Textbook of Rapid Response Systems: Concept and Implementation

Textbook of Rapid Response Systems

Michael A. DeVita    Ken Hillman Rinaldo Bellomo ●

Editors

Textbook of Rapid Response Systems Concept and Implementation

Editors Michael A. DeVita, MD Professor, Critical Care Medicine University of Pittsburgh School of Medicine Department of Critical Medicine Pittsburgh, PA USA Rinaldo Bellomo, MD Chair, Australian and New Zealand Intensive Care Research Centre Professor, Faculty of Medicine University of Melbourne Honorary Professor, Faculty of Medicine Monash University Honorary Professor, Faculty of Medicine The University of Sydney Honorary Principal Research Fellow Howard Florey Institute University of Melbourne Director of Intensive Care Research Staff Specialist in Intensie Care Department of Intensive Care Austin Hospital Melbourne, Australia

Ken Hillman, MBBS, MD, FRCA (Eng), FCICM Professor of Intensive Care Director of the Simpson Centre for Health System Research The University of New South Wales The Australian Institute of Health Innovation The University of New South Wales Liverpool, Australia

ISBN 978-0-387-92852-4 e-ISBN 978-0-387-92853-1 DOI 10.1007/978-0-387-92853-1 Springer New York Dordrecht Heidelberg London © Springer Science+Business Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

To my wife Sharon, and my children Lizzie, Chris, Tim, and Annie who are my life, and to my parents for challenging me and preparing me to achieve. I am indebted to my teachers, Dennis Greenbaum, Jim Snyder, Ake Grenvik, and Richard Simmons, who have taught me what critical care excellence is. MAD To Sue Williams, a loyal and committed colleague of 20 years. KH To the many patients who have suffered and suffer because of an outdated approach to acute hospital care. May this book help make their time in hospital safer. RB

Preface

When we created the Manual of Medical Emergency Teams (MET), Implementation and Outcome Measurement, the concept was relatively new. The term MET was not well recognized and had different meanings to different people. The Institute for Healthcare Improvement (IHI) was just starting to promote the same process using different terminology: the Rapid Response Team (RRT). We created our manual to provide readers with the tools to create teams of their own, and with the resources needed to measurably succeed. Since then, even though it was a mere four years ago, much has happened. Two consensus conferences have been held. The first defined the terminology and the process better. At that meeting, it was recognized for the first time that the intervention is much more than a team. It is a system, the Rapid Response System (RRS), and it has four components, without which the team is unlikely to succeed. A unifying set of terms was created, and a lexicon for describing interventions and reporting outcomes was proposed and is now being utilized more frequently. The aim was to promote the ability to compare interventions between organizations and more accurately analyze results. We assumed that it is possible that an intervention that has nursing responders might have different results than interventions that have physician responders. Differing support structures in the administrative or quality improvement limbs might also impact outcomes. The ability to compare, we believed, was essential to understanding the influence of various components of the system and would enable improvement and growth internationally. At the second consensus conference, which was focused on defining and improving the ability to detect crises outside of the critical care setting (that is, the “afferent limb”), the need for monitoring was explored and a classification system was proposed. Participants recognized the differences between continuous and intermittent monitoring in terms of costs, equipment, and capabilities. Two major purposes of monitoring (continuous or intermittent) were recognized. First, it enables prognostic risk stratification. There is now ample data to show that those with abnormal vital signs are more likely to suffer a serious or lethal event. This risk stratification can facilitate the ability to move patients to a level of staffing and equipment to promote safety. Of course, these prognostic systems are not ­perfect. Patients are identified who in fact do not have an event, while others who will have an event are not recognized. As a consequence, many at the conference promoted vii

viii

Preface

the second function of a monitoring system, the ability to detect critical deteriorations as they occur. This function, of course, requires a continuous monitoring system. Such a system costs more, but it may reduce unexpected mortality and morbidity in hospitalized patients. Future studies will clarify the cost and the benefit of the two approaches. We hope our textbook clearly recounts the issues involved and promotes needed investigations. A second major event that has transpired is the addition by The Joint Commission for the Accreditation of Healthcare Organizations (JCAHO) in North America of a patient safety goal that includes the principles of the Rapid Response System. Healthcare providers must have the capability to detect patients with sudden clinical deterioration and a system in place to rapidly respond to the patient’s needs. These days, most hospitals in the United States have some sort of RRS, with some teams being nurse-led (RRT), and others physician-led (MET). Still others did not create a new team but “hot-wired” existing systems to promote the goal. The use of the RRS is spreading in Europe, Asia, and Central America. In short, in just a few years, it is becoming a global standard. Recognizing the importance of the system, reports are published in major journals with increasing frequency, and it is becoming difficult to keep abreast of the field as it is growing so rapidly. A lively debate exists regarding the benefit of the RRS. In this textbook, we have tried to capture that debate, including potential emerging applications of the system. A year ago, we decided to update our manual to make it current with recent publications. However, as the project progressed, it became obvious that the field had expanded so significantly that more than an update was required. Instead, we chose to create a new work, the first “Textbook of Rapid Response Systems.” We added over a dozen chapters, recruited many new researchers in the field, and have tried to create a comprehensive resource for the clinician, administrator, and researcher. As in our first book, we tried to make each chapter capable of standing alone, yet tightly integrated with the others into a cohesive whole. The RRS concept is now being applied to a number of problems and processes in hospitals that require a “short circuit” to timely and expert help. When we each created our RRS at our home institutions, none of us recognized the many problems that might be amenable to the approach or the potential applications of the system. In this textbook we describe an RRS to rapidly and safely find lost, eloped, or wandering patients, another to immediately support staff who have suffered mental or psychological trauma in the course of their work, and yet another to provide support for suddenly dangerous patients, staff, or visitors. These problems share the common need for early recognition that an RRS provides using additional expertise and hands (afferent limb), and a planned, systematic approach to provide support (efferent limb). The ability to recognize the need, to capture and analyze data to guide change (quality improvement limb), and to provide resources (administrative limb) is also necessary to each application’s success. In a sense, the RRS is becoming, in some hospitals, a “system of systems.” In this textbook, we hope to provide readers with the tools they need to create systems that emulate some of the work reported in the book, and to discuss the expansion of the RRS to address other critical needs.

Contents

Part I  RRSs and Patient Safety   1  Rapid Response Systems History and Terminology............................. Bradford D. Winters and Michael DeVita

3

  2  RRS’s General Principles........................................................................ Ajay D. Rao and Michael DeVita

13

  3  Measuring and Improving Safety........................................................... Bradford D. Winters, Peter J. Pronovost, Marlene Miller, and Elizabeth A. Hunt

19

  4  Integrating a Rapid Response System into a Patient Safety Program........................................................................ John Gosbee

37

  5  Acute Hospitalist Medicine and the Rapid Response System.............. David J. McAdams

47

  6  Medical Trainees and Patient Safety...................................................... Stephen W. Lam and Arthas Flabouris

55

  7  Rapid Response Systems: A Review of the Evidence........................... Bradford D. Winters and Julius C. Pham

65

  8  Healthcare Systems and Their (Lack of ) Integration.......................... Ken Hillman, Jeffrey Braithwaite, and Jack Chen

79

  9  Creating Process and Policy Change in Healthcare.............................. Stuart F. Reynolds and Bernard Lawless

87

ix

x

Contents

10  The Challenge of Predicting In-Hospital Cardiac Arrests and Deaths................................................................................... Michael Buist

93

11  The Meaning of Vital Signs..................................................................... 109 John Kellett, Breda Deane, and Margaret Gleeson 12  Matching Illness Severity with Level of Care........................................ 125 Gary B. Smith and Juliane Kause 13  Causes of Failure to Rescue..................................................................... 141 Marilyn Hravnak, Andrea Schmid, Lora Ott, and Michael R. Pinsky Part II  Creating an RRS 14  Impact of Hospital Size and Location on Feasibility of RRS............................................................................... 153 Daryl Jones and Rinaldo Bellomo 15  Barriers to the Implementation of RRS................................................. 163 Michael A. DeVita and Ken Hillman 16  An Overview of the Afferent Limb......................................................... 177 Gary B. Smith and David R. Prytherch 17  The Impact of Delayed RRS Activation................................................. 189 Daryl Jones, Michael Haase, and Rinaldo Bellomo 18  The Case for Family Activation of the RRS.......................................... 197 Helen Haskell 19  RRT: Nurse-Led RRSs............................................................................ 207 Kathy D. Duncan and Christiane Levine 20  MET: Physician-Led RRSs..................................................................... 221 Daryl Jones and Rinaldo Bellomo 21  Pediatric RRSs......................................................................................... 231 James Tibballs and Richard J. Brilli 22  Sepsis Response Team.............................................................................. 245 Emanuel P. Rivers, David Amponsah, and Victor Coba

Contents

xi

23  Other Efferent Limb Teams: (BAT, DAT, M, H, and Trauma)............ 253 Daniel Shearn and Michael DeVita 24  Other Efferent Limb Teams: Crisis Response for Obstetric Patients............................................................................... 263 Gabriella G. Gosman, Hyagriv N. Simhan, Karen Stein, Patricia Dalby, and Marie Baldisseri 25  Personnel Resources for Responding Teams......................................... 275 Andrew W. Murray, Michael A. DeVita, and John J. Shaefer III 26  Equipment, Medications, and Supplies for an RRS............................. 291 Edgar Delgado, Wendeline J. Grbach, Joanne Kowiatek, and Michael DeVita 27  The Administrative Limb........................................................................ 313 Daryl Jones and Rinaldo Bellomo 28  The Second Victim................................................................................... 321 Susan D. Scott, Laura E. Hirschinger, Myra McCoig, Karen Cox, Kristin Hahn-Cover, and Leslie W. Hall Part III  Monitoring of Efficacy and New Challenges 29  RRSs in Teaching Hospitals.................................................................... 333 Max Bell and David Konrad 30  The Nurse’s View of RRS........................................................................ 341 Donna Goldsmith and Nicolette C. Mininni 31  Resident Training and RRSs................................................................... 347 Geoffrey K. Lighthall 32  Optimizing RRSs Through Simulation.................................................. 357 Melinda Fiedor Hamilton, Elizabeth A. Hunt, and Michael A. DeVita 33  Evaluating Effectiveness of Complex System Interventions................ 371 Jack Chen 34  RRS Education for Ward Staff............................................................... 381 John R. Welch and Gary B. Smith 35  Standardized Process and Outcome Assessment Tool.......................... 397 Gabriella Jäderling and David Konrad

xii

Contents

36  The Impact of RRSs on Choosing “Not-for-Resuscitation” Status............................................................... 405 Arthas Flabouris and Jack Chen 37  The Costs and the Savings....................................................................... 415 Dana Edelson and Rinaldo Bellomo Index.................................................................................................................. 429

Contributors

David Amponsah, MD Ultrasound Director, Senior Staff Physician, Department of Emergency Medicine, Henry Ford Hospital, Detroit MI, USA Marie Baldisseri, MD Associate Professor, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh PA, USA Max Bell, MD, PhD, DESA Department of Anesthesia and Intensive Care, Karolinska University Hospital, Solna, Stockholm, Sweden Rinaldo Bellomo, MD Department of Intensive Care, Austin Hospital, Heidelberg, 3084, VIC, Australia Jeffrey Braithwaite, PhD, MBA, FCHSM, FAIM Professor and Director, The Australian Institute of Health Innovation, Centre for Clinical Governance Research, The University of New South Wales, Sydney NSW, Australia Richard J. Brilli, MD, FCCM, FAAP Chief Medical Officer, Nationwide Children’s Hospital, Columbus OH, USA Michael Buist, MB, ChB, FRACP, FJFICM, MD Rural Clinical School, University of Tasmania, Private Bag 3513, Burnie, TAS 7320, Australia Jack Chen, MBBS, PhD, MBA The Simpson Centre for Health Systems Research, The University of New South Wales, Sydney NSW, Australia and The Australian Institute of Health Innovation, The University of New South Wales, Sydney NSW, Australia Victor Coba, MD Senior Staff Physician, Emergency Medicine, Critical Care Medicine, Henry Ford Hospital, Detroit MI, USA xiii

xiv

Contributors

Karen Cox, PhD, RN Manager, Quality Improvement and Patient Safety Office of Clinical Effectiveness, University of Missouri Health Center, Columbia MO, USA Patricia Dalby, MD Assistant Professor, Department of Anesthesiology, Magee-Womens Hospital, University of Pittsburgh School of Medicine, Pittsburgh PA, USA Breda Deane Data Collection Officer, Nenagh Hospital, Nenagh Co. Tipperary, Ireland Edgar Delgado, BS, RRT Director, Respiratory Care, UPMC Presbyterian Shadyside, Pittsburgh PA, USA Kathy D. Duncan, RN Faculty, Institute for Healthcare Improvement, Cambridge MA, USA Dana Edelson, MD, MS Assistant Professor, Department of Medicine, University of Chicago Medical Center, Chicago IL, USA Arthas Flabouris, MBBS, MD, FCICM, FANZCA Intensive Care Unit, Royal Adelaide Hospital, North Terrace, Adelaide, SA 5001, Australia Margaret Gleeson Clinical Nurse Manager, Nenagh Hospital, Nenagh Co. Tipperary, Ireland Donna Goldsmith, RN, MN, CCRN Austin Health, Heidelberg, VIC, Australia John Gosbee, MD, MS Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Magee-Womens Hospital, Room 2314, 300 Halket Street, Pittsburgh, PA 15213, USA Gabriella G. Gosman, MD Associate Professor, Department of Obstetrics, Gynecology and Reproductive Sciences, Magee-Womens Hospital, University of Pittsburgh School of Medicine, Pittsburgh PA, USA Wendeline J. Grbach, MSN, RN, CCRN, CLNC Curriculum Developer for Simulation Education, UPMC Presbyterian Shadyside School of Nursing, Pittsburgh PA, USA Michael Haase, MD Assistant Professor, Department of Nephrology and Intensive Care, Charité – University Medicine Berlin, Berlin, Germany Kristin Hahn-Cover, MD Medical Director, Office of Clinical Effectiveness, University of Missouri Health Center, Columbia MO, USA

Contributors

Leslie W. Hall, MD Chief Medical Officer, Senior Associate Director of Clinical Affairs, Dean’s Office, University of Missouri Health Center, Columbia MO, USA Melinda F. Hamilton, MD, MSc Department of Critical Care Medicine, University of Pittsburgh Medical Center Director, Pediatric Simulation, Peter M. Winter Institute for Simulation, Education, and Research (WISER) and Children’s Hospital of Pittsburgh Simulation Center, Pittsburgh, PA, USA Helen Haskell, MA Mothers Against Medical Error, 155 S. Bull St., Columbia, SC 29205, USA Laura E. Hirschinger, RN, MSN, AHN-BC Clinical Improvement Specialist, Office of Clinical Effectiveness, University of Missouri Health Center, Columbia MO, USA Marilyn Hravnak, RN, PhD, ACNP-BC, FCCM, FAAN School of Nursing, University of Pittsburgh, 3500 Victoria Street, 336 Victoria Building, Pittsburgh, PA 15261, USA Elizabeth A. Hunt, MD, MPH, PhD Pediatric Intensivist, Assistant Professor, Department of Anesthesiology and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore MD, USA Gabriella Jäderling, MD, DESA Department of Anesthesia and Intensive Care, Karolinska University Hospital, Solna Stockholm, Sweden Daryl Jones, MD, BSc (Hons), MBBS, FRACP, FCICM Department of Intensive Care, Austin Hospital, Studley Road, Heidelberg, VIC 3084, Australia Juliane Kause, BSc, MBBS, MRCP, AKC Consultant in Critical Care Medicine and Acute Medicine, Medical Assessment Unit and Department of Critical Care, Queen Alexandra Hospital, Portsmouth Hospitals NHS Trust, Portsmouth Hampshire, UK John Kellett, MD Department of Medicine, Nenagh Hospital, Nenagh, County Tipperary, Ireland David Konrad, MD, PhD, DEAA Director of Thoracic ICU, Department of Cardiothoracic Surgery and Anesthesiology, Karolinska University Hospital, Solna Stockholm, Sweden Joanne G. Kowiatek, RPH, MPM Pharmacy Manager, Medication Patient Safety, Department of Pharmacy and Therapeutics, University of Pittsburgh Medical Center Presbyterian Shadyside, Pittsburgh PA, USA

xv

xvi

Contributors

Stephen W. Lam, MBBS (Hons), FRACP, FJFICM University of Adelaide, Intensive Care Unit, Royal Adelaide Hospital, North Tce, Adelaide, SA 5001, Australia Bernard Lawless, MD, MHSc, FRCS Assistant Professor, Adjunct Scientist, Provincial Lead, Department of Surgery, St. Michael’s Hospital, University of Toronto, Toronto ON, Canada and Li Ka Shing Knowledge Institute, St. Michael’s Hospital, University of Toronto, Toronto ON, Canada and Critical Care and Trauma, Ontario Ministry of Health and Long-Term Care, St. Michael’s Hospital, University of Toronto, Toronto ON, Canada Christiane Levine, RN, BSN, BS Program Manager of Quality and Patient Safety, Children’s Healthcare of Atlanta at Hughes Spalding, Atlanta GA, USA Geoffrey K. Lighthall, PhD, MD Associate Professor of Anesthesia and Critical Care, Department of Anesthesia, Stanford University School of Medicine, Palo Alto CA 94305, USA David J. McAdams, MD, MS, SFHM, FACP Department of Internal Medicine, University of Pittsburgh Medical Center, 200 Lothrop Street, MUH 826E, Pittsburgh, PA, USA Myra McCoig Coordinator, Risk Management, University of Missouri Health Center, Columbia MO, USA Marlene Miller, MD, MSc Vice Chair of Quality and Safety Initiatives, Associate Professor, Johns Hopkins Children’s Center, Johns Hopkins University, Baltimore MD, USA and Department of Pediatrics, Johns Hopkins University, Baltimore MD, USA and Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore MD, USA Nicolette C. Mininni, RN, MEd, CCRN Advanced Practice Nurse, Critical Care Department of Nursing Education and Research, UPMC Shadyside, Pittsburgh PA, USA Andrew W. Murray, MD, ChB Department of Anesthesiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA

Contributors

xvii

Lora Ott, RN, MSN, BSN School of Nursing, University of Pittsburgh, Pittsburgh PA, USA Julius C. Pham, MD Assistant Professor, Departments of Emergency Medicine, and Anesthesia and Critical Care Medicine, The Johns Hopkins University School of Medicine, Baltimore MD, USA Michael R. Pinsky, MD, FCCP, FCCM University of Pittsburgh, Pittsburgh PA, USA Peter J. Provonost, MD, PhD, FCCM Professor, Director, Departments of Anesthesiology and Critical Care, Surgery, and Health Policy and Management, The Johns Hopkins University School of Medicine, Baltimore MD, USA and Quality and Safety Research Group, Medical Center for Innovations in Quality Patient Care, Baltimore MD, USA David R. Prytherch, MD, PhD, MIPEM, CSci Senior Research Fellow, Queen Alexandra Hospital, Portsmouth Hospitals NHS Trust, Portsmouth Hampshire, UK Ajay D. Rao, MD Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Boston MA, USA Stuart F. Reynolds, MD, FCCP Associate Clinical Professor of Critical Care Medicine, University of Alberta Hospital, 3C1.12 WMC, 8440 112 Street, Edmonton, Alberta, Canada Emanuel P. Rivers, MD Clinical Professor, Vice Chairman, and Research Director, Emergency Medicine and Surgery, Henry Ford Hospital, Wayne State University, Detroit MI, USA Andrea Schmid, RN, PhD School of Nursing, University of Pittsburgh, Pittsburgh PA, USA Susan D. Scott, RN, MSN, CLNC University of Missouri Health System, Office of Clinical Effectiveness, MU Sinclair School of Nursing, Doctoral Student, Columbia, MO, USA John J. Shaefer, III, MD Director, Professor, Lewis W. Haskell Blackman Endowed Chair, Medical University of South Carolina, Charleston SC, USA and Healthcare Simulation, South Carolina, Medical University of South Carolina, Charleston SC, USA and

xviii

Contributors

Department of Anesthesia and Perioperative Medicine, Medical University of South Carolina, Charleston SC, USA Daniel Shearn, RN, MSN UPMC Presbyterian Hospital, Pittsburgh PA 15213, USA Hyagriv N. Simhan, MD, MSCR Associate Professor, Department of Obstetrics, Gynecology, and Reproductive Systems, Magee-Womens Hospital, University of Pittsburgh School of Medicine, Pittsburgh PA, USA Gary B. Smith, MD, FRCAP Consultant in Critical Care Medicine, Department of Intensive Care Medicine, Queen Alexandra Hospital, Portsmouth, UK Karen Stein RN, BSN, MSED, CCRN Clinical Education Specialist, Department of Patient Care Services, Magee-Womens Hospital, University of Pittsburgh School of Medicine, Pittsburgh PA, USA James Tibballs, BMedSc, MBBS, MEd, MBA, MD, MHlth & MedLaw, GDipArts, FANZCA, FJFICM, FACLM Associate Professor, Intensive Care Physician, and Resuscitation Officer, Department of Pediatrics, Pediatric Intensive Care Unit, Royal Children’s Hospital, Melbourne VIC, Australia and Department of Pharmacology, University of Melbourne, Melbourne VIC, Australia John Welch, RN, BSc, MSc Consultant Nurse, Department of Critical Care, University College London Hospitals, NHS Foundation Trust, London, UK Bradford D. Winters, MD, PhD Assistant Professor, Departments of Anesthesiology, Critical Care Medicine and Surgery, The Johns Hopkins University School of Medicine, Meyer 297 600 N Wolfe Street, Baltimore, MD 21298, USA e-mail: [email protected]

Part I

RRSs and Patient Safety

Chapter 1

Rapid Response Systems History and Terminology Bradford D. Winters and Michael DeVita

Keywords  Rapid • Response • Systems • History • Terminology

Principles The Rapid Response System (RRS) concept has matured substantially since its inception in the early 1990s when critical care physicians, primarily in Australia, Pittsburgh, PA, and the UK started asking some crucial questions regarding patients who deteriorated and often arrested on general hospital wards prior to their admission to the ICU. Specifically, they asked exactly what is happening to general hospital ward patients in the minutes and hours prior to their cardio-respiratory arrests and whether we can do something to intervene and halt these deteriorations before the patient arrests or nearly arrests. This was a sea-change in thought and perspective since, at that time, resources focused on resuscitation were primarily concerned with how to improve performance of CPR and ACLS rather than preventing the event to start with. Critical Care physicians were well aware, in a general sense, that patients admitted or readmitted to the ICU from the general ward uncommonly went from “just fine” to critically ill. This sense was confirmed by early studies that clearly showed that arrests and deteriorations were not sudden but rather commonly heralded by long periods of obvious hemodynamic and respiratory instability that was often unappreciated by general ward providers.1–17 The development of critical illness on the general ward was rarely “sudden,” only suddenly recognized. Given this result, critical care physicians reasoned that if we could create usable criteria for general ward staff to use in the early recognition of impending deterioration and empower these staff members to bring a team of critical care physicians

B.D. Winters (*) Departments of Anesthesiology, Critical Care Medicine and Surgery, The Johns Hopkins University School of Medicine, Meyer 297 600 N Wolfe Street, Baltimore, MD 21298, USA e-mail: [email protected] M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_1, © Springer Science+Business Media, LLC 2011

3

4

B.D. Winters and M. DeVita

and/or nurses outside of the ICU to the bedside, we could improve the outcomes of these patients. Data from these studies of the antecedents to arrest provided the basis for developing the physiological criteria that were put into place for general ward staff to use as a guide for making the decision to call for help.13–17 Intensive Care Unit staff formed the team that would come to the patient’s bedside to evaluate, stabilize and help create a new care and triage plan. Through sheer will, and often working in isolation without the support of the health community, these critical care clinicians created a new patient safety and quality initiative, long before patient safety and quality became a national and international concern and had the attention of the public and policymakers.18–49 These early programs were often referred to as Medical Emergency Teams (METs), although other terms, such as Condition C Teams and Critical Care Outreach Teams were also used. This linking defined activation criteria to a response team and empowering the ward staff to summon that team, has become a powerful patient safety and quality initiative that has enjoyed wide adoption in the US, Australia, New Zealand, Canada and the UK and ever-increasing acceptance around the world, such that the first International Conference on Medical Emergency Teams was held in Pittsburgh, PA, in May, 2005. Subsequent conferences have been held each year again in Pittsburgh and also in Toronto, Canada, and Copenhagen, Denmark. The RRS concept has reached such significance that the Institutes for Healthcare Improvement (IHI) included Rapid Response Systems as one of its six “planks” for improving patient in its “100,000 Lives” Campaign.50 Additionally, the essential principles of the RRS have recently been embraced by the Joint Commission (the accreditation organization for US hospitals) as a mandate for American hospitals in the form of National Patient Safety Goal 16 and 16A.51 While this goal does not specifically ask hospitals to create response teams or dictate activation criteria, it requires hospitals to develop systems that “improve recognition and response to changes in a patient’s condition with the organization selecting suitable methods that enable healthcare staff members to directly request additional assistance from a specially trained individual or individuals when a patient’s condition appears to be deteriorating.” Clearly, while the Joint Commission mandate does not demand RRSs by name, RRSs are the logical solution for ­meeting this requirement and providing patients with the safety net they need to help prevent medical deteriorations from progressing and degenerating into an arrest and death. While other solutions have been proposed, such as increased nurse-to-patient ratios, hospitalist services and others, none has the practicality and body of evidence in their favor like RRSs. One of the primary goals of RRSs is to prevent cardio-respiratory arrest and therefore the very high mortality known to be associated with such in-hospital events. Since the physiological instability that precedes the arrest is usually evident for substantial periods of time prior to the arrest, there is significant face validity to the notion that RRSs should result in a reduction in the incidence of cardiac arrest and mortality. Additionally, RRSs should be able to, through early recognition and intervention, reduce unanticipated ICU admission. By catching problems early in

1  Rapid Response Systems History and Terminology

5

their course, it is envisioned that patients not only won’t arrest but also may not even require ICU care and be able to be managed on the general ward. This helps to keep ICU beds open for other patients and improve through-put. Likewise, with reductions in serious deteriorations and complications, length of stay should also decrease. Even when patients still require transfer to an ICU as a result of their deterioration, in principle, having the early intervention afforded by an RRS should have the patient arriving in the ICU in better condition than without such a system. The expected benefit in this circumstance is reduced ICU and hospital mortality and reduced ICU and length of hospital stay. The foundation for achieving these goals is an underlying principle and strength of RRSs, namely that RRSs address the mismatch between the patient’s needs and the available resources on the general wards.52 This imbalance between what the patient needs (human resources, monitoring, specialized equipment and medications) and what the general ward can provide (staffing, monitoring and policy limitations) are at the center of these deteriorations. RRSs are commonly activated by nurses who determine that the patient is seriously ill and cannot be managed under the current circumstances. These circumstances may include staff/acuity limitations, inadequate care plans, and/or new events such as sepsis. Through rapid assessment and intervention, new plans can be developed and communicated to the ward staff and primary service and resource/needs imbalances accounted for resulting in an effective triage and care plan for the patient. Often the patient requires triage to a higher level of care to achieve a re-balancing of resources and needs, but if needs are reduced through RRS intervention, that re-balancing can be achieved with the patient remaining on the ward. Many of these goals and benefits have been realized through the implementation of RRSs, while some have been less successful and yet others not well evaluated.18–49 While outcome measures such as mortality are important to clinicians, regulators and patients, other measures of RRS success and positive impact need to also be considered. Some of these include process of care measures (such as meeting sepsis management guidelines and appropriate institution of Not for Resuscitation status),53–55 patient and nursing satisfaction56–58 and especially the value RRSs bring to staff education in the recognition and management of the critically ill patient who presents as such outside the walls of the ICU.59,60 In fact, this last goal and benefit of RRSs may be the most under-appreciated, although in many ways the most important. RRSs change culture and culture is a crucial element of the health systems in which we work. RRSs are not just teams, they are systems in themselves that include a component that emphasizes and educates in the early detection of problems and a component that responds to the call for help. The RRS functions within a greater system that spans from the patient, through the providers, their environment and up to the departmental, hospital and institutional and even governmental level. This realization requires that RRSs have two additional components besides the activation process and a responding team. The first is an evaluative element that continuously assesses the performance of the RRS and helps to inform the hospital Quality Improvement (QI) process.52 Institutions such as the University of Pittsburgh have used their RRS to scrutinize all of their arrest and MET calls in an ongoing QI process that has had great impact for their

6

B.D. Winters and M. DeVita

hospital.61 The second component is a governance and administration structure.52 This helps to develop, implement and, most crucially, maintain and improve the RRS program. The work of the evaluation/QI element and the governance/­ administrative structure has been greatly improved in the last 2 years with the addition of RRS data fields to the American Heart Association’s (AHA) National Registration for CPR database.62 From this database useful reports and comparisons can be ­generated to support the RRS. While these two additional components are not absolutely essential to having an RRS, they enhance its effectiveness, role and status within the hospital system and are well worth consideration. RRSs have become a great agent for change, encouraging and empowering ward staff to ask for help for their patients. The archaic concept, often held and promulgated by physicians and occasionally others, that calling for help is “a sign of weakness” is washed away by the RRS as it changes the culture to an understanding that the patient and his well-being is the primary concern of all providers and that calling for help is the sign of the wise and caring clinician.

