legislator/Regulator

Supportive Stakeholders

DME & Other Suppliers Low

Pharmaceutical Suppliers Unaffiliated MCOs Unaffiliated Physicians & Medical Group Practices Unaligned Hospitals Non-supportive Stakeholders

Fig 2 .

Marginal Stakeholders

Stakeholder Potential to Cooperate with or Threaten IDS .

organizations (Nooteboom, 1999a) . DMEs and pharmaceutical suppliers do not intend to cooperate with IDNs . They are gaining greater market leverage with consolidation, a simple market strategy (Savage et al ., 2000) . Key Stakeholder Relationships for an IDS

Figure 2 shows that an IDS's supportive stakeholder relationships typically are with affiliated physicians and medical group practices and aligned hospitals . Otherwise, IDSs face a fairly hostile environment due to the large number of internal and external stakeholders who have mixed blessing or nonsupportive relationships with the IDS . Stakeholders with mixed blessing relationships include the consumer as patient and taxpayer, consumer advocacy groups, employers, the local community, unaffiliated medical group practices, unaligned hospitals, the government as purchaser, affiliated MCOs, and physician, nursing and other health service employees' unions .

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On one hand, the state and federal government as a purchaser may potentially cooperate due to the efficiencies of centralized access to a small number of large systems. On the other hand, as a purchaser, state and federal governments historically have exerted enormous financial pressures in the form of substandard reimbursements . Individual consumers and consumer advocacy groups are limited as to their degree of access and choice through cooperation with an IDS, and as taxpayers, may not benefit from a franchise tax . These limits increase their potential to threaten the system in order to increase the quality of care, access, and choice provided . Employers may not use the IDS in their employee benefits packages and threaten the IDS by contracting elsewhere . Local communities are subject to the unified thought processes that may occur in an IDS, which slows market responsiveness and change . They can threaten by lobbying for governmental regulation over IDS entities, thus minimizing governmental cooperation as purchaser, legislator, or regulator. Moreover, while affiliated MCOs may cooperate based on their contracts with the IDS ; they can dictate reimbursement rates and access, which threatens the IDS's profitability . Similar to IDNs, unionized physicians, nursing and health service workers have high potential to cooperate with and to threaten IDSs. However, when dealing with highly consolidated systems, such as the IDSs, any union action will have a greater effect than it might on more decentralized networks of providers . As a stakeholder with a non-supportive relationship, the government as regulator has a high potential to pursue antitrust investigations as IDSs increasingly approach the definition of a monopoly (Heightchew, 1997) . Therefore, the state and federal governments have the potential to threaten IDSs based solely on these systems' organizational structure, and a low potential to cooperate with IDSs . Similarly, unaffiliated medical group practices and MCOs and unaligned hospitals compete directly with IDSs, and they have a low potential to cooperate with the IDSs . Their relationships are also non-supportive .

TOWARD MIXED SYSTEM AND NETWORK FORMS The strategic stakeholder analysis highlights the potential difficulties IDSs will face attempting to manage numerous mixed-blessing and nonsupportive stakeholder relationships . Conversely, while IDNs face a more benevolent set of stakeholder relationships, with fewer nonsupportive and more supportive stakeholders, these networks have difficulty developing economies of scale and accessing capital . Clearly, both forms of IDOs need to evaluate their internal strengths and weaknesses, external environment, and mission and goals to determine how, and whether, they can and should combine network and system


53

forms . If the mission and goals include forming an integrated delivery organization that has processes in place to facilitate full clinical integration, a mixed-form organizational design may be desirable. Three caveats follow . First, IDOs pursuing mixed-form integration need to understand the environmental conditions under which these two organizational forms are advantageous . Second, executives must recognize that each form of organization requires certain managerial competencies to be successful . And, third, combining these forms places extraordinary burdens on the top executive team . These points are further articulated by drawing upon relevant economic, organizational, and strategic theories of management . Environmental Conditions and Organizational Forms Two questions drive this discussion : (1) Under what conditions are network forms of integration advantageous?, and (2) Under what conditions are system forms of integration advantageous? There have been many recent discussions of the strategic pros and cons of networks (Ahuja, 2000 ; Anand & Khanna, 2000; Baum, Clabrese & Silverman, 2000 ; Doz, Oik & Ring, 2000; Gulati, Nohria & Zaheer, 2000 ; Inkpen, 2000 ; Kale, Singh & Perlmutter, 2000; Khanna, Gulati & Nohria, 2000) . However, perhaps the most intriguing appraisals given the above questions - focus on how networks enhance organizational learning and encourage innovation (Nooteboom, 1999a, b, 2000) . As argued earlier, IDOs may seek to integrate the delivery and contracting of health services in order to produce efficiencies through economies of scale and scope (Robinson, 1999) . There are difficulties in achieving such efficiencies, however, especially economies of scope when vertically integrating the valuechain across entities with very different core competencies (Nooteboom, 1999a) . Hospital-driven IDOs have had particular difficulty integrating both managed care organizations and medical group practices (Bums et al ., 2001 ; Kohn, 2000; Weil, 2000a) . One line of argument suggests that these difficulties arise from the IDOs' inability to transform tacit knowledge into documented knowledge that can be distributed across different divisions within the system form (Nooteboom, 1999a) . Similarly, given this line of argument, radical innovation occurs when there are novel combinations of tacit knowledge (Nooteboom, 1999a, b) . Such combinations are more likely to occur within loosely coupled networks than tightly coupled systems (Nooteboom, 1999b) . Moreover, transaction costs (Williamson, 1975) will be less when an IDO is involved in a network based on trust among partners . Trust-based network ties promote the exchange of superior information, make opportunism more costly, reduce the need for

54


contracting of goods and services, and create value via improved inter-firm coordination (Gulati et al ., 2000) . However, network forms have problems competing if their innovations can be assimilated by systems that use generic technologies to achieve economies of scale (Nooteboom, 1999a, 2000) . There are at least two ways in which network dynamics can affect the competitive ability of the IDO, including "lock-in and lock-out effects" and "learning races" (Khanna, Gulati & Nohria, 1998) . Lock-in and lock-out effects occur because of specific stakeholder actions that form constraints for other stakeholders within the network . This can take place due to limited resources, alternate expectations, inter-firm loyalties, and firm power. Learning races occur when an IDO realizes that the benefits of information sharing outweigh continuance of the alliance with a key stakeholder . The faster entity then disbands the alliance and uses the information to its advantage at cost to the slower entity . These two factors can influence the degree of economic returns IDOs can exact from the network depending on their level of expertise with an alliance, thus the notion of "alliance capability" (Anand et al ., 2000) . Several propositions can be drawn from these observations . One, networks have the advantage of potentially producing radical innovations for delivering health care services . Two, these network advantages are most pronounced when the environment is dynamic and turbulent . Three, systems have the advantage of achieving economies scale through coordination when knowledge is explicit, i .e . documented . Four, these system advantages are most pronounced when the environment is stable and generic technologies can be applied . Five, given the ongoing turbulence within the health care industry in the U . S . and the need for innovation (Keating, 2000), IDOs that form federated structures (Nooteboom, 1999a) - i .e . mixed forms - may be best able to achieve both innovation and coordination . Managerial Competencies and Organizational Structures Recent research and theorizing suggests that IDSs' performance depends on managing polarities among key internal stakeholders (Bums, 1999 ; Savage et al ., 1997), while IDNs' performance relies on forming and managing strategic alliances (Anand et al ., 2000 ; Bogue et al ., 1997b ; Halverson et al., 1997) . The success of each organizational form also requires the strategic leveraging of local and regional market forces (Nooteboom, 2000 ; Robinson, 1999) . For example, disease management represents an emergent technique for strategically leveraging IDO capabilities . Combining these three sets of managerial competencies is necessary, arguably, for the success of mixed-form IDOs .


55

Polarity Management Three key elements provide the "glue" to manage internal stakeholder polarities within IDOs (Bums, 1999) . These include standardization, interpenetration, and culture . Standardization helps to make the functional relationships among physician practices, hospitals, and other entities within an IDS both predictable and efficient ; as such, it is a necessary precursor to integrating clinical services . Interpenetration is developed through matrix-style interdependence among the leaders and managers of the internal stakeholders comprising an IDS . In addition, a shared culture or strong linkage in terms of beliefs and values among differing cultures within an IDS stabilizes relationships among internal stakeholders and allows it to pursue its mission with fewer conflicts and miscues (Savage et al ., 1997) . Alliance Management For health care executives, there is evidence that creating value through alliance management, i .e. creating production efficiencies and reducing transaction costs, has a significant learning curve associated with it (Kiel, 2000 ; van Raak, Paulus, van Merode & Mur-Veeman, 1999) . Strategy management researchers assert that firms vary in their "alliance capability", i.e. ability to create value through relationships within a network of organizations (Anand et al ., 2000 ; Gulati et al ., 2000) . As organizations gain experience in developing and being successful in joint ventures (as compared to licensing agreements) they accumulate more value within and across the networked organizational entity (Anand et al ., 2000) . For example, gaining and maintaining an `alliance capability' clearly is necessary for developing a community care network (CCN) . A CCN is a community-wide partnership of health and social service providers, educators, government officials, business people, and community members that collaborate to improve the health and well being of a local communities (Bogue et al ., 1997a ; Bogue et al., 1997b) . This local community involvement is a way to influence healthcare delivery and services to better benefit the community itself . It also serves to educate the community in preventive and self-care management, as well as nurture and facilitate supportive stakeholder relationships . Disease Management To leverage market forces while facilitating clinical integration with both internal and external stakeholders, the IDO should develop an extensive disease management approach to care . Disease management can add value to consumers and payers by increasing perceived quality through increased patient satisfaction (Harvey et al ., 1997b), improving clinical quality and health outcomes (Joshi

56


et al., 1999), and decreasing costs (Baseman et al ., 2000) . Its foundation is based on quantitative data useful in developing standards for diverse populations . The four basic elements include disease modeling, patient segmentation and risk assessment, development of clinical protocols, and preventive medicine through wellness and self-care education (Harvey & DePue, 1997a; Harvey et al ., 1997b) . Most models of disease management assume that the DO is a tightly coupled system (Baseman et al ., 2000 ; Gunter, 1999 ; Joshi et al ., 1999) . However, there is growing recognition that coordination among health care providers, third-party payers, and intermediaries is the cornerstone for successful disease management (DeBusk et al., 1999 ; Tompkins et al ., 1999 ; Whitelaw et al ., 1999) . Mixed form IDOs may be particularly well positioned to gain competitive advantage through implementing disease management processes.

CONCLUSION As regulatory and technological change create turbulence in the health care industry, the mixed-form IDO seems best suited to create innovations while enhancing community access, profitability, and competitive sustainability . Nonetheless, the mixed-form IDO creates greater complexity for health care executives to manage since both a system and a network of alliances must be sustained. In developing and managing an IDO that contains both a core system under unitary ownership and a network of strategic allies, healthcare executives must learn to balance key internal stakeholder interests via the three elements of polarity management . At the same time, executives must also balance the complex strategic alliance relationships intrinsic to the networked aspect of the IDO . In addition, the mixed-form [DO must seek to leverage local and regional market forces by engaging in health service delivery innovations such as disease management. Most importantly, as the mixed-form IDO both nurtures network relationships and focuses on internal efficiencies, it becomes closer to achieving a community healthcare management focus (Charns, 1997), emphasizing both clinical integration and the establishment of a community care network (Bogue et al ., 1997a) . It also should better balance stakeholder interests so that the DDO benefits from multiple - internal, interface, and external - supportive stakeholders . The challenge for health care executives is both to concentrate on the vision of, and to master the management skills needed for, this complex and emergent organizational form .


57

NOTES 1 . These two categories, as used by the AHA, overlap ; hospitals in a system may also be members of a network and vice versa . The AHA categorizes both multi-hospital and freestanding hospitals as systems so long as they own or lease at least three non-hospital, pre-acute (e .g . medical group practices) or post-acute (e .g . nursing home

or home health agencies) health care organizations, which account for at least 25% of the system . Networks, according to the AHA, include groups of hospitals, medical group practices, insurance companies, and/or community agencies that coordinate and deliver health care services to their communities . 2. There are several structural barriers to entry that aid in the formation of monopolistic power once systems have integrated . Hospital staff privileges are one such barrier . For example, if an incoming physician specialist is not granted privileges to the local IDS, that specialist cannot start a day practice wherein admitting privileges were required . The healthcare system is barring entry of such competition, forcing the specialist out of the relevant market area to practice . 3 . Strategic leadership for medical groups : Navigating your strategic web. San Francisco : Jossey-Bass.

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UNDERSTANDING THE MEANING OF HEALTH CARE MANAGEMENT RESEARCH THROUGH THE USE OF A COGNITIVE MAPPING APPROACH Richard M. Shewchuk, Stephen J. O' Connor, Myron D . Fottler and Hanh Q . Trinh ABSTRACT While both health services and management research have been discussed in different literature streams in recent years, there has been no research on how scholars who conduct health care management research view the research process. How do they conceptualize it : what are the dominant themes? The present study is the first to examine the research process from the perspective of the health care management researcher . Focus group meetings were held during the Health Care Management Division's pre-conference workshop at the 1996 Academy of Management meeting . In these meetings, a nominal group technique method was employed to get participants to generate attributes that were personally salient in terms of what "research" meant to them . Thirty distinct attributes were eventually derived, and these were inscribed onto sets (decks) of thirty index cards .

Advances in Health Care Management, Volume 2, pages 63-90 . Copyright ® 2001 by Elsevier Science Ltd. All rights of reproduction in any form reserved . ISBN : 0-7623-0802-8 63

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Questionnaires were later distributed to 78 health management faculty members and doctoral students. In addition to completing the questionnaire, respondents were also asked to do a card-sort of the thirty research attributes to determine possible underlying dimensions and clusters. Analyzing the card-sorted data via multidimensional scaling and hierarchical cluster analysis resulted in the development of a cognitive map of what "research" means to health management researchers . This map consists of thirty attributes arranged across two dimensions and distributed among seven clusters . The clusters are referred to as ; (1) Theory/Relationships/Problems, (2) Analysis, (3) Research Infrastructure, (4) Emotional Outcomes, (5) Extrinsic Expectations, (6) Social Interaction/Self Concept, and (7) The Actualized Researcher. Implications for research orientation, collaboration, and career pathways are discussed .

INTRODUCTION For several years, there has been a ferment in management research regarding the research process . Where management researchers once prided themselves on following the natural science model of research, it has now become more respectable to be introspective about the research process and to be open to alternative approaches (Blair & Hunt, 1986) . Such introspection, however, raises questions about the underlying assumptions of the research methods used and the implications of those assumptions for common research endeavors . The work of Cummings and Frost (1985) was a milestone in the beginnings of a sociology of organizational and management research which systematically examined the research process itself as a legitimate field of study. This early introspective work served to sensitize scholars to various orientations, methodologies, and approaches to research . One's research orientation can be considered a stylistic framework that influences the way phenomena under investigation are interpreted and the manner in which research is conducted . A research orientation should not be interpreted strictly as personality dimensions, dogmatic assumptions, or conflicting research paradigms . Rather, one's personality, assumptions, or research paradigms may represent a dynamic unfolding complementary set of processes . Despite the importance and usefulness of health care management research, empirical efforts to understand the processes and orientations of such research have been limited . Instead, we have had admonitions to examine the process empirically and determine the effectiveness of various approaches, orientations, and methodologies .

Understanding the Meaning of Health Care Management

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A CALL FOR A NEW UNDERSTANDING The present paper examines the research orientations of health care management scholars . Although we frequently see various definitions of "health services research" which include specification of areas needing further research, few studies have addressed how the research process actually is perceived by scholars . A recent monograph written by the Committee on Health Services Research formulated the following definition : Health services research is a multi-disciplinary field of inquiry, both basic and applied, that examines the use, costs, quality, accessibility, delivery, organization, financing, and outcomes of health-care services to increase knowledge and understanding of structure, processes, and effects of health services for individuals and populations (Field, Tranquada & Feasley, 1995, 3) .

The Committee went on to outline priority areas for future research including the organization and financing of health services ; practitioner, patient, and consumer behavior; and the health professions workforce . They also specified which institutions should do what in order to produce the quantity and quality of research needed by our society . While the definition and priority research areas are broad enough to include health care management researchers and what they should do, there has been no attempt to "get inside the mind" of health care management researchers to assess how they perceive the research process in a normative context . Scholars have also pointed out that an individual's research orientation may also be a function of the incentives or penalties of the institutional environment of which they are a part (Hunt & Blair, 1987) . If one management scholar is in a department where basic research published in academic journals is valued, while another is in a department where applied research published in practitioner journals is valued, these differences will undoubtedly impact the research orientations of these scholars (particularly those who choose to remain in their respective departments) (Gray & Phillips, 1995) . Hunt and Blair differentiate four archetypes of management scholars : (1) the "involved scholar" who contributes to both content and process in the field ; (2) the "distant scholar" who contributes only to the field's content ; (3) the "association loyalist" who contributes only to process activities ; and (4) the "local" who contributes to neither content nor process activities in the field . The research orientations of each of the four archetypes are expected to vary . First, the involved scholar and the distant scholar are apt to give a heavier weight to research in general than would the association loyalist and the local . Second, the involved scholar and the distant scholar are likely to have different

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or proceedings, the involved scholar is more likely to give greater emphasis to building the field through such activities as editing a scholarly journal, writing a practitioner-oriented book or article, writing a textbook, serving as chair or discussant at a conference session, and reviewing a scholarly article for a journal or conference. Consequently, the two are likely to have dissimilar research orientations . Not only will management scholars' research orientations vary by their institutional environment, but also by their age, career stage, prestige of degree-granting institution, entrepreneurial orientation, and commitment to a specifc research area (Hunt & Blair, 1987) . The aim of the present study is to examine systematically how health care management scholars define and organize what they view as important in their research activities. In particular, this paper will address the following three questions : (1) How do health care management scholars perceive the components of their research activities? (2) How do health care management scholars cognitively organize these components into mental maps that reflect homogenous clusters of activities? (3) How might the cognitive representations that emerge have implications for health care management research?

METHODS Nominal Group Technique Two nominal group meetings were held during the Health Care Management Division's Preconference Workshop at the 1996 Academy of Management meeting . Groups contained 19 and 22 individuals, respectively . Participants included a mix of doctoral students, assistant professors, associate professors, and full professors, with approximately equal numbers of men and women at each level. The Nominal Group Technique (NGT) (Delbecq, Van de Ven & Gustafson, 1975) process was utilized to obtain information (i .e. words, phrases, statements, or criteria) that individuals perceive as personally relevant in response to the question, "What does research mean to you?" Obviously redundant, vague, or idiosyncratic attributes were eliminated to distill the list to thirty distinct attributes (see Table 1) . Card Sort The statements or phrases describing these attributes were inscribed on index cards. A second group of respondents (n = 78), which included participants from


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Table 1 . Attributes generated by faculty members and doctoral student focus groups in response to the question : "Research : What Does It Mean To You?" 1 . Identifying causal relationships . (Causal Relationships) 2 . Problem identification . (Problem Identification) 3 . Establishing a connection between abstract theory and application . (Connections) 4 . Theory development. (Theory) 5 . Discovering commonalties and anomalies . (Commonalties) 6 . Statistical analyses. (Statistics) 7 . Data . (Data) 8 . Measurement. (Measurement) 9 . Research methods . (Methods) 10 . Pragmatics - Research infrastructure . (Research Infrastructure) 11 . Technology and innovations . (Technology) 12 . Discovery - WOW-Ah Ha - Eureka. (Discovery/Eureka) 13 . Opportunities for creativity and innovation . (Creativity) 14 . Courage to pursue the truth. (Courage) 15 . Persistence and hard work . (Persistence) 16 . Willingness to experience lows along with the highs . (Lows & Highs) 17 . PassionBuming in your soul . (Passion) 18 . Fun/Excitement . (Fun) 19 . An academic expectation . (An Academic Expectation) 20. Publications . (Publications) 21 . Funding . (Funding) 22. Tenure . (Tenure) 23 . Effective way to communicate . (Communicate) 24 . Validation of what I do. (Validation) 25 . Colleagues/Collegiality . (Colleagues/Collegiality) 26. Power . (Power) 27 . Polished persuasive writing. (Writing) 28. Research as a basis for policy-making . (Policy Making) 29 . Never-ending process/Incremental activities . (Never Ending) 30 . Producing a product that is relevant and useful to society . (Relevant Product)

the nominal group meetings, was asked to sort the cards by grouping together perceptually similar attributes into the same piles . This required participants to consider the meaning of each of the thirty attributes as they sorted them into perceptually similar groups . Participants in the second group averaged 41 years of age (sd = 8 .97), with slightly more than half being female (55%) . Participants varied in terms of years of experience (mean = 8 .6 years, range = 0 to 30 years), the number of journal articles published, the number of papers presented at conferences, and extent of research funding (Table 2) . Approximately two-thirds of respondents indicated that research was a priority in their academic roles (Table 2) .

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RICHARD M. SHEWCHUK ET AL . Table 2 .

Gender Age

Characteristics of subjects responding to the card-sorting task (N = 78) . Male Female Ave. age:

Field of study/disciplinary focus Organizational Studies Strategic Management Administration/Policy/Management Information Systems Economics/Finance Research/Outcomes Not reported Current position/level

Associate Professor Assistant Professor Full Professor Instructor Doctoral Candidate/ABD PreDoctoral Candidate Post-Doctoral Fellow Non-Academic Public Sector

45% 55% 41 .3 years (Std . Dev. = 8 .9)

40% 23% 19% 1% 4% 8% 5%

14% 21% 10% 1% 32% 19% 1% 1%

Number of published journal articles 0 1-5 6-10 >10

30% 36% 11% 23%

Number of peer-reviewed papers presented at conferences 0 1-5 6-10 >10

28% 29% 9% 33%

Priority rating of research in academics Lowest Priority Fairly Low Priority Average Priority Fairly High Priority Highest Priority

3% 4% 23% 33% 33%


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Cognitive Mapping Multidimensional Scaling and Hierarchical Cluster Analysis A cognitive mapping approach using multidimensional scaling (MDS) and cluster analysis was used to produce a map-like representation of the cognitive structures that participants used to organize their perceptions of research attributes. The data from the card-sort task provided by each participant consisted of a matrix of co-occurrences (i .e. attributes sorted into the same pile) . The co-occurrence matrices were aggregated across all participants to form a group co-occurrence matrix . This matrix indicated the number of times participants sorted each attribute into similar or dissimilar piles . A group co-occurrence matrix provided data that were used by MDS and cluster analysis to generate an aggregated view of the perceived similarities and dissimilarities of all attributes . The group co-occurrence matrix was analyzed with MDS (ALSCAL algorithm) and cluster analysis . MDS techniques essentially attempt to map or model the similarities (or distances) among perceptual attributes by providing an organized structure that is thought to represent the underlying criteria used by participants in making decisions or judgments about the similarity of attributes (Schiffman, Reynolds & Young, 1981) . Additional interpretive insight into the meaning of the MDS map can be obtained by using cluster analysis . In this analysis the coordinates that are generated by MDS to define the spatial position of each perceptual attribute in multi-dimensional space are grouped in terms of their proximity . Generally, the purpose of cluster analysis "is to divide a set of objects into a smaller number of homogenous groups on the basis of their similarity" (Aldenderfer & Blashfield, 1984, 59) . On the other hand, the main concern of MDS is the relative ordering of attributes along each decisional dimension . Although MDS and cluster analysis are computationally sophisticated, they are not based on statistical theory . Consequently, the validity of an MDS and cluster analysis solution is not necessarily sample size dependent, but instead, a function of the representational adequacy of the sample participating in the sorting task (Speece, 1990) . The graphical representation of the combined MDS/cluster analysis map portrays different aspects of perceived similarity of attributes . Pairs of perceptually similar attributes (i .e . those frequently sorted together) are represented as points that are relatively closer on the map than attributes that are viewed as perceptually dissimilar . When MDS and cluster analysis are used together in examining the same data, we are able to discern both the relative ordering of clusters and . the ordering of individual attributes

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RICHARD M. SHEWCHUK ET AL .