Terminology It is important to have a clear understanding of the terminology for Rapid Response Systems so as to get the most from this book and any review of RRS literature. Historically, the early RRSs were most commonly called “Medical Emergency Teams” or METs, although other terms were also used, including Medical Emergency Response Teams (MERT), Patient-at-Risk Teams (PART), Critical Care Outreach Teams (CCOT), and eventually Rapid Response Teams (RRTs). Some of these terms are used interchangeably in places such as Australia where RRT and MET often mean the same thing. While hospitals and institutions often create specific names for their programs based on local preferences and the desire to use something memorable to encourage utilization, consensus has been developed on specific terminology that should be used when reporting and sharing information and data in the public forum (publications, research articles etc).52,63 The term Rapid Response System refers to the entire system for responding to all patients with a critical medical problem. Most broadly, this can include the Cardiac Arrest Team (Code Team) and the MET as well as other specialized teams that may exist within the hospital, such as a Difficult Airway Response Team, although most commonly and preferably the term RRS is used to refer to systems that seek to prevent deterioration and arrests rather than respond to arrests. This term encompasses both the recognition process (the activation criteria and the activation process) and the responding team. These two sub-components are referred to as the Afferent and Efferent Limbs of the RRS, respectively. Additional confusion may arise when the Code Team and the MET are one and the same in terms of personnel but take on different roles depending on the patient’s situation (arrest versus deterioration).

1  Rapid Response Systems History and Terminology

7

The historical MET and similar systems are now defined through consensus based on the team structure and functionality.52 Teams that include physicians along with nurses, but may also include respiratory therapists and others, are properly called Medical Emergency Teams, which have full capability for assessment, treatment and triage planning, while teams that do not include physicians as responders and rely on nurses and others only are referred to as Rapid Response Teams (RRTs). These nurse-led RRTs often have physician consultation available but the physician does not respond to the bedside as a member of the initial response. RRTs often provide an intermediate range of capability since nurses cannot write orders for therapy. An exception to this is the Nurse Practitioner in the US, who can write a range of orders. As such, true RRTs are able to assess and provide some level of stabilization but if needs and resources are severely out of balance, the patient is likely to require triage to a higher level of care. Teams that provide follow-up service and surveillance on patients discharged from the ICU on a regular basis, as well as response to any general ward patient that may or may not have been in an ICU previously, are described as Critical Care Outreach Teams. These teams are often staffed by nurses and therefore their response to deteriorating patients would be an RRT-type response team. Other terms, such as Patient-at-Risk Team, may be used as the local name for the program and hospitals may choose to call their system an RRT even though it has physicians as responders; such names should only be for local use and should be avoided in the literature. So that proper comparisons may be made, the preferred nomenclature should describe the response component of the RRS as an MET, RRT or CCOT-based on these consensus definitions. As mentioned previously, another important terminology distinction to consider is the difference between the process of recognition that the patient is deteriorating and that of the teams that respond. The process and criteria used for triggering the call for help is called the Afferent Limb, while the response to that call, the team, is the Efferent Limb. While both work in concert as a system, their separate nomenclature and consideration is important. Many think of the Efferent Limb as the RRS but the Afferent Limb is equally important, if not more so since this is where the recognition is made that the patient needs help. Providing a responding team is of less benefit if the patient has already progressed to the point where arrest is imminent; the earlier the recognition is made, the better. Some have argued that it may not even matter who comes to help the patient (a critical care team, a hospitalist team or the primary service) as long as it is recognized that help is needed early enough to make a difference. The importance of early recognition was addressed by the first Consensus Conference on Medical Emergency Teams and then further emphasized by the special Afferent Limb Consensus Conference convened ahead of the third International Conference on Medical Emergency Teams. In these forums, the question of how RRSs might improve their identification of seriously ill general ward patients was considered and debated. The report of the first Consensus Conference52 indicates that RRS should use clear methods of detection for identifying “emergent unmet patient needs” and deteriorations. Objective criteria are preferred and several identification systems exist, including direct vital sign parameters and various scoring systems.52, 64–81 The upcoming report of the Afferent

8

B.D. Winters and M. DeVita

Limb Consensus Conference suggests that technological solutions are going to be essential to better monitoring and detection in the mostly ambulatory general ward patient population but that we still are struggling to determine what best needs to be monitored and how. This is an area of very active research with many exciting possibilities likely to result in the next few years.82–84 The Efferent Limb also continues as an area of active research. New education modalities and strategies such as simulation are being used to improve team performance and function and prepare teams for unusual or rare scenarios. The kind of team that makes up the Efferent Limb probably does matter ‑ not so much by what their title is, but rather by how well they are prepared and how well they work as team members.85–87

Summary RRSs have grown substantially since their inception almost two decades ago to become a robust strategy for improving patient care and healthcare culture. Clinicians who support these initiatives have striven to be evidence-based and thorough, resulting in an ever-expanding body of literature and experience that points to RRSs as a successful systems-based solution to the problem of deteriorating general ward patients and the imbalance of resources necessary to care for them. Clear definitions and nomenclature have aided this process. By working to improve the Afferent and Efferent Limbs of RRSs through methods best suited to their uniqueness and melding them into an effective system, RRSs can continue to be a developing and dynamic patient safety and quality of care improvement paradigm.

References 1. Sax FL, Charlson ME. Medical patients at high risk for catastrophic deterioration. Crit Care Med. 1987;15(5):510–515. 2. Schein RM, Hazday N, Pena M, Robin BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388–1392. 3. Bedell SE, Deitz DC, Leeman D, Delbanco TL. Incidence and characteristics of preventable iatrogenic cardiac arrests. J Am Med Assoc. 1991;265(21):2815–2820. 4. Daffurn K, Lee A, Hillman KM, Bishop GF, Bauman A. Do nurses know when to summon emergency assistance? Intensive Crit Care Nurs. 1994;10(2):115–120. 5. Smith AF, Wood J. Can some in-hospital cardio-respiratory arrests be prevented? A prospective survey. Resuscitation. 1998;37(3):133–137. 6. Buist MD, Jarmolowski E, Burton PR, Bernard SA, Waxman BP, Anderson J. Recognising clinical instability in hospital patients before cardiac arrest or unplanned admission to intensive care. A pilot study in a tertiary-care hospital. Med J Aust. 1999;171(1):22–25. 7. Hillman KM, Bristow PJ, Chey T, Daffurn K, et al. Antecedents to hospital deaths. Intern Med J. 2001;31(6):343–348.

1  Rapid Response Systems History and Terminology

9

8. Hodgetts TJ, Kenward G, Vlachonikolis IG, et  al. Incidence, location and reasons for avoidable in-hospital cardiac arrest in a district general hospital. Resuscitation. 2002;54(2):115–123. 9. Kause J, Smith G, Prytherch D, et al. A comparison of antecedents to cardiac arrests, deaths and emergency intensive care admissions in Australia, New Zealand, and the United Kingdom ‑ the ACADEMIA study. Resuscitation. 2004;62(3):275–282. 10. Hillman K, Bristow PJ, Chey T, et  al. Duration of life-threatening antecedents prior to ­intensive care admission. Intensive Care Med. 2002;28:1629–1634. 11. Franklin C, Mathew J. Developing strategies to prevent in-hospital cardiac arrest: analyzing responses of physicians and nurses in the hours before the event. Crit Care Med. 1994;22(2):244–247. 12. McGloin H, Adam SK, Singer M. Unexpected deaths and referrals to intensive care of patients on general wards. Are some cases potentially avoidable? J R Coll Physicians Lond. 1999;33(37):255–259. 13. Goldhill DR, White SA, Sumner A. Physiological values and procedures in the 24 h before ICU admissions from the ward. Anaesthesia. 1999;54(6):529–534. 14. Morgan RJM, Williams F, Wright MM. An early warning scoring system for detecting ­developing critical illness. Clin Intensive Care. 1997;8:100. 15. Stenhouse C, Coates S, Tivey M, Allsop P, Parker T. Prospective evaluation of a Modified Early Warning Score to aid earlier detection of patients developing critical illness on a general surgical ward. Br J Anaesth. 2000;84:663P. 16. Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified Early Warning Score in medical admissions. Q J Med. 2001;94(10):521–526. 17. Hodgetts TJ, Kenward G, Vlachonikolis IG, Payne S, Castle N. The identification of risk ­factors for cardiac arrest and formulation of activation criteria to alert a medical emergency team. Resuscitation. 2002;54(2):125–131. 18. Lee A, Bishop G, Hillman K, Daffurn K. The medical emergency team. Anaesth Intensive Care. 1995;23:183–186. 19. Goldhill DR, Worthington L, Mulcahy A, Tarling M, Sumner A. The patient-at-risk team: identifying and managing seriously ill ward patients. Anaesthesia. 1999;54(2):853–860. 20. Bristow PJ, Hillman KM, Chey T, et al. Rates of in-hospital arrests, deaths and intensive care admissions: the effect of a medical emergency team. Med J Aust. 2000;173(5):236–240. 21. Buist MD, Moore GE, Bernard SA, Waxman BP, Anderson JN, Nguyen TV. Effects of a medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: preliminary study. Br Med J. 2002;324(7334):387–390. 22. Ball C, Kirkby M, Williams S. Effect of the critical care outreach team on patient survival to discharge from hospital and readmission to critical care: non-randomised population based study. Br Med J. 2003;327(7422):1014–1016. 23. Leary T, Ridley S. Impact of an outreach team on re-admissions to a critical care unit. Anaesthesia. 2003;58(4):328–332. 24. Bellomo R, Goldsmith D, Uchino S, et al. A prospective before-and-after trial of a medical emergency team. Med J Aust. 2003;179(6):283–287. 25. Kenwood G, Castle N, Hodgetts T, Shaikh L. Evaluation of a medical emergency team one year after implementation. Resuscitation. 2004;61(3):257–263. 26. Priestley G, Watson W, Rashidian A, et  al. Introducing critical care outreach: a ward-­ randomised trial of phased introduction in a general hospital. Intensive Care Med. 2004;30(7): 1398–1404. 27. Bellomo R, Goldsmith D, Uchino S, et al. Prospective controlled trial of effect of medical emergency team on postoperative morbidity and mortality rates. Crit Care Med. 2004;32(4):916–921. 28. DeVita MA, Braithwaite RS, Mahidhara R, Stuart S, Foraida M, Simmons RL. Use of medical emergency team responses to reduce hospital cardiopulmonary arrests. Qual Saf Health Care. 2004;13(4):251–254.

10

B.D. Winters and M. DeVita

29. Garcea G, Thomasset S, McClelland L, Leslie A, Berry DP. Impact of a critical care outreach team on critical care readmissions and mortality. Acta Anaesthesiol Scand. 2004;48(9):1096–1100. 30. MERIT Study Investigators. Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial. Lancet. 2005;365(9477):2091–2097. 31. Jones D, Bellomo R, Bates S, et al. Long term effect of a medical emergency team on cardiac arrests in a teaching hospital. Crit Care. 2005;9(6):R808–R815. 32. Jones D, Opdam H, Egi M, et al. Long-term effect of a medical emergency team on mortality in a teaching hospital. Resuscitation. 2007;74(2):235–241. 33. Jolley J, Bendyk H, Holaday B, Lombardozzi KAK, Harmon C. Rapid response teams: do they make a difference? Dimens Crit Care Nurs. 2007;26(6):253–260. 34. Dacey MJ, Mirza ER, Wilcox V, et al. The effect of a rapid response team on major clinical outcome measures in a community hospital. Crit Care Med. 2007;35(9):2076–2082. 35. Chan PS, Khalid A, Longmore LS, Berg RA, Kosiborod M, Spertus JA. Hospital-wide code rates and mortality before and after implementation of a rapid response team. J Am Med Assoc. 2008;300(21):2506–2513. 36. Tibballs J, Kinney S, Duke T, Oakely E, Hennessy M. Reduction of pediatric in-patient­ ­cardiac arrest and death with a medical emergency team: preliminary results. Arch Dis Child. 2005;90(11):1148–1152. 37. Tibballs J, Kinney S. Reduction of hospital mortality and of preventable cardiac arrest and death on introduction of a pediatric medical emergency team. Pediatr Crit Care Med. 2009;10(3):306–312. 38. Brilli RJ, Gibson R, Luria JW, et al. Implementation of a medical emergency team in a large pediatric teaching hospital prevents respiratory and cardiopulmonary arrests outside the ­intensive care unit. Pediatr Crit Care Med. 2007;8(3):236–246. 39. Sharek PJ, Parast M, Leong K, et  al. Effect of a rapid response team on hospital-wide ­mortality and code rates outside the ICU in a children’s hospital. J Am Med Assoc. 2007;298(19):2267–2274. 40. Zenker P, Schlesinger A, Hauck M, et al. Implementation and impact of a rapid response team in a children’s hospital. Joint Comm J Qual Patient Saf. 2007;33(7):418–425. 41. Buist M, Harrison J, Abaloz E, Van Dyke S. Six-year audit of cardiac arrests and medical emergency team calls in an Australian teaching hospital. Br Med J. 2007;335(7631): 1210–1212. 42. Jones D, Egi M, Bellomo R, Goldsmith D. Effect of the medical emergency team on long-term mortality following major surgery. Crit Care. 2007;11(1):R12. 43. Mailey J, Digiovine B, Baillod D, Gnam G, Jordan J, Rubinfeld I. Reducing hospital standardized mortality rate with early interventions. J Trauma Nurs. 2006;13(4):178–182. 44. Tolchin S, Brush R, Lange P, Bates P, Garbo JJ. Eliminating preventable death at Ascension Health. Joint Comm J Qual Patient Saf. 2007;33(3):145–154. 45. Offner P, Heit J, Roberts R. Implementation of a Rapid Response Team decreases cardiac arrest outside of the Intensive Care Unit. J Trauma. 2007;62(5):1223–1228. 46. Dacey M, Mizra R, Wilcox V, et al. The effect of a Rapid Response Team on major clinical outcome measures in a community hospital. Crit Care Med. 2007;35(9):2076–2082. 47. Story D, Shelton A, Poustie S, Colin-Thome N, McIntrye R, McNicol P. Effect of an anesthesia department-led critical care outreach and acute pain service on postoperative serious adverse events. Anesthesia. 2006;61:24–28. 48. King E, Horvath R, Shulkin D. Establishing a Rapid Response Team (RRT) in an academic hospital: one year’s experience. J Hosp Med. 2006;1(5):296–305. 49. Hunt EA, Zimmer KP, Rinke ML, et al. Transition from a traditional code team to a medical emergency team and categorization of cardiopulmonary arrests in a children’s center. Arch Pediatr Adolesc Med. 2008;162(2):117–122. 50. 100K lives campaign. www.ihi.org/IHI/Programs/Campaign/Campaign. Accessed 10.07.09. 51. Joint Commission National Patient Safety Goals. www.jointcommission.org/patientsafety/ nationalpatientsafetygoals/. Accessed 10.01.10.

1  Rapid Response Systems History and Terminology

11

52. Devita M, Bellomo R, Hillmam K, et al. Findings of the first consensus conference on medical emergency teams. Crit Care Med. 2006;34(9):2463–2478. 53. Sebat F, Musthafa AA, Johnson D, et al. Effect of a rapid response system for patients in shock on time to treatment and mortality during 5 years. Crit Care Med. 2007;35(11): 2568–2575. 54. Jones DA, McIntyre T, Baldwin I, Mercer I, Kattula A, Bellomo R. The medical emergency team and end-of-life care: a pilot study. Crit Care Resusc. 2007;9(2):151–156. 55. Chen J, Flabouris A, Bellomo R, Hillman K, Finfer S. MERIT study investigators for the Simpson Center and the ANZICS Clinical Trials Group, the Medical Emergency Team System and not-forresuscitation orders: results from the MERIT study. Resuscitation. 2008;79(3):391–397. 56. Jones D, Baldwin I, McIntyre T, et al. Nurses’ attitudes to a medical emergency team service in a teaching hospital. Qual Saf Health Care. 2006;15(6):427–432. 57. Galhotra S, Scholle CC, Dew MA, Mininni NC, Clermont G, DeVita MA. Medical emergency teams: a strategy for improving patient care and nursing work environments. J Adv Nurs. 2006;55(2):180–187. 58. Salamonson Y, van Heere B, Everett B, Davison P. Voices from the floor: nurses’ perceptions of the medical emergency team. Intensive Crit Care Nurs. 2006;22(3):138–143. 59. Buist M, Bellomo R. MET. The emergency medical team or the medical education team? Crit Care Resusc. 2004;6:88–91. 60. Jones D, Bates S, Warrillow S, Goldsmith D, et al. Effect of an education programme on the utilization of a medical emergency team in a teaching hospital. Intern Med J. 2006;36(4):231–236. 61. Braithewaite RS, Devita MA, Mahidhara R, et al. Use of medical emergency teams (MET) responses to detect medical errors. Qual Saf Health Care. 2004;13:255–259. 62. American Heart Association National Registry for CPR. www.nrcpr.org. Accessed 23.01.10. 63. Cretikos M, Parr M, Hillman K, et al. Guidelines for the uniform reporting of data for Medical Emergency Teams. Resuscitation. 2006;68:11–25. 64. Subbe CP, Davies RG, Williams E, Rutherford P, Gemmell L. Effect of introducing the Modified Early Warning score on clinical outcomes, cardiopulmonary arrests and intensive care utilisation in acute medical admissions. Anesthesia. 2003;58(8):797–802. 65. Goldhill DR, McNarry AF. Physiological abnormalities in early warning scores are related to mortality in adult inpatients. Br J Anaesth. 2004;92(6):882–884. 66. Goldhill DR, McNarry AF, Mandersloot G, McGinley A. A physiologically-based early warning score for ward patients: the association between score and outcome. Anaesthesia. 2005;60(6):547–553. 67. Sharpley JT, Holden JC. Introducing an early warning scoring system in a district general hospital. Nurs Crit Care. 2004;9(3):98–103. 68. Gardner-Thorpe J, Love N, Wrightson J, Walsh S, Keeling N. The value of Modified Early Warning Score (MEWS) in surgical in-patients: a prospective observational study. Ann R Coll Surg Engl. 2006;88(6):571–575. 69. Jacques T, Harrison G, McLaws M, Kilborn G. Signs of critical conditions and emergency response (SOCCER): a model for predicting adverse events in the inpatient setting. Resuscitation. 2006;69:175–183. 70. Harrison GA, Jacques T, McLaws ML, Kilborn G. Combinations of early signs of critical illness predict in-hospital death – the SOCCER study (signs of critical conditions and emergency responses). Resuscitation. 2006;71(3):327–334. 71. Jacques T, Harrison GA, McLaws ML, Kilborn G. Signs of critical conditions and emergency responses (SOCCER): a model for predicting adverse events in the in-patient setting. Resuscitation. 2006;69(2):175–183. 72. Subbe CP, Hibbs R, Williams E, Rutherford P, Gemmel L. ASSIST: a screening tool for ­critically ill patients on general medical wards. Intensive Care Med. 2002;28(suppl):S21. 73. Haines C, Perrott M, Weir P. Promoting care for acutely ill children. Development and evaluation of a paediatric early warning tool. Intensive Crit Care Nurs. 2006;22(2):73–81. 74. Duncan H, Hutchison J, Parshuram CS. The pediatric early warning system score: a severity of illness score to predict urgent medical need in hospitalised children. J Crit Care. 2006;21(13):271–279.

12

B.D. Winters and M. DeVita

75. Subbe CP, Gao H, Harrison DA. Reproducibility of physiological track-and-trigger warning systems for identifying at-risk patients on the ward. Intensive Care Med. 2007;33(4):619–624. 76. Bell MB, Konrad D, Granath F, Ekbom A, Martling CR. Prevalence and sensitivity of MET-criteria in a Scandinavian University Hospital. Resuscitation. 2006;70(1):66–73. 77. Green A, Williams A. An evaluation of an early warning clinical marker referral tool. Intensive Crit Care Nurs. 2006;22:274–282. 78. Cretikos M, Chen J, Hillman K, Bellomo R, Finfer S, Flabouris A. MERIT study investigators. The objective medical emergency team activation criteria: a case-control study. Resuscitation. 2007;73(1):62–72. 79. Smith GB, Prytherch DR, Schmidt PE, Featherstone PI, Higgins B. A review, and performance evaluation, of single-parameter “track-and-trigger” systems. Resuscitation. 2008;79(1): 11–21. 80. Smith GB, Prytherch DR, Schmidt PE, Featherstone PI. Review and performance evaluation of aggregate weighted “track-and-trigger” systems. Resuscitation. 2008;77(2):170–179. 81. Santiano N, Young L, Hillman K, et al. Analysis of medical emergency team calls comparing subjective to “objective” call criteria. Resuscitation. 2009;80(1):44–49. 82. Smith GB, Prytherch DR, Schmidt P, Featherstone PI, et  al. Hospital-wide physiological surveillance. A new approach to the early identification and management of the sick patient. Resuscitation. 2006;71(1):19–28. 83. Watkinson PJ, Barber VS, Price JD, Hann A, et al. A randomised controlled trial of the effect of continuous electronic physiological monitoring on the adverse event rate in high risk ­medical and surgical patients. Anaesthesia. 2006;61(11):1031–1039. 84. Tarassenko L, Hann A, Young D. Integrated monitoring and analysis for early warning of patient deterioration. Br J Anaesth. 2006;97(1):64–68. 85. DeVita MA, Schaefer J, Lutz J, Wang H, Dongilli T. Improving medical emergency team (MET) performance using a novel curriculum and a computerized human patient simulator. Qual Saf Health Care. 2005;14(5):326–331. 86. Wallin CJ, Meurling L, Hedman L, Hedegård J, Felländer-Tsai L. Target-focused medical emergency team training using a human patient simulator: effects on behaviour and attitude. Med Educ. 2007;41(2):173–180. 87. Jones D, Duke G, Green J, et al. Medical Emergency Team syndromes and an approach to their management. Crit Care. 2006;10(1):R30.

Chapter 2

RRS’s General Principles Ajay D. Rao and Michael DeVita

Keywords  Overview • Rapid • Response • System

Introduction Studies focused on hospital outcomes have proven to be conflicting with regards to the Rapid Response System irrespective of whether the responders are Medical Emergency Teams (METs) or Rapid Response Teams (RRTs). On one hand, several studies have shown improved hospital outcomes,1–4 yet on the other, there have been some studies that have also shown negative outcomes.5–7 Despite the literature, many hospitals have incorporated METs and RRTs to promote patient safety. In order to understand the benefits of any form of Rapid Response System requires not only information about the constituents of the response team, but also knowledge of the triggers that set off the cascade of responses. Specifically, understanding the afferent limb (i.e., the calling criteria and the triggering mechanism) can shed light on why (or why not) the efferent limb (the MET or RRT) is effective.8 Indeed, some have argued that the most important part of the RRS is a robust triggering mechanism to reap most of the benefits of an RRS.9 In addition, one might expect that a hospital’s quality improvement efforts may be entwined with events discovered in performing a response, or in a retrospective review of the events. Finally, different hospitals may bring different material and personnel resources to bear in either the response or the review of events. All these factors contribute to the practice of responding to and preventing future patient crisis events. Because of these considerations, experts have concluded that the response ‑ RRT or MET ‑ is a system event and not exclusively a team event. In this chapter, we will describe and provide an overview of the Rapid Response System.

M. DeVita (*) Clinical Professor, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA e-mail: [email protected] M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_2, © Springer Science+Business Media, LLC 2011

13

14

A.D. Rao and M. DeVita

Overview In 2004, experts convened to describe and create a common terminology for teams that respond to patient deterioration outside the ICU. At that time, the participants of the consensus conference recognized a critical observation: All organizations that had successfully created a planned team response had also made a series of interventions in their organizations beyond the creation of a team. They recognized and defined the Rapid Response System.8 The RRS has four components: the afferent limb, the efferent limb, the quality improvement limb, and the administrative limb (Fig. 2.1). The afferent (or event detection and response trigger) limb is one of the most important components of the rapid response system (RRS). This is most likely related to the fact that many failures within the health system’s ability to manage deteriorating patients originate in the afferent limb. In other words, a patient may deteriorate without rescue if he or she is not assessed, or if assessed, the person doing the assessment does not recognize a critical state, or if recognized, a call for help not made, or if made, the responders not arrive (Fig. 2.2). Each step in the chain can be easily broken, all leading to the same outcome ‑ failure to respond to a patient in crisis. In the sense that the afferent limb is responsible for identifying a crisis and triggering a response, it may be both the most important component because without it there is no response. It may also be the

Afferent Limb Trigger

Efferent Limb MET/RRT/CCO specialized resources

Event detection Urgent Un-met Patient Need

Administration oversees all functions Data collection and analysis for Process Improvement

Crisis Resolved

cardiac Arrest Team Trauma Team Stroke Team

Data acquisition point

Fig.  2.1  Rapid Response System structure. When patients have critical unmet needs and as a result are at risk for imminent danger, the afferent limb detects the event and triggers a systemic response. The response provides resources to stabilize and triage the patient to a location where services meet the patient’s needs. Data are collected to determine event rate, resources needed and outcomes, and to enable an analysis of events to prevent or prepare for future events. An administrative mechanism is needed to oversee all components and to provide resources to facilitate the system. MET medical emergency team, RRT rapid response team, CCO critical care outreach

2  RRS’s General Principles

15

Clinical deterioration

Observation by staff

Recognition of abnormality

Knowledge how to call

Knowledge who to call

Decision to call for help

Call for help

Reliable calling mechanism

Team receives alert

Fig. 2.2  Steps in the afferent limb

most error-prone component of the rapid response system because of the many steps in the process, and the fact that patients are often not continuously observed. Logistically, the afferent limb can be divided into three main components: (1)  the selection/diagnostic/triggering criteria; (2) human and/or technologic ­monitoring (with alarm limits); and (3) a mechanism for triggering response. Each one of these components poses unique challenges to any hospital’s attempt to create an RRS as they all break with the traditional hospital culture. These are described more fully in Chaps. 14, 15 and 18, which also deal with the afferent limb. We will note here, however, that a subjective assessment can be a valuable tool for RRS triggering. This relies on the staff’s feelings of being “worried” about a patient. This criterion is usually used in conjunction with the first two systems, but this system is effective in allowing nurses to call for help based on their clinical instincts. Santiano10 has shown that while “nurse worried” is the most common calling criterion, most patients who have a call based on this criterion also met at least one of the criteria in the single parameter system. Others have shown that the reliability of crisis detection and team triggering is increased if objective signs are used.11,12 In actuality, although most published criteria consist of a variety of ­objective measures, many organizations have also included an option for a provider who is “worried.” This essentially represents a “fallback” position to support a staff member who may be unsure of making a call. In a study from Australia, over one-half of “worried” calls ended up falling into one of the other objective calling ­criteria categories.10 Furthermore, it is important that triggering an RRS response should be the inherent responsibility of all hospital personnel. It has been up to each organization to determine which criteria will be used, and, more importantly, to educate the staff accordingly. In general, the most common hospital personnel responsible for triggering these criteria have been nurses. The RRS has enabled nurses to exert their own independent judgment in calling for help through a preset system that goes “around” usual hospital hierarchy.13 The efferent limb consists of the resources that are brought to bear: both personnel and equipment. Thus the efferent limb is more than the response team. The components of the efferent limb, including the types of teams that may be created to deal

16

A.D. Rao and M. DeVita

with a host of different critical situations, are described in Chaps. 19–26. The intention is to restore balance to a situation where the patient’s needs exceed the resources available at a time when the patient’s status is critical and time is of the essence. For most crises, it intends to enable critical care resources to get to the patient’s bedside without bureaucratic, sociological, or logistical barriers. Nevertheless, nurses often continue to choose to call the patient’s primary physician, regardless of how long an RRS has been in place.14 Examples of critically unbalanced resource-to-needs situations include an acute trauma or fall, acute hemorrhage, a lost patient, an obstetric emergency, an unruly patient or family member, or even a staff member who is despondent over committing an error that caused patient harm. To make patients as safe as possible, all these needs should have a planned triggering mechanism and response. It is unlikely that facilities will create all the teams we have identified in this textbook at the outset of creating their RRS. It is only through continuous quality efforts that development of the resources becomes recognized as a need. We and others have found that events that trigger the RRS are examples of situations in which patients were in danger.15 To prevent future dangerous situations, one must have a quality apparatus attached to the RRS. This quality limb should both attempt to prevent critical events as well as improve the response to those events. Both require careful data collection, analysis, and provide feedback to responsible administrative and clinical personnel. These individuals or teams can create needed new processes to attend to both preventive and responsive measures. This limb is addressed in Chaps. 2, 3, 5, 7, 11, 22, and 23. The final component of the Rapid Response System is the Administrative Limb. This limb is responsible for marshalling both personnel and equipment resources. When we at the University of Pittsburgh first started working to improve our ­cardiac arrest response program, we focused on both organizing the responders and overcoming equipment barriers. We found many different types of defibrillators, which led to inefficiencies in equipment use, and costly repairs because of the need to maintain spare parts inventories as well as education needs for our engineers. We worked with our hospital administrators to create a business plan to standardize our defibrillators and crash cart contents, resulting in lower costs and better use of the equipment. Without a strong quality improvement limb to collect and report data, and administrative limb responsive to patient needs, the accomplishment would not have occurred. Since that time, we recognized the need to prevent cardiac arrests by responding sooner to patient deteriorations. Our clinical decision that a response team of critical care clinicians was needed would not have been an implementable conclusion without the resources (including internal ­marketing campaigns) that only administrators and clinical leaders could marshal. It is now being recognized that capturing vital sign data (as frequently as possible) is needed if every patient deterioration is to be assessed and recognized. Some are calling for continuous vital sign monitoring for traditionally unmonitored patients.16,17 Intermittent monitoring provides the requirement of a human-technology interaction, and is usually lower cost. Of course, abnormalities may occur in between assessments, allowing the potential for missing an evolving event for minutes to

2  RRS’s General Principles

17

hours, depending upon the monitoring interval and the specific time of the occurrence relative to the monitoring timetable. Continuous monitoring would likely prevent (or reduce) the occurrence of undetected deterioration; however, it does have major drawbacks worth considering. But moving to an “all patients ­monitored” hospital will require a strong administrative limb to deal with cost and cultural obstacles.

Summary In summary, the Rapid Response System is indeed an integrated system of care. At its best, it requires development and integration of the four limbs of the system. Each limb has a specific goal and place in the chair of care. Each is important to all other pathways of the rapid response system. Most importantly, the degree of development and integration directly affects the effectiveness of the other limbs.

References 1. Bellomo R, Goldsmith D, Uchino S, et al. A prospective before-and-after trial of a medical emergency team. Med J Aust. 2003;179:283–287. 2. Bellomo R, Goldsmith D, Uchino S, et al. Prospective controlled trial of effect of medical emergency team on postoperative morbidity and mortality rates. Crit Care Med. 2004;32:916–921. 3. Buist MD, Moore GE, Bernard SA, Waxman BP, Anderson JN, Nguyen TV. Effects of a ­medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: preliminary study. Br Med J. 2002;324:387–390. 4. DeVita MA, Braithwaite RS, Mahidhara R, Stuart S, Foraida M, Simmons RL. Use of medical emergency team responses to reduce hospital cardiopulmonary arrests. Qual Saf Health Care. 2004;13:251–254. 5. Hillman K, Chen J, Cretikos M, et al. MERIT Study Investigators. Introduction of the medical emergency team (MET) system: a cluster-randomized controlled trial. Lancet. 2005;365: 2091–2097. 6. Kenward G, Castle N, Hodgetts T, Shaikh L. Evaluation of a medical emergency team one year after implementation. Resuscitation. 2004;61:257–263. 7. Chan PS, Khalid A, Longmore LS, Berg RA, Kosiborod M, Spertus JA. Hospital-wide code rates and mortality before and after implementation of a rapid response team. J Am Med Assoc. 2008;300:2506–2513. 8. DeVita MA, Bellomo R, Hillman K, et  al. Findings of the first consensus conference on ­medical emergency teams. Crit Care Med. 2006;34(9):2463–2478. 9. Howell, M. D., Zullo, N., Folcarelli, P., Aronson, M., Moorman, D., Mottley, L., Yang, J., & Sands, K. Monitoring and adjusting a rapid response team implementation using a novel informatics tool. 24th International Conference on Quality in Health Care (ISQuA). 30 September‑3 October 2007 (Boston, MA). 10. Santiano N, Young L, Hillman K, et al. Analysis of Medical Emergency Team calls comparing subjective to “objective” call criteria. Resuscitation. 2009;80(1):44–49. 11. Sakai T, DeVita M. Rapid response system. J Anesth. 2009;23(3):403–408. 12. Foraida MI, DeVita MA, Braithwaite RS, Stuart SA, Mori-Brooks M, Simmons RI. Improving the utilization of medical crisis teams (Condition C) at an urban tertiary care hospital. J Crit Care. 2003;18:87–94.

18

A.D. Rao and M. DeVita

13. Tee A, Calzavacca P, Licari E, Goldsmith D, Bellomo R. Bench-to-bedside review: the MET syndrome ‑ the challenges of researching and adopting medical emergency teams. Crit Care. 2008;12(1):205. 14. Jones D, Baldwin I, McIntyre T, et al. Nurses’ attitudes to a medical emergency team service in a teaching hospital. Qual Saf Health Care. 2006;15:427–432. 15. Braithwaite RS, DeVita MA, Mahidhara R, Stuart S, Simmons RL. Use of Medical Emergency Team (MET) responses to detect medical errors. Qual Saf Health Care. 2004;13:255–259. 16. Taenzer AH, Pyke JB, Mcgrath SP, Bilke GT. Impact of pulse oximetry surveillance on rescue events and intensive care unit transfers. Anesthesiology. 2010;112:282–287. 17. DeVita MA, Smith GB, Adam S, et al. Consensus conference on the afferent limb of rapid response systems: identifying patients at risk. Resuscitation. 2010;81:375–382.

Chapter 3

Measuring and Improving Safety Bradford D. Winters, Peter J. Pronovost, Marlene Miller, and Elizabeth A. Hunt

Keywords  Measuring • Improving • Safety

Introduction It has been a decade since the Institute of Medicine raised the call to action for patient safety in their landmark report, To Err Is Human, which brought to the public’s attention the significant problems with patient safety in our healthcare system.1 This call to action has been heeded by many healthcare leaders, who are actively and vigorously addressing patient safety issues. The healthcare community has worked to educate themselves on methods to improve safety, and strived to execute interventions toward the goal of improving patient safety.2,3 We still have much to do and the science of safety needs to mature rapidly to meet the needs of patients. We especially need to develop effective methods for evaluating the impact of our interventions so that we know what works and where to best invest our resources and answer the question, “Are patients safer?” Ten years later, patients and families want to know if we have made progress. They want to know if the care they are receiving is safer. They want to know if they or their loved ones are less likely to be injured or die as a result of medical care. They do not want our perceptions or predictions. They want evidence to support the notion that we are succeeding. How do we know that our patients are safer and our efforts to improve patient safety are working? Measuring and improving safety is difficult. Not all safety measures lend themselves to examination by randomized, blind, placebo-controlled trials and specific rate reductions. Moreover, the context in which an intervention is implemented can

B.D. Winters (*) Departments of Anesthesiology, Critical Care Medicine and Surgery, The Johns Hopkins University School of Medicine, Meyer 297 600 N Wolfe Street, Baltimore, MD 21298, USA e-mail: [email protected] M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_3, © Springer Science+Business Media, LLC 2011

19

20

B.D. Winters et al.

influence its effect. While some are, we have come to understand that the foundation for success in improvement in-patient safety is the active change from a culture of tolerance for unsafe care to a culture that seeks to eliminate preventable harm. Changing culture is a formidable challenge. Measuring that change and the impact it exerts is almost equally difficult but essential to answering our patients and their families when they ask, “Am I going to be safe?”.2,3 This chapter provides an overview of the issues in measuring patient safety and presents a framework for measuring and improving safety. It is important to recognize that safety is a component of the broader concept of “quality,” which also includes care that is effective, efficient, patient-centered, timely, and equitable.4 The boundaries between these concepts often overlap, and measures can often bridge several categories. For example, is the failure to use an evidence-based therapy a safety measure - a mistake of omission - or an effectiveness measure? Is a complication, such as a catheter-related bloodstream infection that also increases length of stay, a safety or effectiveness measure? For these examples, the answer may be either or both. In terms of understanding whether we have made a positive impact, the distinction is less important than having a valid measure. Thus, in this chapter, we will use the term “safety” to refer to both safety and effectiveness.

Approach for the Organizational Evaluation of Patient Safety Donabedian’s approach to measuring quality of care ­ evaluating how we organize care (the structures), what we do (the processes), and the results we obtain (the outcomes) - also provides a framework for institutions to measure safety.5 Many institutional efforts to improve safety focus on structural measures, such as policies and procedures.6 Institutions may also measure processes and outcomes, although these are generally more difficult to develop and collect than structural measures. For example, organizations may measure how often certain aspects of safe and effective care were performed (a process), or how often certain complications occurred (an outcome).7,8 Unfortunately, not all institutions measure all three. While process and outcome measures are generally preferable to structural measures, they are not sufficient. Generally, process and outcome measures are rates that include a numerator and denominator, but not all measures of safety can, or should, be presented as rates. For example, a single episode of potential harm or actual harm (such as the failure to rescue a single deteriorating patient) may be statistically insignificant in terms of a measure such as in-hospital mortality, but due to the circumstances that led to that failure may be sufficient to trigger an organizational change of great impact. If organizations do not recognize and learn from such single episodes, they fail to maximize opportunities to improve safety. Analysis of multiple single episodes may lead to recognition of patterns that ­further provide insights into opportunities for safety interventions. Additionally, measurement of rates is resource-intensive and not feasible for every type of ­medical error.

3  Measuring and Improving Safety

21

Along with the ability to learn, many other aspects of an organization’s culture have a significant impact on safety.9,10 In aviation, changes in culture, as opposed to technology, have been responsible for most of the advancements in safety over the last two decades.9,11 Within healthcare, communication failures are a common cause of sentinel events.12 (www.jointcommission.org). Indeed, communication patterns within an organization are a reflection of the existing culture. Thus, the measure of both organizational learning and culture may provide insight into an organization’s measure of safety. W. Edwards Deming once said, “There is no true value of anything that is measured; change the method of measurement and you change the result.” The same concept applies to measuring safety. In the absence of universally agreed-upon standard definitions and methods to measure patient safety, including methods for risk adjustment (e.g., healthcare-acquired infections),13 it is unlikely that national measures of patient safety will be effectively achieved. There are multiple ways to measure each area of patient safety. For medication safety, we can have a structural measure, such as the presence of computerized physician order entry; a process measure, such as prescribing errors; or an outcome measure, such as adverse drug events. Moreover, each category (structure, process, or outcome) can be measured in multiple ways. For example, the methods of surveillance for evaluating adverse drug events - many of which use self-reported events, with the numerator being how the adverse event is defined and the denomi­ nator being either patient, number of patient days, or dose - vary widely (see Table 3.1).14–18 Which method is most “correct” is unclear. The result may vary

Table 3.1  Sample of methods to measure medication Number Study studied Numerator Denominator Record Disabling Leape, et al. 30,195 reviewed/ records adverse NEJM admission events (1991) Prescribing Number 289,411 Lesar, errors of orders medication Briceland written orders/ JAMA 1 year (1990) Prescribing Medication 1 year of Lesar, errors orders prescribing Briceland, written errors Stein, detected JAMA and (1997) averted by pharmacist Number Adverse Cullen et al. 4,031 adult of patient drug admissions Crit Care days events over Med 6 months (1997)

Assessed by Physician Reviewer

Rate of events 3.7 per 100 admissions

Physicians

3.13 errors for each 1,000 orders 3.99 errors Pharmacists, per retrospectively 1,000 evaluated orders by a physician and 2 pharmacists Self-report by nurse and pharmacists, daily review of all charts by nurse investigators

19 events per 1,000 ICU patient days

22

B.D. Winters et al.

but they may all be “correct.” In the absence of standardized definitions, comparisons within and between institutions are problematic.19,20 Even with standard definitions, there is concern that comparing outcomes among hospitals is neither scientifically sound nor fair, with differences influenced by insufficient risk adjustment and random error rather than variations in-patient safety.8,19–21 In the face of the movement towards “pay-for-performance” driven measures, this is especially worrisome. In addition, the context in which an intervention is implemented (its staff, resources, leadership, etc.) can influence the impact of an intervention. It is naive to believe that interventions will be equally effective in all healthcare organizations in which they are implemented. Context matters. Yet context should not be viewed as static but rather as dynamic leading to better understanding of mechanism. In basic science, how genes turn on and off, how proteins fold, and how receptors bind was once context. These are now mechanisms and the target for therapies. Likewise, how culture influences outcomes, how leadership drives improvement, and how teamwork impact patients is context and with robust science. These will increasingly become targets for interventions. Based on this background, our approach to evaluating patient safety at the organizational level has four components and prompts the institution to answer the following four questions: 1. How often do we harm patients? 2. How often do patients receive the interventions they should? 3. How often do we learn from our mistakes; and 4. How well have we created a culture of patient safety? This framework is presented in Table 3.2. Table 3.2  Framework for an institutional scorecard for patient safety and effectiveness Example from department Domain Definition of anesthesiology How often do we harm Measures of health careBloodstream infections patients? acquired infections Surgical site infections Using either nationally validated How often do patients process measures, or a receive the interventions validated process to develop a they should? measure, what percentage of patients receive evidence-based interventions

Use of peri-operative beta blockers Elevation of head of bed in mechanically ventilated patients Rates of postoperative hypothermia

How often do we learn from our mistakes?

What percentage of months does each area learn from mistakes

Monitor percentage of months in which the department creates a shared story

How well have we created a culture of patient safety?

Annual assessment of safety culture at the unit level

Percentage change in culture scores for each care area

3  Measuring and Improving Safety

23

Measuring Defects To measure safety, we often estimate reliability in defects per unit, or Sigma, with 1 Sigma defined as defects per units of 10, 2 Sigma as defects per unit of hundreds, 3 Sigma defects per thousand, 4 Sigma defects per ten thousand, 5 Sigma defects per hundred thousand, and 6 Sigma defects per million. Measuring safety is difficult, and the methods are evolving.8 Often we are not clear regarding the unit of analysis for the denominator. In Rapid Response Systems (RRSs), for example, is the appropriate denominator the total number of hospital admissions, or the number of admissions who have no “Do Not Resuscitate” orders? The defect rate can be influenced significantly by the chosen denominator. Measures are often chosen based on their ease of collection (commonly from institutional databases that are kept to satisfy regulatory requirements). They may not reflect the true impact of the safety intervention. There may be measures that better define the impact of the intervention. For example, in RRSs, mortality data is usually analyzed based on total in-hospital mortality because it is easy to glean from commonly kept databases. Moreover, the staff may not be aware of the quality and safety measures collected by the institution and these measures may lack meaning for the frontline staff expected to use them to improve safety. System-level measures need to be meaningful to the workers in their local areas. In our zeal to improve patient safety we run the risk of creating measures of safety as though the goals were based on increasing the number of identified defects rather than actually learning from those defects. In this haste, we have often compromised validity. Many organizations use rates of self-reported adverse drug events as a measure of safety without recognizing that, as for all outcome measures, variations in the method of data collection/definition/data quality, case-mix, and quality, as well as chance, influence outcomes.19 Changes in these rates may reflect an improved culture of safety but they do not indicate that we have learned from them. Moreover, variations in data quality and case-mix are likely to be far greater than the variation in safety, which limits our ability to make inferences about quality of care from these measures. Measures of safety and quality must be important, usable, scientifically sound, and feasible. Importance and usability are value judgments that are typically made by the group, institution, or organization that decides to measure a particular area. Importance is relative and usability refers to its ease of use by those who seek to directly improve safety. Scientifically sound refers to validity and reliability. An indicator is deemed valid if the following criteria are met (www.rand. org)22: • Adequate scientific evidence or professional consensus exists supporting the indicator. • There are identifiable health benefits to patients who receive care specified by the indicator. • Based on experience, health professionals with significantly higher rates of adherence to an indicator would be considered higher-quality providers.

24

B.D. Winters et al.

• Most factors that determine adherence to an indicator are under the control of the health professional (or are subject to influence by the health professional, such as smoking cessation). An indicator is considered to be feasible if 22: • The information necessary to determine adherence is likely to be found in a ­typical medical record. • Estimates of adherence to the indicator based on medical record data are likely to be reliable and unbiased. • A reliable measure produces similar results when measurement is repeated. In many efforts to measure quality of care and safety, the measures are collected without the support of additional staff. With such human resource limitations, the feasibility of a measure figures prominently in its success. To measure quality, we need valid numerators (defects) and denominators (risk pool). To be scientifically sound, both the numerator and denominator must be valid and reliable. Yet there are challenges in measuring both. What constitutes a defect is not well defined in most healthcare areas limiting the ability to measure a numerator. For example, substantial evidence suggests that controlling blood sugar in patients in an intensive care unit (ICU) reduces mortality, yet we do it infrequently. But what might constitute a defect in glucose control? Is it a single high blood sugar, two high sugars, or the average sugar over some period above a defined threshold? In addition, it is unclear what the unit of analysis should be for the denominator. The choice of denominator can change performance by several Sigmas. For ­example, aviation and anesthesiology changed its denominators from minutes flown to takeoffs and landings, and minutes of care to a case, respectively. Thus, if an average flight was over 100 miles, or an average anesthesia case 100 min, the defect rate could change 2 Sigmas without any change in safety. Consider also ways to measure rates of failed extubation in the ICU: Should the denominator be the patient, the ventilator day, or the number of attempted extubations? Unfortunately there are often trade-offs between validity and feasibility of data collection. Often the better the validity of the measure, the greater the workload required to collect it. This may increase both human and other resource needs to the point where feasibility suffers. The converse is also often true where easily collected measures may not be the most valid. It is also important to distinguish whether we are measuring the reliability of a process (what we do) or an outcome (the results we get). While commercial aviation is believed to perform at 6 Sigmas for crashes (outcome), it performs at 1 or 2 Sigmas for on-time departures. Intuitively, outcome measures are more appealing than process measures, yet measuring outcomes pose added risk for bias that often leads to little or no useful information.19,23 Process measures may, like on-time departures, have a more direct impact on the common experience in healthcare. Reliability of an outcome measure can be influenced by variations in the methods of surveillance, in methods of data collection and definitions, in case-mix, in true variation in safety, and random error.23 Among institutions, variation in quality is

3  Measuring and Improving Safety

25

often significantly smaller than variation of other variables. In healthcare, we need to work toward standardized measures of reliability. One excellent example is the National Nosocomial Infections Surveillance (NNIS) program (now called the NHSN) that provides standardized methods to monitor rates of health care-acquired infections.13 Evidence-based processes of care (defects of omission) lend themselves to monitoring rates. However, we currently only have a limited number of validated process measures. A more diverse group of quality measures is needed and these should be appropriately monitored as defect rates. In addition, healthcare organizations need to recognize that the value of some defects lies solely in learning from the numerator; the costs of obtaining an appropriate denominator, even if methodologically feasible, may be prohibitive. Measures of safety need to be valid, yet we can learn from defects that lack denominators. How do we select measures? W. E. Deming again provides some guidance. Measures should be selected to optimize learning: that is, ensure the measure has face validity - is it important to the person expected to use the data? To develop measures that are clinically meaningful, we need the combined input of diverse and independent sources and apply methodological rigor. For example, the exposure risk for a failed extubation is an attempted extubation. Yet rates of failed extubation are often presented using patients or ventilator days as the denominator. 24 To ­estimate feasibility, first test-run the data collection tools. Moreover, the measurement of safety should be approached with the same rigor as that applied in clinical research. Whether we are measuring bloodstream infections as part of a federally funded trial or for hospital safety efforts, we need a valid measure of infections. Much research is needed to advance the science of measuring defects. Given this, what are some possible measures of safety for RRSs? Unanticipated ICU admission, in-hospital mortality and the incidence of cardio-respiratory arrest are commonly used measures, and while they all seem to meet many of the criteria, each has potential problems. For example, unanticipated ICU admission lacks validity. While the intuitive goal would be to reduce this rate, we do not know whether an increase or decrease is high-quality care. Patients who are prevented from deteriorating to arrest may still be sick enough to require ICU admission and since those who arrest and die go to the morgue, an increase in this measure may, in fact, be an indicator of better quality care. Additionally, local culture and general ward resources may have a strong influence on this outcome, leading to wideranging results across institutions. On the other hand, use of chest compressions or intubations may be an appropriate numerator for defects. In addition to the numerator, we need to consider an appropriate denominator or risk group. Although hospital admissions are used commonly as the denominator, patient days may be a more valid denominator. A patient’s risk for arrest is influenced by, among other things, the length of time he is in the hospital. The longer a patient is in the hospital, the greater the risk. Hospital mortality and length of stay may be measures of safety for RRSs but, as with all outcome measures, case-mix will significantly influence these outcomes making comparisons among hospitals difficult to interpret.23 As long as a hospital does not change a product line, case-mix within a hospital is relatively constant, making changes in mortality rate within a hospital

26

B.D. Winters et al.

potentially important and measurable. However, even an apparently unbiased outcome such as in-hospital mortality may not be using the most valid denominator. A certain portion of hospital mortality is not preventable and cannot be expected to be reduced by RRSs. Defining what is preventable and non-preventable is much more difficult and this choice of denominator may lead to different results. Much more effort is needed to produce scientifically sound and feasible measures of safety for RRS. Process measures are an alternative to outcome measures that have only recently been explored as an opportunity for RRS to have a positive impact. Recent evidence suggests that RRSs can have a positive impact on process measures such as appropriate institution of “Not for Resuscitation” status25 and implementing early goal-­ directed fluid resuscitation for severe sepsis and septic shock.26 These types of patient safety and quality measures deserve more research, especially in the area of RRSs. We can also measure context. There are multiple tools to measure culture and scores on culture that can be linked to process and outcomes to better understand context. In addition, we have developed standardized tools (called the team checkup tool) to measure leadership and team behaviors that can also be linked to process and outcome measures. Finally, qualitative analysis of context (asking staff to reflect on what worked and what did not) can help develop conceptual models and hypothesis that can later be tested.

How Might We Improve Safety? There are many examples of nearly flawless, highly reliable systems from nuclear power to commercial airlines to auto racing pit crews. These systems have in common standardized processes, specified roles, high levels of training and education, and a culture dedicated to high performance. Processes are repeatedly rehearsed until a high degree of fidelity is achieved. Thus, despite the high-risk nature of many of these systems, their safety and performance rates are excellent. How might these systems inform patient safety? Virtually all organizations are aware of the need to improve patient safety, and most have committed to doing so. Yet fewer have a clear plan of attack to accomplish this goal. The drive to improve patient safety is still new in healthcare despite the decade since the IOM’s call to action, and culture change takes effort and time. We must view healthcare delivery as a science as well as an art if we are to improve safety. Standardization of processes and applying scientific methods can help achieve higher levels of fidelity and reduce the defects that imperil our patients. Here we present an overview of measuring and reducing defects in healthcare and suggest some potential system-level measures of safety.

A Framework to Improve Reliability In healthcare, most of our processes are between 1 and 2 Sigmas. For a wide variety of processes, patients can rely on receiving the interventions they should half the time,

3  Measuring and Improving Safety

27

or 1 Sigma.27 For some outcomes, defects are 2 to 3 Sigmas - for example, catheter -related bloodstream infection rates and rates of ventilator-associated pneumonia are typically between 1 and 20 per 1,000 catheter or ventilator days, respectively.13,28 Nevertheless, there are some notable exceptions in anesthesiology and in transfusion medicine that are estimated to be 4 or 5 Sigmas (defects per 10,000 or 100,000).29,30 Improving reliability first depends on creating a culture of safety where the entire care team makes the patient their “North Star,” according to which they ­create and implement common goals. A culture of safety allows all members of the care team to speak up when they have concerns and listen when others voice ­concerns. It also creates a “zero tolerance” attitude towards defects. Next comes standardization, specifying what is done and when it should be done.31–33 This contrasts with traditional practice in which the “art of medicine” and “eminence-based medicine” trumps the science and “evidence-based medicine” - individual caregiver practice is unstructured and at times appears chaotic (i.e., care givers do what they want, when they want). In the ICU, the therapies that a patient receives depend more on who is making the rounds, rather than what the evidence suggests resulting in defects in the 1–2 Sigma range. Blood banking approaches the reliability of non-healthcare settings such as commercial aviation because they are standardized. Without standardization, reliability will remain at 10−1 imparting a significant toll on patients. An important aspect of standardization is to simplify or reduce complexity. Every step is a process that has an independent probability of failure. As such, processes that have five steps are more likely to fail than those that have 4, 3, or 2 steps. An analogy is the telephone game, in which a story is told through a series of people: the risk factors for getting a garbled story (a defect) at the end are defined by how complex the story is and how many people it passes through. While this may be an oversimplification, as there are feedback loops that may catch mistakes if we reduce the number of steps in a process, we have a higher probability of improving reliability. Undoubtedly this is an oversimplification, since there are feedback loops that may catch mistakes. Nevertheless, it is helpful to consider ­simplification when we examine our work processes. For example, in our effort to eliminate catheter-related bloodstream infections (CRBSI), our team noted that the operator often had to obtain the equipment for insertion from many different sources. This often led to missing or erroneous items requiring the operator to break sterility in order to get them, or, worse, do without. The “line cart” was instituted as a mobile central location for all supplies necessary for central catheter insertion. This reduces complexity and contributes to the operator’s adherence to our central line insertion guidelines. A second aspect of standardization is ensuring that evidence is translated into practice. Evidence-based therapies that can reduce harm are often not translated into practice because, while significant research efforts are made in developing the therapies, little effort is made to determine how to best deliver these therapies. One model34 designed to address this problem is based on five key components: 1. Focus on systems rather than individual patients; 2. Engage local multi-disciplinary teams to take ownership of the initiative;

28

B.D. Winters et al.

3. Create centralized support for the technical aspects; 4. Encourage local adaptation; and 5. Create a collaborative culture within the local unit and larger system. The specific steps of the model include summarization of the evidence, identifying local barriers to implementation, performance measurement and ensuring all patients receive the intervention. Successful use of this model to support standardization depends also on creating and sustaining the culture of safety. This can be achieved by using the Comprehensive Unit Safety Program (CUSP).35 The CUSP includes five steps: 1. Educate staff on the science of safety; 2. Identify hazards; 3. Partner a senior executive the CUSP team; 4. Learn from one defect per month; and 5. Implement teamwork tools that address communication struggles. The learning objectives include the following: 1. Understand that safety is a property of the system; 2. Understand basic principles of safe design (these include standardizing work, creating independent checks [checklists] for key processes, and learning from mistakes); 3. Recognize that the principles of safe design apply to technical as well as team work; and 4. Understand that teams make wise decisions when there is diverse and independent input. Using strategies such as CUSP can help cement these approaches and concepts into the institutional culture. When this occurs, safety becomes of paramount importance to the whole system. Third, we need to identify and learn from defects as described in the CUSP model. This involves creating independent checks to identify defects. A significant challenge we face in healthcare is developing a shared definition or concept of a defect. To illustrate, we developed a glucose protocol for our ICU, but were only capturing about 80% of patients. To improve reliability, we needed an independent check to identify defects but we had not defined a defect. Although we could have defined it in multiple ways, we decided that in the morning during the shift change, the nurses would review a patient’s glucose and if two blood sugars were out of range, they would talk to the physician and implement the protocol. We defined the defect first and then created an independent check to identify it. To learn from defects, we need to investigate what went wrong and make recommendations for improvement. We have developed a tool kit to learn from a defect. This tool kit (see Table 3.3) helps uncover what happened, why it happened, and what must be done to fix the defect. It differs from Root Cause Analysis (RCA), commonly used by institutions for evaluating sentinel and other critical events, in that while it seeks to answer these questions, it also addresses mitigating factors that may have ameliorated the harm. This has value for application to other defects and processes besides the one at hand.

3  Measuring and Improving Safety

29

Table 3.3  How to investigate a defect Problem statement:  Health care organizations could increase the extent to which they learn from defects What is a defect?  A defect is any clinical or operational event or situation that you would not want to happen again. These could include incidents that you believe caused a patient harm or put patients at risk for significant harm Purpose of tool:  The purpose of this tool is to provide a structured approach to help caregivers and administrators identify the types of systems that contributed to the defect and follow up to ensure safety improvements are achieved Who should use this tool? Clinical departmental designee at morbidity and mortality rounds Patient care areas as part of the Comprehensive Unit-based Safety Program (CUSP) All staff involved in the delivery of care related to this defect should be present when this defect is evaluated. At a minimum, this should include the physician, nurse, and administrator, and others as appropriate (e.g., medication defect includes pharmacy, equipment defect includes clinical engineering) How to use this tool:  Complete this tool on at least 1 defect per month. In addition, departments should investigate all of the following defects: liability claims, sentinel events, events for which risk management is notified, case presented to morbidity and mortality rounds and health care–acquired infections Investigation process I. Provide a clear, thorough, and objective explanation of what happened. II. Review the list of factors that contributed to the incident and check off those that negatively contributed and positively contributed to the impact of the incident. Negative contributing factors are those that harmed or increased risk of harm for the patient; positive contributing factors limited the impact of harm III. Describe how you will reduce the likelihood of this defect happening again by completing the table. List what you will do, who will lead the intervention, when you will follow up on the intervention’s progress, and how you will know risk reduction has been achieved Investigation process I. What happened?  (Reconstruct the timeline and explain what happened. For this investigation, put yourself in the place of those involved in the event as it were unfolding, to understand what they were thinking and the reasoning behind their actions/decisions when the event occurred.) An African American male >65 years old was admitted to a cardiac surgical ICU in the early morning hours. The patient was status-post cardiac surgery and on dialysis at the time of the incident. Within two hours of admission to the ICU it was clear that the patient needed a transvenous pacing wire. The wire was threaded using an IJ Cordis sheath, which is a stocked item in the ICU and standard for pulmonary artery catheters, but not the right size for a transvenous pacing wire. The sheath that matched the pacing wire was not stocked in this ICU, because transvenous pacing wires are used infrequently. The wire was threaded and placed in the ventricle but staff soon realized that the sheath did not properly seal over the wire, thus introducing risk of an air embolus. Since the wire was pacing the patient at 100%, there was no possibility for removal at that time. To reduce the patient’s risk of embolus, the bedside nurse and resident sealed the sheath using gauze and tape II. Why did it happen? Below is a framework to help you review and evaluate your case Please read each contributing factor and evaluate whether it was involved, and if so, whether it contributed negatively (increased harm) or positively (reduced impact of harm) to the incident (continued)

30

B.D. Winters et al.