We used several criteria in assessing the validity of the map produced by these analyses . At the most basic level, the validity of a map is simply a function of its ability to accurately portray the data in a way that makes sense. From a more formal perspective, the MDS map was evaluated by examining specific goodness-of-fit criteria including S-STRESS and RSQ values . These values indicate the level of correspondence between the observed similarities of the attributes (i .e. data produced from the card sort task) and the estimates of these similarities as indicated by the map of interpoint distances between pairs of perceived attributes . In summary, the goal of an MDS analysis is to derive a spatial configuration that will explain the totality of the relationships between all possible pairs of the perceptual attributes under investigation . The interpretation of an MDS space assumes that the ordering of objects in the space is meaningfully related to identifiable and interpretable characteristics that explain their configuration in space. Kruskal and Wish (1978) liken the difference between MDS and cluster analysis to that which might be observed between one's neighborhood of residence and family affiliation . For example, attribute items may "reside" in the same neighborhood and also have primary "family" affiliations with very different groups of items that reside in other neighborhoods .

RESULTS AND DISCUSSION Using data from the card-sorting task, an MDS alternate least squares scaling (ALSCAL) (Statistical Package for the Social Sciences, 1998) analysis was performed . Results suggested a two-dimensional solution as having the best fit . Because there are no distributional assumptions that are made for the card sort input data used in the MDS, precise statistical tests of fit have not been developed (Kruskal & Wish, 1978) . However, the stress and level of correspondence between the rank ordering of the input similarities and the mapped similarities (or distances) (i .e . the R 2) do provide a general indication of the relative fit of different solutions to the data . These general measures indicated that a two-dimensional solution provides a better model than a one-dimensional solution, and did not appear to be any worse in representing the data than a three-dimensional solution . This finding is in keeping with what other researchers have shown in that satisfactory solutions can usually be obtained with two-dimensional structures (Trochim, 1989) . The map representing the two-dimensional solution (see Fig . 1) positions each attribute on the map in terms of its relative location on each dimension . Specifically, the location of each attribute in this two-dimensional space is defined by a pair


Table 3 . CLUSTER

1

CLUSTER 2

CLUSTER 3 CLUSTER 4

CLUSTER 5

CLUSTER 6

CLUSTER 7

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Research Attribute Assignment to Clusters .

(Theory/Relationships/Problems) Causal Relationships Problem Identification Connections Theory Commonalties (Analysis) Statistics Data Measurement Methods (Research Infrastructure) Research infrastructure Technology (Emotional Outcomes) Discovery/Eureka Creativity Courage Persistence Lows and Highs Passion Fun (Extrinsic Expectations and Rewards) An Academic Expectation Publications Funding Tenure (Social Interaction/Self-Concept) Communicate Validation Colleagues/Collegiality (The Actualized Researcher/To Be Someone) Power Writing Policy-Making Never Ending Relevant Product

of coordinates representing each dimension . The hierarchical cluster analysis produced seven clusters of attributes (Table 3) . The seven attribute clusters are superimposed on the map (see Fig . 1) . These clusters are indicative of homogenous groupings of research attributes . The map in Fig . 1 depicts the overall cognitive representation of how various attributes of research are understood

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Dimension 1, the horizontal x-axis, can be viewed as a continuum ranging from the processes and conduct of research on the right, to the outcomes of research on the left. Dimension 2, the vertical y-axis, arranges the various research attributes according to their degree of tangibility. The more tangible aspects of research are located in the upper half of the figure, while the bottom half represents the less tangible aspects of research . The hierarchical cluster analysis generated seven distinct clusters to which each of the thirty research attributes were assigned exclusive membership (see Table 3) . The cluster analysis of the coordinates obtained from the MDS solution are also superimposed. Again, because there are no assumptions that can be made about the distribution of the data used in this analysis, well developed and accepted statistical tests for assessing the adequacy of fit have yet to be developed (Aldenderfer & Blashfield, 1984) . A subjective decision was made to interpret a seven-cluster solution . This decision was informed by examining the pattern in the agglomeration coefficients indicating which attributes were joined to form a cluster and by visually inspecting the dendrogram and icicle plot (Statistical Package for the Social Sciences, 1998) . We next turn our attention to the general concept of research, and using the cognitive map described above, further examine how research is conceived by our sample of health care management academicians . How research is defined varies according to who is doing the defining . From a fairly restrictive perspective, legitimate research can be viewed in terms of its precision and scientific principles . That is to say studies that are "systematic, controlled, empirical, and . . . guided by theory and hypotheses about the presumed relations" (Kerlinger, 1973) among phenomena. More expansive views of research see it as involving any inquisitive activity that results in knowledge creation (DePoy & Gitlin, 1994) . Further, DePoy and Gitlin (1994, 5) contend that research is not possessed by any one discipline or profession, but is a methodical "way of thinking and knowing and has a distinctive vocabulary that can be learned and used . . . " They define research as : Multiple, systematic strategies to generate knowledge about human behavior, human experience, and human environments in which the thought and action process of the researcher are clearly specified so that they are logical, understandable, confirmable, and useful (DePoy & Gitlin, 1994, 5) .

The definition of health services research, given earlier, is more focused . It specifies that health services research is multidisciplinary, that it can be basic or applied, and that it should improve our knowledge and understanding of

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Our analysis shows that the meaning of research to health care management academicians is a unique blend of thinking, knowing, behaving, and feeling that is embodied within thirty distinct attributes graphically arranged along two dimensions and within seven clusters . When, going from right to left along the horizontal dimension (x-axis), there is a transition from process-oriented research activities to research outcomes . Similarly, going from the top to the bottom of the vertical dimension (y-axis) depicts movement from tangible elements of research to those that are less tangible . The arrangement of attributes along the vertical dimension suggests a state or static conceptualization of the research attributes . In contrast, the horizontal dimension seems to suggest a process, and thus could be construed as being more dynamic than the vertical dimension . Practically speaking this could suggest that some researchers may prefer the means of research (e.g . theory, data collection, statistical analyses, writing) over the ends aspect (e.g . affective aspects, social interaction, power, publications) or vice versa . Our MDS results indicate that both process and outcome elements are required to convey the overall schema that defines the meaning of research for researchers .

THE RESEARCH ATTRIBUTE CLUSTERS Theory/Relationships/Problems (Cluster 1) Cluster 1 is termed "Theory/Relationships/Problems" and contains five attributes : discovering commonalties and anomalies, theory development, establishing a connection between abstract theory and application, problem identification, and identifying causal relationships . This cluster lies on the right side of Fig . 1 and immediately below the horizontal axis, indicating a research cluster that is process-oriented and somewhat intangible in character . The cluster is concerned with problem identification, abstract theory and concepts, understanding how and why concepts should be related, and climbing the ladder from abstract theory to more concrete application and vice versa . It is from this research cluster that literature reviews, research questions, propositions, and hypotheses emerge . Analysis (Cluster 2) Cluster 2 is termed "Analysis" and consists of four attributes : methods, measurement, data, and statistics . This research cluster also is located farthest to the right on the horizontal dimension in (see Fig . 1), making it the most process-oriented of the research clusters . Research methods embody the design


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and analysis components of research . It is not the end-result of research, but the means of achieving an outcome . The measurement attribute pertains to the way a concept is specified and operationalized (Shi, 1997) . It is a central part of any analysis, and it is with measurement that issues such as validity and reliability are concerned . The data attribute relates to specific facts (e .g. measurement observations, etc .) that are used as the basis for analytic calculations . Two problems related to data concern operational gaps between theory and data and the increasing difficulty of obtaining data from health care providers . Choi and Greenberg (1983) remark that many of the social science methodologies employed in health services research are plagued by operational gaps, or by greater distance between theory and data . Statistics is the fourth attribute associated with this cluster . This attribute pertains to the manipulation, interpretation, and display of quantitative data . Statistical approaches offer ways by which data that researchers measure and collect can be numerically analyzed. Research Infrastructure (Cluster 3) Cluster 3 is termed "Research Infrastructure" and consists of only two attributes : pragmatics - research infrastructure/technology, and lies on the process-side of the process-outcome dimension . This cluster is concerned with the foundation or supportive features that support research activities . Typically, research infrastructure could include elements of financial support, research assistance, statistical and data management cores, availability of journal subscriptions, and office space and furnishings . Another fundamental component of a research infrastructure is technology - especially computer hardware and software . Shi (1997) notes that computer knowledge is critical for health services researchers . Computers serve as a vehicle for researchers to store data (qualitative or quantitative), analyze data, write-up results, and prepare presentations . Internet technology is emerging as an important mechanism for communicating with colleagues . A description of the resources available at the Cecil G . Sheps Center for Health Services Research at the University of North Carolina at Chapel Hill is an excellent example of a comprehensive research infrastructure . The Center's most valuable resources are its faculty research fellows, staff and associates . Over 120 personnel occupy offices in the Center's facility on Airport Road in Chapel Hill. The staff is composed of faculty-level research fellows, research assistants, programmers and data entry personnel, librarians, business office and other support staff, as well as graduate assistants, Robert Wood Johnson Foundation Clinical Scholars, visiting international research fellows and pre- and post-doctoral fellows . Also affiliated with the Center are 150 research fellows representing more than 20 disciplines

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RICHARD M. SHEWCHUK ET AL . Carolina State University in Raleigh and several private and public agencies throughout North Carolina, the United States and other countries . The Center's resources include state-of-the-art communications using state-of-the-art equipment with the UNC-CH Information Technology Services and an intranet of micro-computers used for word and data processing, presentation development and desktop publishing. The Center offers immediate, 24-hour electronic communication with co-workers located throughout the world via its FIP and World Wide Web server sites . An additional, frequently used resource is the Center's specialized library that supplements the University's extensive holdings. The Center supports itself with funds from the State of North Carolina and with contracts and grants from several philanthropic foundations and federal government agencies, most notably the Agency for Health Care Policy and Research (ACHPR) and the National Institutes of Health (NIH), which includes the National Institute of Mental Health, the National Institute on Aging, the National Cancer Institute and the National Institute of Child Health and Human Development (Sheps Center for Health Services Research, 1999) .

Emotional Outcomes (Cluster 4) Cluster 4 is termed "Emotional Outcomes" and consists of seven attributes : fun/excitement, passion/burning in the soul, willingness to experience lows along with the highs, persistence and hard work, courage to pursue the truth, creativity and innovation, and discovery - WOW - Ah Ha - Eureka . These attributes represent the personal and affective components of doing research which are among the most intangible aspects of the research enterprise . The fun and excitement a person experiences when doing research, coupled with a sense of discovery, begin to make one passionate about the work that they do . In describing the "ideal" emotions researchers should possess for their work, Stark and Watson (1999, 727) advocate more sensual qualities and choose descriptors "such as desire, passion, and even eros ." Such passion for research is especially evident among those who openly refer to their work as not only their hobby, but as a calling . Anyone who engages in the process of research will occasionally face rejection . This could include rejected grant proposals, conference papers and symposia, and journal submissions . In a sense, rejection can be viewed as a natural part of research and provide opportunities for growth . For this reason, engaging in research necessitates a certain level of tenacity and even bravery . Individuals acquire and develop courage when faced with perceived threats such as uncertainty (Asarian, 1981), helplessness, lack of control, embarrassment, powerlessness (Finfgeld, 1999 ; Haase, 1995), and rejection . Many examples of the attributes associated with Cluster 4 are evident in Odin Anderson's (1991) book, The Evolution of Health Services Research . In


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particular, his chapter titled "Working in Applied Social Research: A Selective Sample of People and Projects" is replete with biographical vignettes . In reading this chapter, one is struck by the persistence and determination of these researchers in carrying out their work, and in demonstrating the true passion for what they do . In the foreword to this book, James Greenley recounts the life events of Odin Anderson himself . What follows is a brief passage that clearly illustrates a researcher who was persistent, courageous, and willing to experience the lows with the highs in the face of antagonism and on-going rejection . Anderson makes it clear that the Health Information Foundation and the University of Chicago's Graduate School of Business, where he worked, were organizational contexts that could either facilitate or preclude research . For example, the professional context limited the research and results that colleagues would take seriously ; results or interpretations that seemed inconsistent with the predominantly liberal professional bias were commonly ignored, attacked, or rejected . The historical and political contexts, for instance, were evident in the antagonism directed toward Anderson's research on health maintenance organizations by physicians and private insurance companies . The strength and vehemence of these professional and organizational interests created a stressful research environment for Anderson . At one point, he was summarily thrown out of a meeting of the Group Health Association. He had to live with the possibility that some powerful group, conservative or liberal, would take offense at his work and successfully move to cut off his research funding or get him fired. It was risky to publicize research results . At times, he and his research were attacked by the American Medical Association, from the right, and simultaneously by the more liberal Group Health Association (Greenley, 1991) .

Extrinsic Expectations and Rewards (Cluster 5) Cluster 5 is termed "Extrinsic Expectations and Rewards" and consists of both tangible and outcome dimensions of research including tenure, funding, publication, and an academic expectation . Located in the upper left quadrant of Fig . 1, Cluster 5 is high on both the tangible and outcome dimensions of research. These attributes generally represent elements whose value to research is defined by external entities based on perceived research quality . For example, an institutional decision to grant tenure to a faculty member will be based in some part on the research quality and productivity of the individual in question . Likewise, the decision to publish scholarly articles in a peer-reviewed journal indicates that the research reported within the article is well-regarded by the reviewers and the editors . Similarly, research funding represents a tangible outcome associated with higher quality grant proposals . Funding agencies generally take into account the relevance of the research question, the quality of the methodology, and the potential of the grant writers to actually carry out

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Tenure, publications, and funding are research outcomes that are especially sought after by academicians, and fulfill the fourth attribute in this cluster: an academic expectation . Moving from right to left within Cluster 5 ; we can see that an academic expectation comes first, indicating an ongoing background attribute that can be fulfilled by engaging in research . Next, comes publications and funding that are in immediate proximity of one another . These are both outcome indicators of research productivity and quality that serve to verify that the academic expectation is being met . Both publications and funding are strongly . considered in the decision to grant tenure, which lies even further to the left and represents a second-order outcome within this cluster . Social Interaction/Self Concept (Cluster 6) Cluster 6 is termed "Social Interaction/Self Concept" and consists of three attributes : colleagues/collegiality, validation of what I do, and effective way to communicate. This cluster lies just above the x-axis on the left side of Fig . 1 . These attributes can also be viewed as outcomes of research but with a social proclivity . Colleagues/collegiality lies furthest to the left and implies a collegial element of research that can involve developing and maintaining friendships and/or collaborating with others in order to conduct research . This cluster, above all the others, depicts research as a social experience . Although it is observed that collegial affinity and friendship can often make research more enjoyable and fun, this aspect of collegiality is typically not addressed in research methods texts . However, one aspect of the social dimension of research that has received attention is collaboration . Research collaboration is of value (Floyd, Schroeder & Finn, 1994) because it brings diverse contributors to the task, involves, often times, graduate students and younger faculty in a beneficial learning process, provides multiple individuals opportunities for increasing research productivity (Barnett, Ault & Kaserman, 1988 ; Strahan, 1982 ; Zook, 1987), and generally results in higher quality research (Blair & Hunt, 1986) . The attribute, effective way to communicate, lies at the far right of this cluster. It represents an outcome of research, but also embodies some process-like qualities . For example, Shi (1997) notes that research can be communicated through a variety of venues such as refereed scientific journals, professional conferences, working papers, and monographs . All represent outcomes in that they serve to communicate research results . However, because the research is communicated to others (manuscript reviewers, conference attendees, colleagues) with the hopes of obtaining critical feedback from peers, the act of


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communicating the research itself can serve to further improve the research . Feedback from journal reviewers often helps improve the quality of articles that ultimately appear in print . Feedback from colleagues on working papers or papers presented at professional conferences can assist in getting a manuscript ready for journal submission . For these reasons, research as an effective way to communicate can also manifest process-oriented properties . Validation of what I do, is the attribute that lies at the heart of this cluster. It is an outcome that gives meaning to researchers by reaffirming, authenticating, or verifying who they are as academicians . One might expect that on-going validation of one's self as a researcher tends to promote increased levels of self-efficacy (Bandura, 1997) that serves as reinforcement for motivating continuing research efforts . The Actualized Researcherfoo Be Someone (Cluster 7) Cluster 7 is termed "The Actualized Researcher/To Be Someone" and consists of five attributes : power, polished persuasive writing, a basis for policy making, never ending process/incremental activities, and providing a product that is relevant and useful to society . This cluster wraps closely around the right side of Cluster 6 . Clusters 6 and 7 are the only ones that suggest a social interaction, or how a researcher interrelates with others . However, while Cluster 6 is chiefly concerned with how researchers relate to those they know, Cluster 7 is concerned with how they relate to those they do not know . The power attribute is an outcome-oriented attribute of research . Power has been defined as "the probability that one actor within a social relationship will be in a position to carry out his own will despite resistance, regardless of the basis on which this probability rests" (Weber, 1947) . Thus, power is the ability to exercise influence . A research reputation can provide a power base for an individual with respect to colleagues at the local organization and within the broader profession. The strength of one's research reputation can ultimately bestow such things as tenure, journal editorship, a full professorship, or even a named or chaired professorship . Polished and persuasive writing can also serve to influence others and grant power to the writer . According to Shi (1997, 357), the ability to write is a required skill that is critical and essential "to convey the research to potential funders or users ." Many researchers have a self-image of being articulate and lucid writers . They take the process of writing very seriously and do not always take kindly to having someone else substantially re-write or edit their manuscripts . Writing can even furnish a researcher with a level of power that

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transcends life itself . For example, a researcher will eventually die, but his or her books and other writings will continue to "live" on . The policy-making attribute lies at the very center of the horizontal process-outcome dimension . The applied, context-specific, makeup of health management research affirms that it seeks to improve such things as organizational performance, individual and population health status, as well as health policy . This distinguishes it from more "context-free" disciplines that are less concerned with real-world problems and application (Blair & Hunt, 1986) . Previous research by Caplow and McGee (1958), Hagstrom (1965), and Gray and Phillips (1995) indicate that research for practical purposes usually lacks prestige in the academic community. Because health care management is an exception to this generalization, one outcome of health management research is to have the results incorporated into health policy formulation and implementation decisions (Shi, 1997) . One could surmise that the individual having greater power as a result of their research reputation may have greater influence on policy making . Analysis of existing health policy also serves as an important basis for conducting new research. Consequently, health policy formulation and implementation can be the outcome of research, or the catalyst for stimulating the process of research through health policy evaluations and analysis . Again, note the location of the policy-making attribute at the very center of the process-outcome dimension in Fig . 1 . The final two attributes in this cluster (never ending process/incremental activities and producing a product that is relevant and useful to society) reside very close to each other in the two dimensional space . The never-ending/ incremental attribute suggests just that; there is no end point in health care management research . The context of health care continuously evolves in terms of changing organizational structures, social conditions, illnesses and diseases, consumer preferences, organizational stakeholders, technologies, health care workforce factors, reimbursement issues, and government regulations . It is likely that emergent contexts will continue to create new questions, problems, and issues that can be addressed through research . In addition to the need for more research in response to a changing health care context, good research often raises more questions than it answers . For that reason, research usually spurs additional research that builds on itself incrementally . This last point ties the never-ending/incremental attribute to the relevant and useful attribute . Again, note the nearness of these two research attributes to one another in Fig . 1 . Usefulness is generally considered a fundamental characteristic of research. If the knowledge and understanding obtained from a research study is not useful to anyone, it becomes irrelevant . DePoy and Gitlin (1994, 9) describe the usefulness standard as follows :


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Each researcher, consumer, or professional judges the utility of a study based on his or her own needs and purposes . Usefulness is a subjective criterion in that it is based on one's judgment about the value of the knowledge produced by a study. However, the value of a study and the usefulness of knowledge become more widely accepted as the new knowledge increasingly stimulates further research and promotes the testing and verification of new or existing theory and practice .

From this description, we can see how relevance/usefulness closely relates to the attribute of research as a never-ending/incremental process . Moreover, both of these attributes relate to the polished persuasive writing attribute. When one's research is accepted for publication, the research criterion of relevance/ usefulness is being met (DePoy & Gitlin, 1994) .

IMPLICATIONS The research described in this study resulted in the development of a cognitive map that depicts what "research" means to health care management academicians . The map represents the geographic placement of thirty research attributes in a two-dimensional space. Families or clusters of like attributes were also derived and are positioned along this dimensional framework (see Fig . 1) . The vertical axis of the map represents a dimensional contrast of tangibleintangible attributes . The horizontal axis represents a dimensional contrast of process-oriented versus outcome-oriented research attributes . The seven research attribute clusters are referred to respectively as : (1) Theory/ Relationships/ Problems, (2) Analysis, (3) Research Infrastructure, (4) Emotional Outcomes, (5) Extrinsic Expectations and Rewards, (6) Social Interaction/Self Concept, and (7) The Actualized Researcher/To Be Someone . Note that our respondents identified and organized all of the attributes that Sternberg and Gordeeva (1996) found in their analysis of what makes an article influential . In addition, however, our respondents also identified the attributes of Clusters 3, 4, and 5 (research infrastructure, emotional outcomes, and extrinsic rewards), which did not appear in the Sternberg and Gordeeva (1996) paper . This should not be surprising since the attributes in Clusters 3, 4, and 5 do not necessarily correspond to those attributes of what we might consider a finished research project . Research Orientation and Collaboration Many health services research studies, written grant proposals, and journal article submissions are done collaboratively by interdisciplinary teams of researchers . This is not surprising when one considers that the lens of a single "context-free"

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addressing its various problems through research . Instead, health care is viewed as a "context-specific" field that is dependent upon the contributions of multiple disciplines in order to be best understood (Anderson, 1991) . While a multidisciplinary approach to studying health care is necessary and frequently advocated, it is not without its drawbacks (Richards, 1998) . Researchers in different disciplines often have difficulty working together because they have conflicting research orientations . These orientations may vary in terms of their emphasis on theory, methodology, public policy, and practical problems, as well as the different assumptions undergirding different disciplines (Anderson, 1991 ; Choi & Greenberg, 1983) . For instance, researchers who are newer to the health care context and who come from a "deep disciplinary" background, may be more concerned with theory and methods than with creating a relevant product and contributing to policy debates (Anderson, 1991) . In fact, Gray and Phillips (1995, 176) note that a research study "gaining favorable attention in the policy community or the press may make it suspect in disciplinary eyes ." Sensitivity to differences may also be required as researchers in "context-free" and "context-specific" areas consider and evaluate each other's research efforts . In the absence of such sensitivity, there is little understanding, tolerance, or appreciation for different research orientations even within the broader field of management and organizational studies . Blair and Hunt (1986) contend that an understanding and appreciation of different research orientations can help deal with some of the concerns about management research identified earlier (i .e. lack of practical utility and a focus on fads), They also give examples where teams of researchers from different disciplines (including management) and different research orientations (i .e. quantitative vs . qualitative, context-free vs . context-specific) have come together to produce research which is superior to that which could be done by any individual or group of individuals with similar research orientations . Thus, the mental landscape in Fig. 1, depicting what research means to health management researchers, provides insights for anyone seeking to collaborate on a research project . It can help address such questions as "Who might make a good research partner? Should opposites attract?" We next turn our attention to how this information might be utilized to create well-balanced research teams . Constructing the Research Team Before a determination is made as to who should or should not collaborate, the individuals or groups should make some honest assessment as to where their research strengths lie among the clustered attributes in Fig . 1 . Most individuals and groups of researchers do not exhibit strengths or aptitudes in all areas . It


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is in these less developed areas that point to the type of researcher(s) who might complement the present research entity, be it an individual or a team. For example, a person may have strengths in terms of Cluster 2 (Analysis) and Cluster 3 (Research Infrastructure), such as excellent computer skills, statistical abilities, and extensive experience managing primary and secondary data . While such a person demonstrates strengths relative to Clusters 2 and 3, he or she would need to personally cultivate the less developed clusters or be willing to work collaboratively with others in order to complement present skills . The individual or individuals who would complement the above researcher, likely would have excellent working knowledge of the field of health care management and be very familiar with related academic and practitioner literature . Reading voraciously, engaging frequently in discussions with health care scholars and managers, and thinking deeply about theory and practical problems can serve as a fount of new research ideas, questions, hypotheses, and topics . Contributions of this type are those reflected primarily within Cluster 1 (Theory/Relationships/Problems) . If people with these complementary research strengths were to collaborate, it is very likely they would be able to carry out most of the process activities associated with research (Clusters 1, 2, and 3) . However, in order to obtain desirable research outcomes (Cluster 4, 5, 6, and 7) other collaborators might be called upon to provide contributions reflective of the four remaining clusters . Other needed strengths to further complement this team would be (1) an ability to write clearly and suitably for a particular publication outlet, (2) an ability to target appropriate journals or other venues for communication and dissemination of research results, (3) the availability of valued colleagues who would be able and willing to provide critical feedback and commentary, and (4) the motivation and persistence to keep the entire project moving forward toward completion even in the face of obstacles and setbacks . Combining the entire array of strengths and abilities into a collaborative effort will serve to fulfill what research means to health care management researchers . Research Life Cycle The concepts uncovered by our analysis may also suggest a heuristic framework that arguably depicts an idealized academic trajectory . This trajectory, which is a temporal sequencing of the attributes and clusters in Figure 1, can assist in making sense of how research is understood across a general research life cycle . Academicians may find that distinct attributes of their research tend to become more prominent at different career stages, moving to the forefront, and

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As people move along this idealized career trajectory it is conceivable that they will find that their personal values, beliefs, and motives concerning research change over time . Furthermore, it is conceivable that the expectations that others have of a researcher's content, productivity, and output may also change along this trajectory . Borrowing from the work of Levinson (1978), we posit a hypothetical career life cycle framework that depicts the major career changes that might be experienced by health care management researchers in academic settings (see Fig . 2). The life cycle framework that we suggest consists of five distinct career stages (doctoral student, assistant professor, associate professor, full professor, and near retirement) and five transitory periods (doctoral transition, career entry transition, tenure transition, midcareer transition, and late career transition) . Also identified in this hypothetical portrayal of a career trajectory are clusters and attributes that could be expected to figure prominently at each career stage . Research Life Cycle and Career Paths Doctoral Student Stage Individuals entering a doctoral program will likely pass through an intense period of learning ; this includes learning about research, as well as doing research. Generally, in the pre-dissertation phase, students will take a variety of courses including research methods and design, philosophy of science, and a number of statistics courses . In these courses they learn about such things as concepts, theory, conceptual relationships, research designs, quantitative and qualitative approaches, and statistical techniques . During this stage, students often spend a good deal of their time learning about the processes of research as opposed to actually doing it . However, some students may begin to actually engage in research projects on their own or to assist others in conducting research . Perhaps they are only involved in a "piece" of the project, such as data collection or entry, literature review, analysis, or writing of the results . It is at this point when doctoral students may become active doers of research, as opposed to passive learners, and when they begin to experience the emotional aspects of doing research . Eventually, a doctoral student is expected to undertake a process of writing a dissertation . Although this is a process of learning research under the supervision of a dissertation chair and committee, it is also very much doing research . By this stage, a few students may receive research funding and perhaps some will also have made presentations, or even published a journal article. For doctoral students, we suggest that the clusters involved at the learning stage include primarily Cluster 1 (Theory/Relationships/Problems) and Cluster 2 (Analysis) . As the students become involved with research projects


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they will experience and even become part of Cluster 3 (Research Infrastructure) . Until they reach this point, students have engaged in the processes of research, either by learning or by doing . As they become more personally involved in their own or others' research projects, they will likely begin to experience outcomes, such as those in Cluster 4 (Emotional Outcomes) . As doctoral students approach the end of their dissertations, they may go into the academic job market, seeking an entry-level tenure-track position . This is an early career transition period that leads to the next career stage . Assistant Professor Generally, one would expect that the research conducted in this stage would be similar to that done as a late stage doctoral student, with the exception being that it is done largely independently and at an increased volume. During this career stage assistant professors are highly focused on meeting the academic expectations of their institutions and of the discipline at large . These expectations usually require some involvement in the grant submission process, and an increasing rate of publishing . These activities are usually taken very seriously because of their direct link to promotion and academic tenure . At this stage, because personal stakes are high, Cluster 4 (Emotional Outcomes) and Cluster 5 (Extrinsic Expectations) may be more prominent . Clusters 1, 2, and 3 (Theory/Relationships/Problems, Analysis, and Research Infrastructure) may also develop further at this stage . Assistant professors typically begin to communicate their research through publications and conference presentations and develop nascent networks of colleagues while also achieving a sense of research "self-worth" or validation . As these continue to develop, Cluster 6 (Social Interaction/Self Concept) will begin to emerge as more meaningful and operative . Near the end of this stage, the individual will prepare his or her case for tenure and promotion . If the individual is granted tenure and promoted, a third career stage will come forth . Associate Professor By this stage, the heavy expectations of tenure have lifted . Some researchers might see this as an opportunity to engage in more interesting or higher-risk research projects than they would have attempted as an assistant professor . Academic expectations, such as post-tenure review requirements or the elements necessary for promotion to full professor, still exist and can serve as a motivator for research . One would expect that all the clusters are involved during this stage of one's research career, with Clusters 6 (Social Interaction/Self Concept) and 7 (The Actualized Researcher/To Be Someone) emerging in only some researchers . If


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the individual eventually chooses to seek promotion to full professor, Clusters 6 and 7 will likely continue to dominate . Full Professor Once transitioned into this senior level stage, unless he or she is confronted with strict post-tenure review requirements or has a desire to seek employment elsewhere, he or she is not likely to face external demands to conduct research . If the professor gravitates toward Cluster 7 (The Actualized Researcher/To Be Someone) there is likely to be an intrinsic desire to develop or maintain a research reputation that is likely to sustain the motivation to do research . In some sense, a research reputation can serve as a very strong power base for an academician . One way to achieve this level of power is to conduct and communicate research such that it makes an impact in the literature, among health policy makers, and among health management practitioners and scholars . At this level, the health management scholar may be highly sought after and receive the prestigious chaired and named professorships . As individuals transition into this career development stage and move closer to retirement, they rarely face any significant external pressures to continue their research efforts . However, some researchers may think about the impact of their research as a legacy they can leave for others . Senior research professors may think about their own mortality, and how the profession will remember them once they are gone .

CONCLUSION : WHAT RESEARCH REALLY IS In this paper, we have sought to get inside the minds of health care management researchers and find out what research means to them . What is it comprised of and how do they conceive of it mentally? The answer to this question resulted in thirty attributes and seven clusters distributed among two dimensions . We have addressed some implications of these results, particularly in terms of research orientation, collaboration, and career life cycles . Given these results, what really is at the heart of our conceptualization of research? It appears that the flow and processes of research ultimately lead to Clusters 6 (Social InteractionlSelf-Concept) and 7 (The Actualized Researcher/ To Be Someone) . Interestingly, these are the only two research clusters that indicate how we relate to others . While Cluster 6 focuses on how we relate to those we know, Cluster 7 focuses on how we relate to those we do not know . In a sense, it appears that the end goal of doing research, or of a research career, is not only concerned with what we leave behind in written words . but

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our colleagues and the discipline . The actualized researcher is likely to be well regarded by colleagues and often is a polished persuasive writer who has made some real impact on health policy, practice, and scholarly knowledge . He or she has been affirmed and reaffirmed as a researcher who addresses relevant problems making a lasting contribution . Because people functioning at the actualized level are likely to achieve some degree of professional immortality, perhaps this stage could be thought of as "research nirvana ." Directions for Future Research A number of questions arise from the present study that offer directions for future research . These include the following :

• How do the research profiles as revealed through the cognitive maps differ

by gender, age, career stage, disciplinary focus, and one's personal priority rating of research in academics? Although we collected this data for the present study (see Table 2), the sample (N=78) was not large enough to allow for the meaningful creation and comparison of multiple cognitive maps. • Which research clusters and attributes are more important than others? Can we rank or weight the attributes/clusters to determine if some are viewed as significantly more important than others? In addition to card sorts, future research could also incorporate some measure of importance either by ranking each attribute/cluster, or by rating them on a Likert-type scale measure. • Can we derive research archetypes by individuals and institutional setting? Although this would be a difficult task indeed, it could assist people in several ways . First, it could be useful for job seekers hoping to find a natural employment fit by identifying institutional settings that would be likely to select and retain them, and allow them to be successful as researchers . Second, such archetypes could aid in identifying collaborators who could complement a research team . Third, archetypes could assist in the development of individual researchers by showing them a normative developmental trajectory of the life course of a researcher, and from this an individual could draw inferences as to whether they are "on-time" or "off-time" with respect to the developmental trajectory . Finally, it would be interesting to examine the archetypes of individuals and institutional programs that have made significant contributions to health care management, and therefore, who could provide direction and structure for fledgling researchers and research programs .


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Kruskal, J . B., & Wish, M . (1978) . Multidimensional scaling. Beverly Hills, CA : Sage Publications. Lawler, E ., Mohrman, A ., Mohrman, S ., Ledford, G., Cummings, T., & Associates (Eds) (1985) . Doing research that is useful for theory and practice . San Francisco, CA : Jossey-Bass. Levinson, D. J. (1978) . The seasons of a man's life . New York, NY : Alfred A. Knopf. McGuire, J. (1986). Management and research methodology . Journal of Management, 12(1), 5-17. Morgan, G ., & Smircich, L . (1980). The case for qualitative research . Academy of Management Review, 5(4), 491-500. Richards, L. (1998) . Qualitative teamwork: Making it work. Qualitative Health Research, (91), 7-10 . Schiffman, S . S ., Reynolds, M . L ., & Young, F . W . (1981) . Introduction to multidimensional scaling. New York, NY: Academic Press . Sheps Center for Health Services Research . (1999) . About the Sheps Center - [web page] h ttp ://www .shepscenter.une.edu/aboutcenter/about.html. (Accessed December 10, 1999) . Shewchuk, R . M ., O'Connor, S . J ., & White, J . B . (1991). In search of service quality measures : Some questions regarding psychometric properties . Health Services Management Research, 4(1) : 65-75 . Shi, L . (1997) . Health services research methods. Cincinnati, OH : Delmar Publishers. Speece, D. L. (1990). Methodological issues in cluster analysis: How clusters become real In : H . L. Swanson & B . Keogh (Eds), Learning Disabilities: Theoretical Research Issues . (pp . 210-213). Hillsdale, NJ: Erlbaum. Starbuck, W., & Mezias, J. M. (1996) . Opening Pandora's box : Studying the accuracy of manager's perceptions . Journal of Organizational Behavior, 17(2) : 99-117 . Stark, S ., & Watson, K . (1999). Passionate pleas for "passion please" : Teaching for qualitative research . Qualitative Health Research, 9(6), 719-730 . Statistical Package for the Social Sciences . (1998) . SPSS professional statistics 8 .0. Chicago, IL: SPSS, Inc. Sternberg, R . J., & Gordeeva, T . (1996). The anatomy of impact : What makes an article influential? Psychological Science, 7(2), 69-75 . Strahan, R . F. (1982) . More on JCP publication : Single versus multiple authorship . Journal of Counseling Psychology, 29, 430-431 . Trochim, W . M . K . (1989) . An introduction to concept mapping for planning and evaluation . Evaluation and Program Planning, 12, 1-16 . Weber, M . (1947) . The theory of social and economic organization . New York, NY: Free Press . Zook, A . (1987) . Trend toward multiple authorship : Update and extension . Journal of Counseling Psychology, 34, 77-79.

MANAGED CARE AND MEDICAL PRACTICE GUIDELINES : THE THORNY PROBLEM OF ATTAINING PHYSICIAN COMPLIANCE Howard L . Smith, Steven Yourstone, David Lorber and Bruce Mann

ABSTRACT Medical practice guidelines are increasingly being used by managed care plans to ensure quality of care while achieving cost reductions . However, it is unclear that physicians are complying with these clinical protocols . This paper reviews pertinent literature to assist in : understanding why physicians encounter different incentives for complying with guidelines ; identifying initiatives that managed care plans can utilize in managing clinical guidelines; and, identifying a research agenda for investigating issues surrounding physician compliance with guidelines .

INTRODUCTION Managed care plans face many financial pressures to control service utilization and costs when delivering capitated health care . While inpatient utilization is

Advances in Health Care Management, Volume 2, pages 93-130 . Copyright • 2001 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN: 0-7623-0802-8 93

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paramount in the cost control frenzy, there are also substantial challenges for containing costs associated with outpatient care . Added to these operating pressures is the continuing need to ensure the delivery of quality care, not only to remain competitive among health insurers and providers, but as well to minimize the incursion of malpractice litigation . Medical practice guidelines, clinical pathways, clinical guidelines, and clinical protocols are several terms referring to the same concept : "systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances" (Institute of Medicine, 1992) . Most managed care plans have turned to medical practice guidelines in an effort to assure quality care and to reduce costs (Field & Lohr, 1990) . Fang, Mittman and Weingarten (1996) estimate that 87% of physician organizations are adopting clinical guidelines . Nonetheless, it is unclear that physicians and other clinicians are warmly embracing these guidelines . Wolf, Grol, Hutchinson, Eccles and Grimshaw (1999) argue persuasively that a medical practice guideline industry has evolved and in the process has created a massive information overload for practitioners . This is a world-wide phenomenon with prevalent use of clinical guidelines evident in the United Kingdom, the Netherlands, Finland, Sweden, France, Germany, Italy, Spain, Canada, the United States, Australia and New Zealand (Carmine, 1996) . Commercially produced protocols are increasingly being adopted by managed care plans for benchmarking physician performance . Physicians have expressed concern about the incursion of these guidelines and metrics on the practice of medicine (Brook, 1989 ; Lomas et al., 1989) and recent analyses suggest that professional behavior may be subtly undermining the adoption of guidelines in clinical practice (Feder, Eccles, Grol, Griffiths & Grimshaw, 1999) . Early studies of physician practice behavior under clinical protocols suggest that practitioners do consider altering their behavior, but many practitioners are unable to correctly identify all the steps of protocols prevalent in their specialty (Lomas, Anderson, Domnick-Pierre, Vayda, Enkin & Hannah, 1989) . This problem has been compounded by the proliferation of practice guidelines and revisions in existing guidelines . Managed care organizations face the thorny problem of attaining physician compliance with clinical guidelines . The purposes of this paper are to understand why physicians encounter different incentives to comply with clinical guidelines ; to identify strategies or initiatives that managed care plans utilize in managing medical care guidelines ; to examine significant factors influencing physician compliance with medical practice guidelines ; and, to identify a research agenda for the future that will help to address issues surrounding physician compliance with clinical guidelines .

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THE CONTEXT OF CLINICAL CARE GUIDELINES Medical practice guidelines comprise only one part of a complex puzzle surrounding the direction of medical practice . Significant incentives for change in health care delivery were initiated by the shift from fee-for-service reimbursement to prospective reimbursement accompanying diagnosis related groups (DRGs) in acute care settings . Prospective reimbursement gradually spread beyond hospital walls to ambulatory settings and eventually to how patients were insured . Prepaid and capitated reimbursement soon became the model for health insurance . Managed care represents the latest evolution in a system of incentives linking provider, patient and payment . With fixed insurance payments based on the patient instead of the episode, providers encountered a clear economic rationale to keep the costs of service delivery in check . Unfortunately, the financial incentives also brought the issue of quality of medical care into question since limiting service delivery might adversely influence patient care outcomes . This battle in trade-offs continues to this day . Managed Care Processes Managed care processes, designed to influence the cost of health care delivery costs and to assure the delivery of high quality care, plus the structure of the managed care environment have combined to significantly squeeze medical practice as shown in Fig . 1 . Managed care processes (shown visually on the left hand side of Fig . 1) essentially represent attempts by health plans to maintain the quality of care delivered along with resource investments in care delivery (Reinke, 1995) . These processes may assume various forms ranging from physician report cards (Hofer, Hayward, Greenfield, Wagner, Kaplan & Manning, 1999) and profiles (Greene, Barlow & Newman, 1996 ; Tucker, Weiner, Honigfeld & Parton, 1996) that capture efficiency and effectiveness dimensions of practice such as number of visits, number of procedures, adverse outcomes and referrals (e .g . time devoted to a visit; cost of procedures versus revenue generated ; total cost of care per patient) to outcomes or evidence-based studies and reports that guide clinical practice (Edelman Lewis, 1995 ; Radosevich, 1997) to specific protocols for disease management (Ernster, 1997 ; McFadden et al ., 1995) . Structure of the Managed Care Environment The structure of the managed care environment (shown visually on the


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produces varying incentives for care delivery . The type of financial arrangement between a health plan and group or network of providers partially establishes the incentive for how physicians and other clinicians practice . However, the configuration of the practice - group or staff model versus network model - also affects resource utilization and risk sharing (Gold, Hurley, Lake, Ensor & Berenson, 1995) . Additionally, geographic location of the provider rural versus urban setting - presents unique service delivery challenges relative to productivity, cost and quality, although these outcomes have similar importance to all providers . The end result of these forces is a medical practice environment which significantly constrains practice behaviors and decisions . Physicians no longer have the freedom to practice with relatively complete autonomy . Their practice behaviors and decisions are squeezed by many constraints . The squeeze on medical practice has created a turbulent milieu for physicians which presents demanding care delivery incentives, restrictions and emphasis on outcomes . Risk-sharing by managed care plans has developed to the point that physician incomes are increasingly linked to curtailed services (Woolhandler & Himmelstein, 1995) . By limiting care and attracting more patients to a plan, physicians often can derive significant rewards through bonuses and other incentives (Gold, Hurley, Lake, Esnor & Berenson, 1995) . Risk-sharing also influences patient referral patterns (Franks, Zwanziger, Mooney & Sorbero, 1999 ; Hillman, Joseph, Marby, Sunshine & Kennedy, 1990) . This can threaten the quality of care ; a development that concerns physicians and managed care plan administrators alike (Hillman, Pauly, Kerman • Martinek, 1991) . Care delivery restrictions have become increasingly commonplace as managed care plans attempt to control resource utilization and to improve outcomes . The use of primary care physicians as gatekeepers is a prevalent methodology employed by health plans to control use of specialists, expensive diagnostic services and inpatient services (c .f. Feldman, 1998 ; Halm, Causino • Blumenthal, 1997 ; Volpintesta, 1998) . Gatekeeping produces a number of dysfunctional results including more paperwork, limited access to specialists, less freedom for clinical decisions, and time spent with patients, while adversely affecting overall quality of care and appropriate use of inpatient and laboratory services . Variations in treatment or practice patterns have provided additional rationale for managed care plans to pursue care delivery restrictions (Medical Economics, 1997) . Many examples are apparent in the literature . Health plans located outside of the West and Northeast where coronary artery bypass grafts are lower will

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benchmark . Plans in the Rocky Mountain states and the Northwest will try to establish care restrictions to achieve lower back surgery rates being attained in the Northeast and upper Midwest . Clinical guidelines will be created to reduce the number of unwarranted diagnostic tests that primary gatekeepers order in the course of their practices (Browner, 1998). Research has shown that only 30% of diagnostic tests for digoxin and gentamicin levels were appropriate (Bates, Boyle, Rittenberg, Kuperman, Ma'Luf, Menkin, Winkelman & Tanasijevic, 1998) because physicians ignore Bayesian reasoning in clinical practice (Reid, Lane & Feinstein, 1998) . Inefficient care delivery behaviors such as these ultimately lead to practice restrictions . Physician profiling (i .e . provision of objective data on practice behaviors and outcomes) has risen as a methodology for both managed care plans and providers to be vigilant about service delivery processes and outcomes . Considerable debate has surfaced in the literature regarding the validity of profiles and report cards (cf. Bindman, 1999 ; Lied, 1999) . Representative studies of physician profiling (cf. Hendryx, Wakefield, Murray, Uden-Holman, Helms & Ludke, 1995) demonstrate positive results from providing profiling information to clinicians not only in lower costs, but also favorable health care outcomes . Physician profiling can be improved through proper design and implementation strategies which address physician resistance (Bell, 1996) . The Squeeze on Medical Practice Figure 1 indicates that the squeeze on medical practice has created an emphasis on outcomes physician productivity, cost of care and quality of care . This has translated to systems that measure outcomes and that feed back data to providers, patients and insurers in order to inform decisions (Steinwachs, Wu & Skinner, 1994) . Whether preventive services for older patients (Burton, German & Shapiro, 1997), emergency care (Brook, 1998), public mental health outpatient programs (Hendryx, Dyck & Srebnik, 1999), or nursing care (Heacock & Brobst, 1994; Lichtig, Knauf & Milholland, 1999), outcomes measurement is increasingly prevalent . Several authorities argue that quality of care and provider performance reports should focus on improving consumer health, not simply on cost control or enhancing quality to score well on National Committee for Quality Assurance measures (Galvin, 1998 ; Sennett, 1998 ; Their & Gelijins, 1998) . It has been argued that outcomes programs enable providers to select the most efficient disease management methodology producing the best health outcome while delivering highest value to patients and insurers (Ortmeier, 1997) . Thus, as suggested in Fig . 1, important care delivery outcomes - provider


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productivity, cost and quality of care - become the focus of planning for patient care (Adams & Wilson, 1995) and the creation of systems recognized for delivering exemplary care . Outcomes programs have also been touted because they enable providers to gain greater understanding about how the organization of care in their delivery system ultimately shapes clinical outcomes (Aiken, Sochalski & Lake, 1997) . In contrast to these benefits, pervasive variations in treatment services and outcomes associated with care delivery are well-documented whether involving office-based treatment of diabetes (Weiner, Parente, Garnick, Fowles, Lawthers & Palmer, 1995), pneumonia (Whittle, Jeng Lin, Lave, Fine, Delaney, Joyce, Yound & Kapoor, 1998), low back pain (Carey, Garrett, Jackman, McLaughlin, Fryer & Smucker, 1995) or other conditions . Additionally, practitioners are not always receptive to interventions that attempt to guide their practices (Hargraves, Palmer, Orav & Wright, 1996) . Epstein (1995) indicates that medical practice guidelines which flow from outcomes studies possess many problems including incomplete measures which only partially report on care delivery ; tendencies for physicians to increase "upcoding" of suspected conditions in order to minimize risk; over-emphasis on specific care delivery processes for which publicly disseminated information conveys the quality of a plan/provider ; and, operational impediments (e .g . small sample sizes for some conditions) which render measures incomparable . Evidence-based Medicine and Practice Guidelines Another term for outcomes focused care delivery is evidence-based medicine which implies that physicians utilize the best information available to make decisions about patient care (Medical Economics, 1999) . Outcome studies generate new information about the best clinical practices which in turn establishes a basis for the development of new standards (Leape, 1995) . This information is folded into clinical guidelines and made available to physicians for disease management (Ellrodt, Cook, Lee, Cho, Hunt & Weingarten, 1997) . Data create a platform for successive refinement of care delivery (Ebert, 1995 ; Grimshaw & Russell, 1993 ; Pronovost, Jenckes, Dorman, Garrett, Breslow, Rosenfeld, Lipsett & Bass 1999 ; Randolph, 1999), but problems remain in physicians correctly using the guidelines (Barratt, Irwig, Glasziou, Cumming, Raffle, Hicks, Grey & Guyatt, 1999 ; Hayward, Wilson, Tunis, Bass & Guyatt, 1995 ; Wilson, Hayward, Tunis, Bass & Guyatt, 1995) . There are literally thousands of clinical guidelines available to physicians, many of which have been created by professional specialties and subspecialties.