Table 3.3  (continued) Contributing factors (example)

Negatively contributed

Positively contributed

Patient factors Patient was acutely ill or agitated (Elderly patient in renal failure, secondary to congestive heart failure.) There was a language barrier (Patient did not speak English.) There were personal or social issues (Patient declined therapy.) Task factors Was there a protocol available to guide therapy? (Protocol for mixing medication concentrations is posted above the medication bin.)

XX

Were test results available to help make care decision? (Stat blood glucose results were sent in 20 min.) Were tests results accurate? (Four diagnostic tests done; only magnetic resonance imaging [MRI] results needed quickly — results faxed.) Caregiver factors Was the caregiver fatigued? (Tired at the end of a double shift, nurse forgot to take a blood pressure reading.) Did the caregiver’s outlook/perception of own professional role impact on this event? (Doctor followed up to make sure cardiac consultation was done expeditiously.) Was the physical or mental health of the caregiver a factor? (Caregiver was having personal issues and missed hearing a verbal order.) Team factors Was verbal or written communication during handoff clear, accurate, clinically relevant, and goal-directed? (Oncoming care team was debriefed by outgoing staff regarding patient’s condition.) Was verbal or written communication during care clear, accurate, clinically relevant, and goal-directed? (Staff was comfortable expressing concern regarding high medication dose.) Was verbal or written communication during crisis clear, accurate, clinically relevant and goal-directed? (Team leader quickly explained and directed the team regarding the plan of action.) Was there a cohesive team structure with an identified and communicative leader? (Attending physician gave clear instructions to the team.) Training and education factors Was the caregiver knowledgeable, skilled, and competent? (Nurse knew dose ordered was not standard for that medication.) Did the caregiver follow the established protocol? (Provider pulled protocol to ensure steps were followed.) Did the caregiver seek supervision or help? (New nurse asked preceptor to help mix medication concentration.)

XX

(continued)

3  Measuring and Improving Safety

31

Table 3.3  (continued) Information technology/computerized physician order entry factors Did the computer/software program generate an error? (Heparin was chosen, but Digoxin printed on the order sheet.) Did the computer/software malfunction? (Computer shut down in the middle of provider’s order entry.) Did the user check what was entered to make sure it was correct? (Caregiver initially chose 0.25 mg, but caught error and changed it to 0.025 mg.) Local environment factors Was adequate equipment available and was it working properly? (There were two extra ventilators stocked and recently serviced by clinical engineering.) Was operational (administrative and managerial) support adequate? (Unit clerk out sick, but extra clerk sent to cover from another unit.) Was the physical environment conducive to enhancing patient care? (All beds were visible from the nurse’s station.) Was enough staff on the unit to care for patient volume? (Nurse ratio was 1:1.) Was there a good mix of skilled and new staff? (A nurse orientee was shadowing a senior nurse and an extra nurse was on to cover the senior nurse’s responsibilities.) Did workload impact the provision of good care? (Nurse caring for 3 patients because nurse went home sick.)

XX

Institutional environment factors Were adequate financial resources available? (Unit requested experienced patient transport team for critically ill patients, and one was made available the next day.) Were laboratory technicians adequately in-serviced/educated? (Lab technician was fully aware of complications related to thallium injection.) Was there adequate staffing in the laboratory to run results? (There were 3 dedicated laboratory technicians to run stat results.) Were pharmacists adequately in-service/educated? (Pharmacists knew and followed the protocol for stat medication orders.) Did pharmacy have a good infrastructure (policy, procedures)? (It was standard policy to have a second pharmacist do an independent check before dispensing medications.) Was there adequate pharmacy staffing? (There was a pharmacist dedicated to the ICU.) Does hospital administration work with the units regarding what and how to support their needs? (Guidelines established to hold new ICU admissions in the emergency department when beds are not available in the ICU.) III. How will you reduce the likelihood of this defect happening again?

Specific things to be done to reduce the risk of the defect

Who will lead this effort?

Follow-up date

Bedside nurse called Central Supply and requested pacing wires and matching sheaths be packaged together

Bedside nurse

1 week

How will you determine the risk is reduced? (action items) Supplies are packaged together

32

B.D. Winters et al.

These steps: 1. Create a culture of safety; 2. Standardize what and when actions are done; and 3. Identify and learn from defects - provide a framework to improve reliability. Transfusion medicine offers an example of how the application of these principles created a high reliability process: using discharge data, the estimated incidence of a transfusion reaction in healthcare is 4 per 100,000. How did they achieve such success? They standardized, created independent checks for key processes, and learned from defects (see Table 3.3). Physicians often resist standardization and outside regulators, such as the Joint Commission. All too often they are relied upon to force the change in culture. This is in fact the case for RRSs. It took the Joint Commission requiring, as one of its patient safety goals for 2009, that hospitals implement better systems to respond to deteriorating patients on general hospital wards (www.jointcommission.org). While they did not explicitly require Medical Emergency or Rapid Response Teams (RRTs), these are a logical choice to meet this requirement. The concept of physician autonomy is deeply ingrained in the practice of medicine and is often at odds with the need to standardize practice. When physicians are asked to relinquish their autonomy in order to standardize practice, we need to be sure that those standards are just, wise and supported by the best evidence possible. The process by which these standards are developed needs to be transparent with the full account of risks, benefits and cost estimates considered.36 Although regulations may be an important driver for standardization and culture change, there are far too many processes to rely on this strategy alone. Indeed, we need the courage of leaders within our healthcare systems to support standardization and culture change. To date, most efforts to improve reliability of evidence-based therapies in healthcare have focused on practice guidelines: a series of conditional probability, or “if yes then ‘x’” statements.34 The Centers for Disease Control and Prevention’s (CDC’s) guidelines for preventing catheter-related bloodstream infections, a nearly 100-page document (www.cdc.gov), is one example. It is not surprising that the use of guidelines alone has met with little success.37,38 Under time pressure, it is difficult for care givers to think in terms of conditional probabilities.39 An additional problem is that most guidelines have been developed for physicians, ignoring other members of the care team who could provide an independent check. A checklist is one tool to help standardize work processes and increase reliability. Checklists have led to significant improvements in aviation, nuclear power, and rail safety. Useful checklists transform a complex diagnostic/­ therapeutic decision into a series of simple yes/no tasks. It is first necessary to identify which parts of a task are “mission critical,” especially those supported by strong evidence, and develop measures for those tasks. In addition to the “line cart” for central line insertion, we developed a checklist based on five key ­processes distilled from the CDC guidelines for preventing catheter-related infection and virtually eliminated this defect in our ICUs.28 This kind of checklist can

3  Measuring and Improving Safety

33

also be used to monitor performance, with each item serving as a process measure of quality of care.7,40 Measurement then becomes a tool to improve performance.

Why RRSs Can Improve Safety Rapid Response Systems are well grounded in the science of safety outlined above. In many, and perhaps even most, sentinel events, someone either did not speak up, or spoke up but was not heeded because of a hierarchical or punitive culture (people had previously been reprimanded when they spoke up). With RRSs, frontline staff are empowered - indeed encouraged - to call the MET or RRT when they are concerned. This requires a strong culture of safety. Frontline staff is also educated to call for help based on a standardized set of parameters, in the absence of which the trigger for calling for help happens too late once an arrest has occurred. The RRS identifies problems early, when there is still time to recover from them. As such, RRSs are based on sound safety theory and would be expected to improve safety.

Summary The science of measuring safety is gradually maturing. Some measures of safety lend themselves to rates, while others do not. We have described an approach for organizations to answer the question, “Are patients safer?” We also have summarized the issues regarding measuring and improving reliability, and provided a framework for improving safety. With these measures, we defer to the wisdom of care givers and administrators to identify and mitigate safety concerns, but also attempt to provide a framework to assist the caregiver with safety efforts. The need to improve quality and safety is significant, and hospitals are learning how to accomplish this goal. Rapid Response Systems are grounded in safety theory and offer the promise to reduce patient harm. While imperfect, the current data would suggest that they do. We hope that practical strategies such as those proposed here will help move safety and quality efforts forward.

References 1. Kohn LT, Corrigan JM, Donaldson MS, eds. To Err Human: Building a Safer Health System. Washington, DC: National Academies Press; 2000. 2. Altman DE, Clancy C, Blendon RJ. Improving patient safety – five years after the IOM report. N Engl J Med. 2004;351(20):2041–2043. 3. Wachter RM. The end of the beginning: patient safety five years after “To Err Is Human.” Health Aff. 2004:1–12.

34

B.D. Winters et al.

4. Crossing the Quality Chasm: a New Health System for the 21st Century. Committee on Quality of Health Care in America, Institute of Medicine. Washington, DC: National Academies Press; 2001. 5. Donabedian A. Evaluating the quality of medical care. Millbank Mem Fund Q. 1966;44(3): 166–206. 6. Paine LA, Baker DR, Rosenstein B, Pronovost P. The Johns Hopkins Hospital: identifying and addressing risks and safety issues. Jt Comm J Qual Saf. 2004;30(10):543–550. 7. Haya R, Rubin H, Pronovost PJ, Diette G. The advantages and disadvantages of process-based measures of health care quality. Int J Qual Health Care. 2001;13(6):469–474. 8. Pronovost PJ, Nolan T, Zeger S, Miller M, Rubin H. How can clinicians measure safety and quality in acute care? Lancet. 2004;363(9414):1061–1067. 9. Sexton JB, Thomas EJ, Helmreich RL. Error, stress, and teamwork in medicine and aviation: cross-sectional surveys. BMJ. 2000;320(7237):745–749. 10. Shortell SM, Marsteller JA, Lin M, et al. The role of perceived team effectiveness in improving chronic illness care. Med Care. 2004;42(11):1040–1048. 11. Sexton JB, Klinect JR. The link between safety attitudes and observed performance in flight operations. In: Proceedings of the 11th International Symposium on Aviation Psychology. Columbus, OH: The Ohio State University; 2001:7–13. 12. Pronovost PJ, Weast B, Bishop K, et al. Senior executive adopt-a-work unit: a model for safety improvement. Jt Comm J Qual Saf. 2004;30(27):59–68. 13. NNIS System. National Nosocomial Infections Surveillance (NNIS) system report, data ­summary from January 1992 through June 2003, issued August 2003. Am J Infect Control. 2003;31(8):481–498. 14. Bates DW, Leape LL, Cullen DJ, et  al. Effect of computerized physician order entry and a  team intervention on prevention of serious medication errors. JAMA. 1998;280(15): 1311–1316. 15. Flynn EA, Barker KN, Pepper GA, Bates DW, Mikeal RL. Comparison of methods for detecting medication errors in 36 hospitals and skilled-nursing facilities. Am J Health Syst Pharm. 2002;59(4):436–446. 16. Lesar TS, Briceland LL, Delcoure K, Parmalee JC, Masta-Gornic V, Pohl H. Medication prescribing errors in a teaching hospital. JAMA. 1990;263(17):2329–2334. 17. Lesar TS, Briceland L, Stein DS. Factors related to errors in medication prescribing. JAMA. 1997;277(4):312–317. 18. Leape LL, Cullen DJ, Clapp MD, et  al. Pharmacist participation on physician rounds and adverse drug events in the intensive care unit. JAMA. 1999;282(3):267–270. 19. Lilford RJ, Mohammed MA, Braunholtz D, Hofer TP. The measurement of active errors: methodological issues. Qual Saf Health Care. 2003;12(suppl 2):ii8–ii12. 20. Hayward RA, Hofer TP. Estimating hospital deaths due to medical errors: preventability is in the eye of the reviewer. JAMA. 2004;286(4):415–420. 21. Cook DJ, Montori VM, McMullin JP, Finfer SR, Rocker GM. Improving patients’ safety locally: changing clinician behaviour. Lancet. 2004;363(9416):1224–1230. 22. Brook RA. The RAND/UCLA Appropriateness Method. Methodology Perspectives. AHCPR 95–0009. Rockville, MD: Public Health Service; 1994:59–70. 23. Lilford R, Mohammed MA, Spiegelhalter D, Thomson R. Use and misuse of process and outcome data in managing performance of acute medical care: avoiding institutional stigma. Lancet. 2004;363(9415):1147–1154. 24. Pronovost PJ, Jenckes M, To M, et al. Reducing failed extubations in the intensive care unit. Jt Comm J Qual Improv. 2002;28(11):595–604. 25. Jones DA, McIntyre T, Baldwin I, Mercer I, Kattula A, Bellomo R. The medical emergency team and end-of-life care: a pilot study. Crit Care Resusc. 2007;9(2):151–156. 26. Sebat F, Musthafa AA, Johnson D. Effect of a rapid response system for patients in shock on time to treatment and mortality during 5 years. Crit Care Med. 2007;35(11):2568–2575. 27. McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med. 2003;348(26):2635–2645.

3  Measuring and Improving Safety

35

28. Berenholtz SM, Pronovost PJ, Lipsett PA, et  al. Eliminating catheter-related bloodstream infections in the intensive care unit. Crit Care Med. 2004;32(10):2014–2020. 29. Romano PS, Geppert JJ, Davies S, Miller MR, Elixhauser A, McDonald KM. A national profile of patient safety in U.S. hospitals. Health Aff. 2003;22(2):154–166. 30. Zhan C, Miller MR. Excess length of stay, charges, and mortality attributable to medical injuries during hospitalization. JAMA. 2004;290(14):1868–1874. 31. Reason J. Combating omission errors through task analysis and good reminders. Qual Saf Health Care. 2002;11(1):40–44. 32. Reason J. Managing the risks of organizational accidents. Aldershot: Ashgate Publishing Ltd; 1997. 33. Weick KE, Sutcliffe KM. Managing the Unexpected: Assuring High Performance in an Age of Complexity. San Francisco: Jossey-Bass; 2001. 34. Pronovost PJ, Berenholtz SM, Needham D. Translating evidence into practice: a model for large scale knowledge translation. BMJ. 2008;377:a1714. 35. Pronovost PJ, Berenholtz SM, Goeschel C. Improving patient safety in intensive care units in Michigan. J Crit Care. 2008;23(2):207–221. 36. Matthews SC, Pronovosot PJ. Physician autonomy and informed decision making: Finding the balance for patient safety and quality. JAMA. 2008;300(24):2913–2915. 37. Grol R. Improving the quality of medical care: Building bridges among professional pride, payer profit, and patient satisfaction. JAMA. 2001;286(20):2578–2585. 38. Gross PA, Greenfield S, Cretin S, et  al. Optimal methods for guideline implementation: ­conclusions from Leeds Castle meeting. Med Care. 2001;39(8 suppl 2):II85–II92. 39. Klein GA. Sources of Power: How People Make Decisions. Cambridge Massachusetts Institute of Technology: MIT Press; 1999. 40. Haya R, Rubin H, Pronovost P, Diette G. Methodology matters. From a process of care to a  measure: The development and testing of a quality indicator. Int J Qual Health Care. 2001;13(6):489–496.

Chapter 4

Integrating a Rapid Response System into a Patient Safety Program John Gosbee

Keywords  Integrating • MET • Patient • Safety • Program • Rapid • Response

Overview Since at least the publication of the Institute of Medicine’s report To Err Is Human,1 most healthcare organizations have been struggling to find and eliminate hazards. Their struggle arises from the complex mixture of issues that plague any organization dealing with the seemingly easy problems to be solved by a new safety program. Many healthcare organizations soon realize they are dealing with organizational psychology issues that require tools from change management. Somewhat fewer facilities are aware of the problems ingrained in human factors engineering of systems, devices, and tools. We will define these terms and how they apply to Rapid Response Systems (RRS) and their efferent limb, the Medical Emergency Team (MET) and Rapid Response Team (RRT) throughout this chapter. An MET or RRT response is not just a wonderful tool to improve morbidity and mortality associated with hospital medical crises and cardiopulmonary resuscitation, it is also an indirect tool to address the struggles to improve quality and safety throughout a healthcare organization. Conceptually and empirically, most hospitals will likely need RRS programs due to findings from human factors engineering and healthcare.

J. Gosbee (*) Human Factors Engineering & Healthcare Specialist, Red Forest Consulting, LLC and University of Michigan Health System, 3812 Lake Pointe Lane, Ann Arbor, Michigan, USA e-mail: [email protected]

M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_4, © Springer Science+Business Media, LLC 2011

37

38

J. Gosbee 

Creating and Sustaining Safety The difficulty of creating and sustaining a patient safety program cannot be underestimated. Logistic and strategic questions quickly overwhelm the best and brightest: What are the most frequent or remediable adverse events that hurt and kill patients? Why did these adverse events occur? What can we do about the root causes of these events? What sources can provide effective remedies? Why are people so resistant to using safety remedies? To answer these questions, hospitals have used safety methods required by regulatory organizations (e.g., Joint Commission on Accreditation of Healthcare Organizations (JCAHO)) or governments (e.g., state departments of health). These methods include root-cause analysis (RCA); failure mode and effect analysis (FMEA); and traditional quality improvement tools.2,3 These safety and quality approaches work best in organizations that are developing a so-called “high-­ reliability organization.”4 An RRS can complement RCA and FMEA activities that will be described more fully. An RRS can also provide the tangible proof that the organization is serious about the “safety culture” described for high-reliability organizations. Specifically, certain aspects of RRSs are especially suited to meet many of the criteria in a specific model of organizational change described by Rodgers,5 a model that has been accepted for many decades. This theory looks at factors such as perceived relative advantage, compatibility with existing values, and norms and trial-ability.

Definition and Relevance of Human Factors Engineering The human factors engineering field is several decades old and has been applied in various organizations and domains when they face design, personnel, and policy issues such as those surrounding an RRS.6 Briefly, human factors engineering is the discipline that studies human capabilities and limitations and applies that information to safe, effective, and comfortable system design.7,8 It includes the design of tools, machines, and systems that take into account human capabilities, limitations, and characteristics. Ergonomics, usability engineering, and user-centered design are considered synonymous or closely related to human factors engineering, which is based on design-related aspects of several biomedical disciplines. From a systems perspective, a person is receiving input from a “clinical assessment machine,” processing that input, and creating an output that goes to the “healthcare machine.” Anthropometrics and biomechanics cover most of the physical aspects of input and output. The science of sensation and perception is related to input to the person. Cognitive psychology, which covers models and theories of human performance, memory, and attention, relates to the processing of the input and ­initiating the output. Observations and studies regularly conclude that many design issues thwart even the best attempts at resuscitation and the application of critical care expertise.9

4  Integrating a Rapid Response System into a Patient Safety Program

39

Some researchers have seen problems with using defibrillators ‑even those made for novices.10 Others have identified design problems with defibrillators, even when testing individuals like paramedics who use them often.11 The layout and human factors aspects of the medication drawers in many crash carts can add minutes of delay to well-intentioned and -motivated clinicians and their ability to retrieve key medications.12 Lack of proper transitions of care and teamwork during and following resuscitation exists even in the best clinical care.13 The breakdowns and missed opportunities are accentuated by time pressure, design of devices, and even the layout and furnishings of the resuscitation area.14 All of this evidence points to the need to use METs or RRTs to avoid or abort crises ‑even if the most highly skilled personnel and fully staffed settings are available.

The MET as a Driving Force for a Patient Safety Program For many reasons, an RRS and events that the METs or RRTs respond to can be a key driving force for a hospital safety and quality program. First, there are the difficulties and limitations of commonly used safety methods. Second, an RRS is a broad-sweeping safety initiative that impacts and is visible to many sites in the healthcare organization, and to many types of professionals and personnel. Third, as a safety or quality activity, RRSs have the most successful change attributes that are cited in change management theory and practice.

Root Cause Analysis Most healthcare organizations perform many RCAs per year due to JCAHO requirements and the general standard of practice in the patient safety movement. The basics of the RCA include: 1 . Deciding when to do an RCA 2. Figuring out what happened (e.g., people and devices involved, sequence of events) 3. Making decisions about root causes and contributing factors 4. Developing remedies or action plans, and approaches to measure effectiveness 5. Convincing and selling to management and staff, and then (hopefully) implementing the action plans There may be more than one team or individual doing these general steps. Depending on the event to be studied, each general step might take hours or weeks to complete. An MET or RRT can aid all five general steps in the RCA process, but has the most effect on two troublesome steps: deciding when to do an RCA, and convincing, selling, and implementing action plans. When initiating an RCA on an adverse event, the hospital has to know several things besides just the severity of that specific

40

J. Gosbee 

event: What is the severity of events like the one in question, what is the frequency of this kind of adverse event, and how often is the event severe? In a robust RRS program, there are several adverse events that lead to the response team being called. Braithwaite et al identified 31% of MET events that were associated with medical errors (adverse events and close calls).15 In their hospital system experience, they found 18.4 events per 1,000 hospital admissions. This is similar to the experience of Australian hospital systems,16 which reported five MET responses per 1,000 admissions. Thus, most hospital systems could have a rather large body of knowledge about adverse events and close calls. This data would be several times larger than that obtained from auditing just cardiac arrest events, because crises seem to occur five to ten times more frequently. If the operators log all MET/RRT calls they make, the MET/RRT call itself provides two functions: it provides additional resources to prevent that patient from dying, and it enables creation of a database of crisis events to fuel patient safety reviews. Thus MET/RRT calls may help overcome perhaps the most difficult aspect of performing quality indicator activities: finding errors worth fixing, since people are notoriously poor at recognizing errors as they occur, or reporting them when they do recognize them. As mentioned previously, the events detected by MET/RRT are quite diverse. This can aid in determining which of the many types of reported events upon which a hospital should do an RCA. Braithwaite et al15 identified 67.5% of the 114 adverse event-associated MET/RRTs as diagnostic errors, such as incorrect or delayed diagnosis or delay or incorrect action following monitoring or test data. They also saw 59.6% related to treatment errors, including problems during or following surgery and medication administration. Finally, 26.3% of the MET events included problems arising from “prevention”; examples of prevention problems encompassed prophylactic treatment (e.g., anticoagulation for deep vein thrombosis) and telemetry monitoring issues for patients with hyperkalemia. The richness and diversity of data from events or vulnerabilities that lead to an MET activation can help the RCA team throughout their process. In short, people do poor root-cause analyses; some studies have demonstrated that developing accurate and specific root causes and contributing factors is problematic. Carroll et al17 looked at problem-investigation teams in nuclear power plants and chemical plants. In a quantitative analysis of 27 RCA teams at three different nuclear power plants, they found “a disappointing level of depth and completeness, insight, and clarity,” The researchers were able to make some correlation between some attributes of the team members and the deeper and clearer RCAs. Their analysis found that “more training in teamwork” and “more varied plant experience” were the strongest positive predicting attributes. These attributes may be more widespread or likely to be increased in organizations that accept the central concepts behind RRS processes, such as calling for help early.18 Another troublesome step in RCA is the final one: convincing, selling, and implementing the action plans. Action plan implementation is the step where healthcare organizations and RCA teams discover how hard it is to change a system, and how resistant personnel can be if the organization has not embraced a culture of safety. It is difficult to convince managers and frontline personnel that

4  Integrating a Rapid Response System into a Patient Safety Program

41

just one event or close call is serious enough for them to change. In essence, one must convince caregivers that their current workflow is wrong and a new, untested work plan is better. With data from adverse events leading to the creation of an MET or RRT, and workflow changes directed at preventing repeats of actual neardeath events, it is much more likely to change mindsets and practices. For instance, an RCA about an empty oxygen cylinder almost being used during patient transport might result in an action to purchase cylinders with a more direct indication of contents (indicator valves). However the same problem that caused a  near-death event from hypoxemia would more highly motivate not only the ­bedside caregivers, but also the administrators who oversee purchasing choices and materials management. Furthermore, procurement committees will likely accept the additional cost if there were more than one event. Because MET/RRT responders tend to find similar types of errors, creating lists of similar events is not difficult. For example, if the organization had five MET/RRT events that involved confusion over oxygen cylinder levels, the organization would be less likely to blame an individual and more likely to blame the system. Also, frontline respiratory therapists, purchasers, transport personnel, nursing staff, administrators, and physicians are more likely to become allies instead of naysayers if they know about all five events.

Failure Mode and Effect Analysis Most healthcare organizations perform at least one FMEA per year due to JCAHO requirements and the general standard of practice in the patient safety movement. The general steps of a FMEA include19: 1 . Identifying and prioritizing a high-risk process 2. Flowcharting the process and subprocesses 3. For each subprocess, developing potential failure modes and prioritizing based on risk (risk priority is usually the product of severity, frequency, and detectability) 4. For each failure mode cause, identifying actions to remedy them 5. Convincing, selling, and then (hopefully) implementing the action plans There may be more than one team or individual performing these general steps. Depending on the process to be studied, each general step might take hours or weeks to complete. Much less has been written about the problems or shortcomings in applying FMEA in healthcare.20 However, since FMEA shares many attributes with RCA, many of the ideas and findings about the complementary role of the RRS are likely true. In addition, some safety professionals think that there are many ways to inadvertently misuse FMEA as a safety tool.21 One could infer that data from the events proceeding RRS events and close calls seem invaluable for the FMEA team in all five general steps listed above.

42

J. Gosbee 

For example, the RRS data can be used to develop realistic failure modes and failure mode causes. An FMEA team might only consider two failure modes in the monitoring and treatment of conscious cardiac care unit patients: 1 . Malfunction of physiologic monitors 2. The patient falling while getting out of bed. RRS data would have provided them with a third failure mode such as that described by Braithwaite: bradycardia/ asystole from delay in pacemaker placement. Or the team might not conceptualize the failure mode cause of “permanent pacemaker placement considered a low priority consult.” Having a body of RRS data-associated adverse events and their causes will make the FMEA process more efficient The process of convincing and selling the action plan from FMEA is more difficult than RCA, since many healthcare personnel may not be motivated to change when no “real” event occurred. But just as the RRS data helps sell and convince personnel to try and accept action plans from RCAs (as described above), it will help promote FMEA action plans.

Safety Culture and High-Reliability Organizations MET/RRTs can also provide the tangible proof that the organization is serious about the safety culture described for high-reliability organizations. MET/RRT characteristics meet many of the criteria in one specific model of organizational change described by Rodgers.5 This model has been accepted and applied by many organizations for many years. The theory looks at five crucial factors for organizational change to occur: 1 . Perceived relative advantage 2. Perceived as compatible with existing values and norms 3. Perceived low (or lack of ) complexity 4. Trial-ability (ease of doing it on a trial basis) 5. Observe-ability (visibility of the change to non-experts) In contrast, one can see that the required safety method of RCA fares only average in each of the five organizational change factors. For those convinced that safety is an issue, they would positively perceive the relative advantage RCA (factor 1). However, many novices would see the several-hour process of RCA as burdensome when they believe the remedies, such as enforcing policies, are apparent in minutes of analysis. RCA is also perceived as somewhat compatible with existing values/norms (factor 2) and high complexity (factor 3). Since RCA team meetings often take place weekly and last 2 h, busy clinicians would say that trial-ability is low (factor 4). Finally, as evidenced in Carroll’s work,17 many RCAs result in training or policy changes that will not be viewed as really much of a change (factor 5).

4  Integrating a Rapid Response System into a Patient Safety Program

43

AN RRS comes out much better than RCA when judged against each of the five crucial factors for organizational change. The following analysis assumes that management of the organization is serious about rewarding, not punishing, providers for calling for help early. Providers see a large relative advantage to have an outside team deal with the clinical issues of their patient efficiently and effectively (factor 1). Certainly if an organization using an RRS (either RRT or MET) has nearly the success with decreasing mortality and crisis code frequency as some U.S. and Australian hospitals, the relative advantage will be clear to all stakeholders, from the boardroom to the classroom. Calling for help early, accurate and reliable team communication, and teamwork are the hallmarks of high-reliability organizations as well as RRS. Thus, Rodgers’s second factor, compatibility of values and norms, will increase as the organization moves forward. In contrast, organizations that do not value teamwork and constructive critique will have dissonance with this crucial factor for change. METs and RRTs will have to be perceived as being of low complexity. This book contains many examples of the importance of making METs and RRTs seamless with code teams, paging systems, and other hospital ward activities (see Chaps. 12, 17, and 18). Also, short lists of understandable, objective criteria for activating the RRS increase organizational acceptance. There are mixed aspects of RRSs when judging against the last two factors, trialability and observe-ability of success in organizational change (factors 4 and 5). Some providers are unaffected by changes in the organization due to MET/RRT implementation; for them, MET/RRTs seem easy to try out. However, an MET or RRT trial may not seem so easy or non-threatening to personnel in critical care units, existing crisis code teams, and others who play a role in solving urgent or emergent problems. Non-experts can understand fewer codes for acutely ill ward patients more easily, if they are made aware of this. Changes in morbidity in critical care areas may not be as appreciated by some management. However, in many facilities, quality and outcome measures of various types are now tracked by many non-direct care providers, so visibility of better outcomes would be higher and organizational change more likely in those settings of transparency.