1 00


(Santos, Cifaldi, Gregory & Seitz, 1999), breast symptoms (Barton, Elmore & Fletcher, 1999), cervical cancer screening (McFall, Warnecke, Kaluzny & Ford, 1996 ; Melnikow, Nuovo & Paliescheskey, 1996), cesarean sections (Bums, Geller & Wholey, 1995), laparoscopic surgery (Colegrove, Winfield, Donovan & See, 1999), prostrate cancer treatment (Potosky, Merrill, Riley, Taplin, Barlow, Fireman & Lubitz, 1999), arthritis (Keller, Majkut, Kosinski & Ware, 1999), alternative medicine (Spencer & Jonas, 1997) and health profiles (Ware, Kosinski, Bayliss, McHorney, Rogers & Raczek, 1995) represent a few of the clinical areas health services researchers have studied that ultimately add significant information to prevailing medical practice guidelines . The challenge for physicians is to keep abreast of the continual flow of new information about diagnosis and treatment regimens. This is not a new problem as physicians have always faced the problem of integrating new information within their practices . What is new, however, are the implications of managed care plans adopting medical practice guidelines as a standard for assessing physicians' performance (Flamm, 1999) .

Initiatives for Increasing Compliance Managed care providers, physicians, and medical societies have been searching for promising initiatives that will encourage medical staff members to comply with practice guidelines. Although the health services and medical literatures are addressing current issues of medical guideline compliance, a rich literature on compliance and influence is also available in psychology . Kelman (1961), for example, proposed different processes of influence which are applicable to medical practice guidelines . Physicians might comply with guidelines because they have to as a result of organizational or professional expectations . Alternatively, they might comply as a means of identification ; that is, they follow them because they want to fit within their medical community . Physicians may also comply due to internalization ; that is, they follow them because they believe in their efficacy . Recent behavioral research in business settings has greatly extended the empirical and theoretical foundations upon which the health services and medical disciplines can draw in understanding physician compliance with medical practice guidelines (cf. Chatman, 1989 ; Chatman & Barsade, 1995 ; Jehn & Chatman, 2000 ; O'Reilly, Chatman & Caldwell, 1991 ; Tusi, Egan & O'Reilly, 1992) . Above all, the health services and medical literatures suggest that providers must demonstrate creativity in their approaches at increasing compliance . As medical practice guidelines become institutionalized in practice and as medical schools expose students to basic guidelines underlying care, a more auspicious environment will be developed


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from which compliance should flourish . Until these events occur, managed care organizations will need to develop innovative strategies to raise compliance. Table 1 provides an overview of several leading initiatives that have been tested in clinical settings. Improving Access In order for physicians to utilize medical practice guidelines they should be readily accessible . Furthermore, mechanisms should be available to update the guidelines as new information is reported . Unless these two design features accompany a managed care provider's guideline information system, it will be difficult for physicians to keep abreast of the guidelines and this may encourage them to fall back on traditional practice behaviors that ignore the guidelines . Physicians face a daunting challenge in accessing guidelines because the number of guidelines has rapidly expanded . Simply because there are many guidelines surfacing in the respective disciplines and subdisciplines does not mean that physicians will take the time to ascertain which guidelines are prevalent in their area of expertise, or how these guidelines fit within the structure of guidelines adopted in their practice . One example of the challenge facing primary care physicians is illustrated by the choice of compendiums on providing preventive care . Weingarten (1999) identified four compendiums of preventive practice guidelines : Clinician's Handbook of Preventive Services, National Guideline Clearinghouse, Clinical Practice Guidelines Director and U.S. Preventive Services Task force Guide to Clinical Preventive Services . Which compendium is the best? Which compendium should practitioners utilize in understanding medical practice guidelines? Which compendium integrates the last evidence and expert interpretations? Which compendium offers the easiest referral? These are significant questions that Weingarten (1999) raised in the course of reviewing the primary sources . For the most part his research indicates that the compendiums vary in screening criteria ; integration of evidence-based findings ; focus on preventive services ; and, explanations regarding why guidelines conflict . He observes that in order for practice guidelines to have meaning for physicians, the guidelines must be easily accessible as a means for answering basic clinical questions . Given the conflicting nature of many guidelines, the proliferation of guidelines and the inability of managed care plans to deliver guidelines into the hands of physicians in a timely and informative manner, it is clear that there are significant problems surrounding accessibility . Technoloev could provide the answer to many of these questions and


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computerized information systems and the presence of the internet are strong facilitating factors which could assist in raising compliance by physicians in integrating guidelines within their practice behaviors . Lobach and Hammon (1997) reported the results of a six-month study of computerized clinical guideline use at a primary care clinic . The clinic adapted the American Diabetes Association's guidelines for patients with chronic diabetes mellitus . Medical staff members used a consensus-based approach for defining the clinic's protocol in order to ensure buy-in by staff members . After the guideline was defined, a computer-assisted management protocol was developed to assist physicians in managing care . Compliance with the protocol was ascertained by laboratory test summaries and audits of medical records. Thirty physicians participating in the trial were compared to 28 physicians who had minimum exposure to diabetic care . Compliance for the physicians who had access to the computerized management algorithm was 32% versus 15 .6% for the control group . These results support the contention that accessible medical practice guidelines can enhance compliance . The study also underscores a high level of investment necessary to operationalize clinical guidelines . Peer Review Professionals are inherently motivated to seek the approval of other professionals within their respective fields . This characteristic of medical professionals can be used to great advantage in achieving compliance with medical practice guidelines. The issue for managed care organizations is establishing a peer-based system that maintains participation and that is inexpensive to implement. The best form of peer review is one that is not forced on professionals, but that evolves naturally out of a consensus attempting to achieve well-embraced professional goals . Simultaneously, professionals must take ownership in designing and implementing a peer-based system if commitment is to be achieved . Medical practice guidelines offer a perfect opportunity to build on professional values and goals . Only physicians can ultimately agree on the content and precise elements underlying any clinical protocol . In the final analysis they are the basis for creating practice guidelines and the system for their application within care delivery. Goebel (1997) reported a study of peer review feedback that helped to promote compliance with medical practice guidelines in an ambulatory care clinic . Residents at the Marshall University School of medicine were introduced to nine preventive care service guidelines for use in an ambulatory care clinic . Every eight weeks the residents received four medical records for patients who received care from another resident . The peer review entailed reviewing notes


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for the most recent office visit and completing a quality assurance form . The record and completed quality assurance form are then returned to the resident physician caring for the patient. This resident then develops a care plan for the patient's next visit . An attending physician provided oversight on this peer review process . The results of this trial indicated a consistently higher delivery of four preventive care services outlined in the clinical protocols . Physicians who are immersed in high volume care delivery associated with managed care may doubt that such interventions can be developed outside the medical school setting. They would have to sacrifice some patient care in order to review colleagues' charts . This concern overlooks the important finding from the Goebel (1997) study. It may be that consistent, low-level peer monitoring is sufficient to encourage practitioners to follow clinical guidelines . If a physician knows that his/her patient care delivery has a reasonable probability of being scrutinized, it is likely that they will devote more attention to following guidelines . The issue then evolves into determining the frequency of review and extent (i .e . number) of patient records sampled. It remains for physicians and managed care organizations to design innovative peer review systems that are not overly obtrusive, do not raise expenses, and yet encourage effort toward compliance by all medical staff members . Reminders and Feedback

With the massive number of patients that some physicians serve, and considering the wide variety of conditions that patients present to physicians, it is understandable that medical practice guidelines may be overlooked in the care delivery process . Offering reminders and feedback on service delivery represent another initiative for improving compliance with medical practice guidelines. The key questions surrounding this intervention are : when to deliver the reminder or feedback; how to best convey the information ; and, how often to review compliance to ascertain whether the system is working . The use of feedback and reminders also presents a challenge of maintaining the interest of physicians - delivering information of value without judgment while reinforcing the importance of following clinical protocols . Reminder/feedback systems are susceptible to becoming a bureaucratic artifact that is easily forgotten or ignored after the novelty wears off. The value of reminders was demonstrated in a study by Weingarten and colleagues (1994) involving practice guidelines for patients with chest pains who are at low risk for complications . Patients with chest pains have traditionally been admitted to the coronary care unit . This practice was intended

1 06


experience of coronary care units has typically indicated that a significant percentage of patients (on order of greater than 70%) do not have acute myocardial infarction (Fineberg, Scadden & Goldman, 1984 ; Pozen, D'Agostino, Mitchell, Rosenfeld, Guglielmino, Swartz, Teebagy, Valentine & Hood, 1980) . Remaining in the coronary care unit has also shown to have deleterious effects on patients who do not present conditions of myocardial infarction (Falk, 1979 ; Hackett, Cassem & Wishnie, 1968 ; Sykes, Evans, Boyle, Mcllmoyle & Salathia, 1989). In the Weingarten (1994) study, physicians received both written and verbal reminders about practice guidelines for patients who presented low risk for acute myocardial infarction. A physician utilization review coordinator contacted physicians whose patients remained in the hospital longer than 24 hours after admission and for whom there were low risks for an acute condition. A significant increase in practice guideline compliance was observed as well as a significant decrease in the length of stay (Ellrodt, Conner, Riedinger & Weingarten, 1995 ; Weingarten, 1993) . Tierney, Hui and McDonald (1986) investigated the use of concurrent reminders and delayed feedback about preventive care guidelines in an effort to increase compliance . Eleven preventive care protocols were identified as having low compliance at a clinic . The clinic added two protocols . Monthly the clinic's information system searched through medical records of patients who had received care and had an indication for preventive care delivery, but who had not received the service(s) . This written feedback was then sent to the attending physician . Written reminders were also tested as a strategy for increasing compliance with clinical protocols . The night before scheduled visits, reminders were placed in patients' charts along with suggested preventive care guidelines . Although there was a statistically significant increase in the use of protocols, the level of use still remained modest . Reminders had a greater impact on compliance with medical practice guidelines than did feedback. Stabilize Guidelines Compliance with medical practice guidelines may be adversely affected by their inherent instability as new medical evidence is incorporated and practice experience indicates revisions to improve the guidelines . Physicians may tend to interpret this instability as a reason to ignore guidelines . Managed care organizations are challenged to remove this convenient rationale for overlooking sound medical practice protocols . Evidence from a . number of studies suggests that sound organization and management practices in managed care organizations can contribute substantially to compliance by physicians (cf.


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Other authorities have postulated that managed care organizations are more likely to have designed and implemented programs which encourage the use of medical practice guidelines . Thompkins, Bhalotora, Garnick and Chilingerian (1996) reviewed the literature on physician profiling and concluded that higher profiling use occurs in medical groups that develop sound management practices and policies. Medical management tools, such as clinical protocols, enable groups to transmit important practice information to medical staff . Managed care organizations are also more likely to establish quality assurance mechanisms that motivate physicians to follow practice guidelines essential in maintaining health . Klabunde, O'Malley and Kaluzny (1997) studied the rate of compliance of physicians with a new guideline for mammography developed by the National Cancer Institute . They observed that physicians tended to ignore the new guideline and expressed negative reactions to the revised guideline . Managed care providers demonstrate an enhanced ability to integrate revised guidelines within their system of medical practice patterns . Educate Providers

Table 1 indicates that another strategy for attaining compliance involves educating providers about medical guidelines and their use . Training in this sense should include not only the content of guidelines and their application, but also the technology that supports guidelines . Physicians with busy practices may not have the time to monitor guidelines despite repeated efforts from managed care plans to keep them informed. The matter is made worse when a physician is networked with several managed care plans. In this situation there may be more opportunities to become confused if the plans recommend different guidelines . This may leave physicians in the position of ignoring all of the guidelines, or applying the guideline of preference, due to the confusion. Multiplicity of guidelines can be compounded when the technology for accessing guidelines presents a barrier. Not every physician is user-comfortable or familiar with the compendiums containing practice guidelines . The computerized guidelines may present an additional challenge in access for those physicians who are not networked with a computerized system of practice guidelines . Access to the computerized guidelines may be difficult in some geographic areas (e .g . rural areas) . O'Conner, Quiter, Rush, Wiest, Meland and Ryu (1999) conducted a study of hypertension guideline implementation in primary care settings . Physicians received training for consistent hypertension treatment, standardization of blood pressure measurement, documentation of blood pressure readings, improved

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HOWARD L . SMITH ET AL .

patient recall system to issue patient reminders . The results of these interventions indicated a 15% increase in the proportion of patients with hypertension meeting the care guideline. The authors observed that this increase should be viewed as significant in view of the large percentage of adults who present indications of hypertension, but who do not have their blood pressure clinically controlled . Education served as an intervention to achieve greater compliance . Similar findings surfaced in a study by Katz (1999) when examining medical practice guidelines for unstable angina and patient care . Katz discovered that knowledge-based factors and organizational inefficiencies often preclude the proper implementation of clinical guidelines for unstable angina . In addition to educating physicians, providing support through clinical algorithms and guidance on using the algorithms can help to raise compliance . Factors Affecting Clinical Protocol Compliance As suggested in Fig . 2, four primary factors influence the extent to which physicians embrace clinical protocols when delivering services including the current status of practice guideline implementation in their clinical setting ; initiatives for improving the management of practice guidelines ; practice setting characteristics ; and, medical profession autonomy on the part of physicians . Figure 2 suggests that if a managed care plan or medical group wants to encourage physicians to comply with clinical protocols, it must attend to each of these four sources of influence . However, there is insufficient research on practice guideline compliance to predict which of these factors is strongest in any given setting, and insufficient research explaining how the factors interact (together) in affecting clinical protocol compliance . Status of Practice Guidelines The current status of practice guidelines within a managed care plan or medical group is a contextual factor setting a base for improvement in the consistent use of guidelines . Sound organization and development of guidelines creates a climate where more sophisticated applications are possible (Harris, 1995) . Managed care providers, especially staff model health maintenance organizations, may design and implement better structures for medical practice guidelines than in other settings . A health maintenance organization has many incentives for establishing a rational and efficient structure for clinical protocols . The use of guidelines standardizes care and in the process creates a foundation for lowering costs and maintaining high quality care (Keslin, Jarrell & Gregory, 1999) . The guidelines are also valuable in attaining accreditation standards as


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well as in documenting performance . Consequently, it is not surprising to observe that managed care plans often attempt to maintain a well-organized system of clinical practice guidelines . Physician incentives to comply with the guidelines represent another structural factor associated with the status of guideline implementation . Lagoe and Aspling (1996) discuss the complex incentives and disincentives at play from the perspective of physicians . Physicians may tend to view practice guidelines as reducing quality of care because they encroach obtrusively into the exam room, not unlike other intrusive influences of managed care (e .g . gatekeeping, prior permission, etc .) . The guidelines can increase risk if the physician decides that a course of treatment outside the guideline is warranted, and if an adverse result arises there is greater probability that this failure to strictly follow the guideline can be used in litigation . The reverse situation can also occur - where the physician follows the guideline to the letter and yet an adverse result implies that another course of action should have been taken . Physicians may perceive that practice guidelines reflect an obsession with cost control that has diminished the quality of medical practice . This is a significant disincentive for complying with clinical guidelines . Practice guidelines are symbolic of the larger effort within the health care system to control costs . The beneficiary of this control is not the physician necessarily, but employers, insurers and consumers . In this regard, clinical guideline use may be perceived as an attempt by insurers and health care institutions (such as hospitals) to pass on the pain associated with cost control . It is not too surprising that some physicians associate their practice income loss with these efforts to standardize care . Thus, the guidelines are seen in a negative light as hindrances to medical practice . While some physicians resist compliance with clinical practice protocols due to quality of care, cost control and litigation reasons, many others see the erosion of the art of medicine as the primary disincentive for compliance (Scott, 1995) . The delivery of high quality care cannot be assumed within the boundaries of clinical algorithms . Sound medical practice balances both science and art . Thus, physician judgment is critical in determining diagnosis and treatment plans . A medical practice guideline may be useful in some primary care situations, especially involving preventive services . However, the guidelines become less relevant in situations where complex considerations (involving biological, mental, genetic and similar factors) confuse the choices available to providers and patients . It can be argued that the control of medical practice represented by clinical guidelines is simply inappropriate to the profession - that medical care cannot be automated. Thus, the art of medicine and its practice is a significant consideration for any physician when faced with the imperative to


111

follow clinical guidelines (Haycox, Bagust & Walley, 1999) . Resistance to following guidelines represents a form of retaliation and strategy to undermine a bureaucratic system perceived as destroying professional autonomy . Balanced against the disincentives for compliance are many compelling reasons recommending that physicians strictly adhere to the guidelines . Most guidelines are the products of professional societies and associations ; that is, an end product from the community of medical specialists and subspecialists (Paniello, Virgo, Johnson, Clemente & Johnson, 1999) . In this respect, peers establish many clinical guidelines . This is a strong rationale for physicians to adopt clinical guidelines. Physicians typically want to follow the latest and best practices that their profession has identified . A related incentive for adhering to clinical guidelines stems from evidence-based medicine (Cook, Greengold, Ellrodt & Weingarten, 1997) . By gathering data on care delivery processes and outcomes, evidence-based algorithms incorporate scientific findings that guide clinical judgment. Physicians logically want to follow the most scientific reasons for delivering care in the interest of practicing the best care . There are numerous side benefits from using evidence-based medicine with a significant positive benefit resulting from decreased exposure to malpractice liability (Hyams, Shapiro & Brennan, 1996) . Evidence-based medicine may also integrate cost and quality trade-offs which provides explicit guidance for practitioners and simultaneously helps to minimize costs . Another factor to consider is the status of practice guideline implementation . The burden normally falls on the physician and the medical record to trace the status of preventive care and adherence to prevailing algorithms . In the future it is possible that the health care system may come to expect a more accountable role from patients . Managed care should not assume a one-way relationship where the patient is always on the receiving end . If consumers are able to assert their rights for health care, then they should also demonstrate responsible behavior . In this regard, patients can actively participate in collaborating with physicians and other providers in the delivery of care . This may imply providing patients greater access to the clinical guidelines that a managed care plan supports . An educated and active partner in care delivery - the patient - is one which may facilitate following the best practice exemplified in medical practice guidelines . Strategies for Managing Practice Guidelines Given the status quo for a health care provider's use of medical practice guidelines, physician compliance can be influenced through numerous strategies

1 12


organization and coordination of clinical protocols, providers should devote attention to numerous avenues that can positively affect physician compliance . First, access is a key for raising compliance . Unless physicians are attached to a single managed care plan, there is a high probability that they are flooded with information about clinical protocols from the panels on which they serve and from their specialty or subspecialty . The problem is not a shortage of information, but an extraordinary flood of information . The problem is compounded because the guidelines are seldom stable (Czaja, McFall, Warnecke, Ford & Kaluzny, 1994) . New information from medical research and practice results in alterations in even the most fundamental practice guidelines . For physicians who serve on several panels or networks, the problem is exacerbated . Each plan may specify different protocols for the same diagnosis and treatment . Thus, compliance can be influenced by the manner in which physicians receive, file and update information on practice guidelines. Providers must design strategies that drive physicians to, rather than away from, protocol use . Second, the implementation of practice guidelines can be enhanced through peer review of compliance . Simply providing guidelines to physicians does not ensure that they will be followed. Unless there is some sort of monitoring, there is no guarantee that providers will consistently utilize guidelines, especially when the use of protocols leaves the impression of encroaching on professional prerogatives . Peer review is a promising strategy for raising protocol use . However, this initiative must be balanced by cost considerations . If clinical control excessively raises costs, the incentive for the managed care provider to utilize guidelines in the first place can be lost . Third, practice guideline implementation can be improved by offering physicians immediate and post-care reminders . By alerting physicians to guidelines that may be applied for forthcoming patient visits, the physician is better able to access the guideline and to apply it. Again, this strategy can raise costs unless the system of reminders is carefully managed . Compliance can also be increased by post-care reviews which represents consistent feedback . Fourth, physician compliance with medical practice guidelines improves when an effort is made to stabilize and organize the guidelines in an intelligent way that supports practice (Bergstrom, 1997 ; Stason, 1997). Managed care plans can be accompanied by constraining policies and programs . While this has certain dysfunctional effects, it can also promote a more efficient system of guidelines that is updated constantly ; that offers providers easy access ; and, that educates them on significant changes in their specialties and subspecialties . The goal is to create systems that are user-friendly and that result in physicians seeking information on guidelines as a normal aspect of their care to patients . Fifth, Fig . 2 indicates that educating physicians about guidelines - their content and application - is a


113

promising way to improve compliance . Simply providing guidelines to physicians is not sufficient . The guidelines should be accompanied by continuing education in the proper application in order for the pro to have maximum benefit . Practice Setting Characteristics Staff Versus Network Models The characteristics of a practice setting will influence physician compliance with medical practice guidelines . Figure 2 indicates that at least three characteristics influence physician compliance. First, the type of practice setting - staff model versus network model - affects the structure, organization and coordination of practice guidelines ; the physician incentives for compliance ; and the extent to which patients collaborate in guideline implementation . These variables in turn influence physician compliance . Table 2 depicts hypothesized relationships between type of managed care setting (i .e . staff model versus network model) and practice guideline implementation . A staff model organization usually retains physicians as staff members . Network models affiliate with physicians who serve as quasi staff members that are loosely coupled with the providers . Preferred provider organizations, independent practice organizations and point of service plans are typical network models. As Table 2 indicates, despite their increasing prevalence, network models are less favorable for implementing clinical practice guidelines . Staff model managed care settings are predicted to have a positive impact on practice guideline structure, organization and coordination whereas network Table 2 .