Patient Safety Overall General concepts discussed in patient safety communities include normalization of deviance and normalization of complexity ‑overly complex phrases that get at the observations in healthcare of something being out of place or hard to use. The general observations, if correct, also conspire to permit certain complication rates for procedures and patient interventions. Careful analysis of events antecedent to an RRS activation provides a stark set of data about how healthcare devices have grown overly complex, or standard policies needlessly convoluted. Once again, the attention of healthcare personnel is focused on these issues by the criticality of the event (respiratory or cardiovascular distress) and the fact that many of the events recur.

44

J. Gosbee 

Implementation of METs or RRTs will tend to move the norm; instead of trying to prevent deaths, organizations have a tool to prevent crises, and to help prevent those crises that do occur from turning into a death. Calling for help early can be promoted to become the norm instead of the exception.22

Summary Using the prescribed patient safety tools of RCA or FMEA has only partially helped healthcare organizations with the struggle to find and eliminate system vulnerabilities. Organizations soon find that easy problems with easy answers are not common. Fortunately, the Rapid Response System, and in particular the response teams MET and RRTs provide a service that is complementary and supportive of other safety methods, since up to 30% of team activations are associated with patient safety issues. AN RRS is also needed since there are many ingrained problems with human factors engineering of systems, devices, and tools involved in resuscitation. That is, there are intransigent constraints to the maximum effectiveness in dealing with cardiopulmonary emergencies. Most important are the RRS features that organizational theory and observation support as crucial success factors to turning an organization into a highly reliable one, with a solid safety culture.

References 1. Kohn LT, Corrigan JM, Donaldson MS, eds. To Err Is Human: Building a Safer Health System. Washington, DC: National Academies Press; 2000. 2. Bagian JP, Gosbee JW, Lee CZ, Williams L, McKnight SD, Mannos DM. VA’s root cause analysis system in action. Jt Comm J Qual Improv. 2002;28:531–545. 3. Stalhandske E, DeRosier J, Patail B, Gosbee JW. How to make the most of failure mode and effect analysis. Biomed Instrum Technol. 2003;37:96–102. 4. Weick KE, Sutcliffe KM. Managing the Unexpected: Assuring High Performance in the Age of Complexity. San Francisco, CA: Jossey Bass; 2002. 5. Rodgers E. Diffusions of Innovations. 5th ed. New York: Free Press; 2003. 6. Sanders MS, McCormick EJ. Human Factors in Engineering and Design. 7th ed. New York: McGraw-Hill; 1993. 7. Gosbee JW, Lin L. The role of human factors engineering in medical device and medical system errors. In: Vincent C, ed. Clinical Risk Management: Enhancing Patient Safety. 2nd ed. London: BMJ; 2001. 8. Gosbee JW. Introduction to the human factors engineering series. Jt Comm J Qual Saf. 2004;30:215–219. 9. Donchin Y, Gopher D, Olin M, et al. A look into the nature and causes of human errors in the intensive care unit. Crit Care Med. 1995;23:294–300. 10. Mattei LC, McKay U, Lepper MW, Soar J. Do nurses and physiotherapists require training to use an automated external defibrillator? Resuscitation. 2002;53:277–280. 11. Fairbanks RJ, Shah MN, Caplan S, Marks A, Bishop P. Defibrillator usability study among paramedics. In: Proceedings of the Human Factors and Ergonomics Society 47th Annual Meeting. Santa Monica, CA: Human Factors and Ergonomics Society; 2004.

4  Integrating a Rapid Response System into a Patient Safety Program

45

12. McLaughlin RC. Redesigning the crash cart: usability testing improves one facility’s medication drawers. Am J Nurs. 2003;103:64A, 64D, 64G–64H. 13. Xiao Y, Hunter A, Mackenzie CF, Jeffries NJ, Horst R. The LOTAS Group. Task complexity in emergency medical care and its implications for team coordination. Hum Factors. 1996;38:636–645. 14. Xiao Y. Human and technology factors in coordination in emergencies. In: Medicine, Technology and Human Factors in Trauma Care: A Civilian and Military Perspective. Baltimore, MD: National Study Center; 2001:16–21. 15. Braithwaite RS, DeVita MA, Mahidhara R, Simmons RL, Stuart S, Foraida M. Medical Emergency Response Improvement Team (MERIT). Use of medical emergency team (MET) responses to detect medical errors. Qual Saf Health Care. 2004;13:255–259. 16. Bellomo R, Goldsmith D, Uchino S, et al. A prospective before-and-after trial of a medical emergency team. Med J Aust. 2003;179:283–287. 17. Carroll JS, Rudolph JW, Hatakenaka S. Learning from high hazard organizations. In: Staw B, Kramer R, eds. Research in Organizational Behavior. Greenwich, CT: JAI; 2003. 18. Carroll JS, Rudolph JW, Hatakenaka S. Lessons learned from non-medical industries: root cause analysis as culture change at a chemical plant. Qual Saf Health Care. 2002;11:266–269. 19. ECRI. An introduction to FMEA. Using failure mode and effects analysis to meet JCAHO’s proactive risk assessment requirement. Failure modes and effect analysis. Health Devices. 2002;31:223–226. 20. DeRosier J, Stalhandske E, Bagian JP, Nudell T. Using health care failure mode and effect analysis: the VA National Center for Patient Safety’s prospective risk analysis system. Jt Comm J Qual Improv. 2002;28:248–267. 21. Spath P. Worst practices used in conducting FMEA projects. Hosp Peer Rev. 2004;29:114–116. 22. Foraida M, DeVita MA, Braithwaite RS, Stuart SA, Brooks MM, Simmons RL. Improving the utilization of medical crisis teams (Condition C) at an urban tertiary care hospital. J Crit Care. 2003;18:87–94.

Chapter 5

Acute Hospitalist Medicine and the Rapid Response System David J. McAdams

Keywords  Acute • Medicine • Hospitalist • Specialty • Rapid • Response • System

History of the Hospitalist Movement Traditionally, the Primary Care Physician (PCP), usually an internist or family practice physician, has been responsible for outpatient and inpatient care. There have been many forces in healthcare that have pushed toward a separation of care provided to patients in both of these locations. Changes in hospital management systems, hospital size, increasing severity of patient illness, and out-of-control healthcare costs have all been integral in the push towards an inpatient physiciandriven care model.1 Within the context of these changes, there has been a growing sense of PCP dissatisfaction in the ability to provide timely and efficient care to both their outpatient and inpatient populations. This has ultimately given birth to the hospital medicine “specialist.” This emerging specialty is defined, much like Critical Care and Emergency Medicine, by the site of care rather than a disease, patient population, or organ-system.1 While physicians with inpatient care duties have existed both in North America and Europe for some time, the appearance of the hospital physician is a newer phenomenon. Certainly, the ever-present “house-officer” has had a place in history as the physician who essentially lives in the hospital; however, this role has been mainly restricted to the medical trainee with little experience and much responsibility, and has served as a rite of passage to become the more senior and less-present attending physician. In distinction, however, the hospitalist physician is a more experienced physician, not under the same training and hierarchical constraints as

D.J. McAdams (*) Department of Internal Medicine, University of Pittsburgh Medical Center, 200 Lothrop Street, MUH 826E, Pittsburgh, PA, USA e-mail: [email protected] M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_5, © Springer Science+Business Media, LLC 2011

47

48

D.J. McAdams

the house-officer, who is available at almost all times to the care needs of those patients in the hospital setting. It has been almost 10 years since the coining of the term “hospitalist” by Wachter and Goldman.1 Definitions have been reworked and adapted, but currently the Society of Hospital Medicine (SHM) has defined Hospitalists as, “physicians whose primary professional focus is the general medical care of hospitalized patients. Their activities include patient care, teaching, research, and leadership related to Hospital Medicine.”2 The drive and expansion of this newer field of medicine has been felt throughout the US and abroad, and its popularity continues to grow exponentially. During the past decade we have seen this new specialty form its own professional society, have dedicated journals, and inundate existing, wellrespected, traditionally general medicine journals with abundant evidence-based literature. SHM estimates indicate that there were about 2,000 hospitalists in 1998, 8,000 in 2003, and that number is expected to rise to as much as 30,000 by the end of 2010.2 Indeed, this is one of the only fields of medicine where there is a vast surplus of jobs comparative to physicians to fill them. The majority of hospitalists have been trained in internal medicine (89%), mostly general internal medicine (51%); there is a large subset of internists who have subspecialty training (38%), usually in pulmonary medicine, critical care medicine, or a combination of the two.3 The remainder are made up mainly of ­family practice physicians, pediatricians, and other subspecialists like infectious disease and cardiology. Currently, there is no formal training required to become a hospitalist. However it is indeed true that a significant amount of one’s training in internal medicine is geared toward care of the hospitalized patient. However, there are at least six hospitalist fellowships currently in existence with more being planned for the future. In many ways, these are designed like general internal medicine fellowships, gearing the physician towards further experience in education and clinical research while providing continued exposure to inpatients and their medical problems.

Models of Hospitalist Care Wachter has described four stages of hospital care that help to illustrate the driving forces behind hospitalist models.4 These stages help us to understand inpatient care structure, but they are not meant to be hierarchical nor do hospital systems sequentially pass through them. Rather, they are meant as a tool to help us understand that many external forces predicate how hospital care is provided. The first stage is the PCP model in which every PCP cares for his/her own patients admitted to the hospital. This has been the classic model of care in medicine. The second stage involves rotating coverage of hospitalized patients between members in a private practice. Each physician takes turns caring for those patients admitted. This model became popular as groups started to get larger and increase the number of patients in their practices. In the third stage, we see the emergence of a dedicated hospital physician who cares for inpatients. PCPs may hand over care to the hospital physician, but are

5  Acute Hospitalist Medicine and the Rapid Response System

49

not required to do so. In stage four, in contrast to the voluntary hospitalist stage, PCPs are required to hand over care to the inpatient physician. Every stage has its own associated advantages and disadvantages. For example, in stages three and four, the inpatient physician can provide continuous care to admitted patients while the PCP is free to spend more time in the office setting. However, this may lead to ­discontinuity of care due to multiple providers, or dissatisfaction in not being able to see one’s own doctor. Given the forces of healthcare today, many, if not most, hospital systems are at least in part relying on at least a voluntary hospitalist system of care, as described in stage three above. There are numerous hospitalist models of care in place today. In many ways, the models continually redefine themselves based on changes in hospitals themselves and changes in physician training. For example, recent restrictions in house staff work hours have necessitated that hospitals find alternative ways to cover patients. One type of model includes a private practice group employing a hospitalist to admit and care for their patients. A much more popular model is that in which a private practice group of inpatient physicians provide care to those patients admitted to the hospital. Typically, these hospitalist groups contract out to private practices or hospitals to care for their patients. These former models are popular with community facilities. Other models include those in which hospitals and health maintenance organizations hire their own inpatient physicians. Finally, many academic centers now have divisions or sections of Hospital Medicine. Academic hospitalists generally work in direct patient care less than private hospitalists, usually between 1 and 6 months per year. However, their time is usually supplemented by activities such as house staff training, academic research, and administrative duties.

Benefits of Hospitalist Systems As one might imagine, there are several areas of benefit inherent in having a dedicated physician caring for patients requiring hospitalization. This doctor is not limited or constrained by the problems imposed by having an office practice. As such, the hospitalist is available throughout the day or night to see patients immediately, meet with family members and loved ones, and respond to emergency ­situations. The hospitalist is also in a prime position to foster a culture of patient safety, primarily by participating in multidisciplinary teams.5 Additionally, by ­virtue of the fact that this doctor practices only in the hospital, over time he or she becomes more attuned to developing and maintaining the necessary skills to manage acute inpatient medical issues. Hospital medicine is a relatively young field, but the body of evidence in the literature showing benefits of this new system is growing rapidly. Published data demonstrates that utilizing hospitalists decreases total costs per case and patient’s length of stay6; preserve patient satisfaction despite not having direct PCP involvement in care6; trend towards a decrease in short-term mortality7; provide benefit in end-of-life care8; and improve resident education.9 There is also data to suggest that

50

D.J. McAdams

some of these changes, particularly length of stay and cost per case, are derived only when experienced hospitalists are present in a program or after a program has been established for some time.7 This is of growing concern since the recent explosion of popularity in hospital medicine has left many slots open for inexperienced hospitalists, and since some programs are designed to be transient in nature and are filled by recent graduates from residency. Nonetheless, benefits derived from ­hospitalist use are widely present, and certainly this concern will diminish over the next decade as the number of providers begins to equilibrate with the number of available employable positions. A large number of hospitalist literature and journals now exist. Interestingly, almost every journal devoted to hospital medicine has a section in each publication focusing on quality improvement or patient safety. Again, the fact that these physicians are working within the hospital most of the time affords them the unique ability to police the system, recognize areas of improper or inefficient care management, and formulate and carry out care plans that have been proven to enhance inpatient care.

Hospitalists as Acute Providers Compared to hospital models from decades ago, sicker patients are admitted to and stay in the hospital. No longer are the majority of patients simply staying in facilities awaiting tests. Most have serious, volatile problems, and clearly their conditions can change at any time. One can, therefore, make an argument that round-the-clock care of patients by an in-house physician is much more beneficial that traditional outside overnight call coverage.10 By virtue of focused training in hospital medicine as well as advanced cardiac life-support (ACLS) techniques, the hospitalist is in a prime position to care for the inpatient in urgent and emergent situations. In general, adverse events follow a gradual clinical patient deterioration, and much of the time the signs of impending doom go unrecognized or are even ignored.11 While there is not much direct data to suggest a link between hospitalists and early recognition of deterioration yet, there is some suggestion that the omnipresence of the hospitalist allows for more prompt recognition of acute problems with patients and implementation of appropriate and directed care to prevent adverse outcomes.7,9 The hospitalist can work alone in this venue, but more commonly he or she works on a multidisciplinary team as part of a Rapid Response System (RRS). The concept of a “code team” is not new, and certainly many facilities rely on intensivists and intensive care unit (ICU) teams to provide emergency care. The newer trend is an attempt to make these teams more focused, and more rapid to respond to less severe crises, and avoid delays in care for suddenly critically ill patients. This has mostly been done by having a smaller number of well-trained staff respond to the emergency in a controlled fashion, rather than a larger number of junior staff with sub-optimal skills or experience. While the RRS is composed of

5  Acute Hospitalist Medicine and the Rapid Response System

51

many parts, the response teams (MET or RRTs) can be comprised of any number and type of care provider experienced in resuscitation skills. METs generally involve a combination of hospitalists (non-intensivist or intensivist), ICU nurses, respiratory ­technicians, anesthesiologists, and even emergency room physicians, whereas an RRT does not have a physician as a first responder. In this situation, a hospitalist is a convenient and effective physician who can respond should the RRT need physician backup. The use of a hospitalist system does not preclude the need for an RRT or MET. Rather, the two usually go hand in hand. The two main types of hospitalists, nonintensivists and the intensivists, both can be a part of this response team. The nonintensivist (those inpatient physicians trained in a primary specialty but without critical care training) often do not have major instruction beyond basic life-support and ACLS, and in particular may lack complex airway management skills. Often this non-intensivist hospitalist is the first responder to an urgent or emergent situation, is involved in calling the RRT to the bedside, and can certainly be involved as an integral member of the MET, including the “code leader.” However, the more skills-based aspects of code management, again mainly related to difficult airway problems or other procedures, may be reserved for the intensivist. In general, the major benefit of the non-intensivist hospitalist to the system is being in a position (geographically and intellectually) to foster a more rapid and astute recognition of the clinical deterioration of patients, and then set in motion the necessary elements to trigger the rapid response system to send a team to the aide of the patient. There continue to be clinical trials examining the usefulness of RRTs and METs. At least two studies (both were non-randomized and non-blinded) have shown some benefit to having an RRS, namely a decreased incidence of unanticipated ICU transfers, lower incidence of death without a DNR, a decreased incidence of and mortality for in-hospital cardiac arrests, and a reduction in overall hospital mortality.12,13 There has been at least one meta-analysis evaluating the effects of an RRS on clinical outcomes, and this study failed to find any consistent improvement in outcomes through the use of an RRS in the 13 studies included.14 Nevertheless, there may be some advantage from an RRS; however the extent of the advantage remains to be demonstrated.

Thoughts for the Future It is evident that the wave of the future in hospital care will almost universally involve the hospitalist. Yet given the rapid nature with which this assumption is occurring, steps will need to be taken to ensure that hospitalists are prepared for the situations they will encounter on a daily basis. Instituting steps to improve retention (incentive programs, reasonable shifts and work hours, etc.) will likely improve performance and care delivery in programs that employ hospitalists. There may also be changes in residency training programs to allow candidates interested in a career in hospital medicine an opportunity to obtain

52

D.J. McAdams

more experience in the care of the inpatient and in managing inpatient emergencies. While more fellowships for hospital medicine may continue to emerge, it remains to be seen if completing a fellowship will ever be required for those wishing to pursue a hospital-based position. Ultimately, it may become necessary to define the specific types of training required for hospital medicine, and this will almost certainly evolve around management of acute scenarios. Steps need to be taken in order to fully train hospitalists to deal with emergent events, particularly non-intensivists. In academic centers, residents are being given less and less exposure to urgent or emergent events and procedures. Interestingly, they are getting more controlled experience in the lab setting but much less bedside emergency situation experience. And since there is no formal training in Hospital Medicine that is required, much of these duties are falling onto the shoulders of already busy and short-staffed intensivists. Focused training for hospitalists participating in multidisciplinary teams (METs) or aiding a nurse-led team when called (RRT), may prove to be extremely beneficial for every aspect of patient care. While the former will almost certainly allow for better management of quality issues and patient safety, the latter will literally be the basis for provision of care during acute hospital emergencies.

References 1. Wachter RM, Goldman L. The emerging role of “hospitalists” in the American health care system. N Engl J Med. 1996;335:514–517. 2. Society of Hospital Medicine (SHM). ; 2010. Accessed January 2010. 3. Lindenauer PK, Pantilat SZ, Katz PP, Wachter RM. Hospitalists and the practice of inpatient medicine: results of a survey of the National Association of Inpatient Physicians. Ann Intern Med. 1999;130(4 Pt 2):343–349. 4. Wachter RM. An introduction to the hospitalist model. Ann Intern Med. 1999;130:338–342. 5. Shojania KG, Wald H, Gross R. Understanding medical error and improving patient safety in the inpatient setting. Med Clin North Am. 2002;86(4):847–867. 6. Wachter RM, Goldman L. The hospitalist movement 5 years later. JAMA. 2002;287(4): 487–494. 7. Meltzer D, Manning WG, Morrison J, et  al. Effects of physician experience on costs and outcomes on an academic general medicine service: results of a trial of hospitalists. Ann Intern Med. 2002;137:866–875. 8. Auerbach AD, Pantilat SZ. End-of-life care in a voluntary hospitalist model: effects on communication, processes of care, and patient systems. Am J Med. 2004;116:669–675. 9. Kulaga ME, Charney P, O’Mahony SP, et al. The positive impact of initiation of hospitalist clinician educators: resource utilization and medical resident education. J Gen Intern Med. 2004;19:293–301. 10. SHM Benchmarks Committee. Value added by hospitalists: hospital medicine programs add value through extraordinary availability (24/7). Hospitalist. 2004;8:19–22. 11. Buist M, Bernard S, Anderson J. Epidemiology and prevention of unexpected hospital deaths. Surg J R Coll Surg Edinb Irel. 2003;1(5):265–268. 12. Bristow PJ, Hillman KM, Chey T, et al. Rates of in-hospital arrests, deaths and intensive care admissions: the effect of a medical emergency team. Med J Aust. 2000;173:236–240.

5  Acute Hospitalist Medicine and the Rapid Response System

53

13. Buist MD, Moore GE, Bernard SA, Waxman BP, Anderson JN, Nguyen TV. Effects of a medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: preliminary study. BMJ. 2002;324:1–6. 14. Ranji SR, Auerbach AD, Hurd CJ, O’Rourke K, Shojania KG. Effects of rapid response ­systems on clinical outcomes: systematic review and meta-analysis. J Hosp Med. 2007;2(6): 422–432.

Chapter 6

Medical Trainees and Patient Safety Stephen W. Lam and Arthas Flabouris

Keywords  Medical • Trainees • Patient • Safety

Healthcare, Healthcare Facilities and Medical Trainees As the next generation of medical practitioners, medical trainees form an important part of the medical profession. Even though they are trainees, they are a vital healthcare resource, contributing to patient care, research and academia. Their ability to contribute is profoundly influenced by their prior undergraduate academic education and supervised clinical experience. Progression through the postgraduate years is associated with a gradual reduction in clinical supervision as expertise is accumulated. Assessment is typically both formative and summative and continues until the trainee is considered safe to practice without further supervision and gains the relevant qualifications to do so. Postgraduate clinical training generally occurs in large healthcare facilities. Patient profiles and illness types (or “case mix”) determine the healthcare provision that is required from medical trainees. In turn, the learning environment for trainees is determined by the case mix to which they are exposed, along with other factors such as level and quality of supervision, resources and working conditions. Thus there is a “shared dependence,” where patients depend on trainees to provide safe and competent care, while the trainees rely on patients to provide a suitable learning environment from which to gain quality training and experience.

S.W. Lam (*) University of Adelaide, Intensive Care Unit, Royal Adelaide Hospital, North Tce, Adelaide, SA 5001, Australia e-mail: [email protected]

M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_6, © Springer Science+Business Media, LLC 2011

55

56

S.W. Lam and A. Flabouris

The Healthcare Environment Delivering care in a hospital setting has become increasingly complex and risky.1 The population is aging2,3 with increasing co-morbidities and changing disease demographics.4–6 Healthcare technology is becoming more complex7 and patients often present with chronic and sometimes terminal conditions. Meanwhile, hospitals seek to achieve cost efficiency through reducing acute hospital beds, streamlining inpatient care, staff reductions, and a greater emphasis on home care. Within that setting, education is less of a “core” activity and viewed as more of an “add-on.”8 The changing needs of patients is also reflected by an increase in demand for a new specialist in hospital medicine, or “hospitalist,” capable of providing competent institutional care in a team environment and handling both acute medical events9 and palliative care issues.7,10 The rapid growth in technological and scientific advances resulting from better understanding of complex disease processes has fueled the growth of medical specialization. The number of American Medical Association accredited specialties and subspecialties increased from 14 in 1927 to 41 by 1985, after which growth was exponential, reaching 124 by the year 2000.11 Highly technical “proceduralists” and specialists are now limiting their practices to specific diseases, or organs; treat certain populations (e.g., pediatricians); or operate in specific geographical areas (e.g., emergency departments). Because of the associated technical complexity and cost of such procedures, many of these services are restricted to academic and acute care medical facilities. As a result, there has been a decline in the number of medical practitioners devoted to comprehensive and whole individual care. Medical specialization has been criticized as being fragmented12 and confusing to patients and general practitioners alike, with risk to the perception of medicine as an ­integrated profession.13

Medical Trainees: The Undergraduate Years The quality of a trainee’s learning depends on what they already know.14 When exposed to clinical practice, they attempt to make sense of new experiences by using their existing knowledge. Thus, the primary role of medical schools is the education of medical students – preparing them with the necessary knowledge and skills for structured and supervised practice in acute care facilities. Increasingly, this role has had to compete with research and other non-teaching activities. In the 1990s, the medical curriculum was criticized for being too rigid, with overuse of didactic teaching methods and rote memorization.15 The emphasis of undergraduate training and examination has shifted from the didactic acquisition of academic knowledge towards a focus on patient-oriented knowledge and problem-based learning.7,16,17 The adoption of patient-based learning methods has been undertaken with a view to improving the link between undergraduate training and postgraduate provision of patient care.7,16–18 It also allows undergraduate training to evolve with

6  Medical Trainees and Patient Safety

57

changing patient needs on the wards and the development of teamwork and leadership skills through group learning. Recognition of the importance of practical skills assessment has lead to the use of such examination techniques as the Observed Structured Clinical Examination (OSCE). For the assessment of competency in critical care skills, a teaching methodology that incorporates structured clinical and multidisciplinary, problem-based instruction19 with that of OSCE and/or computer simulation-based assessment have been shown to be effective.20 While clinically oriented, these teaching methods employ simulated scenarios with minimal direct provision of patient care; hence, there is little opportunity for compromising patient safety.

Medical Trainees and Patient Safety: The First Few Years Medical issues requiring provision of care can be separated into two types: • Those associated with an already identified illness (e.g., provision of elective surgical procedure or drug treatment for a known problem) • Those associated with unanticipated acute medical problems or complications (e.g., undiagnosed illnesses, idiosyncratic drug reactions, iatrogenic complications arising from treatment and nosocomial infections acquired from the healthcare environment)

Provision of Care for Identified Illnesses The supervision of postgraduate trainees in their provision of patient care should be adjusted according to the trainees’ level of experience and assessed competency. Predictable illness clinical pathways can be used to oversee clinical performance, but the value of senior clinical oversight should not be ignored. 21 Such oversight can be useful in detecting missed diagnoses as well as providing educational feedback upon performance.

Provision of Care for Medical Incidences Because of the frequent and routine nature of many aspects of general ward care, such as prescribing intravenous fluids, many healthcare institutions utilize the most junior members of the healthcare team as the first point of contact to address routine issues. In dealing with these, most junior trainees remain unsupervised and receive little feedback22 unless an adverse event occurs. This is despite the fact that

58

S.W. Lam and A. Flabouris

supervision has been recognized as the “single most important element upon which graduate educational training is dependent.”23,24 The high frequency of minor medical issues arising in general wards has also created the need for 24-h “on-call” medical officers to deal with them. On such shifts, medical trainees are often given a wide range of smaller, less focused tasks. Several tasks for multiple patients may be allocated to the same individual simultaneously, often from different areas of the hospital. The priority of such tasks may vary for reasons ranging from the level of perceived urgency of the patient’s clinical condition to the need to meet required timeframes and deadlines (e.g., awaiting transfer to the operating room). As such, medical trainees are often faced with the need to triage priorities and handle important tasks with multiple distracting issues under significant time pressures. “On-call” shifts are typically long and extend outside normal working hours. The mode of presentation of medical emergencies is frequently subtle or nonspecific; and their early recognition and correct management is crucial to patient safety and outcome.9,21,25–28 Subtle indicators of a more severe underlying process can be easily overlooked among the burden of routine tasks. A recent international survey of patients who suffered cardiac arrests, death, or unanticipated intensive care unit admissions in hospitals revealed that significant physiological abnormal findings were present in many patients prior to those events.29 For some patients in this study, medical staff had reviewed them, thus highlighting the possible preventability of such adverse events.29 Other studies have documented patients with abnormal and/or inadequately attended clinical findings who subsequently experienced potentially preventable adverse events.28,30 Inappropriate working conditions can also hinder a trainee’s ability to correctly identify and separate warning signs of impending disaster from more minor complaints and issues, and provide appropriate care in a timely manner where required.31–35 Postgraduate medical education in acute care facilities is tailored toward clinical expertise in select medical domains through a specialized, structured curriculum, which is not consistent with a more whole-patient approach. Medical trainees undertaking specialist training therefore often lack sufficient skills to meet patient needs,17,36–38 particularly with respect to the recognition and management of medical incidences, which may present initially in a subtle manner. Training in the basic aspects of recognizing and caring for patients with critical illness is often lacking, not only in the undergraduate years39,40 but often in the postgraduate period as well,41,42 and may remain in a poor state after completion of the chosen medical specialty and among specialty supervisors.43

Improving Patient Safety in Institutions with Medical Trainees Responses to acute medical emergencies should be immediate, organized, predetermined and involve a team of appropriately trained and resourced clinical staff. A good example is a trauma team response.44,45 The organization of trauma management has

6  Medical Trainees and Patient Safety

59

resulted in a significant reduction in preventable deaths.46,47 However, for inpatients with acute medical emergencies, the most junior doctors are usually left to recognize and manage such emergencies on their own. Not only may they lack the required critical care skills, but they also lack the crucial skills of being able to communicate, coordinate, and organize a team response. Often monitoring and procedural equipment are not available and senior assistance may be remote or not provided in a timely fashion. This is especially so in acute care facilities, where response to acute ward medical emergencies may be limited to a team that responds only to cardiac arrests. As demonstrated in this book, a team that responds to acute medical emergencies other than for in-hospital cardiac arrests is a concept that is becoming increasingly popular.48–51 Ideally, medical trainees should be trained in basic and advanced resuscitation skills, no matter what their primary specialty training. However, the expectation that all such trainees would be able to regularly perform or practice those skills is hard to sustain. It is more important that trainees be instructed in the early recognition of at-risk patients,9,21,25–28 and then perhaps integrate themselves within a formal hospital medical emergency response team.

Postgraduate Training and Specialization Complicated patients need practitioners who are able to manage undifferentiated illness, often along with multiple specialist teams and/or other generalists. Focus on one area of practice with specialist training invariably leads to a lack of knowledge and experience in other areas. The multi-factorial causes of adverse events in the Quality in Australian Health Care Study showed that technical competency, problem-solving ability, communication, performance, and system design all contributed to the quality of medical care and thus should be considered integral components of the postgraduate education curriculum.52 Thus, in this age of increasing specialization it is crucial that postgraduate training maintains a more balanced approach to acute care. At the very least, medical trainees should be taught to recognize warning signs that may herald a greater emergency and be empowered to refer as appropriate or seek other critical care involvement during times of medical crises. Training time spent within a critical care-type environment for all sub-specialization postgraduate training programs may provides trainees with a greater knowledge of acute illness.53 Support for the concept of the hospitalist has grown as a result of issues of patient safety and a drive for lower inpatient costs.54,55 The rise of the hospitalist mirrors that of intensive care and emergency medicine, but which is occurring in the general wards. Hospitalists have become the preferred providers of postgraduate medical education among medical trainees in some countries.56 Training and retention of basic and advanced life-support skills requires a multidisciplinary, coordinated, and integrated team approach. Such training is best

60

S.W. Lam and A. Flabouris

served through clinical exposure within dedicated critical care units, simulation technology and skills laboratories.57 Training that also involves instruction in triage, emergency planning and preparation, team leadership, teamwork and team organization during emergency response should be included. Consideration for such training should begin in the undergraduate years. A system of regular accreditation is an essential component. Practitioners who have been disciplined by state medical-licensing boards are three times as likely to have displayed unprofessional behavior while in medical school.58 It is increasingly recognized that the issue of “professionalism” should be introduced to undergraduate education.59,60

Summary With changing hospital patient demographics and rapidly advancing healthcare technology, it is becoming increasingly important for healthcare systems to evolve to meet their new challenges. Medical trainees, as a vital healthcare resource, provide both elective and emergency medical care within acute healthcare facilities. Postgraduate training and medical team structure often place junior trainees at the forefront of identifying and responding to the deteriorating patient. This requires them to deal with issues ranging from the trivial to the more complicated and often subtle presentations of acute medical emergencies. Their ability to recognize these signs and trigger an appropriate response is crucial to minimizing serious adverse events for such patients. For medical trainees to safely and efficiently fulfill their roles in emergent and elective patient care, undergraduate and postgraduate training will need to provide them with the appropriate skills, environment, balance between specialization and general medicine and appropriate supervision.

References 1. Kohn LT, Corrigan JM, Donaldson MS, Molla S. To Err Is Human: Building a Safer Health System. Washington, DC: National Academy Press; 2000. 2. Population Division, Department of Economic and Social Affairs, United Nations Secretariat. World population prospects: the 2002 revision. Highlights. New York: United Nations. ; 2003 Accessed 27.04.09. 3. World Health Organization. The World Health Report 1998: Life in the 21st Century – A Vision for All. Geneva: WHO; 1998. 4. van Weel C. Chronic diseases in general practice: the longitudinal dimension. Eur J Gen Pract. 1996;2:17–21. 5. van Weel C, Michels J. Dying, not old age, to blame for costs of health care. Lancet. 1997;350(9085):1159–1160.

6  Medical Trainees and Patient Safety

61

6. Resnick NM, Marcantonio ER. How should clinical care of the aged differ? Lancet. 1997;350(9085):1157–1158. 7. Chantler C. The role and education of doctors in the delivery of health care. Lancet. 1999;353(9159):1178–1181. 8. Dent AW, Crotty B, Cuddihy HL, et al. Learning opportunities for Australian prevocational hospital doctors: exposure, perceived quality and desired methods of learning. Med J Aust. 2006;184(9):436–440. 9. McQuillan P, Pilkington S, Allan A, et  al. Confidential inquiry into quality of care before admission to intensive care. BMJ. 1998;316(7148):1853–1858. 10. McCahill LE, Dunn GP, Mosenthal AC, Milch RA, Krouse RS. Palliation as a core surgical principle: Part 1. J Am Coll Surg. 2004;1999(1):149–160. 11. Donini-Lenhoff FG, Hedrick HL. Growth of specialization in graduate medical education. JAMA. 2000;284(10):1284–1289. 12. Grumbach K. Primary care in the United States – the best of times, the worst of times. N Engl J Med. 1999;341(36):2008–2010. 13. Martini CJM. Graduate medical education in the changing environment of medicine. JAMA. 1992;268(9):1097–1105. 14. Dyrbye LN, Harris I, Rohren CH. Early clinical experiences from students’ perspectives: a qualitative study. Acad Med. 2007;82(10):979–998. 15. Christakis NA. The similarity and frequency of proposals to reform U.S. medical education: constant concerns. JAMA. 1995;274(9):706–711. 16. Howe A, Campion P, Searle J, Smith H. New perspectives – approaches to medical education at four new U.K. medical schools. BMJ. 2004;329(7461):327–331. 17. Jones R, Higgs R, Angelis C, Prideaux D. Changing face of medical curricula. Lancet. 2001;357(9257):699–704. 18. Dornan T, Bundy C. What can experience add to early medical education? Consensus survey. BMJ. 2004;329(7470):834–840. 19. Hill D, Stalley P, Pennington D, Besser M, McCarthy W. Competency-based learning in ­traumatology. Am J Surg. 1997;173(2):136–140. 20. Rogers PL, Jacob H, Rashwan AS, Pinsky MR. Quantifying learning in medical students ­during a critical care medicine elective: a comparison of three evaluation instruments. Crit Care Med. 2001;29(6):1268–1273. 21. Reilly BM. Physical examination in the care of medical inpatients: an observational study. Lancet. 2003;362(9390):1100–1105. 22. Lack CS, Cartmill JA. Working with registrars: a qualitative study of interns’ perceptions and experiences. Med J Aust. 2005;182(2):70–72. 23. Australian Curriculum Framework for Junior Doctors. . Accessed 30.04.09. 24. Iglehart JK. Revisiting duty-hour limits – IOM recommendations for patient safety and ­resident education. N Engl J Med. 2008;359(25):2633–2635. 25. Hillman K, Bristow PJ, Chey T, et  al. Antecedents to hospital deaths. Intern Med J. 2001;31:343–348. 26. Franklin C, Mathew J. Developing strategies to prevent inhospital cardiac arrest. Analyzing responses of physicians and nurses in the hours before the event. Crit Care Med. 1994;22(2):244–247. 27. Bedell SE, Deitz DC, Leeman D, Delbanco TL. Incidence and characteristics of preventable iatrogenic cardiac arrest. JAMA. 1991;265(21):2815–2820. 28. Schein RMH, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388–1392. 29. Kause J, Smith G, Prytherch D, Parr M, Flabouris A, and for the Intensive Care Society (UK), and Australian and New Zealand Intensive Care Society Clinical Trials Group ACADEMIA Study Investigators. A comparison of antecedents to cardiac arrests, deaths, and emergency intensive care admissions in Australia and New Zealand, and the United Kingdom – the ACADEMIA study. Resuscitation. 2004;62(3):275–282.

62

S.W. Lam and A. Flabouris

30. Garrad C, Young D. Suboptimal care of patients before admission to intensive care. BMJ. 1998;316(7148):1841–1842. 31. Homes G. Junior doctors’ working hours: an unhealthy tradition? [editorial]. Med J Aust. 1998;168(12):587–588. 32. Olson LG, Ambrogetti A. Working harder – working dangerously? Fatigue and performance in hospitals. Med J Aust. 1998;168(12):614–616. 33. Sexton JB, Thomas EJ, Helmreich RL. Error, stress, and teamwork in medicine and aviation: cross-sectional surveys. BMJ. 2000;320(7237):745–749. 34. Lockley SW, Cronin JW, Evans EE, et al. Effect of reducing interns’ weekly work hours on sleep and attentional failures. N Engl J Med. 2004;351(18):1829–1837. 35. Landrigan CP, Rothschild JM, Cronin JW, et  al. Effect of reducing interns’ work hours on serious medical errors in intensive care units. N Engl J Med. 2004;351(18):1838–1848. 36. Smith GB, Poplett N. Knowledge of aspects of acute care in trainee doctors. Postgrad Med J. 2002;78(920):335–338. 37. Meek T. New house officers’ knowledge of resuscitation, fluid balance and analgesia. Anaesthesia. 2000;55:1128. 38. Goldacre MJ, Lambert T, Evans J, Turner G. Preregistration house officers’ views on whether their experience at medical school prepared them well for their jobs: national questionnaire survey. BMJ. 2003;326(7397):1019–1022. 39. Harrison GA, Hillman KM, Fulde GWO, Jacques TC. The need for undergraduate education in critical care (results of a questionnaire to year 6 medical undergraduates, University of New South Wales and recommendations on a curriculum in critical care.). Anaesth Intensive Care. 1999;27(1):53–58. 40. Buchman TG, Dellinger RP, Raphaely RC, Todres ID. Undergraduate education in critical care medicine. Crit Care Med. 1992;20(11):1588–1603. 41. Gillard JH, Dent TH, Jolly BC, Wallis DA, Hicks BH. CPR and the RCP. Training of students and doctors in UK medical schools. J R Coll Physicians Lond. 1993;27:412–417. 42. Redmond AD. Training in resuscitation. Arch Emerg Med. 1987;4:205–206. 43. Thwaites BC, Shankar S, Niblett D, Saunders J. Can consultants resuscitate? J R Coll Physicians Lond. 1992;26:265–267. 44. West JG, Williams MJ, Trunkey DD, Wolferth CC. Trauma systems. Current status – future challenges. JAMA. 1988;259(24):3597–3600. 45. Pagliarello G, Dempster A, Wesson D. The integrated trauma program: a model for cooperative trauma triage. J Trauma. 1992;33(2):198–204. 46. Shackford SR, Hollingworth-Fridlund P, Cooper GF, Eastman AB. The effect of regionalization upon the quality of trauma care as assessed by concurrent audit before and after institution of a trauma system: a preliminary report. J Trauma. 1986;26(9):812–820. 4 7. Draaisma JM, de Haan AF, Goris RJ. Preventable trauma deaths in the Netherlands – a ­prospective multicenter study. J Trauma. 1989;29(11):1552–1557. 48. Lee A, Bishop G, Hillman KM, Daffurn K. The medical emergency team. Anaesth Intensive Care. 1995;23:183–186. 49. Stenhouse C, Coates S, Tivey M, Allsop P, Parker T. Prospective evaluation of a Modified Early Warning Score to aid detection of patients developing critical illness on a surgical ward. Br J Anaesth. 2000;179(6):663P. 50. Kerridge RK, Saul WP. The medical emergency team, evidence-based medicine and ethics. Med J Aust. 2003;179(6):313–315. 51. Goldhill OR, Worthing L, Mulcahy A, Tarling M, Sumner A. The patient-at-risk team: ­identifying and managing seriously ill ward patients. Anaesthesia. 1999;54:853–860. 52. Wilson RM, Runciman WB, Gibberd RW, et al. The quality in Australian health care study. Med J Aust. 1995;163:458–471. 53. Zhu JN, Weiland TJ, Taylor DM, Dent AW. An observational study of emergency department intern activities. Med J Aust. 2008;188(9):514–519. 54. Wachter RM, Goldman L. The emerging role of hospitalists in the American health care system. N Engl J Med. 1996;335(7):514–517.

6  Medical Trainees and Patient Safety

63

55. Wachter RM. Hospitalists in the United States – mission accomplished or work in progress? N Engl J Med. 2004;350(19):1935–1936. 56. Hauer KE, Wachter RM, McCulloch CE, Woo GA, Auerbach AD. Effects of hospitalist attending physicians on trainee satisfaction with teaching and with internal medicine rotations. Arch Intern Med. 2004;164(16):1866–1871. 57. Riley RH, Grauze AM, Chinnery C, Horley RA, Trewhella NH. Three years of “CASMS:” the world’s busiest medical simulation centre. Med J Aust. 2003;179(11/12):626–630. 58. Papadakis MA, Teherani A, Banach MA, et  al. Disciplinary action by medical boards and prior behavior in medical school. N Engl J Med. 2005;353(25):2673–2682. 59. Association of American Medical Colleges. Learning objectives for medical student education – guidelines for medical schools: Report I of the Medical School Objectives Project. Acad Med. 1999;74(1):13–18. 60. Cruess SR, Cruess RL. Professionalism must be taught. BMJ. 1997;315(7123):1674–1677.

Chapter 7

Rapid Response Systems: A Review of the Evidence Bradford D. Winters and Julius C. Pham

Keywords  Rapid • Response • Systems • Review • Evidence

Introduction Long before the development of the Rapid Response System (RRS) concept, nurses and physicians have been aware that patients rarely deteriorate suddenly. Once practitioners started to ask questions such as “What is happening in the minutes, hours and even days before a patient deteriorates to a cardiorespiratory arrest?” or “Is there something we can do to intervene?” the steps towards creating a new patient safety and quality initiative began. Several studies sought to identify the antecedents to these events and define what might be the most ­predictive signs and symptoms to watch for. The results of these inquires were then linked to an intervention where a team can be summoned based on these changes in a patient’s condition to attempt to halt the progression to a more severe situation or even an arrest. This idea has matured from the early Medical Emergency Teams (METs) piloted in Australia and the US to more comprehensive and diverse systems that include Rapid Response Teams (RRTs), Critical Care Outreach Teams (CCOTs) and other strategies to bring additional resources to the bedside of a patient developing a critical illness. While this strategy makes intuitive sense and has strong face validity, is it supported by the evidence? Do RRSs improve patient safety and quality of care and are they cost-effective? In this chapter we will review the published literature for RRSs to try and address these questions.

B.D. Winters (*) Departments of Anesthesiology, Critical Care Medicine and Surgery, The Johns Hopkins University School of Medicine, Meyer 297 600N Wolfe Street, Baltimore, MD 21298, USA e-mail: [email protected]

M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_7, © Springer Science+Business Media, LLC 2011

65

66

B.D. Winters and J.C. Pham

Evaluating the Evidence Evidence may come from a wide range of sources and vary significantly in quality and quantity. When we weigh the evidence for an intervention, we must be sure to consider these factors. While a thorough review of evidence-based medicine is out of the scope of this chapter, we will address some guiding principles. First, we should always seek the highest possible quality of evidence when designing studies and reviewing the data to inform our decision‑making. Evidence may be categorized based on level of quality (see Table 7.1).1 At the very top (Level 1) are systematic reviews and meta-analyses of randomized controlled ­trials (RCTs) that exhibit a high degree of homogeneity. These are followed by individual RCTs with narrow confidence intervals. Level 2 studies include historical or concurrent cohort trials. Level 3 includes case-controlled studies. Level 4 evidence consists primarily of case series and case studies and Level 5 data is based on expert opinion, physiological principles, bench‑top basic science data or experience. Level 1 trials are able to establish “cause and effect” while studies that do not actively control the intervention in their design can only establish an association. Level 1 evidence should always be the goal; however, it may not always be available to answer a particular question or may be impractical to carry out in a research setting. There are many situations where the “best” attainable evidence may only be Level 2 quality or lower, leaving us to rely on this best available evidence to guide our decisions. While we should not be dogmatic on insisting on Level 1 or even Level 2 data when it is not practical or possible, we must be very critical in our appraisals, especially if the intervention carries great cost or risk. How to balance quantity of evidence with quality is more problematic. Do numerous lower‑quality studies trump a single high‑quality study with conflicting results? How many lower‑quality studies does it take? What if the aggregate number of patients in the lower quality study(s) is vastly larger than the higher quality study(s)? Finally, how do we reconcile or own biases towards the results? Clearly, the answers are difficult, especially when study quality varies significantly. It is no wonder that different reviewers often come to very different conclusions. These issues will become important as we review the RRS literature. Table 7.1  Levels of evidence Evidence level Types of included studies Level 1a Meta–analysis and systematic reviews of RCTS Level 1b RCTs (single and multiple institution) Level 2a Cluster randomized trials, concurrent cohort controlled trials, step–wise trials Level 2b Historically (before/after) controlled trials Level 3 Case controlled studies Level 4 Case studies, case series without controls Level 5 Expert opinion, experience, pathophysiological reasoning, basic science data

7  Rapid Response Systems: A Review of the Evidence

67

Identifying the Deteriorating Patient, the RRS Afferent Limb Several groups became interested in the time period leading up to a cardiorespiratory arrest in the late 1980s and the early 1990s. While these studies do not address the question of whether RRSs are effective, they lay the foundation for why we have developed RRSs and deserve some consideration, since we still are asking them two decades later: “How do we best predict who is experiencing a serious deterioration and is in need of ‘rescue’?” Early chart reviews of patients who had experienced a cardiorespiratory arrest showed clear physiologic abnormalities in variables such as heart rate, respiratory rate and mental status and were also found to be present in patients who went on to arrest.2–19 These signs and symptoms were often present for many hours, if not days,3, 6–8,12 and often went unrecognized even when health care professionals visited the patients.7 Most agreed that tachycardia, bradycardia, tachypnea, oxygen desaturation, low systolic blood pressure, respiratory distress and mental status changes were the clearest signs. While difficult to quantify, concern or worry on the part of nursing staff was also considered predictive of progression to arrest. These retrospective results led to the widespread use of these physiological limits and “worry or concern” being used as “alert” or “activation” criteria for RRSs. This has been recently validated as effective.18 The sensitivity and specificity of physiological limits for preventing arrest is unclear. Several authors have tried to determine if better use can be made of these discretely measured physiological triggers. Some have tried to assign numerical values to degrees of abnormality, which is then summed to create a composite score. Many different “alert” or “activation” systems have been reported; some have been reported as successful,20–34 but others have poor inter‑rater reliability on assigning and calculating these scores.35 This has been noted in other scoring systems.36 Even individual physiological triggers used in RRSs have inter‑rater variability. On average though, simpler scores have been found to work better but not necessarily better than specific vital signs35,37 Bell et al.38 found similar results when comparing restricted to extended criteria. Extended criteria were found to have low specificity and would likely lead to numerous false alarms that could easily overburden an RRS. These authors, however, cautioned that restrictive criteria carried the risk of higher rates of failure to rescue. Others39–41 have also noted this tendency for low sensitivity and low positive predictive value, but one39 did find high specificity for a combination of heart rate, respiratory rate, systolic blood pressure and change in mental status. Attempts to modify the cutoffs for these triggers did not improve the results. A second consideration is the frequency with which patients are monitored. Even if physiological limits are predictive of deterioration, patients in general wards are infrequently monitored, allowing for significant deteriorations to occur before they may even have the chance to be recognized. Buist et al noted that the median time for the occurrence of vital sign changes in general ward patients before their arrest was about 6‑7 h.7 If vital signs are only taken every 8 h, which is common in hospitals in the US, there are significant opportunities to miss a serious problem.

68

B.D. Winters and J.C. Pham

As noted before, this is compounded by the frequent lack of realization that the signs are worrisome. If intermittently collected physiologic vital sign criteria (individual or aggregated into a score) may be less than adequate to optimize opportunities for intervention, can we develop electronic continuous systems, like those used in the ICU, and successfully apply them to general ward patients? Several barriers exist, including the need for patient mobility, high‑fidelity uninterrupted monitoring for these mobile patients and, most especially, an acceptable signal to noise ratio so that all patients’ deteriorations are recognized with minimal false alarms. Many technologies are rapidly developing to address the need for wireless high fidelity monitors. Controlling the signal noise problem is much more difficult. Attempts to address this problem using algorithms to analyze the data streams42–44 and create more reliable “indexed” values44 are in their early stages but offer potential. Improving how we monitor patients on general wards is a crucial element if we are to realize the full potential of RRSs.

The Efferent Limb: The Responding Team Unlike the afferent limb, there is less evidence evaluating the team that responds to a deteriorating patient. This efferent limb may be staffed in myriad ways, depending on the human resources available. Many programs use METs, which include physicians as well as nurses, respiratory therapists and others on the team, while RRTs are nurse‑led teams without physician staffing. While most of these clinicians are based out of the ICU or are critical care‑trained, other staffing models include hospitalists using the code team in a dual role, responding to both45 or even using the primary service as the responders although their response must be immediate when activation criteria are met. To date, there are no head‑to‑head comparisons of these different models of team staffing and there is no evidence to support the superiority of one model over another. In absence of clear data for guidance, choosing a staffing model for an RRS still depends on local resources and culture. Understanding and improving team function has become the subject of interest in a variety of fields, including RRSs. Jones et al have suggested that commonly encountered RRS situations, such as respiratory distress, deserve standardization and protocols, which alone has been shown to improve the quality of care.46 Simulation is a powerful tool for understanding how teams function, identifying opportunities for improvement and for developing and testing protocols for care in urgent/emergent situations such as those frequently encountered by RRS teams. DeVita et al at the University of Pittsburgh have been particularly active in using this strategy to assess RRS team performance. They have shown that team performance can be significantly enhanced through simulator education and training.47 Wallin et al have found similar results especially in the effect on skills. However, while they found improved performance, they also found that this type of education did not help improve attitudes towards “safe” teamwork.48 Education, in general, has been frequently cited as being essential to RRS success.46, 49, 50 Although performance

7  Rapid Response Systems: A Review of the Evidence

69

is essential, there is also much value in cultivating the “culture of safety.” However, to expect that simulation education alone can change culture is shortsighted. Changing culture and attitudes requires a multi‑pronged approach, including simulation.

The Rapid Response System: Is It Effective? The effectiveness of RRSs has been examined using a variety of outcome measurements including in‑hospital mortality, unanticipated ICU admission, incidence of cardiorespiratory arrest, ICU mortality, and hospital, and ICU length of stay (LOS). Recently, research has also evaluated the impact of the RRS on the institution of “not for resuscitation” (NFR) status and the timely goal‑directed resuscitation and administration of broad spectrum antibiotics in patients with sepsis. Outcome measures, like mortality, often are more attractive methodologically, and are often preferably sought by hospital administrators and regulatory agencies. Process measures are often more difficult to get a handle on but are potentially even more important. Rapid response systems seem to have benefit, especially for the outcomes in hospital mortality and cardiorespiratory arrest. However, the data is not homogeneous. Currently only two studies using a randomized methodology exist51,52 and only one examined more than one outcome (the MERIT study). This large, multi‑center study51 found no change in unexpected deaths, cardiac arrests or unplanned admissions to the intensive care unit (ICU). A smaller single institution study also found a significant improvement in mortality.52 Both studies were cluster randomized. Priestley’s study52 also performed a second historical control methodology that corroborated their results; and while not equivalent to blind randomization, such a study would be nearly impossible to achieve with an intervention like RRSs. Even cluster‑randomized methodologies are difficult and controlling, for the Hawthorne effect is extremely problematic. In fact one could argue that a Hawthorne‑like effect is needed to successfully implement a new system as opposed to introducing a new drug. This was one of the problems cited as a possible reason for the negative results of the MERIT study, which showed that many of the calls in the control hospitals demonstrated MET‑type activity rather than cardiac arrest calls.51 All hospitals in the study could not be blinded and were aware that they were being measured. This explanation is underscored by the fact that both the control and the RRS hospitals all significantly improved their mortality and arrest rates as compared to their baseline pre‑study values by roughly the same amounts negating any measurable differences between groups. Additionally, a very recent in‑depth re‑examination of the MERIT study data found that 50% of the time, when the standard cardiac arrest team was called in the “no‑MET” control hospitals, the call was for a patient not experiencing a cardiac or respiratory arrest. This suggests that control hospitals were, in fact, engaging in MET activities but through their cardiac arrest teams. Additionally, under‑utilization of the Medical Emergency Teams in the MET hospitals even when clear activation

70

B.D. Winters and J.C. Pham

criteria were present in patients and a wide variability across the individual hospitals in the number of MET calls and outcomes affects the ability to interpret the original study’s data and draw conclusions. Given this information, Chen et al approached the results from a different perspective, analyzing the data to determine if early intervention made a difference whether it was by a Medical Emergency Team or a cardiac arrest team. They found that early intervention (by any team, control or MET hospital) did result in a significant reduction in all cardiac arrests as well as unexpected cardiac arrests. This significant result was also found to exist for unexpected hospital deaths.53 This suggests that despite the original MERIT study results, a more in-depth look at the data demonstrated positive results that support the RRS and MET concept of early recognition and response to the patient’s bedside. Given these considerations, the MERIT study’s original data, when aggregated with the Priestley study, the point estimate, still, is favorable (0.76) but the confidence interval is wide (0.39–1.48), making it non‑significant as noted by both the systematic review of Winters et al54 and the Cochrane Systematic Review of randomized trials.55 The systematic review of Ranji et al treated the Priestley study separately as a time‑interrupted trial and did not aggregate the data.56 Unfortunately, the data re‑analysis by Chen et al cannot be subjected to meta‑analysis in combination with the Priestley data since the numerator and denominators are defined differently as this would likely lead to an even more favorable result. All of the other studies that have examined mortality and incidence of arrest in adults are nonrandomized but the results are more favorable and consistent. While data quality prevents including most studies in an aggregate analysis, meta‑analysis of the studies providing adequate numerator and denominator data57–68 shows a significant reduction in cardio‑respiratory arrest [OR = 0.625 (CI 95% = 0.502–0.777)] and hospital mortality [OR = 0.886 (CI 95% = 0.771–0.994)] (see Figs. 7.1 and 7.2). These represent 37.5% and 11.4% reductions, respectively. Most of the other non‑randomized studies, including those done in children, also show significant reductions in these outcomes, especially the incidence of arrest.69–73 These benefits also seem to be sustained over time. Buist et al have reported data over a 6‑year timeframe that shows sustained reductions in cardio‑respiratory arrest.74 This result is echoed by Jones et al, who found a sustained reduction in the incidence of cardio‑respiratory arrest over a 4‑year period. Additionally, over the 4  years, surgical patients had reductions in hospital mortality with the RRS program, with two of those years being statistically significant although this did not occur with medical patients. It is unclear why medical patients did not receive the same mortality benefit.59,60 Perhaps their problems are different from surgical patients and RRSs are more effective at intervening with the deteriorations that kill surgical patients. It is also interesting that the effect on arrest rates seems more powerful than the effect on mortality here and in other studies. This, along with the differential effect seen by Jones’s group, may suggest that while RRSs can prevent arrests, their ability to prevent eventual death is more limited, especially in certain patient groups. Many patients admitted to hospital have very severe or terminal illnesses and are unlikely to survive their hospital stay. Rapid response systems would not be expected to affect this, but trying to control it is nearly impossible.

7  Rapid Response Systems: A Review of the Evidence

71

Fig. 7.1  Aggregate analysis of effect on the incidence of cardio–respiratory arrest: nonrandomized studies

Bristow Buist Bellomo-03 Kenward Bellomo-04 Bellomo-07 Garcea Dacey Jolley Chan Combined .4

1

RR of death

2

Fig. 7.2  Aggregate analysis of RRS effect on in–hospital mortality: nonrandomized studies

Jones et al also examined the effect an RRS has on the long‑term mortality of the individual surgical patients finding a benefit extending well beyond hospital discharge.75 Again, early effective interventions in the types of problems surgical patients tend to have may explain this extended benefit as well as the in‑hospital benefit.

72

B.D. Winters and J.C. Pham

The effect of RRSs on another commonly examined outcome, unanticipated ICU admission, is quite variable. The MERIT study is the only randomized trial to evaluate for this and found no significant change.51 Two more recent non‑randomized studies found decreases in ICU admissions,67,76 while two found no change.68,77 Earlier studies58, 63 found statistically significant reductions but one61 found a statistically significant increase. This variability is not surprising, given the effect that individual hospital systems, resources and culture have on which patients get admitted to the ICU and under what circumstance. Changes in unanticipated ICU admissions should not be viewed as good versus bad but rather in the context of the institution’s culture. When admission rates go up, but mortality and arrest rates go down, it is inappropriate to consider this a failure. Two studies have examined RRSs in combination with other patient safety initiatives and reported favorable results.78,79 Both studies found reductions in mortality, but that component attributable to the RRS is unknown. One of the studies79 also found a reduction in the cardio‑respiratory arrest rate, which was most likely attributable to the RRS. The IHI 100,000 Lives Campaign likewise reports mortality reduction among its participating hospitals80 but uses a six‑plank program of which RRSs are only one component. Additionally, not all hospitals implemented all planks and the IHI cannot attribute their observed reductions to any specific plank. Other outcomes, such as ICU mortality and LOS, either have too few reports and/or unclear denominators, making interpretation difficult. Like ICU admission, it is unclear whether LOS should go up or down with an RRS, since patients who are rescued may have much longer LOS than those who die. Additionally, there are many local factors that affect LOS, making generalizability of the data difficult. The effect of RRSs on the process of care is an area for great potential that has only been explored in a limited fashion. Sebat et al studied septic and hypovolemic shock patients over a 5‑year period and found that having an RRS significantly improved such process measures as institution of appropriate goal‑directed fluid therapy. These improvements were associated with reductions in mortality especially for those with septic shock.81 While it has not been studied in a rigorous manner yet, many papers have alluded to the number of patients appropriately made NFR after an RRS activation. Perhaps the need to activate the RRS underscores the patient’s severe condition and creates a forum in which these discussions may begin. We have personally experienced this in our own RRS program on several occasions. A post hoc analysis of the MERIT study database,82 as well as a separate pilot study,83 have begun to more formally explore how RRSs may benefit this process of care. Other outcomes that RRSs may help with include nursing satisfaction, nurse retention, education and patient and family satisfaction. Unfortunately, much of the evidence in support of these is anecdotal. Where family RRS activation is available, families report tremendous support of the system. Nurses are generally quite positive, with some finding the idea of stopping such programs abhorrent.84–86 Hopefully, in the future, survey and resource studies of these measures will provide higher quality evidence.