Staff versus Network Models and the Implementation of Medical Practice Guidelines . Managed Care Setting

Practice Guideline Implementation

Staff Model

Practice Guideline Structure, Organization & Coordination • Access via Networked Computers • Process for Updating Guidelines • Systematic Assessment of Guideline Efficacy • Process to Educate Providers Physician Incentives for Compliance Patients' Collaboration in Implementing Guidelines

+ + + + -

`+' = Medical practice guidelines are facilitated in the practice setting

Network Models (PPOs, IPAs, POS)

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models do not generally facilitate practice guideline management. The network model will require more effort and resources to achieve the same level of practice guideline according to Table 2 . Staff model arrangements have a propensity to offer better structure for information and computer systems . This can provide easier access to clinical guidelines through networked computers . Admittedly, network models can offer a similar arrangement via the internet, but not within the context of the host organizations' local server . The staff model physician can access a single electronic source whereas the network model physician may have to access several sets of practice guidelines depending upon who the patient is and from which insurer the patient receives coverage . The staff physician may also address several types of insurers across patients, but the host organization can bundle practice guidelines, can reduce conflicts among the guidelines and can provide a more integrated information system . Staff model organizations are more likely to develop a process for updating practice guidelines and for ensuring that the guidelines are readily available to staff members . Network models will also make every effort to keep their guidelines current and to ensure that physician members are cognizant of the guidelines . However, physician members of the network may not immediately recognize changes in guidelines if they are following other guidelines associated with other plans . The staff model provider is better able to reduce redundancies in guidelines and to maintain efficiency by which the guidelines are managed and communicated to physicians . In effect, the staff model sets a platform from which change and improvement are more seamless . Network models can achieve these same goals, but usually at greater expense . Both staff model and network model practice settings pursue the systematic assessment of guideline efficiency ; that is, strategies to streamline medical protocols that better inform physicians and that enable physicians to comply with the guidelines . However, staff modes have a better basis for systematically assessing the extent to which guidelines are properly implemented . Communication and access are easier for the staff organization because of the direct connection with physicians and the presence of administrative staff who are responsible for maintaining the system of guidelines . Similarly, staff models should possess processes and systems that efficiently and effectively deliver continuing education to clinicians. The staff organization is more likely to manage physician education due to the grouping of physicians at common clinic sites . This relieves staff models of the additional coordination challenges facing network models . Table 2 suggests that neither staff models nor network models have an advantage in offering incentives for compliance . If a physician in either setting fails to comply with a guideline the consequence is essentially the same . A


115

significant pattern of noncompliance in either the staff or network situation calls for intervention . The primary advantage that a staff model possesses relative to the noncompliant physician is to terminate employment . However, the network model can also terminate the relationship with the offending physician . In either case the incentive for the physician is to maintain the relationship . Beyond the incentive of termination, both staff and network models can offer the same incentives to facilitate compliance by staff physicians . The staff model may have additional ability to implement incentives, but for most purposes the type of incentives are not unique in these managed care settings . Patient collaboration in implementing practice guidelines does not appear to be unique for either staff or network model . The key to capturing patient compliance relates to the length of the association between the patient and the managed care plan . The longer that a patient is associated with a provider, the more likely they will be exposed to care delivery interventions surrounding medical practice guidelines . This is not unique to the arrangement for physician staffing . Both staff and network models have the same ability to encourage patient collaboration in the use of guidelines . Both staff and network models rely on physicians to assist in implementing patient-oriented programs . Rural Versus Urban Milieu

The geographic location of a medical practice can influence medical practice guideline implementation and compliance . A study of care for diabetes mellitus among rural Medicare recipients in Minnesota indicated the need for an additional 30,000 hours of primary care physician services and a concomitant increase in the number of primary care physicians serving the population (Yawn, Casey & Hebert, 1999) . These findings relate to one practice guideline . Given the thousands of guidelines that exist, the actual application of clinical protocols across rural populations could result in a staggering demand for health care services in rural areas . In part, this finding is an indictment of the rural health delivery system . There is insufficient care available in many rural locations within the United States . The application of a standard or benchmark such as a clinical guideline demonstrates how rural populations can be truly undeserved . It is staggering to consider the resources that are needed to bring these populations up to the minimum specified in any medical practice guidelines . Although the Yawn, Casey and Hebert (1999) study focuses primarily on the effects of practice guidelines on the need for services, the research also has numerous implications for physician compliance with guidelines . Rural areas are often underserved . Practitioners must focus on delivering services in a situation that is often less than ideal . Physicians may not have the necessary

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basic clinical guidelines . In a few instances, some care is better than no care, even if this means that the specific requirements of a guideline are not met . Rural clinics can be substantially limited in their access to information . Although internet capabilities exist to facilitate access to clinical guideline compendiums for both urban and rural providers, rural communities may not have requisite communications capabilities such as those that exist in urban settings to support medical practices . If rural physicians cannot access fundamental information from the internet (or other technological support for medical practice), then it will be extremely difficult for them to implement guidelines . Finally, rural physicians may already have busy practices due to the tendency for rural areas to be underserved . The additional time that it may take to keep abreast of the latest practice guidelines may be traded-off for more time spent in delivering care . Guidelines become an ideal that should be pursued, but realistically can seldom be achieved without sacrificing care delivery . The situation is aggravated by the lack of managed care penetration into rural areas . Managed care plans are more likely to have established a set of clinical protocols for physicians within a network . Yet, rural physicians may not have equivalent access as urban physicians to managed care plans that have invested significantly in information systems support . Thus, the rural physician faces a comparably greater challenge in accessing medical practice guidelines and in maintaining a current file of guidelines that has been updated . The situation is even less conducive to physician compliance in using guidelines due to the lack of managed care coverage for patients. Many managed care plans invest considerably in educating patients about preventive care services . This patient education enables them to collaborate with physicians in the delivery of care and adherence to clinical protocols . Admittedly, even in urban areas this collaborative effect may be limited to preventive services . Nonetheless, it is a basis for development that rural physicians and patients cannot participate in at this time . Depth of Managed Care Figure 2 also indicates that the depth of managed care within communities can affect physician compliance with medical practice guidelines . Communities which have greater managed care penetration and which have more sophisticated managed care arrangements are more likely to observe greater compliance with clinical guidelines by physicians . Higher managed care penetration implies a higher probability of competition for enrollment . Plans must distinguish their services, and quality of care becomes a dominant factor for differentiating themselves from competitors . The ability to provide impressive reports for following National Committee on Quality Assurance standards is one means to convey the ability to deliver higher quality of care . Competition on the standards


117

raises the bar of performance when there is greater depth of capitation within a community . There is also a greater likelihood that a community with greater depth of managed care will have utilized medical practice guidelines over a longer period of time . Thus, physicians in the community are more conversant in the guidelines ; have worked out the problems in accessing the guidelines ; have incorporated the guidelines within the normal course of their practices ; and, understand the rhythms for updating by specific plans . Medical Profession Autonomy A fourth factor influencing physician compliance with medical practice guidelines according to Fig. 2 is medical practice autonomy . Historically, physicians have experienced very powerful professional socialization . This process has dissipated in recent years . Nonetheless, there are still remnants of professional expectations and norms that dominate the field . The physician has significant autonomy in caring for patients ; autonomy that is respected by law and society . The result of this perquisite is an intense belief in rugged professional individualism . Many physicians do not mesh well with organizations because they are trained to think independently and to challenge assumptions about organizational authority . Smith, Piland and Discenza (1990) have theorized that many trade and professional workers achieve an elevated state of independence due to unique skills, knowledge and economics . They postulate that those individuals who possess relative independence in the work setting can take on the characteristics of free agents ; that is, employees can behave like free agents . It is clear that the concept of free agents applies to physicians as a whole and individually . For the most part, physicians tend to: be committed to their profession ; perceive that most medical care organizations are alike ; act in self-interest; are willing to change organizational affiliations with little encouragement ; develop limited loyalty to medical care organizations ; and, perceive substantial differences in reciprocity between what they invest in an organization and what the organization returns to them . Each of these characteristics of autonomy will be examined in turn because they are predicted to influence physician compliance with medical practice guidelines as shown in Table 3 . Commitment to the Profession Physicians, as free agents, are predicted to be more committed to their profession than they are to a medical group, managed care organization or other health care institution . They identify themselves as members of the medical nrofes-

118 Table 3 .

HOWARD L . SMITH ET AL .

Professional Autonomy of Physicians and the Implementation of Medical Practice Guidelines. Influence on Implementation of Medical Practice Guidelines

Professional Autonomy Manifested as Free Agent Attributes Commitment to the profession rather than to an organization (e .g ., a managed care plan) Organizational equality (i .e ., managed care plans are viewed as essentially equal) Self-interest (i .e., physicians' sense of self-interest overrides concern for an organization) Willingness to change affiliations (i .e ., physicians are willing to associate with many insurers) Short-run loyalty (i .e., physicians are not indelibly bound to a managed care plan) Inequality in reciprocity (i.e ., physicians perceive that they invest more in a managed care plan than vice versa)

Staff Model

Network Model

+/+ +/+ +

+' = Medical practice guidelines are facilitated in the practice setting. -' = Medical practice guidelines are not facilitated in the practice setting .

physicians are not favorably disposed to complying with medical practice guidelines championed by any particular managed care plan . If anything, physicians will support clinical guidelines that are established by their specialty or subspecialty . But, they are reluctant to let an organization dictate the correct or preferred steps in care delivery . By upholding the preeminence of the profession, physicians experience a sense of freedom to practice without deep regard to their clinical affiliation . Primary care can be delivered in a variety of settings (e .g . rural referral center, community health center, hospital, etc .) and for a wide array of organization types (e .g. private clinic, multispecialty group practice, etc .) . Table 3 predicts that this free agent attribute is detrimental to facilitating compliance with clinical protocols in network model managed care organizations because physicians are not closely linked to the network . Staff model managed care plans are more likely to establish a close relationship which may counterbalance physician autonomy ; but, physicians may still act independently thereby undermining clinical practice guidelines . Organizational Equality

As free agents, physicians are predicted to view most medical care organizations as the same . One managed care plan may have a few redeemable attributes


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over another, but these positive attributes are seldom significant enough to overcome the tendency of physicians to function mentally as free agents . By equating managed care organizations, physicians set the stage for noncompliance with managed care plan prescribed clinical protocols . The correct medical practice protocol for any given situation is that which the physician has personally adopted, not the guideline set by a managed care organization . This line of thought is especially prevalent for physicians practicing in network model health care plans . They are reluctant to follow medical practice guidelines which some organizational authority has deemed appropriate . In contrast, physicians in staff model health maintenance organizations are more likely to follow the clinical protocols adopted by their organization because they have a greater knowledge of the medical leaders who helped define the protocols ; they may have participated in the formation of the protocols ; and, they understand and buy into the organization's plans and efforts to deliver care . Self-interest Physicians are predicted to place their self-interest over that of the organization(s) for which they provide care, and therefore act as free agents. A free agent is most concerned with self and how to achieve personal goals. Non-free agents tend to view their personal goals within the context of the organization where they are employed . Personal goals are achieved within the context of the organization . Thus, the individual must sacrifice some progress toward personal goals in order to function effectively within the organizational context . In network model managed care plans, physicians' concern for self-interest overrides their concern for the organization . In these cases physicians are less likely to comply with clinical protocols unless physicians see that the protocols are contributing to the accomplishment of personal goals . The same phenomenon applies in staff model settings, but to a lesser extent. Physicians who are members of staff model group practices will also pursue their self-interest, but they recognize that what is good for the group is also good for them personally . Hence, they are more likely to follow medical practice guidelines than physicians in network models . Willingness to Change Affiliations Free agents are willing to change affiliation at a moment's notice if they perceive that their personal position is enhanced . If an organization offers them more money or better work environment, they will change affiliations . In the case of physicians, health care organizations may try to lure them to a better practice setting in terms of equipment and staffing . They may be offered more vav or

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HOWARD L'. SMITH ET AL.

susceptible to switching from one organization to another in the interest of fulfilling their personal and professional goals . The fact that physicians are willing to change affiliations adversely affects compliance with clinical protocols for those physicians who are members of network model managed care organizations . If the guidelines become too obtrusive to medical practice, these network physicians may simply move to another set of relationships with managed care organizations . As Fig . 2 suggests, physicians in staff model managed care organizations are less likely to be influenced by the phenomenon of affiliation change. They have self-selected out of the quest for a frequent change of affiliations in favor of stability . Consequently, they are willing to accept some of the constraints that their managed care organization has established in the way of practice behaviors . They are more likely to follow medical practice guidelines . Short-run Loyalty

Free agents not only display a willingness to change affiliations, but they also possess short-run loyalty to any organization . Free agents are more likely to question what an organization has done for them lately . Physicians still possess tremendous flexibility in where and for whom they practice medicine . Physicians are not indelibly bound to any particular organization . Thus, they can often change affiliations as they choose . The managed care environment has created greater constraints as far as this mobility is concerned, but physicians are still able to consider many geographical settings and types of organizations in their quest for the best practice environment. This freedom adversely affects compliance with medical practice guidelines in both the staff model and network model settings. Willing to change affiliations and with limited loyalty to the present medical care organization, physicians are less likely to comply with what they perceive to be obtrusive medical practice guidelines (especially those that they view as incorrect given their training and experience) . Inequality in Reciprocity

Finally, Fig. 2 indicates that free agents tend to perceive an inequality in reciprocity . Free agents believe that they give more to organizations than they receive from organizations . In the case of physicians, it is predicted that they may perceive they are providing a managed care organization with a unique gift - their medical practice gifts . Yet, the organization hardly reciprocates . Physicians receive remuneration and a setting in which to practice their profession, but this hardly equates with their contribution . Physicians are predicted to view themselves as giving more to a managed care plan than that which the managed care plan gives back to them . Managed care organizations


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establish all sorts of barriers that make it very difficult for them to actually practice medicine. As a result, physicians in network model managed care plans are less likely to comply with medical practice guidelines . In contrast, physicians in staff model practices have already accepted a difference in reciprocity . They have acknowledged that the managed care organization meets several of their needs (e .g . coverage for call after hours, a sound retirement plan, stability in paycheck, etc .) which warrants complying with clinical protocols in order to assist the organization . By helping the organization, physicians in staff model groups are helping themselves .

A RESEARCH AGENDA Physician compliance with medical practice guidelines presents a thorny problem for managed care organizations (Davis, 1996) . Many different sources are responsible for formulating clinical protocols and usually these authorities rely on physicians to create the guidelines. Even though a medical professional society or association may recommend a particular standard, clinical guidelines are often adapted to the local practice setting in order to account for the unique characteristics of that setting including the patient population. With several managed care organizations in any given community requesting physicians to utilize often modified versions of nationally formulated protocols, there is an inevitable confusion among physicians about which guideline to follow . New medical evidence recommends updating the existing guidelines . With these forces in place, it is to be expected that compliance will be difficult to attain . Several strategies have been identified in the medical field for improving compliance despite these constraints . There are a number of issues that can be resolved in the future in order to improve the management of medical practice guidelines in managed care . Following is a research agenda that can guide applied research which may help managed care organizations improve physician compliance with clinical guidelines . A Conceptual Model

Figure 2 presented a conceptual model of factors influencing physician compliance with medical practice guidelines . A fruitful first step in research will focus on testing the contribution of each factor (and interrelational combination of factors) to physician compliance with clinical guidelines . In this regard, research could test the relative contribution to attaining compliance by practice setting characteristics, physician autonomy, status of practice guideline implementation, and new initiatives for practice guideline implementation .

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Which factor(s) is most important in explaining variances in compliance? Where should health care managers address attention, effort and resources in attempts to raise compliance levels? Which factor(s), if any, is beyond the control of health care managers in the ability to shape and influence promising levels of compliance? Are there other factors which have significant influence on physician compliance? How do these factors affect the proposed conceptual model? As the medical field continues to gain experience with clinical practice guidelines and their implementation, do any of the variables in the conceptual model become less important from a managerial perspective? These are a few of the issues about compliance that should be addressed in future research . Management Strategies This review of the literature has surfaced a broad representation of strategies or initiatives that are being tested, and in some cases institutionalized, in the efforts to increase compliance . No single source has integrated these strategies together for consideration by managed care providers. Nonetheless, there is much experimentation and adaptation occurring in practice (Frances, Kahn, Carpenter, Frances & Docherty, 1998 ; Gregory, Cifaldi & Tanner, 1999) . Compliance is a continuing problem that faces managed care plans . As NCQA and other accreditation standards evolve in the health care field, compliance will grow in importance . If managed care plans cannot achieve and document exemplary performance in care delivery, then they may lose accreditation, or at least become less competitive due to a lower quality of care . Medical practice guidelines are designed to achieve basic standards of care which in total lead to managed care and health maintenance . It is imperative that managed care plans attain physician compliance in order to survive and thrive in the competitive environment . As this literature review has suggested, physicians are often not warmly embracing protocols because they infringe on the autonomy of their practices . Thus, health care managers face a difficult predicament when attempting to encourage physicians to comply with a professional expectation where such efforts can often be interpreted as coercion . Paradoxically, if physicians do comply then they not only help to improve the health of their patients, but also the financial health of the organizations which provide physicians with financial support . Research can profitably be directed toward understanding which strategies for compliance have general applicability across medical disciplines, specialties and subspecialties . Are there specialties or subspecialties for which the most promising compliance strategies are ineffective? What are the causal factors that undermine these initiatives? What modifications are required to ensure that


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these constraining factors are minimized? What lessons can be learned from these modifications for improving compliance in other practice settings? In the final analysis, answers to these questions will help to identify the most optimal set of approaches for encouraging physician compliance with clinical protocols . It is unlikely that a single approach to gaining compliance is optimal . More likely a core of common strategies are most conducive to attaining compliance . Research can identify this core of strategies and thereby help to focus health care managers' efforts in modifying compliance strategies to the needs and peculiarities of specific managed care environments . Integrated Guidelines Most studies of medical practice guidelines focus on a single clinical protocol (e .g . diabetes mellitus) or a set of protocols (e .g . preventive care guidelines) . Further research is needed in integrating guidelines within medical specialties and subspecialties . What are the best pathways for achieving comprehensively integrated guidelines? How can health care managers assist physicians in this effort within a managed care setting? What forms of technological support are needed to achieve integration? What resources are needed to support integration and, once achieved, what resources are needed to update and maintain the guidelines? Research on integration can also begin to answer the complex question of duplication and conflicting guidelines . Physicians who practice in network model settings are more likely to receive several sets of guidelines. They are faced with the decision of following one, all, or none of the clinical protocols . Research could be directed to reducing this ambiguity from the system. Health care managers can benefit from evidence-based findings indicating the adverse effects on compliance by mixed messages from competing guidelines . Health care managers can also identify collaborative methodologies that network model managed care plans utilize to reduce redundancy and duplication for physician staff members . Practice Setting Effects The type of practice setting - staff model versus network model - is a powerful variable affecting physician compliance with medical practice guidelines . As Tables 2 and 3 suggest, practice settings can influence the success of guideline implementation and the extent to which physicians view the guidelines as coercive . Research should be undertaken to test the predicted relationships in Tables 2 and 3 as a means for better understanding the effects of staff versus network model impact, and possible strategies for managing this impact . As

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Table 2 predicts, staff model settings are more conducive to supporting guideline compliance due to access via networked computers, processes for updating guidelines, systematic assessments of guideline efficacy, and processes for educating providers . Research should focus on how to achieve similar results in network model settings . Table 2 also predicts that neither staff nor network models are positively associated with incentives for compliance or patient collaboration in implementing guidelines . Are these predicted relationships correct? If so, research should ascertain how to positively influence physician incentives and patient collaboration in managed care settings . Physician Autonomy Table 3 predicts that physician autonomy will influence implementation of medical practice guidelines . Are these predicted relationships functional in practice? Table 3 suggests that staff model practice settings are more likely to mitigate the autonomy of physicians compared to network settings . Research can ascertain whether these relationships are, in fact, functioning . If network models are less likely to overcome physician autonomy as a constraining factor on clinical protocol compliance, additional studies should investigate the appropriate strategies that might be used in network model settings to overcome the adverse effects of free agent behavior by staff physicians . Managing Information Compliance with medical practice guidelines will remain difficult as long as medical research and experience continue to shape standards of care . Physicians are confronted by an incredible explosion of knowledge about medical care that is difficult enough without the complexities of continually revised clinical protocols . Research should examine how to update clinical guidelines and how to best inform physicians when these guidelines have been revised . Health care managers can benefit from studies that analyze how clinical guidelines can be integrated within existing clinical databases so that practice, patient record and clinical protocols are considered simultaneously in a seamless system . Research is also needed in the optimal avenues for including practitioners' input on what they believe to be the appropriate protocols for their unique settings and needs of their patients . The Prospects for Compliance Physician compliance with medical practice protocols is very significant for managed care and all of medical practice . While many forces are reshaping


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medical practice, which makes implementation of clinical protocols a challenge for health care managers, there remains a promising perspective that should not be forgotten. Amid the struggle to standardize care, to raise the quality of medical practice, and to deliver best cost care, medical practice guidelines have evolved as a promising direction and important guiding principle of managed care . The struggle by health care managers to achieve improvements in obtaining physician compliance with these guidelines is worth the effort and cost because in the final analysis the ultimate beneficiaries will be patients and our system of health care delivery .

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MANAGED CARE AND DRUG TREATMENT PRACTICES : A MODEL OF ORGANIZATIONAL RESPONSE TO EXTERNAL INFLUENCE Christy Harris Lemak and Jeffrey A . Alexander ABSTRACT We draw upon and integrate two organizational theory perspectives to develop a conceptual model of how managed care influences the treatment practices of outpatient drug treatment providers . First, using resource dependence theory, we suggest that treatment practices will vary as a function of an organization's dependence on managed care and the scope and stringency of oversight mechanisms used by managed care firms . Second, we apply institutional theory to suggest that the expectations of the professional staff and sources of legitimacy will also directly influence treatment practices. Finally, we draw upon previous integrative frameworks and argue that institutional factors will also indirectly influence treatment by moderating the negative effects of managed care dependence and oversight.

Advances in Health Care Management, Volume 2, pages 131-159 . Copyright ® 2001 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN: 0-7623-0802-8 131

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CHRISTY HARRIS LEMAK AND JEFFREY A . ALEXANDER

INTRODUCTION In response to the high costs associated with substance abuse and mental health services in the United States, there has been rapid growth of managed care in this sector over the past several years . It is estimated that by the end of 1999, the mental health and substance abuse benefits of nearly 177 million people were included in managed behavioral care programs, a 23% increase from the previous year (Findlay, 1999) . In the public sector, nearly every state has implemented managed care programs for mental health and substance abuse conditions (Manderscheid & Henderson, 1995) . There is intense debate regarding the problems and benefits of managed care for substance abuse and mental health care (Institute of Medicine, 1997) . Managed behavioral care programs have the potential to dramatically alter cost, access and quality of mental health and substance abuse treatment practices by influencing the practice patterns of providers (Mechanic, Schlesinger & McAlpine, 1995 ; Wells et al ., 1995 ; Gold et al ., 1995) . Much of the controversy surrounding the spread of managed care in behavioral health stems from the fact that many of the oversight requirements and utilization mechanisms of managed behavioral care specifically target for change those treatment practices commonly associated with effective care (e.g . length of treatment, provision of supplemental services) . Thus, the type and degree of provider response to managed care requirements may be particularly problematic . The central goal of this paper is to develop a conceptual model for understanding the relationships between managed care and outpatient substance abuse treatment (OSAT) organizations . The model suggests that the treatment practices of OSAT organizations are established in response to interdependence with managed care firms, as well as in response to direct and indirect influences of institutional pressures from professional treatment staff and other sources of organizational legitimacy . The proposed model represents an integration of two organizational theory perspectives : resource dependence theory and institutional theory . The paper makes a contribution to the existing research in two ways . First, despite the rapid growth of managed care in the behavioral health sector and the controversy surrounding its potential impact on treatment practices, there is limited understanding of the effects of managed care on drug treatment providers (Institute of Medicine, 1997 ; Beinecke, Goodman & Lockhart, 1997 ; Beinecke & Lockhart, 1998 ; French et al ., 1996 ; Alexander & Lemak, 1997a, b, c) . Most studies of managed care and drug treatment have been largely descriptive and atheoretical . The unique features of addiction and the special characteristics of drug treatment providers call for new conceptual models that may help us

Managed Care and Drug Treatment Practices

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understand the joint relationship between managed care requirements and the organizational practices of treatment providers . Second, the environmental and organizational characteristics of drug treatment organizations present an opportunity to apply and extend organizational theory. Specifically, OSAT organizations are typically small organizations operating within complex environments . Many drug treatment units are highly dependent upon other organizations such as managed care firms, general acute care hospitals and community agencies for client referrals and revenues . At the same time, OSAT units must continuously respond to various advocacy groups, licensing bodies, accreditors and other professional standards involved in specifying appropriate and "best" treatment practices . This complex network of private and public, technical and institutional influences offers an opportunity to apply and integrate institutional theory and resource dependence perspectives . We review the research literature in these areas and develop a conceptual model that melds these two organizational theory perspectives in order to enhance the understanding of how managed care affects drug treatment organizations .

BACKGROUND We begin with a brief description of OSAT organizations and the treatment practices that are most directly linked to client outcomes (duration, intensity, medical and social services) . Next, we present a descriptive profile of managed care in this sector, with an emphasis on the existing empirical research regarding the ways that managed care firms attempt to influence these and other treatment practices . Finally, we present and discuss our proposed conceptual framework . Key Treatment Practices of OSAT Organizations Research supports the general notion that substance abuse treatment can be effective (McLellan et al ., 1997) . It is generally accepted by the scientific community that positive treatment outcomes are strongly associated with : (1) the length of time clients spend in treatment, (2) the intensity of treatment received, and (3) the availability of specialized services for medical and social problems of clients (Institute of Medicine, 1997 ; McLellan et al ., 1997) . Treatment duration is the most important predictor of various post-treatment outcomes, including reduced drug use, fewer arrests, improved employment outcomes and fewer subsequent readmissions . This association holds for clients with a wide range of addiction problems receiving treatment in all substance abuse treatment modalities (McLellan et al ., 1997 ; McKay et al ., 1994 ; Moos, Finney & Cronkite 1990 ; DeLeon, 1984 ; Bell, Richard & Feltz, 1996 ; Ershoff, Radcliffe &

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Gregory, 1996 ; Hoffmann & Miller, 1992 ; Hoffmann et al ., 1989 ; Simpson & Savage, 1980) . Recent studies suggest that the effect of longer treatment on improved post-treatment outcomes is due in large part to the frequency and intensity of treatment, as well as the range of services that clients receive when they have longer treatment stays (Simpson et al ., 1997 ; Hoffman et al ., 1994 ; McLellan et al., 1993 ; Shoptaw et al ., 1994; Simpson et al ., 1995) . There is evidence that more intense treatment improves abstinence in outpatient settings (Campbell et al., 1997) ; improves outcomes for cocaine dependent clients in outpatient treatment (Higgins et al ., 1993) and other modalities (Hoffman et al ., 1994 ; Kang, Kleinman & Woody, 1991) ; and makes methadone maintenance more, effective (Simpson et al ., 1995) . Finally, the quantity and range of treatment services provided within a program, including counseling, physician care, referral for employment, housing and family therapy are important factors in explaining the variability in effectiveness among treatment programs (McLellan et al ., 1997, 30) . Most clients in substance abuse treatment have one or more significant problems in the following areas : medical status, employment and self-support, family relations and psychiatric function (Weisner et al ., 1996) . Studies over the past decade have shown that specialized medical and social services focusing on these addiction-related problems can be effective in improving treatment results (McLellan et al ., 1997) . While there is scientific consensus that the outcomes of outpatient substance abuse treatment are linked to treatment duration, treatment intensity and the availability of medical and social services, considerable variation exists in the approach to and outcomes of treatment across various provider organizations . Much of this variation can be attributed to uncertainty surrounding the interpretation and implementation of these treatment practices . This uncertainty stems from different aspects of the diagnosis and treatment process . First, there is often uncertainty in the diagnosis of addiction disorders, with increased need to obtain complex, sensitive information about potential non-addiction issues that may affect selection of the appropriate treatment program, such as information on multiple drug use, coexisting mental health disorders, patient financial and social surroundings . For example, some clients may start and stop treatment several times before successfully remaining in treatment . In other cases, mental health conditions and social factors such as a lack of family support cannot be immediately determined . These and other complexities make it difficult to identify the most appropriate treatment plan at the time of initial diagnosis . Second, there is a lack of consensus among treatment providers about precise levels of treatment duration or intensity that are most appropriate for diagnosed


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addiction disorders. This may be related to the existence of multiple ideologies and approaches within the substance abuse treatment system (e .g., 12-step versus medical models) (D'Aunno, Sutton & Price, 1991) . It may also be related to the considerable variation in the settings and modalities of treatment that are available, including for example, small independent providers, halfway houses, large outpatient facilities, "intensive" outpatient programs and employee assistance programs. The treatment staff and specific treatment approach may vary across settings, with treatment provided by recovering addicts, certified substance abuse treatment counselors, psychiatrists, Ph .D.-trained psychologists and others . This creates a complex, varied system of care with no single, "best" approach . Profile of Managed Care and Drug Treatment Organizations As drug treatment organizations work to provide appropriate, effective treatment to clients, they must also contend with external influences on organizational operations . In recent years, managed care has played an increasingly important role in the environment of drug treatment providers, with the potential to shape treatment practices and other aspects of care . Managed care for drug treatment and mental health services are typically grouped together and defined as managed behavioral care. Along with its rapid growth in recent years, this industry has become increasingly complex, with public and private programs organized in a variety of forms (Findlay, 1999 ; Jeffrey & Riley 2000 ; Croze 2000 ; SAMHSA 2000) . For example, substance abuse treatment and mental health services often are provided through separate "carve out" arrangements with specialty managed care organizations (Frank & McGuire, 1998 ; Hodgkin, Horgan & Garnick, 1997) . Other organizations, including large employers and state governments, choose to "carve-in" behavioral health care services and develop their own managed care programs and treatment systems, often integrating them with general acute care insurance initiatives (SAMHSA, 2000) . Outpatient substance abuse treatment units represent a central component of the drug abuse delivery system, accounting for nearly 70% of those in treatment (Substance Abuse and Mental Health Services Administration, 1995) . Managed care firms often prefer outpatient treatment services due to lower costs relative to inpatient and residential settings and because outpatient care is often the least restrictive alternative for clients (Institute of Medicine, 1997) . The trend toward outpatient settings has continued in recent years, supported also by the absence of definitive research that indicates that better outcomes are achieved in inpatient versus outpatient settings (McLellan et al ., 1997) . In 1995, about 38% of OSAT units were involved in managed care, with, on average, 46% of their revenues from managed care arrangements (Alexander & Lemak, 1997 ; Alexander et al .,

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CHRISTY HARRIS LEMAK AND JEFFREY A. ALEXANDER

1998). OSAT units are most dependent on private managed care arrangements which constitute 26% of revenues, compared with 12% from Medicaid managed care and 8% from other public managed care programs . OSAT units have an average of 6 .7 contractual managed care arrangements, out of a total 8 .8 arrangements . Further, 12% of OSAT units have no contractual managed care arrangements and 20% have contracts accounting for less than half of all managed care arrangements . On the other hand, 23% of the units report that 100% of their managed care arrangements were contractual (Lemak, 1998) . The most common form of managed care oversight involves limiting the number of visits received by clients . On average, 73% of OSAT managed care clients are subject to some type of visit limits from the managed care firm . Managed care firms also dictate the nature of the utilization review process . Specifically, 34% of OSAT managed care clients were subject to requirements that at least some of the utilization review correspondence be in writing, as compared with telephone calls to the managed care organization . Further, for over 56% of the managed care clients, managed care firms specify that utilization review correspondence must occur with a member of the treatment staff and not with clerical or administrative personnel assigned to such activities (Alexander & Lemak, 1997) . Managed care firms are also involved in the specification of the nature and types of treatment to be reimbursed . On average, managed care firms specify the content of treatment plans for 37% of managed care clients and require follow-up with clients after discharge for 30% of all managed care cases . The use of sanctions was less prevalent among the 1995 NDATSS respondents . Managed care firms disallowed claims after treatment ended for an average 31 % of managed care clients (Alexander & Lemak, 1997) . Finally, the degree of strictness or stringency of the oversight by managed care is often expressed as limits on the numbers of visits that are authorized for payment . There is variation in the number of visits authorized, from a few to several visits. On average, 19% of OSAT managed care clients had no visit limits, 39% had more than 20 visits authorized, 30% had 11-20 visits authorized, 11% had 6-10 visits authorized and 5% of the clients had the most stringent visit limits, with 5 or fewer OSAT visits authorized (Lemak, 1998) . Does Managed Care Target Specific Treatment Practices? It is clear that the role and extent of managed care have increased dramatically in the drug treatment sector in recent years . The mechanisms used to influence and control provider behavior represent an integral element of most managed care programs . Despite its importance, few studies have examined how managed care firms influence, control, or otherwise "manage" drug treatment practices


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(Institute of Medicine, 1997 ; SAMHSA, 2000). We have summarized the empirical research on the oversight practices of managed care firms in the drug treatment sector in Table 1 (found in the Appendix) . These studies represent a foundation of research regarding managed care and substance abuse treatment practices . Several problems, however, characterize this research . First, there are few comprehensive studies that focus specifically on managed care activities and effects in outpatient settings . Thus, there is no clear understanding of how managed care may influence treatment practices in this integral part of the drug treatment delivery system . Second, those studies that focus on the organizational effects of managed care have included either a small number of case studies or a single state managed care initiative . The findings to date may therefore be biased by the specific attributes of a few managed care programs or a single state Medicaid system. Finally and most importantly, the research to date in this area has been largely descriptive, with little conceptual or theoretical foundation . This results in an inadequate conceptualization of how OSAT organizations must handle the potentially competing demands of managed care and multiple sources of organizational legitimacy . Further, the uncertainty surrounding addiction diagnosis, treatment and recovery make potential conflicts between meeting best practices and efforts to control costs or increase efficiency particularly relevant to research in this field. To our knowledge, no existing research has considered how treatment providers simultaneously address institutional pressures (e .g . from accreditors and professional staff) and technical demands (e .g . from managed care firms) . For example, the lack of evidence-based precision regarding levels of treatment duration and intensity may give managed care organizations greater opportunity to reduce care by limiting covered visits more stringently . Alternatively, however, this uncertainty may give treatment professionals more leverage in their attempts to obtain approval for more visits, more intense treatment and other services on behalf of managed care clients . We suggest that, with few exceptions, research on drug treatment organizations has not been driven by theory, with a notable absence of organization theory perspectives . In this paper, we develop a conceptual model that integrates resource dependence theory and institutional theory, thus providing a theoretically grounded framework for future research on the effects of managed care on drug treatment organizations .

CONCEPTUAL MODEL We develop a conceptual model with three components . First, using resource dependence theory, we suggest that treatment duration, treatment intensity and

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the provision of medical and social services will vary as a function of an OSAT unit's dependence on managed care, as well as the scope and stringency of oversight mechanisms used by managed care firms . Second, we apply institutional theory to suggest that the expectations of professional staff and sources of legitimacy will also directly influence treatment practices . Finally, we draw upon previous frameworks that integrate resource dependence and institutional perspectives and argue that institutional factors will also indirectly influence treatment by moderating, or constraining the negative effects of managed care dependence and oversight . This final portion of the model is important because it provides a new way of integrating resource dependence and institutional theory . The model is shown in Fig . 1 and discussed in detail below . Resource Dependence Explanations Resource dependence theory (Aldrich, 1976 ; Pfeffer & Salancik, 1978) is helpful in understanding why and how OSAT organizations respond to managed care firms . Resource dependence theory maintains that, in order to survive, organizations must obtain resources from the environment . When there is a limited or uncertain supply of resources, organizations must find ways to ensure a stable and steady flow of them, including securing resources through transactions with other organizations . In essence, resource dependence theory describes the development and nature of interorganizational power and the way such power affects the activities of organizations (Pfeffer & Salancik, 1978) . Specifically, resource dependence theory has two major components . First, it describes how organizations are constrained by other organizations that control critical resources . Next, it suggests the ways in which organizations respond to external influence . Most studies of resource dependence theory emphasize the latter component and describe activities of organizations to reduce dependence on other organizations in order to acquire increased autonomy (Pfeffer, 1982) . In the next sections, we review the resource dependence literature in order to apply both components of the theory to OSAT organizations and managed care. Organizations that control key resources have power over the structure and behavior of other organizations that depend on those resources for survival (Pfeffer & Salancik, 1978) . This component of resource dependence theory has been researched and empirically supported in different sectors . For example, increased dependence on government funding was found to be associated with organizational pursuit of policies favored by the government, including various human resource policies (Greening & Gray, 1994 ; Pfeffer, 1982) . Also,


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dependence upon various external organizations was predictive of innovation activities in nursing facilities (Banaszak-Holl, Zinn & Mor, 1996), contract management decisions of hospitals (Alexander & Morrisey, 1989), buffering activities of large firms (Meznar & Nigh, 1995), the composition of hospital boards of directors (Pfeffer, 1972), joint venture activities (Pfeffer & Nowak, 1976), nursing home participation in managed care (Zinn et al ., 1999), various organizational structures (Dastmalchian, 1984, 1986 ; Wheeler, Mansfield & Todd, 1980), the strategic orientation of oil industry firms (Little, Li & Simerly, 1995), and, ultimately, the survival of organizations (Sheppard, 1995) . Resource dependence theory offers a way to understand the relative importance of the resource providers of a given organization . In this case, it provides a set of conditions that may explain why some OSAT units are more dependent on managed care than others and therefore, why units alter treatment practices in response to managed care . Few studies have considered the entire set of conditions predicted to explain compliance (Pfeffer, 1982) . In fact, the theory does not suggest how organizations respond when they are faced with multiple external organizations of near equal importance . The second component of resource dependence theory posits that organizations seek to manage uncertainty in their environment in order to achieve greater autonomy . Pfeffer and Salancik (1978) suggest a range of responses that organizations may take when faced with conditions of asymmetrical dependence, including : (1) avoiding influence ; (2) managing and avoiding dependence ; (3) altering organizational interdependence ; and (4) adapting or complying to the demands of key resource providers . Given that OSAT organizations depend on a variety of exchange relationships to secure a steady flow of clients and revenues, they must constantly make decisions regarding organizational structure and treatment practices, including whether and how to respond to managed care organizations' demands . This paper argues that OSAT organizations will choose the latter - adapt and conform to the requirements of managed care firms by changing treatment practices . Organizations may change their structure or behavior to comply with the demands of other organizations in order to secure a stable flow of resources (Pfeffer & Salancik, 1978) . Though they may prefer to remain autonomous, OSAT units may have little choice but to respond to managed care firms. This response - compliance with managed care demands - is of theoretical importance for several reasons . First, most of the theoretical discussion and empirical tests of resource dependence theory focus on the processes by which organizations either : (1) alter the conditions of interdependency ; (2) proactively manage the demands of the environment; or (3) both (Pfeffer, 1982 ; Sheppard, 1995 ; Banaszak-Holl, Zinn & Mor, 1996 ; Alexander & Morrisey, 1989) .


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More specifically, studies have shown that organizations facing dependency have greater board interlocks (Boyd, 1990) ; seek administrative control over resource providers (Dastmalchian, 1984) ; suppress technological developments as a way to increase organizational autonomy (Dunford, 1987) ; and seek a variety of environmental linkages (Gargiulo, 1993 ; Pfeffer, 1972 ; Provan, Beyer & Kruytbosch, 1980) . Very little attention is given to situations in which actions to reduce dependence and alter environmental conditions are not viable alternatives for organizations . There are no studies that describe situations in which organizations are constrained to the extent that strategies that increase organizational autonomy are not feasible . Pfeffer and Salancik discuss the problems of organizational conformance, but do not offer examples of studies of this response (1978) . Compared to many other health services providers such as hospitals, OSAT units are smaller, less differentiated and have a smaller proportion of administrative and clerical staff. These organizations with simple structures may be more vulnerable to the demands of the environment (Flynn, 1993) . For example, Topping and Calloway found that resource scarcity was an overriding factor in the environments of small mental health service organizations in rural communities in the South . The authors specifically identify how these small service providers have few opportunities to proactively plan for and address environmental changes, leading to the development of informal, often ineffective mental health delivery systems in rural areas (Topping & Calloway, 2001) . In general, larger organizations are more likely to have greater degrees of specialization and a larger administrative component (Child, 1972 ; Pugh, Hickson & Hinings, 1969 ; Blau, 1970) . These attributes provide and support a wider range of alternatives, including diversification and environmental influence, that can increase organizational autonomy . Cook and colleagues found support for a theoretical model in which organizations such as hospitals respond to environmental uncertainty along hierarchical, time-ordered sequences or paths (Cook et al ., 1983) . In this model, adaptation occurs at three organizational levels - institutional, managerial and technical - and follows a systematic sequence whereby organizational changes are made first at the institutional level and last when they involve any activity that relinquishes decision control at the technical level . Carter suggests that small organizations have only two levels - managerial and technical and asserts that in small firms the responsibility for interpreting and responding to the environment rests with the manager/owner (Carter, 1990) . This study did not, however, consider how organizations respond when environmental demands deal specifically with attributes of the technical core of the organization .

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CHRISTY HARRIS LEMAK AND JEFFREY A . ALEXANDER Research Propositions from Resource Dependence Theory

Our model applies resource dependence theory in a situation where relatively small and powerless organizations (OSAT facilities) comply with the demands of other important organizations (managed care firms) in their environments . We present the following specific research propositions . First, the importance or essentiality of a resource refers to the organization's need for the resource in order to function, operate, or provide services . This dimension incorporates elements of substitutability and criticality (Jacobs, 1974 ; Aldrich, 1976 ; Pfeffer & Salancik, 1978 ; Provan, Beyer & Kruytbosch, 1980) . In general, resource dependence theory posits that, all else being equal, organizations will respond to the demands for resources that constitute a greater proportion of total organizational inputs or outputs (Pfeffer & Salancik, 1978) . OSAT units depend upon a steady flow of clients and revenues in order to function effectively and survive . When a greater percentage of these resources are under external influence, OSAT providers are more likely to respond to the demands of managed care firms . There is great variation in the extent to which OSAT clients and revenues are covered by managed care arrangements, thus suggesting : Proposition 1 : The percentage of total revenues covered by managed care will be negatively associated with treatment duration, treatment intensity and the provision of medical and social services . Second, Pfeffer and Salancik argue that power accrues to those organizations that have a greater ability to determine the allocation or use of key resources (1978) . There are varying levels of discretion regarding clients and treatment practices among the many types of managed care arrangements held by OSAT units . For example, some managed care arrangements involve contracts, in which specific rules are set regarding client treatment and reimbursement for services . Other managed care arrangements are informal, ad hoc arrangements between an OSAT provider and an insurer that are established when a client initiates treatment. When managed care arrangements are more formalized, managed care firms have more discretion over the allocation and use of clients and funds and thus, treatment providers have less power to resist their demands regarding treatment . We suggest : Proposition 2 : The number of contractual managed care arrangements will be negatively associated with treatment duration, treatment intensity and the provision of medical and social services . Third, the dependence of one organization on another also derives from the concentration of resource control, or the extent to which input or output


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transactions are made by a relatively few, or only one, significant organization (Pfeffer & Salancik, 1978) . The important question is not how many suppliers or purchasers are in the market, but rather, whether the focal organization has access to the resource from additional sources . Dependence on one supplier is less to the extent that alternative sources are available (Cook, 1977) . Greater managed care penetration in the market means that OSAT organizations have fewer, non-managed sources of clients and revenues . We, therefore, suggest: Proposition 3 : The degree of managed care penetration in the market will

be negatively associated with treatment duration, treatment intensity and the provision of medical and social services .

Fourth, as organizations seek to achieve greater control over key environmental resources, they may dictate how other, less powerful, organizations must behave in order to gain access to those resources . Thus, less powerful organizations must conform with externally imposed requirements in order to gain access to resources controlled by more powerful firms . For example, managed care firms use a variety of controls to insure that substance abuse services provided in OSAT units are consistent with their own objectives . These managed care oversight mechanisms typically serve to control access to care and/or regulate the amount, type, or quality of care (Wells et al ., 1995 ; Institute of Medicine, 1989) and can include various forms of utilization review, treatment planning, pre-certification, or limits on the number of visits that may be provided . These oversight requirements represent the management or control of treatment practices away from the actual site of service delivery and, as such, are the mechanisms by which managed care firms influence OSAT providers that are dependent upon them. When the bureaucratic influences of powerful external actors apply to a greater proportion of organizational resources or reach a larger proportion of the activities of the firm, they are more likely to be effective in changing organizational practices . This is because, in situations where external demands are greater in scope, the focal organization is left with a smaller proportion of resources and practices over which they have complete control . In other words, there are fewer opportunities to establish practices that are consistent with their own objectives, rather than those of external actors . Thus, the scope of managed care oversight may be defined as the extent or reach of oversight mechanisms in place at an OSAT organization . There is variation in the degree to which different managed care firms use oversight activities across different treatment providers . In some units, managed care oversight activities may affect only a small proportion of total clients . In other units, however, oversight activities must be dealt with for a large proportion of the client base . When more clients are covered by managed care oversight,

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OSAT units have fewer opportunities to set and maintain treatment practices without external influence . We suggest : Proposition 4 : The scope of managed care oversight will be negatively associated with treatment duration, treatment intensity and the provision of medical and social services . Finally, the stringency of external oversight refers to the strictness or severity of the oversight mechanisms used by key external actors . When powerful external actors place stringent rules and requirements on other organizations, these organizations have fewer alternatives regarding their responses to the requirements . When oversight is less strict, however, the targeted organization has more opportunities to define compliance with demands and, therefore, maintains more autonomy in responding to the external requirements . For example, managed care firms may have limits on the number of visits that are authorized for payment. There is variation, however, in the number of visits authorized, from a few to several visits . When managed care oversight is more stringent, OSAT units are provided with fewer alternatives regarding treatment practices and therefore OSAT units will respond to managed care demands to a greater degree, suggesting : Proposition 5 : The stringency of managed care oversight activities will be negatively associated with treatment duration, treatment intensity and the provision of medical and social services . Institutional Theory Explanations Thus far, this paper suggests how and why outpatient substance abuse treatment processes may be influenced by external demands . OSAT organizations are embedded in "a complex network of state and federal agencies, professional associations and advocacy groups and licensing and funding sources" (D'Aunno & Vaughn, 1995, 38) . In order to survive, treatment providers must obtain the legitimacy and support that comes from conforming to the expectations of these constituents. These external expectations may, therefore, have a strong influence on treatment duration, treatment intensity and medical and social services provided to clients. Further, the uncertain nature of substance abuse treatment means that treatment practices are determined to a great extent by the treatment staff (Hasenfeld, 1992 ; D'Aunno, Sutton & Price, 1991). The treatment staff of OSAT units is often composed of professionals, including those with masters degrees, doctorates, or special training in substance abuse and mental health treatment


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(D'Aunno, 1996) . Individuals who have training and experience as professional treatment providers also manage many OSAT organizations . The staff of OSAT units may, therefore, dictate treatment practices based largely upon their beliefs and the norms and standards of their professional training, affiliation and experience. As managed care firms seek to control the costs of substance abuse treatment; they often impose requirements on substance abuse treatment that may conflict with the norms and standards of professional treatment staff and the expectations of licensure and accreditation bodies . Shore and Beigel noted that the activities of managed behavioral care "pose aggressive challenges to features of the treatment of mental disorders that have been accepted for nearly half a century . . . [including] the definition of mental illness, the nature of professional accountability, the ethics of practitioners, the organization of practice and the allocation of professional resources" (1996, 116) . Institutional theory posits that organizational decisions are influenced by environmental factors, and, that organizations exist within multiple environments (Meyer & Rowan, 1977 ; DiMaggio & Powell, 1983 ; Scott, 1987). Technical environments are those within which a product or service is exchanged . Organizations are rewarded by the technical environment for effective and efficient control of the work process . Within the technical environment, OSAT organizations must be cost-efficient so that they are attractive to potential clients and, most importantly managed care firms . In addition, they must respond to the task contingencies of varied client needs and expectations . These technical environmental pressures may affect organizational decisions about treatment duration, treatment intensity and the medical and social services provided to clients . Institutional environments include the elaboration of rules and requirements to which organizations must conform in order to receive legitimacy and support (Meyer & Rowan, 1977) . The institutional environment or context, therefore, includes a set of understandings and expectations of appropriate organizational form and practice (Tolbert, 1985 ; Zucker, 1987). Organizations responding to the same environmental conditions take on similar characteristics, becoming isomorphic with each other . There are different mechanisms of isomorphic change in organizations, including political, mimetic and coercive pressures (DiMaggio & Powell, 1983 ; Scott, 1987) . Institutional pressures may influence OSAT practices . For example, political influence and government regulations may result in coercive isomorphism among OSAT facilities . Thus, OSAT units may experience pressure from government agencies regarding length of treatment, treatment intensity, or the medical and social services provided for clients . When there is uncertainty in

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the environment, organizations may imitate other successful organizations through mimetic processes . Further, as described above, the power of professions and the taken-for-granted notion of appropriate treatment practices may shape organizations through normative pressures . OSAT units must respond to these institutional forces from accreditation bodies, sponsoring organizations and the professionals as they determine treatment practices . Conforming to institutional environmental rules may be difficult for these organizations, as they face fragmented environments in which multiple groups make uncoordinated, often conflicting demands (Meyer & Rowan, 1977) . Research Propositions from Institutional Theory We suggest the following research propositions from institutional theory . First, the traditional stance of professional substance abuse treatment professionals is to serve as an advocate for the client, arranging for or providing whatever treatment is deemed necessary, without regard to cost (Shore & Beigel, 1996) . For many of these treatment professionals, working with insured clients in a pre-managed care, fee-for-service environment or under well-funded government programs supported this stance . Professional treatment staff, due to their increased education and training may be more aware of the treatment evaluation research that provides evidence that longer, more intense treatment that addresses non-treatment problems with medical and social services can be more effective (McLellan et al ., 1997) . OSAT units with a greater proportion of professional treatment staff are therefore less likely to accommodate managed care demands regarding treatment . We suggest : Proposition 6 : The proportion of total treatment staff who are professionally trained will be positively associated with treatment duration, treatment intensity and the provision of medical and social services . Second, OSAT organizations have a variety of opportunities for licensure and accreditation, including by federal agencies such as the Joint Commission on Accreditation for Health Care Organizations (JCAHO), state mental health and substance abuse treatment agencies, state Medicaid programs and county and local governmental bodies (D'Aunno, 1996) . In general, the expectations of these organizations are developed from treatment evaluation research findings regarding effective treatment practices . We suggest : Proposition 7: The number of licenses and accreditations will be positively associated with treatment duration, treatment intensity and the provision of medical and social services .