7  Rapid Response Systems: A Review of the Evidence

73

Finally, we consider whether RRSs are cost‑effective. Unfortunately, there are almost no studies directly addressing whether RRSs have financial benefits through the implementation of an actual program. One study87 that did do so used a modified RRS benefits calculator originally created by William Ward,88 estimating a cost savings of US $170,000. However, as Mr. Ward pointed out in an editorial, their modifications of the calculator to emphasize cost saving misses an important point. Costs are mostly fixed. Keeping a patient on the general ward and avoiding an ICU admission does not allow you to reduce costs. You still need the staff to cover the ICU bed. The bed still “costs” money. The hospital is just not generating any revenue from it because it is now empty. Cutting staff to save costs only hampers your ability to provide quality. Generating revenue through improved processes and quality that allows you to care for more patients efficiently and more safely with fewer complications (like an arrest), is where the real financial benefit from RRSs can come from. As Ellen Lasser noted, “Cost savings will not be achieved by cutting corners, but rather by eliminating processes that lead to poor outcomes and ultimately high costs.”89 As RRSs seek to do just that, we should see evidence emerge that they are in fact, cost‑effective.

Summary Overall, the balance of evidence indicates that RRSs are effective. While the largest randomized study was underpowered and inconclusive, a smaller randomized one was positive. Numerous non‑randomized studies have demonstrated benefit individually and in aggregate. This is especially true for the ability of RRSs to reduce the incidence of cardio‑respiratory arrest. The situation is not as strong for their ability to reduce mortality, although the trend is quite favorable. It is likely that surgical patients and those experiencing shock may experience a greater benefit from RRSs, although this does not mean that RRSs should be reserved only for those patients. This would be logistically difficult in many hospitals and may be viewed as unethical by many, since the evidence is limited in this regard. The ability to study RRSs and their effectiveness is somewhat limited by the nature of the intervention. Their implementation cannot be blinded, individual patient randomization is nearly impossible, and confounders are difficult to control. Additionally, their widespread implementation into many hospitals in the US, Australia and the UK makes future randomization extremely difficult. Other places, like Europe or Asia, may be able to generate additional randomized studies, but non‑randomized cohort studies may be the highest quality data that can be achieved. Given these restrictions, we must rely on this level of evidence as it is. It is hoped that as further studies are published, additional attention will be given to outcomes such as nursing and patient/family satisfaction, staff retention, culture change, safety climate and especially process measures. All of these measures deserve attention as we seek to create safer systems for our patients.

74

B.D. Winters and J.C. Pham

References 1. Straus SE, Richardson WS, Glasziou P, Haynes RB. Evidence‑Based Medicine. 3rd ed. Edinburgh: Churchhill Livingstone; 2005:169. 2. Sax FL, Charlson ME. Medical patients at high risk for catastrophic deterioration. Crit Care Med. 1987;15(5):510–515. 3. Schein RM, Hazday N, Pena M, Robin BH, Sprung CL. Clinical antecedents to in‑hospital cardiopulmonary arrest. Chest. 1990;98(6):1388–1392. 4. Bedell SE, Deitz DC, Leeman D, Delbanco TL. Incidence and characteristics of preventable iatrogenic cardiac arrests. JAMA. 1991;265(21):2815–2820. 5. Daffurn K, Lee A, Hillman KM, Bishop GF, Bauman A. Do nurses know when to summon emergency assistance? Intensive Crit Care Nurs. 1994;10(2):115–120. 6. Smith AF, Wood J. Can some in‑hospital cardio‑respiratory arrests be prevented? A prospective survey. Resuscitation. 1998;37(3):133–137. 7. Buist MD, Jarmolowski E, Burton PR, Bernard SA, Waxman BP, Anderson J. Recognising clinical instability in hospital patients before cardiac arrest or unplanned admission to intensive care. A pilot study in a tertiary‑care hospital. Med J Aust. 1999;171(1):22–25. 8. Hillman KM, Bristow PJ, Chey T, Daffurn K, et al. Antecedents to hospital deaths. Intern Med J. 2001;31(6):343–348. 9. Hodgetts TJ, Kenward G, Vlachonikolis IG, et al. Incidence, location and reasons for avoidable in‑hospital cardiac arrest in a district general hospital. Resuscitation. 2002;54(2):115–123. 10. Kause J, Smith G, Prytherch D, et al. A comparison of antecedents to cardiac arrests, deaths and emergency intensive care admissions in Australia, New Zealand, and the United Kingdom ‑ the ACADEMIA study. Resuscitation. 2004;62(3):275–282. 11. Nurmi J, Harjola VP, Nolan J, Castren M. Observations and warning signs prior to cardiac arrest. Should a medical emergency team intervene earlier? Acta Anaesthesiol Scand. 2005;49(3):702–706. 12. Hillman K, Bristow PJ, Chey T, et al. Duration of life‑threatening antecedents prior to intensive care admission. Intensive Care Med. 2002;28:1629–1634. 13. Franklin C, Mathew J. Developing strategies to prevent in‑hospital cardiac arrest: analyzing responses of physicians and nurses in the hours before the event. Crit Care Med. 1994;22(2):244–247. 14. McGloin H, Adam SK, Singer M. Unexpected deaths and referrals to intensive care of patients on general wards. Are some cases potentially avoidable? J R Coll Physicians Lond. 1999;33(37):255–259. 15. Goldhill DR, White SA, Sumner A. Physiological values and procedures in the 24 h before ICU admissions from the ward. Anaesthesia. 1999;54(6):529–534. 16. Goldhill DR, Worthington L, Mulcahy A, Tarling M, Sumner A. The patient‑at‑risk team: identifying and managing seriously ill ward patients. Anaesthesia. 1999;54(2):853–860. 17. Buist M, Bernard S, Nguyen TV, Moore G, Anderson J. Association between clinically abnormal observations and subsequent in‑hospital mortality: a prospective study. Resuscitation. 2004;62(2):137–141. 18. Santiano N, Young L, Hillman K, et al. Analysis of medical emergency team calls comparing subjective to “objective” call criteria. Resuscitation. 2009;80(1):44–49. 19. Hodgetts TJ, Kenward G, Vlachonikolis IG, Payne S, Castle N. The identification of risk ­factors for cardiac arrest and formulation of activation criteria to alert a medical emergency team. Resuscitation. 2002;54(2):125–131. 20. Stenhouse C, Coates S, Tivey M, Allsop P, Parker T. Prospective evaluation of a Modified Early Warning Score to aid earlier detection of patients developing critical illness on a general surgical ward. Br J Anaesth. 2000;84:663P. 21. Lee A, Bishop G, Hillman K, Daffurn K. The medical emergency team. Anaesth Intensive Care. 1995;23:183–186.

7  Rapid Response Systems: A Review of the Evidence

75

22. Morgan RJM, Williams F, Wright MM. An early warning scoring system for detecting developing critical illness. Clin Intensive Care. 1997;8:100. 23. Goldhill DR, McNarry AF. Physiological abnormalities in early warning scores are related to mortality in adult in‑patients. Br J Anaesth. 2004;92(6):882–884. 24. Goldhill DR, McNarry AF, Mandersloot G, McGinley A. A physiologically‑based early warning score for ward patients: the association between score and outcome. Anaesthesia. 2005;60(6):547–553. 25. Sharpley JT, Holden JC. Introducing an early warning scoring system in a district general hospital. Nurs Crit Care. 2004;9:98–103. 26. Gardner‑Thorpe J, Love N, Wrightson J, Walsh S, Keeling N. The value of Modified Early Warning Score (MEWS) in surgical in‑patients: a prospective observational study. Ann R Coll Surg Engl. 2006;88:571–575. 27. Harrison GA, Jacques T, McLaws ML, Kilborn G. Combinations of early signs of critical illness predict in‑hospital death ‑ the SOCCER study (signs of critical conditions and emergency responses). Resuscitation. 2006;71:327–334. 28. Jacques T, Harrison GA, McLaws ML, Kilborn G. Signs of critical conditions and emergency responses (SOCCER): a model for predicting adverse events in the inpatient setting. Resuscitation. 2006;69:175–183. 29. Subbe CP, Hibbs R, Williams E, Rutherford P, Gemmel L. ASSIST: a screening tool for critically ill patients on general medical wards. Intensive Care Med. 2002;28(Suppl 1):S21. 30. Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified Early Warning Score in medical admissions. Q J Med. 2001;94(10):521–526. 31. Subbe CP, Davies RG, Williams E, Rutherford P, Gemmell L. Effect of introducing the Modified Early Warning score on clinical outcomes, cardio‑pulmonary arrests and intensive care utilisation in acute medical admissions. Anaesthesia. 2003;58(8):797–802. 32. Haines C, Perrott M, Weir P. Promoting care for acutely ill children. Development and evaluation of a pediatric early warning tool. Intensive Crit Care Nurs. 2006;22(2):73–81. 33. Monaghan A. Detecting and managing deterioration in children. Paediatr Nurs. 2005;17(1):32–35. 34. Duncan H, Hutchison J, Parshuram CS. The pediatric early warning system score: a severity of illness score to predict urgent medical need in hospitalised children. J Crit Care. 2006;21(13):271–279. 35. Subbe CP, Gao H, Harrison DA. Reproducibility of physiological track‑and‑trigger warning systems for identifying at‑risk patients on the ward. Intensive Care Med. 2007;33(4): 619–624. 36. Polderman K, Christiaans HMT, Wester JP, Spijkstra JJ, Girbes ARJ. Intra‑observer variability in APACHE II scoring. Intensive Care Med. 2001;27(9):1550–1552. 37. Gao H, McDonnell A, Harrison DA, Moore T, et  al. Systematic review and evaluation of physiological track and trigger warning systems for identifying at‑risk patients on the ward. Intensive Care Med. 2007;33(4):667–679. 38. Bell MB, Konrad D, Granath F, Ekbom A, Martling CR. Prevalence and sensitivity of MET‑criteria in a Scandinavian university hospital. Resuscitation. 2006;70(1):66–73. 39. Cretikos M, Chen J, Hillman K, Bellomo R, Finfer S, Flabouris A. MERIT study investigators. The objective medical emergency team activation criteria: a case‑control study. Resuscitation. 2007;73(1):62–72. 40. Smith GB, Prytherch DR, Schmidt PE, Featherstone PI, Higgins B. A review, and performance evaluation, of single‑parameter “track and trigger” systems. Resuscitation. 2008;79(1):11–21. 41. Smith GB, Prytherch DR, Schmidt PE, Featherstone PI. Review and performance evaluation of aggregate weighted “track and trigger” systems. Resuscitation. 2008;77(2):170–179. 42. Smith GB, Prytherch DR, Schmidt P, Featherstone PI, et  al. Hospital‑wide physiological surveillance. A new approach to the early identification and management of the sick patient. Resuscitation. 2006;71(1):19–28.

76

B.D. Winters and J.C. Pham

43. Watkinson PJ, Barber VS, Price JD, Hann A, et al. A randomised controlled trial of the effect of continuous electronic physiological monitoring on the adverse event rate in high risk medical and surgical patients. Anaesthesia. 2006;61(11):1031–1039. 44. Tarassenko L, Hann A, Young D. Integrated monitoring and analysis for early warning of patient deterioration. Br J Anaesth. 2006;97(1):64–68. 45. Hunt EA, Zimmer KP, Rinke ML, et al. Transition from a traditional code team to a medical emergency team and categorization of cardiopulmonary arrests in a children’s center. Arch Pediatr Adolesc Med. 2008;162(2):117–122. 46. Jones D, Bates S, Warrillow S, Goldsmith D, et al. Effect of an education programme on the utilization of a medical emergency team in a teaching hospital. Intern Med J. 2006;36(4):231–236. 47. DeVita MA, Schaefer J, Lutz J, Wang H, Dongilli T. Improving medical emergency team (MET) performance using a novel curriculum and a computerized human patient simulator. Qual Saf Health Care. 2005;14(5):326–331. 48. Wallin CJ, Meurling L, Hedman L, Hedegård J, Felländer‑Tsai L. Target‑focused medical emergency team training using a human patient simulator: effects on behaviour and attitude. Med Educ. 2007;41(2):173–180. 49. Cretikos MA, Chen A, Hillman KM, Bellomo R, Finfer S, Flabouris A. MERIT Study Investigators. The effectiveness of implementation of the medical emergency team (MET) system and factors associated with use during the MERIT study. Crit Care Resusc. 2007;9(2):205–212. 50. Buist M, Bellomo R. MET. The emergency medical team or the medical education team? Crit Care Resusc. 2004;6:88–91. 51. MERIT Study Investigators. Introduction of the medical emergency team (MET) system: a cluster‑randomised controlled trial. Lancet. 2005;365(9477):2091–2097. 52. Priestley G, Watson W, Rashidian A, et  al. Introducing critical care outreach: a ward‑­ randomised trial of phased introduction in a general hospital. Intensive Care Med. 2004; 30(7):1398–1404. 53. Chen J, Bellomo R, Flabouris A, Hillman K, Finfer S. MERIT Study Investigators for the Simpson Centre and the ANZICS Clinical Trials Group. The relationship between early emergency team calls and serious adverse events. Crit Care Med. 2009;37(1):148–153. 54. Winters BD, Pham JC, Hunt EA, Guallar E, Berenholtz S. Pronovost PJl. Rapid response systems: a systematic review. Crit Care Med. 2007;35(5):1238–1243. 55. McGaughey J, Alderdice F, Fowler R, Kapila A, et al. Outreach and Early Warning System (EWS) for the prevention of intensive care admission and death of critically ill adult patients on general hospital wards. Cochrane Database Syst Rev. 2007;18:CD00552. 56. Ranji SR, Auerbach AD, Hurd CJ, O’Rourke K, Shojania KG. Effects of rapid response systems on clinical outcomes: systematic review and meta‑analysis. J Hosp Med. 2007; 2(6):422–432. 57. Bellomo R, Goldsmith D, Uchino S, et al. A prospective before‑and‑after trial of a medical emergency team. Med J Aust. 2003;179(6):283–287. 58. Bellomo R, Goldsmith D, Uchino S, et  al. Prospective controlled trial of effect of medical emergency team on postoperative morbidity and mortality rates. Crit Care Med. 2004;32(4):916–921. 59. Jones D, Bellomo R, Bates S, et al. Long‑term effect of a medical emergency team on cardiac arrests in a teaching hospital. Crit Care. 2005;9(6):R808–815. 60. Jones D, Opdam H, Egi M, et al. Long‑term effect of a medical emergency team on mortality in a teaching hospital. Resuscitation. 2007;74(2):235–241. 61. Buist MD, Moore GE, Bernard SA, Waxman BP, Anderson JN, Nguyen TV. Effects of a medical emergency team on reduction of incidence of and mortality from unexpected cardiac arrests in hospital: preliminary study. BMJ. 2002;324(7334):387–390. 62. Chan PS, Khalid A, Longmore LS, Berg RA, Kosiborod M, Spertus JA. Hospital‑wide code rates and mortality before and after implementation of a rapid response team. JAMA. 2008;300(21):2506–2513.

7  Rapid Response Systems: A Review of the Evidence

77

63. Bristow PJ, Hillman KM, Chey T, et al. Rates of in‑hospital arrests, deaths and intensive care admissions: the effect of a medical emergency team. Med J Aust. 2000;173(5):236–240. 64. Kenwood G, Castle N, Hodgetts T, Shaikh L. Evaluation of a medical emergency team one year after implementation. Resuscitation. 2004;61(3):257–263. 65. DeVita MA, Braithwaite RS, Mahidhara R, Stuart S, Foraida M, Simmons RL. Use of medical emergency team responses to reduce hospital cardiopulmonary arrests. Qual Saf Health Care. 2004;13(4):251–254. 66. Jolley J, Bendyk H, Holaday B, Lombardozzi KAK, Harmon C. Rapid response teams: do they make a difference? Dimens Crit Care Nurs. 2007;26(6):253–260. 67. Dacey MJ, Mirza ER, Wilcox V, et al. The effect of a rapid response team on major clinical outcome measures in a community hospital. Crit Care Med. 2007;35(9):2076–2082. 68. Garcea G, Thomasset S, McClelland L, Leslie A, Berry DP. Impact of a critical care outreach team on critical care readmissions and mortality. Acta Anaesthesiol Scand. 2004;48(9):1096–1100. 69. Tibballs J, Kinney S, Duke T, Oakely E, Hennessy M. Reduction of pediatric in‑patient cardiac arrest and death with a medical emergency team: preliminary results. Arch Dis Child. 2005;90(11):1148–1152. 70. Tibballs J, Kinney S. Reduction of hospital mortality and of preventable cardiac arrest and death on introduction of a pediatric medical emergency team. Pediatr Crit Care Med. 2009;10(3):306–312. 71. Brilli RJ, Gibson R, Luria JW, et al. Implementation of a medical emergency team in a large pediatric teaching hospital prevents respiratory and cardiopulmonary arrests outside the intensive care unit. Pediatr Crit Care Med. 2007;8(3):236–246. 72. Sharek PJ, Parast M, Leong K, et  al. Effect of a rapid response team on hospital‑wide ­mortality and code rates outside the ICU in a children’s hospital. JAMA. 2007;298(19): 2267–2274. 73. Zenker P, Schlesinger A, Hauck M, et al. Implementation and impact of a rapid response team in a children’s hospital. Joint Comm J Qual Saf. 2007;33(7):418–425. 74. Buist M, Harrison J, Abaloz E, Van Dyke S. Six‑year audit of cardiac arrests and medical emergency team calls in an Australian teaching hospital. BMJ. 2007;335(7631):1210–1212. 75. Jones D, Egi M, Bellomo R, Goldsmith D. Effect of the medical emergency team on long‑term mortality following major surgery. Crit Care. 2007;11(1):R12. 76. Ball C, Kirkby M, Williams S. Effect of the critical care outreach team on patient survival to discharge from hospital and re‑admission to critical care: non‑randomised population based study. BMJ. 2003;327(7422):1014–1016. 77. Leary T, Ridley S. Impact of an outreach team on re‑admissions to a critical care unit. Anaesthesia. 2003;58(4):328–332. 78. Mailey J, Digiovine B, Baillod D, Gnam G, Jordan J, Rubinfeld I. Reducing hospital standardized mortality rate with early interventions. J Trauma Nurs. 2006;13(4):178–182. 79. Tolchin S, Brush R, Lange P, Bates P, Garbo JJ. Eliminating preventable death at Ascension Health. Joint Comm J Qual Saf. 2007;33(3):145–154. 80. 100  K Lives Campaign. http://www.ihi.org/IHI/Programs/Campaign/Campaign; 2009 Accessed 05.01.09. 81. Sebat F, Musthafa AA, Johnson D, et  al. Effect of a rapid response system for patients in shock on time to treatment and mortality during 5  years. Crit Care Med. 2007;35(11): 2568–2575. 82. Chen J, Flabouris A, Bellomo R, Hillman K, Finfer S. MERIT Study Investigators for the Simpson Centre and the ANZICS Clinical Trials Group. The Medical Emergency Team System and not‑for‑resuscitation orders: results from the MERIT study. Resuscitation. 2008;79(3):391–397. 83. Jones DA, McIntyre T, Baldwin I, Mercer I, Kattula A, Bellomo R. The medical emergency team and end‑of‑life care: a pilot study. Crit Care Resusc. 2007;9(2):151–156. 84. Jones D, Baldwin I, McIntyre T, et al. Nurse’s attitudes to a medical emergency team service in a teaching hospital. Qual Saf Health Care. 2006;15(6):427–432.

78

B.D. Winters and J.C. Pham

85. Galhotra S, Scholle CC, Dew MA, Mininni NC, Clermont G, DeVita MA. Medical emergency teams: a strategy for improving patient care and nursing work environments. J Adv Nurs. 2006;55(2):180–187. 86. Salamonson Y, van Heere B, Everett B, Davison P. Voices from the floor: nurses’ perceptions of the medical emergency team. Intensive Crit Care Nurs. 2006;22(3):138–143. 87. Thomas K, Vanoyen Force M, Rasmussen D, Dodd D, Whildin S. Rapid response team: ­challenges, solutions, benefits. Crit Care Nurse. 2007;27(1):20–27. 88. Ward WJ. The business case for implementing rapid response teams [power point presentation]. http://www.ihi.org/IHI/Topics/CriticalCare/IntensiveCare/Tools Business Case for Implementing RRTs Presentation; 2009 Accessed 05.01.09. 89. Lanser E. Outcomes and performance measurement. Redefining how healthcare is strategized and delivered. Healthc Exec. 1999;14(4):20–24.

Chapter 8

Healthcare Systems and Their (Lack of ) Integration Ken Hillman, Jeffrey Braithwaite, and Jack Chen

Keywords  Healthcare • systems • integration European monks established acute hospitals as an adjunct to their monasteries to care for Christian soldiers on their way to and from the crusades. The hospitals gradually separated from the monasteries to become more autonomous in both their locations and functions. Although separated from the monasteries geographically, they often remained formally attached to religious orders; in some instances, this relationship continues to this day. The study of medicine soon became part of some European universities, such as Padua and Florence in Italy, and then gradually to other universities across Europe. The teaching of medicine remained largely centered on public hospitals. Even to this day, public hospitals play a major role in undergraduate teaching. However, the practice, as opposed to the teaching of medicine was, until the middle of the twentieth century, based on physicians treating fee-paying patients, usually in their own homes. While medical practitioners would earn their living treating individual fee-­paying patients, they remained attached to public hospitals in order to teach medical ­students and supervise junior doctors in training. These apprentices would be responsible for the majority of care in public hospitals. The hospitals were largely charitable. The clinician would visit the public hospital for several hours each week to attend the poor.

K. Hillman (*) The Simpson Centre for Health Services Research, Critical Care Services, Liverpool Hospital, The University of New South Wales, Locked Mailbag 7103, Liverpool BC, NSW 1871, Australia and The Australian Institute of Health Innovation, The University of New South Wales, Sydney, NSW 2052, Australia e-mail: [email protected] M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_8, © Springer Science+Business Media, LLC 2011

79

80

K. Hillman et al.

Teaching and research were performed on these patients. Everyone seemingly gained. The sick received free care; medical students and junior medical staff learned the art of medicine; and the senior clinicians’ conscience and sense of virtuousness were satisfied.1 Because the hospital depended on the physician giving his time for free, the hospital function was structured around his convenience. For example, each senior doctor had access to his own ward and nursing staff. A hierarchy of junior medical staff in training was attached to each specialist. Surgeons had their own operating rooms and recovery areas. The legacy of these arrangements is that hospital systems have been established around the needs of specialist doctors, not the patients.2–4 This is reinforced by medical training that is largely centered around the doctor/patient relationship. Doctors are taught about individual patient signs, symptoms, history, diagnosis and treatment. Students today may learn more about public health and communication skills than in the past, but usually not much about how to establish and work within systems built around the needs of the patient. The hospital system designed for the hospital’s senior physicians probably worked reasonably well until approximately the middle of the last century. Up until then, hospital treatment was based on a small number of operations and procedures, a few primitive investigative tools, and a small range of therapeutic medicines. Hospitals were often places to manage the sick with bed rest and convalescence. An explosion of medical knowledge occurred beginning in the 1950s. Complex surgery, such as cardiac valve replacement, transplant surgery and cancer surgery became commonplace. Great advances occurred in anesthesia, which made the performance of these procedures possible. Physicians developed a wide range of drugs, including antibiotics, chemotherapy and antiarrhythmics. As a result of complex surgery, sophisticated postoperative care was necessary. The speciality of intensive care was born. The skills used to support patients in the operating and recovery rooms (such as artificial ventilation and administration of powerful drugs such as vasopressors) enabled patients, who would have died otherwise to survive, including those with poliomyelitis and severe infections. However, to this day, patients usually remain under an individual clinician who “owns” them. In larger institutions, nursing staff, together with a hierarchy of junior medical staff, often still manage the day-to-day care of the patients. The management of patients through a hospital is often inefficient, dislocated and disorganized.4 In part, this is due to high levels of complexity. The problem of delivering safe care within an antiquated system is exacerbated by the increase in medical specialization combined with the changing nature of hospital patients. Patients are now older with multiple co-morbidities.5 There is an increasing mismatch between these complex at-risk patients with multi-system problems and physicians who have specialized training in a limited area; (e.g. neurology); in one geographical area (e.g. emergency medicine); one population type (e.g. rehabilitation and pediatrics); or in procedures (e.g. surgeons). For example, a patient may be treated by a renowned plastic surgeon supported by excellent nursing staff and trainee doctors. But, let us imagine that,

8  Healthcare Systems and Their (Lack of) Integration

81

despite a high level of care, the patient bleeds postoperatively. Hypovolemic shock is not a common occurrence on a plastic surgery ward. The patient becomes tachycardic and hypotensive for some time. Nursing staff inform the most junior medical staff, who, in turn, report through their hierarchy. The patient may also have co-morbidities, such as ischemic heart disease, hypertension, non-insulin dependent diabetes and chronic lung disease. The hypotension causes myocardial and renal ischemia. A physician is called who orders an EKG that shows ischemia. Aspirin and beta-blockers are ordered. As a result, the bleeding becomes worse and the tachycardic response is blunted. We argue that the system of care fails because it is a system designed to perform elective surgical procedures and assumes that patients will have an uncomplicated postoperative course and that physicians and nurses will be able to recognize and treat deviations in the course of the patients’ illness. The attending doctors and nurses are not trained in the basic principles of how to recognize seriously ill patients, let  alone on how to deliver advanced resuscitation. Furthermore, the system’s care co-ordinating function is missing. In-hospital patients with cross-specialty problems (for example, medical disease in a surgical patient, or surgical illness in a medical patient) are treated using a complex system of referral. The treating medical teams refer problems that are outside their own areas of expertise to other colleagues. This works well for situations that are not life-threatening but, for the increasing population of at-risk patients in acute hospitals, the lack of systems that work at the interfaces between specialists, professions and departments may contribute to excessive morbidity and mortality.6 Seriously ill patients require the urgent attention of specialists such as those trained in intensive care medicine. While intensive care specialists are competent at recognizing and managing events such as ischemia and hypoxia, they have, until recently, practiced within their own four walls.5–8 Thus, the intensive care unit (ICU) is simply another silo in the hospital and, if a seriously ill patient is fortunate enough to receive their care within this domain, they have a good chance of being well managed. However, if the hospital has no system for recognizing at-risk patients, their outcome may be poor. The usual referral process takes time. Ischemia and hypoxia, even in relatively minor degrees, need urgent recognition and intervention. When the patient behaves in a predictable fashion, the silos in healthcare usually work well. Individual doctors, and the areas in which they work, are trained to provide excellent standards of care. However, patients are increasingly falling through gaps between these silos. Many patients die potentially preventable deaths in acute hospitals.9,10 These deaths represent the “tip of the iceberg” of harms that befall patients due to system failures in hospital. For every potentially preventable death, there are many patients who suffer serious adverse events. Up to 80% of hospital cardiac arrests are preceded by at least 8  h of slow deterioration 11; and there are a similar number of potentially preventable antecedents that precede ­hospital deaths 12 and unexpected admissions to the ICU.13 New ways of integrating care around patient needs are being explored and tested. For example, North America has been using “hospitalists” for several years.14

82

K. Hillman et al.

They have a wide range of expertise but concentrate more on acute medicine, especially in the context of older patients with co-morbidities. The hospitalist also understands about continuity and co-ordination of patient care, managing the patient’s in-hospital course and arranging a seamless transition back to a community setting.14 This is one of the ways of counteracting the lack of integration in acute hospital systems. There have also been other patient-centered systems that work on a wholeof-hospital basis – so-called Rapid Response Systems (RRS). They have been designed to recognize seriously ill patients in terms of vital signs and observational abnormalities. There are many forms of RRSs,15–17 the details of which are described in other chapters in this book. While the RRSs were initially established to identify and respond to seriously ill patients, the challenge of implementing a hospital-wide system has highlighted the lack of integration in acute hospitals. In a cluster randomized study evaluating the Medical Emergency Team (MET) system,18 it was found that in the MET hospitals less than half of all patients who suffered an adverse event had their vital signs measured within 24 h of the event. Moreover, only half of all patients who had criteria that defined serious illness had an emergency call made. Obviously, a system based on identifying the seriously ill will not be effective if the criteria defining critical illness are not measured frequently enough. Nor will it function if, after a patient has met the criteria, staff do not activate a call to trigger a response. Silo-based care in acute hospitals has existed for many centuries and because it is so entrenched, it has become difficult to implement whole-of-hospital systems. In order to overcome the lack of integration and to effectively implement a RRS, there are a minimum of five essential components that must be simultaneously instituted (See Table 8.1). Table 8.1  Essential components for implementing a Rapid Response System Calling criteria

Rapid response

Evaluation of the system

Education Ownership

Predefined levels of vital sign and observational abnormalities need to be agreed on and displayed across the organization for the recognition of seriously ill and at-risk patients An around-the-clock response must be available with at least one person skilled in all aspects of advanced resuscitation Agreed data must be collected in order to define the extent of the problem and track the effectiveness of the implementation strategy. The data must be packaged and widely distributed in order to drive effect implementation All staff in the organization must be aware of the system and how to activate it The system must be supported by senior management and clinicians in a formal way in order to ensure effective implementation and sustainability

8  Healthcare Systems and Their (Lack of) Integration

83

Identification of the Seriously Ill At-Risk Patient Successful identification is based on: • Abnormal vital sign readings ‑ pulse rate, respiratory rate and blood pressure. • Abnormal observations, such as airway obstruction, seizures and a decreased level of consciousness. • Other measurements, such as oxygen saturation and urine output can also be included. • The so-called calling criteria must also include “staff concern.” In a mature RRS, staff concern accounts for almost 50% of all emergency calls.