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Theoretical Convergence

There is growing interest among organizational theorists to explore the complimentarity of resource dependence and institutional theory (Oliver, 1991 ; Tolbert, 1985) . Generally, both theories acknowledge the role of the wider environment in creating demands and pressures to which organizations must respond if they are to survive. Both theories "emphasize the importance of obtaining legitimacy for the purposes of demonstrating social worthiness and mobilizing resources" (Oliver, 1991, 150) . The theories differ, however, in regard to the nature of organizational response to external pressures . Institutional theory holds that organizations isomorphically conform to societal expectations, while resource dependence argues that organizations exercise a wide range of active choices when confronted with externally-induced demands . Oliver suggests that convergence of the theories allows for the accommodation of "interest-seeking active organizational behavior when organizational responses to institutional pressures are not assumed to be invariably passive and conforming across all institutional conditions" (Oliver, 1991, 146) . In other words, Oliver's integrative framework combines the determinism of institutional theory with the strategic choice of resource dependence . She proposes a model of varying responses to institutional pressures, ranging from passive conformity to proactive manipulation . The nature of organizational response will vary depending on the pressures applied, who is applying them, how they are applied and the nature of the environment in which they occur . Previous research has simultaneously considered resource dependence and institutional influences . Greening and Gray found that institutional and resource dependence explanations are distinct but complementary with regard to issues management. Specifically, they suggest that institutional pressures create a context within which managers exercise discretion, given particular dependencies and other issues (Greening & Gray, 1994) . Goodstein suggests that organizations evaluate the degree to which conformity to institutional pressures enhances or constrains their likelihood of obtaining key resources from the environment . Further, as adoption of certain organizational practices becomes more widespread in an organizational field, expectations for compliance with the practice escalate . Organizations that do not respond to these norms risk their ability to acquire resources and legitimacy, thus reducing their competitive advantage in the marketplace (Goodstein, 1994) . Ingram and Simons concluded that organizations respond in a systematic, calculated manner to institutional pressures regarding work-family issues . Specifically, they demonstrate that strategic response was determined by both institutional pressures and the demands of key external exchange partners

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(Ingram & Simons, 1995) . Using a simpler framework with hypotheses from both resource dependence and institutional theory, Blum, Fields and Goodman found that both perspectives were helpful in understanding the organizational level determinants of the percentage of women in management positions in medium and large private sector firms (Blum, Fields & Goodman, 1994) . Zinn, Weech and Brannon showed that both rational adaptive and institutional factors were associated with Total Quality Management adoption in nursing homes (Zinn, Weech & Brannon, 1998) . Similarly, Sleeper and colleagues found that HMO choice of capitation was linked to both technical and institutional factors (Sleeper et al ., 1998) . Goodrick and Salancik also provide an integrated perspective of resource dependence and institutional theory (Goodrick & Salancik, 1996) . They suggest that organizational interests and dependencies play a role in selecting practices, but in addition to the constraint established by prevailing institutions, rather than as an alternative to them. In' a study of hospital Cesarean birth rates, they found that uncertainty in institutional norms provided discretion for decisionmakers . Their integrative framework suggests three conditions that contribute to "incomplete institutionalization" of practice norms or standards . These conditions include : (1) when the institutions concern goals while the means to achieve the goals are unspecified ; (2) when the knowledge base for practices is not clear cut; and (3) when institutional values themselves are uncertain, such that beliefs about legitimate purposes are in conflict or even contradictory (1996) . Thus, organizational interests interact with institutional uncertainty to produce variations in organizational structures and practices . Thus, one model integrating resource dependence and institutional theory suggested by Oliver (1991) and supported by others (Greening & Gray, 1994; Goodstein, 1994 ; Ingram & Simons, 1995) suggests that organizations make strategic choices among institutional and resource dependence factors in the determination of organizational structures and practices . Alternatively, another integration of the theories (Goodrick & Salancik, 1996) suggests that institutional processes and particularly, uncertainty in the degree to which they are institutionalized, set the bounds or limits in which organizational, or resource dependence, interests may influence organizational structure and practice . Both frameworks underscore the importance of considering both institutional and resource dependence influences on organizational practice . Research Propositions from Integration of the Theories This paper applies and extends the previous integrative perspectives for resource dependence and institutional theories by suggesting that institutional factors not


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only directly influence treatment practices, but also indirectly influence treatment by moderating or constraining the effects of managed care dependence and managed care oversight . The proposed direct influences of institutional factors on OSAT duration were discussed in the previous section . The proposed indirect influences of professional staff and sources of legitimacy are described below . Organizations will be less willing to conform with environmental pressures when these pressures or expectations are not compatible with internal norms and standards . Oliver (1991) suggests that organizations will choose defiance or manipulation strategies when the level of consistency between external demands and the normative standards of internal staff is low . In this paper, the proportion of professional treatment staff is expected to constrain the responses of OSAT units to the demands of managed care firms . Specifically, professional accountability may be challenged by the mechanisms used by managed care firms to influence treatment practices . A defining principle of professionalism is that professionals are held accountable only to their peers (Shore & Beigel, 1996) . Managed care oversight activities such as prior authorization and utilization review may violate this notion . OSAT units with a greater proportion of professional staff are more likely to resist accommodation to managed care demands, thus constraining the negative relationships between managed care and treatment duration, treatment intensity and the provision of medical and social services . Proposition 6a : The greater the proportion of total treatment staff who are professionally trained, the less negative the association between unit dependence on managed care and treatment duration, treatment intensity and the provision of medical and social services . Proposition 6b : The greater the proportion of total treatment staff who are professionally trained, the less negative the association between the scope of managed care oversight and treatment duration, treatment intensity and the provision of medical and social services . Proposition 6c : The greater the proportion of total treatment staff who are professionally trained, the less negative the association between the stringency of managed care oversight and treatment duration, treatment intensity and the provision of medical and social services . Organizations will be more likely to resist external pressures when there is a greater degree of constituent multiplicity (Oliver, 1991) . Organizations must respond to a variety of external laws, regulations and expectations . According to Oliver, "the collective normative order of the environment is not necessarily unitary or coherent : organizations often confront multiple, conflicting pressures

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that bound the ability of organizations to conform" (1991, 162) . The multiple bodies that issue licenses and accreditation place requirements on OSAT organizations with regard to treatment practices . Thus, organizations that obtain licenses and accreditation from more organizations will be more likely to resist managed care demands regarding treatment practices, thus constraining the negative relationships between managed care and treatment duration, treatment intensity and the provision of medical and social services . Proposition 7a : The greater the number of licenses and accreditations, the less negative the association between unit dependence on managed care and treatment duration, treatment intensity and the provision of medical and social services . Proposition 7b : The greater the number of licenses and accreditations, the less negative the association between the scope of managed care oversight and treatment duration, treatment intensity and the provision of medical and social services . Proposition 7c: The greater the number of licenses and accreditations, the less negative the association between the stringency of managed care oversight and treatment duration, treatment intensity and the provision of medical and social services .

CONCLUSIONS The model presented here focuses on organizational compliance with the external demands of key resource providers . The model draws upon resource dependence and institutional theory to suggest that organizations may have distinct responses to institutional and organizational, or resource dependence pressures from the environment . It may therefore help us understand the various ways that organizations may respond . For example, in some cases, organizations may respond isomorphically to normative institutional pressures and in other cases respond to the demands associated with external dependencies with managed care firms, or some combination of these responses . Further, tests of this model will provide an opportunity to examine possible moderating effects of institutional pressures on resource dependence responses . Specifically, institutional pressures may moderate or limit relationships between managed care and treatment practices, through the power of professional treatment staff and sources of organizational legitimacy . In this way, the framework allows for consideration of more complex relationships between


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institutional pressures, the consistency of these norms, the multiplicity of external constituents and the relative dependence of the unit on various external actors . Finally, there are unique attributes of OSAT units that make this application of resource dependence and institutional theory particularly interesting and important . First, OSAT units are relatively small, simple organizations facing conditions of great dependence . Second, OSAT units rely on a variety of sources of clients and revenues and face a variety of potentially conflicting demands regarding their practices. These features provide an interesting and appropriate context to examine how resource dependence and institutional factors independently and jointly influence organizational action . Finally, the uncertain nature of the means (treatment practices) and ends (treatment effectiveness) of OSAT units provides a unique opportunity for a study of external control of organizational action . While such uncertainty suggests variation in treatment practices that may be explained through a conceptual model based in resource dependence and institutional theory, it may also limit the generalizability of study results to other organizations that face similar degrees of uncertainty . Finally, this framework introduces a line of research that specifically considers how compliance (or any external control) is achieved . While the mechanisms of external influence are included in resource dependence theory, they are most often studied by considering characteristics of the management team or governing body of the focal organization . Empirical testing of this model may contribute to the literature by determining whether and how direct behavioral control influences organizational practice. Finally, the current model raises questions about potential systematic variation of dependence and oversight mechanisms, which has not previously been considered in theoretical and health services research models . The model presented here may therefore increase our understanding of how treatment organizations respond to the external influences of managed care . In addition, the conceptual model provides a rich foundation for future research on the effects of managed care on different types of health and human services organizations .

ACKNOWLEDGMENTS An earlier version of this paper was presented at the 1999 Academy of Management Annual Meeting (Health Care Division) . The authors wish to thank Tom D'Aunno and Jane Banaszak-Holl for their helpful suggestions . This research was supported by grants 5R01-DA03272 and 5R01-DA087231 from The National Institute on Drug Abuse .

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THE STRATEGIC IMPORTANCE OF OPEN ACCESS FOR HMOs IN A COMPETITIVE ENVIRONMENT Marjorie L . Icenogle, John E . Gamble, Norman B . Bryan and Daniel A. Rickert ABSTRACT Competition in the managed care industry has intensified as the industry has reached maturity. The current competitive environment of the industry and an increasing industry-wide emphasis on cost containment have resulted in declining profits, lower levels of member satisfaction, and increasing member disenrollment. Many health maintenance organizations (HMOs) have begun to reorient their approach to competitive advantage in the industry by offering their members open access to specialists . HMO executives believe that open access will reduce the degree of differentiation achieved by fee-for-service (FFS) plans and thereby will allow HMOs to attract additional employers and members away from FFS plans and to improve overall member retention . Unfortunately, there is no empirical evidence to support this assumption . This study is the first empirical test of the strategic importance of member autonomy and open access in a

Advances in Health Care Management, Volume 2, pages 161-185 . Copyright C 2001 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN : 0-7623-0802-8 161

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MARJORIE L . ICENOGLE ET AL.

managed care environment . The study expands the model of consumer satisfaction with a health care system proposed by Luft (1981) and tested by Mummalaneni and Gopalakrishna (1997), and incorporates Porter's (1980) theory of competition in mature industries . The model utilized in this study assesses the relative importance of autonomy in selecting specialists (open access), service convenience, value/pricing, and HMO resources on member satisfaction with care and intentions to remain with the HMO. Results show that all four factors significantly influence satisfaction and that subsequently, satisfaction influences intentions to remain enrolled in the plan. In addition, the importance of autonomy is demonstrated by significant direct and indirect paths to intentions to remain in the plan.

INTRODUCTION Since the Health Maintenance Organization Act of 1973 was signed into law, managed care has grown to account for the largest portion of U .S . health care plans. By the end of 1997, 85% of all U .S . employees participating in employer provided health plans were enrolled in managed care plans, with health maintenance organizations (HMOs) accounting for approximately 30% of the market (Bell, 1998) . HMOs originated as an attempt to control rising health care costs, while improving the quality of patients' long-term health . The HMO concept is designed to ensure that every patient has a primary care physician who is responsible for managing all aspects of that patient's care, with a focus on prevention rather than treatment . Mitka (1998) notes that Paul Ellwood, M .D ., an early advocate of managed care and the physician that created the name, "health maintenance organization," claims that during the early years of managed care, power was successfully shifted away from physicians to large group purchasers of medical services. The increased power of purchasers helped reduce the growth of health care expenditures by approximately $500 billion, but failed to meet original expectations for improved quality and competition in the health care industry (Ellwood in Mitka, 1998) . Reinhardt argues that HMOs have become private health care regulators, rather than health maintenance organizations because HMO participants do not remain in plans long enough for the managed care plan to improve patients' long-term health (Mitka, 1998) . Under conditions of short membership duration, it is not economically viable for the HMO to make up-front investments in each new member to minimize long-term health maintenance costs (Mitka, 1998).

The Strategic Importance of Open Access for HMOs in a Competitive Environment

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As the managed care industry reaches maturity, Ellwood's prediction that the industry is in for another power shift in which consumers and patients gain power by exercising their rights to enroll in plans that offer the highest quality and value (Mitka, 1998), is consistent with Porter's (1980) theories of competition in mature industries . Evidence of this shift is seen as the increasing emphasis on cost containment has led members to demand improvements in the quality and breadth of managed care services and has resulted in high disenrollment rates for many managed care plans . Managed care executives identified member retention as the key challenge to the long-term success of managed care plans and believe that the importance of retention will increase as the managed care environment becomes more saturated (Wood, 1998) . Efforts to improve retention have primarily focused on member satisfaction with care based on the assumption that satisfaction translates into intentions to retain membership . Research has shown that members enrolled in managed care plans are consistently less satisfied with certain facets of care than members of fee-for-service (FFS) plans (Mummalanei & Gopalakrishna, 1997) . One of the facets of satisfaction where the greatest variance exists between FFS plans and HMOs is members' access to specialist physicians . HMO executives have begun to recognize that as markets have matured, consumers have greater knowledge of health care issues, have high expectations for medical services, and the desire to select their providers in the same way that they make other important purchases (Gemme, 1997) . As a result, some HMO executives have initiated new strategies to address changes in the competitive environment and buyer preferences . One strategy receiving attention from industry observers is the introduction of open access managed care products that eliminate the HMO gatekeeper function of primary physicians . This strategy is directed toward improving member satisfaction and retention (Halm, Causino & Blumenthal, 1997 ; Klein, 1997 ; Kreier, 1996) . Although it is intuitively appealing to believe that open access will improve satisfaction and retention, this assumption has no empirical support . The purpose of this study is to test this assumption in a field study . Other studies have investigated the factors that influence member satisfaction with health care delivery (e .g . Gabbott & Hogg, 1995 ; Mummalaneni & Gopalakrishna, 1997) ; however, these studies did not include autonomy in selecting health care providers . This paper reports the first phase of a longitudinal study designed for an HMO in the Southeastern U .S . to determine if open access to specialists influences member satisfaction with care and intentions to continue enrollment in the plan . The study tests a model of member satisfaction and intentions to remain in the plan, which includes the exogenous variables of autonomy, HMO resources, convenience, and pricing .

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THEORETICAL FOUNDATIONS Competition in the Health Care Industry HMO legislation of the 1970s resulted, in part, as a strategy to help reduce rising Medicare-related health care costs . The growth of HMOs was limited until the 1980s when U.S . employers faced increases in medical insurance costs that exceeded 10% annually . Consequently, managed care plans gained acceptance and by 1997 their collective market share grew to 85% (Mitka, 1998). As managed care has increased its penetration of the U .S . health care industry, it has entered a mature stage, which presents new competitive challenges (Kertesz, 1997 ; McDonald, 1997 ; Mitka, 1998) . Declining Industry Profitability Porter (1980) suggests that declining industry profitability is consistent with industry maturity . The managed care industry shows signs of maturity as industry margins have declined in recent years . Jacob (1998) notes that in 1994 industry net profit margins averaged 2 .4% with 90% of HMOs achieving profits, but in 1997 the industry average net profit fell to -1 .2% with only 47% of HMOs recording profits . The poor industry profitability was attributed to increased medical costs, rising prescription drug costs, and industry maturity-bred price competition . Medical costs increased by 3% in 1996 and by an estimated 3% to 5% in 1997 while premiums increased by only 0 .5% in 1996 and 2% to 4% in 1997 (Jacob, 1998 ; Katz, 1998) . Some HMOs increased premiums by as much as 9% during 1998, but these increases only modestly bolstered industry profitability, as medical costs and prescription drug costs also grew (Jeffrey, 1999) . Competition in Mature Markets In mature and saturated markets, historical growth rates are more difficult to achieve so managers are likely to aggressively attempt to lure customers away from rival firms (Porter, 1980) . McDonald (1997) suggests that competition in managed care is occurring primarily along two fronts ; managed care plans are striving to entice members away from FFS plans, as well as away from other managed care plans . Porter (1980) cautions that competitive battles for market share in mature markets are accompanied by high cost consequences. He suggests two alternatives that may be more cost-effective than recruiting new members : (a) increasing sales to existing customers, and (b) retaining current customers . The importance of member retention in managed care is widely recognized, especially since disenrollment increases costs and reduces


165

revenue (Wood, 1998) . In addition to the loss of premiums, plans should consider the cost of member acquisition and reacquisition which ranges from half a month's to two months' premiums, and the marketing and sales costs to overcome the negative comments of members who left the plan (Wood, 1998). Expectations of Direct and Indirect Buyers of Healthcare Plans Researchers have consistently recognized that the cost advantage of HMOs continues to be an attractive feature in selecting a health care plan (Luft, 1981 ; Mummalaneni & Gopalakrishna, 1997) . However, as members' experience in a plan continues, other aspects of health care, such as convenience, availability of resources, and access to care become increasingly important to member satisfaction (Kertesz, 1997 ; Luft, 1981 ; Mummalaneri & Gopalakrishna, 1997) . The limitations of some managed care plans, may lead to consumer frustration and provide motivation to look for alternatives that allow more autonomy and fewer restrictions (Gemme, 1997 ; Kertesz, 1997) . HMO members are the consumers of healthcare services but because of their indirect buyer status they have little direct leverage over managed care organizations (MCOs) (Porter, 1980 ; Savage, Campbell, Patman & Nunnelley, 2000) . A change in employment may be an individual's only approach to changing health plans other than to express their dissatisfaction with their healthcare coverage to their employer. Until very recently most employers placed little weight on employee satisfaction with healthcare coverage in selecting a health plan since a change in employment would typically be viewed by most employees as a high switching cost from one health plan to another. However, as the job market has tightened employers are beginning to modify a variety of management practices, including compensation and benefits, to retain their employees . Even though cost is still a major consideration, more employers are considering such "responsible purchasing" criteria as geographic coverage and member satisfaction when selecting a health plan (Lo Sasso, Perloff, Schied & Murphy, 1999) . Private employers and federal, state, and local governments are the direct buyers of services provided by MCOs, and unlike their employees, employers have very low switching costs from one health plan to another (Savage et al ., 2000) . As a result of their low switching costs and volume purchases, employers have considerable leverage in negotiating with MCOs (Porter, 1980) . Klein (1997) notes that not only do employers recognize that employees prefer health plans that offer greater choice, but many employers have begun to find that HMO gatekeeping restrictions forces employees to miss more time at work because of the need for multiple office visits for a single illness .

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MARJORIE L . ICENOGLE ET AL .

Relationship Between Cost and Access As increasing competition squeezes industry profit margins and buyers begin to exert greater leverage on sellers, managers must address the opposing challenges of reducing overall costs and adding differentiating features to lure demanding buyers . These contradictory objectives have led some HMO managers to choose between two strategies. One strategy involves reducing costs by restricting access to health services and limiting referrals to specialists . Kertesz (1997) found that HMO members in mature managed care markets reported declining levels of satisfaction and a reduced likelihood of continuing enrollment in the plans due to restricted access (Kertesz, 1997) . Other approaches aim to increase retention by utilizing strategies designed to improve member orientation programs, improve access to health and administrative information, or improve access to preferred primary providers and specialists (Wood, 1998) . All of these strategies are based on the assumption that overall satisfaction with health care leads to intentions to retain membership in the health plan. In order to develop a model that will adequately test these assumptions, previous studies of member satisfaction are reviewed in the following section . Studies Examining Member Satisfaction One of the first comprehensive efforts to identify the dimensions of patient satisfaction with medical services was conducted by Ware, Snyder, Wright and Davis (1983) . Their research ultimately identified six widely accepted dimensions of patient satisfaction : availability of resources, access to care, costs, continuity of care, interpersonal manner of the care provider, and the technical quality of care . Subsequent studies have included these dimensions . A recent study by Mummalaneni and Gopalakrishna (1997) presented what they believe to be the main elements of a model of consumer satisfaction with a health care system, based on Ware et al. (1983) . Their model proposed that satisfaction is influenced by consumer costs, access to health care, and abundance of resources in the delivery system . The analysis compared the satisfaction levels of members enrolled in fee-for-service (FFS) plans to members enrolled in HMOs to show that FFS consumers have higher satisfaction ratings than managed care consumers on a variety of satisfaction indicators . They also utilized regression analysis on the entire sample of FFS and HMO members, in which the independent variables were comprised of several single items and three scales and the dependent measure was satisfaction with care . Although the regression analysis presented interesting results, their analysis did

The Strategic Importance of Open Accessfor HMOs in a Competitive Environment

167

not include a structural analysis of the causal relationships among all the constructs in the model . Satisfaction with HMO Resources The availability of HMO resources such as hospitals, medical specialists, and family practitioners has been shown to be related to overall satisfaction with health care (Mummalaneni & Gopalakrishna, 1997 ; Ware et al., 1983) . Mummalaneni and Gopalakrisha (1997) found that the availability of family doctors and availability of medical specialists, were both significant predictors of overall satisfaction with health care coverage . Satisfaction with Cost to Consumer The cost of health care coverage has been suggested to be associated with overall satisfaction of care in managed care plans (Kertesz, 1997 ; Luft, 1981 ; Mummalaneni & Gopalakrishna, 1997) . Mummalaneni and Gopalakrishna (1997) and Kertesz (1997) agreed that HMO consumers were significantly more satisfied with cost of medical care than FFS consumers . Mummalaneni and Gopalakrishna (1997) also found that for members of both FFS plans and HMOs, the cost of the plan to the member was significantly related to overall satisfaction with health care . Satisfaction with Access to HMO Resources Mummalaneni and Gopalakrishna (1997) noted that it has been argued that access-related factors are associated with overall satisfaction with health care coverage . Their study found that the following variables are significantly related to overall satisfaction of the health care plan : satisfaction with .office hours, availability of emergency care, waiting time at medical offices, and the convenience of medical care . FFS and HMO consumers did not hold significantly different satisfaction levels with all access-related variables with the exception of waiting times, parking facilities, and convenience of medical care, with HMO consumers having significantly greater satisfaction with waiting times and FFS consumers having significantly greater satisfaction with the parking and convenience . Autonomy in Selecting Providers The role of patient autonomy in selecting health care providers has not been empirically evaluated, but has been suggested to have an important role in improving the overall satisfaction of HMO members . Jones (1997) argues that health care consumers' levels of self-sufficiency and empowerment in selecting a health care plan contribute to overall satisfaction with their health care

168


coverage, and that access to health plan providers is a third key facet of satisfaction. He cautions that none of these three components of HMO satisfaction are typically included in managed care satisfaction instruments . The managed care gatekeeper approach which limits member access to specialists is viewed unattractively by HMO members, physicians, and paying employers (Halm, et al ., 1997 ; Klein, 1997) . Klein (1997) notes that many employers that contract with HMOs to provide health care coverage for their employees have found that gatekeeping forces employees to miss more time at work because of the need for multiple office visits for a single illness . Also, Klein (1997) notes that under the best case scenario, the gatekeeper process is viewed neutrally by consumers and employers, but when the gatekeeper process becomes inefficient, consumer and payer satisfaction declines . Increasingly HMOs are considering allowing open access to specialists to satisfy the demands of consumers . Open access reportedly benefits all involved parties . The primary care physician saves time and effort in completing referral paperwork and the HMO saves administrative costs in enforcing that referrals are obtained (Halm, et al ., 1997) . The patient saves time by making only one visit directly to the specialist, and the employer gains productivity because employees do not have to miss work for the referral visit to the primary care physician (Klein, 1997) . The increased convenience and freedom of choice for members is assumed to increase satisfaction of care and intentions to remain enrolled in the health care plan (Jones, 1997 ; Kreier, 1996) . Relationship Between Satisfaction and Intention The view that member satisfaction and member retention are linked is consistent with Cronin and Taylor (1992) who found that consumer satisfaction has a significant effect on purchase intentions . This view is supported by Klein (1997) who observed that member and employer dissatisfaction tends to precede disenrollment. Jones (1997) posits that dissatisfied HMO customers will be motivated to change plans and that stable HMO membership is necessary for the long-term viability of the managed care plan . Wood (1998) disagrees that satisfaction and retention are close correlates by pointing to industry statistics that reflect that some managed care plans achieve high average satisfaction ratings, but still suffer from high member attrition rates . However, Wood (1998) agrees that member retention is critical to an HMO's success because of lost premiums, high member enrollment costs that range between one and two months premiums, and administrative costs of disenrollment such as copying or transferring records .


169

Proposed Model

Based on the previous studies of member satisfaction and observations of the managed care industry's competitive environment, the following model is proposed to measure members' satisfaction with care and intentions to remain in the HMO health plan. This model is adapted from the model presented by Mummalaneni and Gopalakrishna (1998) who suggested that customer satisfaction studies should focus on administrative variables over which the health care plan has some control, rather than uncontrollable factors such as a physician's interpersonal skills . It is proposed that members' overall satisfaction with health care is influenced by members' perceptions of autonomy in selecting providers, fairness of the health care plan's pricing, adequacy of HMO resources, and convenience of care . Given that observers suggest that member dissatisfaction precedes disenrollment (Klein, 1997), and that satisfaction has been shown to affect purchase intentions (Cronin & Taylor, 1992), the model proposes that high levels of satisfaction with care will influence decisions to remain in the HMO . The proposed model is shown in Fig . 1 .

Fig. 1 .

Proposed Path Model of the Facets of HMO Member Satisfaction with Care and Intentions to Remain in the Managed Care Plan .

170


METHODOLOGY Procedures The health plan organization in the study has approximately 90,000 members in two southern states and offers multiple product offerings . The managers were interested in conducting an open access pilot program to determine if open access to specialists would increase member satisfaction with care and improve retention . Since the purpose of this study was to establish benchmark measures of the importance of open access on overall plan satisfaction, this study was completed before the change to open access was announced to the members . The results of the initial study have established baseline measures for members' perceptions of overall satisfaction with the plan, intentions to remain in the plan, satisfaction with the HMO's resources, satisfaction with pricing, convenience, and autonomy in selecting providers . The HMO identified one employer, a regional university, as the test site for open access . The university, which has 4,100 employees enrolled in the HMO, employs 2,400 in association with the university and employs 2,500 at four teaching hospitals in a single metropolitan area . Data were collected using telephone interviews in which the interviewers recorded the responses in a computer database as the interviews were conducted . The population dataset included all the employees of the organization who were enrolled in the HMO. A computer program that automatically dialed phone numbers from the population dataset randomly selected subjects . The interviewer asked to speak with the employee (member) . When the employee answered, the interviewer informed the member that she was conducting a survey about the HMO health plan and would like to ask a few questions about the member's satisfaction with his health care coverage . Members were told that their participation was voluntary and that their responses would be confidential, unless the member requested that his name be included with the responses . Respondents were also informed that they could refuse to answer any question . Members who stopped the interview before completing the entire questionnaire were dropped from the study . Sample The researchers followed Bollen's (1989) recommended sample size of at least five observations for each free parameter . This rule of thumb suggests a minimum sample size of 260 (52 parameters x 5 respondents per parameter = 260 respondents) . In order to ensure adequate sample size, given the


171

possibility of missing values, the researchers set the minimum number of responses at 400. Interviewers continued to call members until 400 completed response sets were obtained . Because several interviewers were calling members simultaneously, completed response sets were recorded for 404 members . To obtain 404 response sets, 2,756 calls were placed. Six hundred thirty-six members refused to participate . The remainder of the calls that did not result in a response set included : no answer (n = 808), busy (n = 34), wrong numbers (n = 140), lines not in service (n = 408), answering machines (n = 235), call answered by computer modem or fax (n = 68), and ineligible members (n = 23) . Twenty-eight of the respondents were eliminated from the sample because they answered one or more questions in the measurement model with "I refuse to answer." The median age of respondents was 43 .35% and 69% were female . Respondents were employed in the following areas : 35% by the university (12% faculty, 4% administration, 19% staff), 47% were employed by the university's hospitals (35% medical staff and 12% non-medical staff), and 14 .5% were employed by the College of Medicine (6 .2% faculty and 8 .3% staff) . Measures The study conducted by Mummalaneni and Gopalakrishna (1997) provided the basis for the items which measure the following four factors : convenience, price, availability of resources, and overall satisfaction . These items were adapted from the Patient Satisfaction Questionnaire (PSQ) originally developed by Ware et al . (1983) . All of the items in the measurement model used a five-point, five-anchor Likert-type response format with anchors ranging from strongly agree to strongly disagree . The items developed or adapted for the model in this study are listed in Table 1 . The questionnaire also contained the following demographic items : age, gender, and employment classification . Convenience of Care Mummalaneni and Gopalakrishna (1997) identified five aspects of convenience which are important to health care : location, emergency care, providers' office hours, parking facilities, and waiting time at the place of care ; however, based on the PSQ, they labeled this factor "access ." Gabbott and Hogg (1995) distinguished between two components of accessibility : physical accessibility and treatment accessibility . For clarification, we chose to label the physical accessibility factor "convenience" because the items in this scale measure the convenience of physical access . The survey included five convenience items : availability of emergency care, convenient locations, convenient office hours

172

MARJORIE L . ICENOGLE ET AL. Table 1 . Scale Items Used to Measure the Constructs Included in the Model of HMO Customer Satisfaction and Customer Retention .

Customer Autonomy Autonomyl Autonomy2 Autonomy3 Autonomy4

Under the _ health plan, I have significant freedom in selecting my primary physician When my primary care physician decides I need to see a specialist, I can decide on my own which specialist to visit. I have considerable independence in selecting specialists when I have a specific health problem. Under the health plan it is easy for me to obtain care from physicians outside the plan's network .

Availability of Resources Resources I Resources2 Resources3 Resources4 Resources5 Resources6

There are enough family doctors in the health plan network . There is a shortage of family doctors in the - health plan network.(R) There are enough specialist doctors in the - health plan network . There is a shortage of specialist doctors in the health plan network .(R) There are enough hospitals in the _ health plan network . More hospitals are needed in the _ health plan network .(R)

Satisfaction with Pricing Pricing 1 Pricing2 Pricing3 Pricing4

The The The The

monthly fee charged by the _ health plan is fair . amount I am charged for my - health plan coverage is reasonable. co-pay charged by the _ health plan for office visits is fair . co-pay charged by the _ health plan for prescriptions is fair .

Convenience of Care Convenience1 With - health plan, it is easy to get medical care quickly in a medical emergency. Convenience2 My primary physician has office hours that are convenient for me . Convenience3 The specialists I see have office hours that are convenient for me. Convenience4 Places where you can get medical care under the - health plan are conveniently located . Convenience5 I am usually kept waiting a long time when I am at the doctor's office .(R) Overall Customer Satisfaction Overall Satl Overall Sat2 Overall Sat3 Overall Sat4

I am satisfied with the medical care I receive through the _ health plan . I am fully satisfied with the care I receive from the doctors in the _ health plan . Given the monthly fees that I pay for coverage, I am satisfied with the medical care I receive under the _ health plan . There are things about the medical care I receive under the health plan that could be greatly improved.(R)


Table] .

173

Continued .

Intention to Remain Remain1 Remain2 Remain3 Remain4 Remain5

If - offered additional health care plans, I would consider switching my health coverage to another plan .(R) I would change my health insurance provider if it were possible .(R) I am not interested in looking for coverage with another health insurance plan . I would consider changing employers to obtain better health care coverage.(R) I intend to look for another health insurance plan within the next six months .(R)

(R) Indicates reversed scored item .

for physicians, and specialists, and one item to measure waiting time in the primary physician's office . The parking convenience item included in the Mummalaneni and Gopalakrishna study was not included, because all of the hospitals in the geographical area of the study have adequate parking that is free to patients and visitors . Availability of Resources Based on items included in the PSQ, six items were adapted to measure satisfaction with resources, two each to measure the availability of primary physicians, the availability of specialists and the adequacy of the number of hospitals . Fairness of Pricing Researchers have consistently recognized that the cost advantage of HMOs continues to be a most attractive feature in selecting a health care plan (Luft, 1981 ; Mummalaneni & Gopalakrishna, 1997) . Therefore, the cost of premiums and co-payments are both likely to be important to overall HMO satisfaction . The questionnaire contained four items to measure fairness of pricing ; two items measure fairness of monthly premiums and one item measures fairness of co-payments for office visits and another measures fairness of co-payments for prescriptions . Autonomy in Selecting Providers The gatekeeper concept in HMOs ensures that the primary care physician is responsible for granting access to specialized medical treatment . In order to measure the importance of autonomy in selecting providers, four items were developed following the format of the self-determination items developed by Spreitzer (1995) . Two items measure autonomy in selecting a primary physician, while two items measure autonomy in selecting specialists .

174


Overall Member Satisfaction with Care Three of the four items measuring overall satisfaction the health care received were adapted from Mummalaneni & Gopalakrishna (1997) . One additional item was created for this study, "Given the monthly fees that I pay for coverage, I am satisfied with the medical care I receive under the - health plan ." Intentions to Remain in the Health Plan Five items were developed to measure intentions to remain in the health plan. These items were patterned after items measuring employee intentions to leave their current employers (Aquino, Griffeth, Allen & Horn, 1997) . Data Analysis The responses were subjected to various analytic procedures, including the calculation of means and standards deviations and the determination of skewness and kurtosis . In order to assess participation bias, the demographic characteristics of the sample were compared to the demographic characteristics of the population . Analysis revealed that the sample characteristics matched the characteristics of the HMO members of this employer . To ensure that the items measured the intended constructs, the items analyzed in the subsequent measurement model were subjected to a principal components analysis with a promax rotation to facilitate interpretation of the factors (SAS Institute, Inc ., 1985) . From the exploratory principal components analysis, scales were developed and then the internal consistency of the scales was assessed using Cronbach's alpha. Data were entered into PRELIS 2 prior to input into a structural equations program (LISREL 8) . PRELIS computed the covariance matrix used in the subsequent structural equation analyses and examination of the results from the PRELIS analyses suggests that problematic levels of skewness and kurtosis are not present in the data . Both the measurement and structural aspects of the model were assessed before and during the analyses to ensure the model's identification . Structural models that are identified have a unique solution for the parameters in the model (Bollen, 1989) . Global identification was assured with a combination of identification rules, namely the t-rule, which is a necessary but not a sufficient condition for identification, and the two-indicator rule which is a sufficient, but not a necessary condition for identification . All of the constructs had three or more manifest indicators except price/value, which had two indicators . Local identification was assured with the calculation of the inverse of the information matrix . Thus, the model under consideration is assumed to be identified.


175

A two-step procedure suggested by Anderson and Gerbing (1988) was used to assess the hypothesized model (see Fig . 1) . The two-step procedure ensured that the latent measures of the hypothesized model were theoretically and statistically acceptable prior to assessing the structural relationship among these latent constructs . First, the measurement model was assessed to determine the viability of the factor structure of the six latent constructs . Fit statistics such as global, incremental (i .e . incremental type 2 and 3 fit statistics), and residual type fit statistics suggest that the measurement model for this research is acceptable for subsequent structural analyses (GFI = 0 .92, NNFI = 0 .92, CFI = 0.92, RMSEA = 0 .05, RMR = 0 .04) . Next, a series of nested models was tested to determine the viability of the structural relations of the hypothesized model . First, the saturated model was compared to the hypothesized model by examining the relative fit indices and incremental indices . Next, the modification indices were examined to revise the hypothesized model, after which the relative fit indices and incremental indices of the revised model were compared to the hypothesized model . Results The means, standard deviations, and covariances of the items included in the structural equation analyses are reported in Table 2 . The principal components analysis resulted in six factors, with each factor representing the constructs in the proposed model ; however, only 19 of the 28 items had significant loadings on only one factor. The other nine items either had no significant loading on any factor (minimum loading of 0.50 required) or had high cross factor loadings and were consequently eliminated from the study . The two items measuring the adequacy of the number of hospitals did not load on the availability of resources scale . The two items measuring fairness of the co-payments did not load on the pricing factor. In the convenience scale, the items measuring convenience of locations and the item measuring waiting time in the doctor's office did not have significant loadings . The fourth item in the satisfaction with care scale, "There are things about the medical care I receive under the - health plan that could be greatly improved," was removed due to an insignificant loading. Two of the items in the intention to remain scale were eliminated : (a) "I would consider changing employers to obtain better health care coverage ;" , and (b) " I intend to look for another health insurance plan within the next six months ." Table 3 presents the item loadings computed from the principal components analysis, with a promax rotation on the 19 variables of interest . Results support the suspected factor groupings for the 19 items, with the six factors representing approximately 65% of the variance . Cronbach's alpha coefficients for each of

176


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The Strategic Importance of Open Access for HMOs in a Competitive Environment Table 3 . 1 Resources 1 Resources2 Resources4 Resources3 Autonomy3 Autonomy2 Autonomy l Autonomy4 Overall Satl Overall Sat2 Overall Sat3 Pricing2 Pricing) Remain) Remain2 Remain3 Access3 Access4 Access) Cronbach's Coefficient Alpha

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Factor Analytic Results .

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the subsequent scales used in this analysis are also reported in Table 3 . All scales had an alpha reliability of 0.70 or higher with the exception of one, convenience of care, which had a reliability of 0 .62 . The structural analysis, like the measurement model analysis, was conducted using the maximum likelihood estimation procedure. The standardized solution for the final revised model is displayed in Table 5 . The models were assessed by both absolute and incremental fit measures, in addition to reviewing error terms and the standardized residuals of the fitted covariance matrix . The results of the error term and standardized residual analyses are mixed, but overall the analyses are positive and encouraging. There were no negative error terms ; however, there were a small number of standardized residuals greater than 2 .58. The median standardize residual was 0 .00, but the fitted covariance matrix underestimated the covariance of Q3 (There are enough family doctors in the Health Plan network .) and Q18 (There are enough specialist doctors in the Health Plan network .) (9 .93) ; the covariance of Q18 and Q23 (There is a shortage of specialist doctors in the Health Plan network.) (7 .44) ; and the covariance of Q20 (The amount that I am charged for my Health Plan coverage is reasonable .) and Q33 (Given the monthly fees that I pay for

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Table 5 . Standardized Solution of Revised Model . Lambda Y Q27 Q32 Q33 Q9 Q28 Q29 Lambda X Q2 Q14 Q16 Q17 Q3 Q13 Q18 Q23 Q6 Q20 Q4 Q25 Q26

Satisfy 0 .74 0.60 0.59

Autonomy 0.70 0.65 0 .58 0 .76

Intent

0 .63 0 .80 0.65 Resource

0.67 0.63 0.71 0.69

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0 .17

0 .24

coverage, I am satisfied with the medical care I receive under the Health Plan .) (6 .08). Similarly the fitted covariance matrix overestimated the relationship between Q18 and Q13 (There is a shortage of family doctors in the Health Plan network.) (-5 .26) ; Q6 (The monthly fee charged by the Health Plan is fair.) and Q33 (-4 .45) ; and Q3 and Q13 (-4 .44) . From this analysis it appears that the manifest indicators posing the greatest problems are Q13, Q18, and Q33 . Therefore, subsequent analyses in the second phase of this research will determine if these relationships are the result of sampling fluctuations or perhaps non-linear relationships among the variables, or both . Results of the structural analysis suggest that the saturated model fit the data better than the hypothesized model (0X 2 = 33, df = 4, p < 0.05) . Although the

180


fit statistics appear to be very close for the two models, two fit statistics compel acceptance of the saturated model as the preferred model . For the hypothesized model (see Fig. 1) Hoelter's (1983) Critical N (CN) falls below 200 (CN = 196) and the Expected Cross-Validation Index (ECVI) is higher (1 .20 versus 1 .13) . Given that the present research is mainly exploratory (see Joreskog & Sorbom, 1993 for a brief discussion on the acceptability of using structural equation methodology in an exploratory mode), the modification indices were consulted, which suggested freeing a path from autonomy to intention to remain. The rational for freeing this path is supported in the discussion section of the paper. The revised model is shown in Fig . 2 . The nested tests of the revised model with the saturated and hypothesized models (see Table 4) reveal that the revised model does differ from and fits the data better than the hypothesized model, but does not differ from the saturated model . However, the revised model is preferred over the saturated model mainly due to its parsimony (saturated model PNFI = 0 .69, revised model PNFI = 0.71) and the lack of theoretical justification for the saturated model. Various fit statistics (e .g . NNFI = 0 .90, CFI = 0.92, IFI = 0.92, RMR = 0.04) attest the adequacy of fit of the revised model to the data . The revised model shown in Fig . 2 shows the relationships among the structural variables . The maximum likelihood parameter estimates, which are reported for

* p < 0 .05 ** p 00 - C AO 0)

J N o bq b y .. > v

b N

yz

~~ a ~o

--N

en

ub~

•

10

U~

H) W) V \O r 00 01 O .~

•

g ro o O U 0 Q cLC

JULLET A . DAVIS ET AL.

302

the robustness of the Medicaid model, a separate model substitutes the percent of private payor residents as the dependent variable . Given that attracting private payor residents may require different strategies, we expect to find opposite results between the Medicaid and private payor models .

RESULTS Medicaid by Strategy and Structure Preliminary analysis supports the presence of an interactive relationship between strategy and structure . A cross tabulation of the average percent of Medicaid residents by each strategy and structure index substantiates the presence of an interaction between the two constructs . The dependent variable clearly varies by the level of the independent variables . Therefore, for this data, an interaction is present if the effect of strategy on the percent of Medicaid residents varies by the structure variables . Table 3 shows the mean number of Medicaid residents by strategy and structure . The results of the strategy only model (Table 4) show a significant and negative relationship between a domain-offensive strategy and the proportion of Medicaid residents in the facility . This finding supports the hypothesis that as a facility becomes more domain-offensive, performance improves . This finding suggests that as the facility offers more services and engages in activities that generally cost more, it is more likely to attract non-Medicaid clients . Several of the control variables - profit status, total facility beds, the Medicare market share, nursing home concentration, and the per capita unemployment rate - were also significant. The second hypothesis states that the interaction of strategy with the decentralization index and the knowledge-enhancing index would be negatively related to the proportion of Medicaid residents . Table 5 shows the results of the Table 3.

Percent Medicaid by Dichotomized Strategy and Structure Variables . Range

0-1

Strategy

2-5

Decentralization Index

5-11 12-18

69.63 71 .39

64.20 62.14

Knowledge Enhancing Index

3-10 11-23

70.23 70.68

63 .41 62.74

Strategy, Structure and Performance in Nursing Facilities

Table

303

4. Model 1 : Strategy Only .

Variable

B

Constant Strategy Index (Domain Offensive) Profit Status Medicaid per diem reimbursement rate Log of the total facility beds Log of the county level Medicare market share Log of the nursing home bed concentration within the county 1992 per capita income 1992 unemployment rate

25 .878* -3 .242*** 6 .085* 0.059 5 .557* -7.025*** 8.601*** 0 .000 1 .711*

Standard Error 11 .422 0.946 2.510 0 .052 2 .414 1 .551 1 .908 0.000 0 .665

Rz = 0 .243 Adjusted R2 = 0.214 ***p

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