Response to the Seriously Ill Patient • If a patient meets any one of the predefined criteria, a rapid response is mandatory. • The response must always include at least one person who is skilled in all aspects of advanced resuscitation. • It is acknowledged that a list of calling criteria and a response alone will not bring about a “safe” system. The availability of an appropriate response around the clock requires education of existing staff.

Education • All hospital staff need to be aware that an around-the-clock system exists for the identification of, and response to, the seriously ill. They must also be familiar with how to activate the system. This would be the responsibility of individual hospitals and would include strategies such as the calling criteria being included on the back of all hospital name badges; laminated versions of the criteria being made available in all general wards and public places; and explaining the system as part of all hospital staff orientation programs. • There is a general acceptance that the level of skills and knowledge of junior medical, nursing and other ward staff regarding acute medicine, recognizing signs of the deteriorating patient and simple treatment measures is less than satisfactory and education programs should aim to correct this. • The aim of any RRS is to have a least one person available around the clock who has the necessary skills and knowledge to attend to seriously ill at-risk patients in every acute hospital. It must be emphasized that this is a minimum standard, not an optional consideration. It is pointless to identify seriously ill patients if

84

K. Hillman et al.

there are no staff members trained in handling emergencies. Specific education programs, ideally based in specifically designed skills laboratories may be necessary.

Evaluation • Evaluation19 is critical as part of the implementation process and to ensure sustainability. • The evaluation data must be valid and reliable as well as inexpensive to collect. They must accurately reflect how well the system is working and how and where it can be improved. Evaluation must be owned and operated by each institution. • Evaluation of the local system by local staff is the single most important factor in transferring practices elsewhere and sustainability. • The four most important outcomes for evaluating a health system (and specifically the RRS) are: –– –– –– ––

Potentially preventable deaths Potentially preventable cardiac arrests Potentially preventable intensive care admissions Potentially preventable is defined by the event being preceded by one of the calling criteria where there has been no response. –– Number of rapid response calls per 1,000 admissions. This is the single most accurate determinant of effectiveness and sustainability. A system that is just beginning has between three and seven calls per 1,000 admissions and a mature, more effective system has between 40 and 50 calls per 1,000 admissions. • The outcome indicators must be attractively packaged and regularly fed back to all levels of the institution.

Support • Such a system will not work without high-level administrative as well as widespread clinical support. • The Institute of Healthcare Improvement (IHI) in the United States as well as Canadian and Scandinavian experiences suggests that making hospitals safe by providing RRSs for at-risk patients was the single most important factor and therefore the highest priority for saving lives. In Canada and some Scandanavian countries, the most senior executive in the health region/institution was given the responsibility for implementation and sustainability of the RRS. Leadership seems therefore essential support for a successful system.

8  Healthcare Systems and Their (Lack of) Integration

85

• Usually, a specific overarching regional and institutional committee is established to both establish and maintain the system. The committee reviews whether the strategies for the identification of the at-risk patient are being effectively implemented. They also ensure that widespread educational strategies are in place; and, importantly, regularly review the outcome indicators and adjust the system as appropriate. • While the organization framework for the system could be embedded within the existing hospital structure, the system itself requires a separate structure and brief and it should be directly accountable to the institutional senior executive. For example, data for evaluation may already be collected within the organization but successful implementation depends on recognizing the challenges of combining all existing functions and levels into a cohesive system with separate responsibility and accountability. The process of implementing an RRS in an organization influences the culture20 of that organization.21 For example, it facilitates the organization to develop a template for other hospital-wide patient-centered initiatives. It encourages hospital administration and clinicians to work together in establishing other patient safety programs. The process empowers staff who are delivering healthcare directly to patients to have the confidence not only to observe and measure patient vital signs and observations, but also to take action based on those measurements. The pioneers of intensive care created an environment in which the specialty could be nurtured. From within ICUs there developed educational strategies for training specialists, as well as a place to consolidate the legitimacy of the specialty and to refine the knowledge and skills necessary to deliver a high level of care. Now that the specialty of critical care medicine has been secured within the walls of the ICU, the next major advance in intensive care medicine is to contribute to the creation of systems to either prevent admission to ICU or optimize the outcome of those we manage in the ICU. As early as 1974, Peter Safar,22 one of the pioneers in intensive care, stated that “The most sophisticated intensive care often becomes unnecessarily expensive terminal care when the pre-ICU system fails,” The development of patient-centered systems to improve safety has been a major step forward in increasing hospital integration.

References 1. Marsh WJ. Physicians, practitioners and fees. BMJ. 1878;1:197–198. 2. Hillman K. The changing role of acute‑care hospitals. Med J Aust. 1999;170:325–328. 3. Braithwaite J, Vining RF, Lazarus L. The boundaryless hospital. Aust NZ J Med. 1994;24(5):565–571. 4. Braithwaite J, Lazarus L, Vining RF, Soar J. Hospitals: to the next millennium. Int J Health Plann Manage. 1995;10(2):87–98. 5. Hillman K, Parr M, Flabouris A, Bishop G, Stewart A. Redefining in-hospital resuscitation: the concept of the medical emergency team. Resuscitation. 2001;48(2):105–110. 6. Hillman K. Critical care without walls. Curr Opin Crit Care. 2002;8(6):594–599.

86

K. Hillman et al.

7. Hillman K. A hospital-wide system for managing the seriously ill. Minerva Anestesiol. 1999;65(6):346–347. 8. Hillman K. Expanding intensive care medicine beyond the intensive care unit. Crit Care. 2004;8(1):9–10. 9. Wilson RMcL, Runciman WB, Gibbert RW, et al. The quality in Australian health care study. Med J Aust. 1995;163:458–471. 10. Brennan TA, Leape LL, Laird N, et  al. Incidence of adverse events and negligence in ­hospitalized patients: results of the Harvard Medical Practice Study 1. N Engl J Med. 1991;324(6):370–376. 11. Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388–1392. 12. Hillman KM, Bristow PJ, Chey T, et  al. Antecedents to hospital deaths. Intern Med J. 2001;31(6):343–348. 13. Bristow PJ, Hillman KM, Chey T, et al. Rates of in-hospital arrests, deaths and intensive care admissions: the effect of a medical emergency team. Med J Aust. 2000;173:236–240. 14. Wachter RM, Goldman L. The emerging role of “hospitalists” in the American health care system. N Engl J Med. 1996;335(7):514–517. 15. Goldhill DR, Worthington L, Mulcahy A, Tarling M, Sumner A. The patient‑at‑risk team: Identifying and managing seriously ill ward patients. Anaesthesia. 1999;54(9):853–860. 16. Bright B, Walker W, Bion J. Clinical review: outreach ‑ a strategy for improving the care of the acutely ill hospitalized patient. Crit Care. 2004;8(1):33–40. 17. Coombs M, Dillon A. Crossing boundaries, re‑defining care: the role of the critical care ­outreach team. J Clin Nurs. 2002;11(3):387–393. 18. MERIT Study Investigators. Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial. Lancet. 2005;365(9477):2091–2097. 19. Braithwaite J, Westbrook MT, Tranglia JF, et al. Area health systems changing in support of patient safety? A multi-methods evolution of education, attitude and practice. Int J Health Care Qual Assur. 2007;20(7):585–601. 20. Braithwaite J, Greenfield D, Westbrook MT. Contrasting and converging perspectives on organisational culture and climate. In: Braithwaite J, Hyde P, Pope C, eds. Culture, Climate and Teams in Health Care Organisations. London: Polygrave Macmillan; 2009. 21. Berwick DM, Calkins DR, McCannon CJ, Hackbarth AD. The 100, 000 Campaign: setting a goal and a deadline for improving health care quality. JAMA. 2006;295(3):324–327. 22. Safar P. Critical care medicine-quo vadis. Crit Care Med. 1974;2(1):1–5.

Chapter 9

Creating Process and Policy Change in Healthcare Stuart F. Reynolds and Bernard Lawless

Keywords  Rapid • Response • Systems • Public policy • Hospital • Innovation

Introduction The word “policy” is often bantered about and it is assumed that everyone has or uses a fundamental definition for policy and hence, policy development. In broad terms, policy can refer simply to a “plan of action” or “statement of aims or goals.” However defined, it is then difficult to interpret who is involved in policy planning and what are the key functions of policy development, policy implementation and subsequent evaluation. To better understand some of these nuances, William Jenkins defines policy as a set of incremental decisions taken by a political figure or group regarding the prioritization of goals and the means to achieve these goals. James Anderson describes public policy as a purposive course of action aimed at dealing with a problem identified by the government. These begin to capture some of the key elements of public policymaking and the inherent link to government as a key player in policy development and implementation.

Changing Healthcare Policy Policy to support large-scale implementation has not historically been rooted in scientific evidence and frequently not well supported by anecdotal evidence.1 Using evidence for policymaking, particularly in the healthcare sector, has been weak, especially when compared to other industries. Health and social policies generally apply to a breadth of communities or individuals through a variety of disparate mechanisms that can subsequently make programs difficult to evaluate S.F. Reynolds (*) Associate Clinical Professor of Critical Care Medicine, University of Alberta Hospital, 3C1.12 WMC, 8440 112 Street, Edmonton, Alberta, Canada e-mail: [email protected] M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_9, © Springer Science+Business Media, LLC 2011

87

88

S.F. Reynolds and B.Lawless

with scientific rigor.2 Even focused healthcare policies seem to rarely be evaluated, owing to difficulties monitoring multiple activities, the challenges of observing for disparate effects, or timelines that do not allow for observing meaningful change. Also, the “politics” of policymaking would have that politicians or decision makers are less interested in science or health impact and more interested in financial implications or views of particular groups and communities.3 The process of ­“evidence policy making” is not enhanced by the fact that structural barriers to communication exist between researchers and decision makers. This can include differences of priorities, language, means of communication, interpretation of ­findings and definition of final products of research. The policy cycle makes up the regular business of government. It strives to be incremental, continuous and, hopefully, systematic. Despite what may appear to be a good model for prospective planning, the creation of new public policy is often rooted in a response to a disastrous situation. The outbreak of SARS in Ontario in 2003 demonstrated that as a provincial resource, critical care was not well coordinated on a systems level, or even within individual institutions. Even though SARS primarily affected only Ontario’s largest urban area, Toronto, the effect on hospital services and the impact on the availability of critical care resources were across the entire province. A relatively small number of infective patients (70) had a major impact on the province-wide critical care system. Within Toronto, this resulted in the closure of hospital emergency departments, cancellation of elective surgical procedures as well as halting the normal transfer patterns of patients between ­hospitals. Hospitals outside Toronto lost their usual referral destination for patients requiring tertiary and quaternary care. The impact that a poorly coordinated and functioning critical care system could have on many other processes within hospital systems became glaringly apparent. However, SARS was not the only precipitating event to give support to Ontario’s critical care strategy. It became obvious that the addition of critical care capacity could not be the sole answer. A well-functioning and integrated critical care strategy was required to mitigate the demand on surgical and critical care services imposed by the demographic pressure of an aging population. Furthermore the ongoing specter of a pandemic increased the awareness that a provincial critical care strategy was required. With strong support from the Ministry of Health and Long-Term Care and, in collaboration with healthcare decision makers and critical care stakeholders, a sevenpronged strategy was implemented to achieve three core goals: 1 . Improve access to critical care resources 2. Improve the quality of care provided in critical care areas across the province 3. Improve system integration so that intensive care units did not function in silos, but moved to be able to leverage critical care as a resource across the province (see Fig. 9.1) Key to the strategy was the development of a provincial rapid response system, known as the Critical Care Response Team Project (CCRT). It was readily apparent that CCRT’s were an innovation well situated to meet the three core goals (see Fig. 9.2).

9  Creating Process and Policy Change in Healthcare

Fig. 9.1  Critical care strategy

Fig. 9.2  Critical Care Response Team Project

89

90

S.F. Reynolds and B.Lawless Be not the first by who the new is tried, nor the last to lay the old aside. Alexander Pope, an essay on criticism

Healthcare innovations are not simple, and Pope’s quote presages that there is a dynamic sociologic interplay between healthcare innovation and healthcare culture. This complex interplay thus makes implementation and evaluation inherently ­complex. Rapid response systems (RRS) are a complex healthcare innovation that result in significant process and culture change. It presents research challenges. There is an inherent complexity to randomizing policies to whole populations or communities: achieving agreement of measurement and analysis, maintaining internal integrity, timing interventions with data collection and the inherent political nature of the evaluation process are unique to the policy experimental setting.3 Thus many policies and innovations need to be evaluated from a social science paradigm, rather than the traditional medical evaluation ­paradigm.4 A social science paradigm enriches the evaluation by explaining why certain innovations are readily adopted and successful, while others are rejected or do not perform, evaluation from a social science perspective answers the question of why a policy, process or program works or does not work. Rogers,5 in his book Diffusion of Innovation, defined an innovation as an idea, a practice that is perceived as new by an individual or an organization. The diffusion of the innovation is the process whereby the innovation is communicated through members of a social system. To obtain widespread acceptance, an innovation needs to demonstrate a relative advantage. This requires that the new idea must offer significant improvements from current practice. Also, innovations with minimal complexity are more apt to be accepted. Finally, when people see the results of an innovation, the observability increases the likelihood that the innovation will be both utilized and accepted. Current data suggests that patients are at risk of adverse events, including ­cardiac arrest and death while residing in hospitals. Most of these adverse events are predictable, and therefore preventable; often through simple interventions.6,7 The relative advantage of an RRS is that it provides a systematic mechanism to both identify and respond to patients at risk of clinical deterioration. This is significantly better than traditional medical practice, where the patient is required to significantly deteriorate prior to obtaining critical care expertise.8,9 The RRS concept is not a complex notion, but rather a common sense innovation; simply put ‑ early detection and action will be simpler and more effective than delayed detection and resuscitation. A landmark trial in the care of patients with severe sepsis and septic shock has given credence to this concept.10 Finally, an RRS is not restricted to the four walls of an ICU; instead, the impact is readily and consistently observed throughout the hospital. If an innovation appears to have sufficient merit on the basis of relative advantage and complexity, the degree to which it is adopted depends on the characteristics of those within the social system.11 The diffusion of innovation theory identifies characteristics of those who, within an organization, are apt to support change or innovation. Early support can be expected from those within the organization themselves are innovators. Early adopters of innnovation are usually well integrated within the

9  Creating Process and Policy Change in Healthcare

91

organization. These individuals are often the opinion leaders and perceived as role models for peers. Early majority adopters are characterized by frequent interactions with peers, but are unlikely to be opinion leaders and tend to deliberate before adopting new ideas. Late majority adopters are characterized as skeptical and cautious, and their motivations for change comes from pressure from peers and economic sources. The last group to adopt, or most likely to not adopt, are unfortunately referred to as ­“laggards.” Ryan and Gross characterized this group as isolated, with a point of reference in the past, suspicious of innovation and not considered opinion leaders. An effective communication strategy will increase the number of people willing to adopt an innovation. Stakeholder input will be helpful with initial design and subsequent acceptance of an innovation. Communication during implementation that clearly defines goals and responsibilities with opinion leaders, team members, end-users and administration is imperative. From an RRS perspective, it is important to seek out the opinion leaders and innovators within the hospital system. They are often, but not always, found in leadership positions within the hospital structure. Acceptance by leadership will serve to build a foundation of system-wide acceptance and ensure that there is alignment of RRS goals with organizational values; thereby improving the chance of RRS success.12 Rapid response systems have the opportunity to be a readily accepted innovation on the basis of need alone. However, as Dodgson and Bessant13 describe, the success of an innovation relies on the recipient of the innovation doing something with the resource provided. This explains the relationship between the uptake of service (adoption) of RRS and reduction in cardiac arrests and other adverse events.14,15 The question needs to move from “Does the innovation work?” to “Why does it work and in what context?” This is referred to as a realist evaluation.16,17 Policy creation can be the result of needs identified after stresses on a system unveil disparity. This was the case with the critical care strategy in Ontario. It was developed in response to SARs, and the anticipated demographic demand. As stated previously, policy evaluation is fraught with significant confounders; traditional medical evaluation techniques that focus on clinical outcomes are of limited utility. Many of the benefits and outcomes of RRS policy will not be realized during early days. The first focus during policy implementation should therefore be on diffusion of the innovation, creating an environment that will allow the innovation to thrive. Therefore, program acceptance or utilization is a reasonable first outcome measure. It is folly to focus on clinical outcomes early in the establishment of an RRS policy as demonstrated in the MERIT trial,15 whereby the failure of MET hospitals to significantly reduce clinical outcomes was attributed to the ineffectiveness of METs, rather than the incomplete diffusion of the MET concept. It is imperative that RRSs be continuously evaluated. The very presence of the program will generate a new equilibrium within the system. Continuous program evaluation and modification is required for feedback to improve RRS service and improve system-wide function.

92

S.F. Reynolds and B.Lawless

The success of an RRS policy is dependent on the diffusion of the RRS innovation via a structured and audited implementation process across multiple hospitals. This structure must promote local leadership and, at the same time, provide central coordination and support.

References 1. Letherman S, Sutherland K. Designing national quality reforms: a framework for action. Int J Qual Health Care. 2007;19(6):334–340. 2. Shimkhada R, Peabody JW, Quimbo SA, Solon O. The quality improvement demonstration study: an example of evidence-based policy-making in practice. Health Res Policy Syst. 2008;6:5. 3. Davies P. Policy evaluation in the United Kingdom. In: KDI International Policy Evaluation Forum, Seoul, Korea; 2004. 4. Berwick D. The science of improvement. JAMA. 2008;299(10):1182–1184. 5. Rogers EM. Diffusion of Innovations. 4th ed. New York: The Free Press; 1995. 6. McGloin H, Adam S, Singer M. The quality of pre-ICU care influences outcome of patients admitted from the ward. Clin Intensive Care. 1997;8:104. 7. McQuillan P, Pilkington S, Allan A, et  al. Confidential inquiry into quality of care before admission to intensive care. BMJ. 1998;316(7148):1853–1858. 8. Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388–1392. 9. Buist MD, Jarmolowski E, Burton PR, Bernard SA, Waxman BP, Anderson J. Recognizing clinical instability in hospital patients before cardiac arrest or unplanned admission to intensive e care. A pilot study in a tertiary-care hospital. Med J Aust. 1999;171(1):22–25. 10. Rivers E, Nguyen B, Havstad S, et al. Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med. 2001;345(19):1368–1377. 11. Tyan B, Gross NC. The diffusion of hybrid seed corn in two Iowa communities. Rural Sociol. 1943;8:15–24. 12. Soumerai S, McLaughlin TJ, Gurwitz JH, et  al. Effect of local medical opinion leaders on quality of care for acute myocardial infarction. JAMA. 1998;279(17):1358–1363. 13. Dodgson M, Bessant J. Effective Innovation Policy: A New Approach. New York: Routledge; 1996. 14. Jones D, Bellomo R, Bates S, et al. Long-term effect of a medical emergency team on cardiac arrests in a teaching hospital. Crit Care. 2005;9:R808–R815. 15. MERIT Study Investigators. Introduction of the medical emergency team (MET) system: a cluster randomised controlled trial. Lancet. 2005;365(9477):2091–2097. 16. Reynolds S. Sustainability of RRS presentation. 17. Pawson R, Tilley N. Realistic Evaluation. London: Sage; 1997.

Chapter 10

The Challenge of Predicting In-Hospital Cardiac Arrests and Deaths Michael Buist

Keywords  Predicting • Patient • Hospital • Crisis • Cardiac • Deaths

Introduction In this chapter, we first explore the similarities and differences between the current hospital crisis of iatrogenic patient deaths, which are now the fourth most common cause of death in UK,1 and the sixth most common in US,2 and the theories that have been used to explain and manage organizational crises that occur in other industries. We then critically examine the studies to date that attempt to predict the in-hospital patient management crises. Finally, we examine the place of hard defenses such as electronic monitoring and alert systems to protect patients from the healthcare system. In the longer run, there needs to be a significant and fundamental change to the “soft defenses,” such as the training of all our frontline healthcare workers, so that such potential patient crises are predicted and managed earlier to prevent iatrogenic morbidity and mortality.

Organizational Crisis Theory: Hazards, Defenses and Latent Conditions James Reason, in his book “Managing the Risks of Organizational Accidents,” states that organizational accidents, as opposed to individual accidents, are predictable events.3 An individual accident is one in which a person or group of people

M. Buist (*) Rural Clinical School, University of Tasmania, Private Bag 3513, Burnie, TAS 7320, Australia e-mail: [email protected]

M.A. DeVita et al. (eds.), Textbook of Rapid Response Systems: Concepts and Implementation, DOI 10.1007/978-0-387-92853-1_10, © Springer Science+Business Media, LLC 2011

93

94

M. Buist

makes an individual slip, lapse, or error of judgment with the net result being an adverse outcome either to the person or the people who erred, or to the person or people in the immediate vicinity. As such there is usually a relatively tight, simple explanation for cause and effect in an individual accident. For, example if one makes the error of judgment to drive a motorcar on the wrong side of the road, there is a high likelihood of an accident, which will involve the person who made the error of judgment, along with any other bystanders. On the other hand, organizational accidents have “multiple causes involving many people at different levels of an organization.”4 These events, while usually infrequent, are often catastrophic. Analyses of such organizational accidents often reveal that the defenses an organization has to prevent such catastrophes are breached by a unique series of sequential hazards that play out in an environment of latent conditions. There is always a tension within an organization to balance resource allocation for production and profit generation as opposed to the implementation, maintenance and updating of defenses to protect the organization from crisis. Resource allocation for production of profit is a core tenant of a commercial organization. It is a process that has easily measured endpoints with relatively simple relationships between resource allocation and production. On the other hand, resource allocation for organizational defenses has no such relationship and the benefits of such defenses are difficult to measure. As such, if an organization has little exposure to hazards that may cause a crisis, it can be difficult to allocate resources to defenses, in the face of societal or financial drivers to maximize production. This tension thus creates the landscape, or latent, conditions that may predispose an organization to crisis.4 The defenses within an organization can be simply categorized into either “hard” or “soft.” Hard defenses are physical barriers, where no human discretion can apply. Soft defenses relate to laws, rules, policies, procedures, guidelines and often, as a last resort, “common sense.” These soft defenses are human constructs, however, and as such their implementation, utilization, analysis, improvement or otherwise and even avoidance can occur at an individual operator level. Furthermore, operator interpretation and implementation or lack thereof inevitably becomes an organizational issue often dependent on where in a particular organization the “tension” between production and protection sits.4

Iatrogenic Patient Death: Individual or Organizational Accident? Thus, we turn to the crisis in safety of healthcare. Up until this point, we have used the terms “crisis,” “catastrophe” and “accident” to mean the same thing: a sudden overwhelming event with considerable damage to those involved. For the purposes of the remainder of this chapter, we will confine ourselves to a definition of crisis as an unexpected, iatrogenic in-hospital death (Box 1). The fact that in an epidemiological, societal, political, and medico-legal sense these deaths constitute a crisis has been made in other chapters.

10  The Challenge of Predicting In-Hospital Cardiac Arrests and Deaths

95

BOX 1 A 47-year old, previously completely well male underwent a semi-elective thoracotomy for an empyema. The surgical procedure and anesthetic were uneventful. The patient returned to the ward at 15:00 with a heart rate of 130 bpm. Otherwise his observations were unremarkable. The surgical registrar was concerned about the heart rate and the patient’s inability to pass urine postoperatively. She instructed the intern to insert a urinary catheter if the patient failed to pass urine by 18:00. At 18:00 there was no urine output, the heart rate was 140 bpm. Despite the intern’s insistence, the patient refused to have a urinary catheter inserted. Otherwise the patient’s condition was stable. The day intern handed over the patient in a verbal report to the night resident medical officer (RMO) at 22:00. The night RMO was summoned urgently to see the patient at 23:30 when the patient’s blood pressure dropped to 85/60 mmHg. The heart rate was now 150 bpm. The RMO assessed that the patient was hypovolemic and administered 2  l of intravenous fluid, and ordered a blood transfusion. With this intervention, the blood pressure improved and the RMO went about his other tasks. There were no further observations on the patient until 02:30 when the blood pressure was observed to be 75/55 mmHg. The RMO again responded promptly and commenced further fluid resuscitation. Again there was a transient improvement in the patient’s condition. At about 04:00 the RMO was concerned enough about the patient to telephone the on-call surgical registrar (offsite, on-call due to financial restraints). The RMO explained the patient’s condition to the registrar. The surgical registrar was concerned and stated that he would come in early at 07:00 to review the patient prior to the commencement of his operating list. At 05:30, the patient lost consciousness, and the nursing staff put out a cardiac arrest call. Despite the best efforts of the anesthetic registrar and the ICU registrar, the patient could not be resuscitated and he was declared deceased at 06:00.

When a patient enters a hospital, he enters a system where he will be exposed to a variety of hazards, which in turn have numerous defenses in place to prevent an adverse patient outcome. Operations, anesthesia, medical interventions and procedures, drugs and fluids and even oxygen therapy constitute the hazards. Some hard defenses exist in anesthesia, whereby the administration of hypoxic gas mixtures is physically prevented, otherwise most other defenses in the general hospital ward environment are soft. These soft defenses include treatment policies and procedures, manual alarm systems, and ad hoc hierarchical and lateral human checking systems. Soft defenses are very reliant on the training and education that healthcare workers receive. Superimposed on these layers of hazards and defenses that the patient is confronted with, there are the latent conditions that exist most obviously within the patient, but more insidiously within the hospital as an organization. A patient’s past medical history, family history, social history-associated co-morbidities, drug regimen,

96

M. Buist

and allergies, largely constitute their latent conditions. These conditions, and their relation to the current presenting complaint that brings the patient into the hospital system, is territory that individual healthcare workers are usually extremely well trained in and familiar with. Hospital latent conditions are not so explicit, particularly to the patient or the frontline healthcare worker. They are made up of a complex matrix of production imperatives, such as the financial operating environment, political and societal imperatives, medico-legal and insurance concerns, compliance issues imposed by various regulatory bodies (often with associated financial incentives or disincentives) and workforce and work-practice issues. In the acute care hospital, the distinction between individual and organizational accidents is blurred. First, the crisis of iatrogenic patient death is insidious. Although epidemiologically this is a crisis that may constitute an epidemic, to the individual practitioner or even hospital, these unfortunate events may not appear as part of an epidemic, largely because, at an individual level, these events occur relatively infrequently, over a long timeframe. For example, The Quality in Australian Healthcare Study looked at a random sample of 14,179 admissions to 28 hospitals in two states of Australia, in 1992, and documented 112 deaths (0.79%), including 109 cases where the adverse event caused greater than 50% disability (0.77%).5 Nearly 70% of the deaths, and 58% of the cases of significant disability were considered to have a high degree of preventability. Thus, for the individual clinicians, treating departments and units, and even the 28 study hospitals themselves, their actual experience of these outcomes over the year would be minimal (one or two cases). Secondly, the defenses that hospitals have in place to protect patients have not significantly changed over recent decades. In particular, there are few, if any, “hard” defenses, and the “soft” defenses are overly reliant on the skills and abilities of the frontline healthcare workers, principally the junior doctor and nurse. In particular, at least in Australia and UK, several studies indicate that the medical undergraduate syllabus does not provide graduates with the basic knowledge, skills, and judgment to manage acute life-threatening emergencies.6–9 These studies identified deficiencies in cognitive abilities, procedural skills, and communication. Further analysis of the causative factors associated with the adverse events in The Quality in Australian Health Care Study found that cognitive failure was a factor in 57% of these adverse events.10 In this analysis, cognitive failure included such errors as failure to synthesize, decide and act on available information; failure to request or arrange an investigation, procedure or consultation; lack of care or attention; failure to attend; misapplication of, or failure to apply, a rule, or use of a bad or inadequate rule.10 In a two-hospital study from UK that looked at 100 sequential admissions to the intensive care unit (ICU) from ward areas, it was found that 54 had suboptimal care on the ward prior to transfer.11 This group of patients had a mortality rate of 56%. Some of the sub-optimal treatment factors included failure to seek advice, lack of knowledge, failure to appreciate clinical urgency, and lack of supervision. Undergraduate and postgraduate curricula have been slow to embrace a patient safety culture.12,13 The hospital organizational response to the issue of adverse events and iatrogenic deaths has generally been to attempt to document and audit incidence, reinforce the traditional hierarchal referral model of care, and to incorporate a plethora of written policies and procedures into the clinical

10  The Challenge of Predicting In-Hospital Cardiac Arrests and Deaths

97

e­ nvironment with little in the way of sustained organizational attempts to “close the loop.” In the acute hospital setting, the frequent turnover of workers through frontline care delivery positions and the expectation that the hospital is a “training” setting may reduce the organizational ability to “see” such events and to retain corporate memory of them, let alone to have the sophisticated procedures in place to undertake root cause analysis and organizational learning to take place. Finally, the hospital environment is a complex and dynamic matrix of political, administrative, financial, work place and workforce variables that interact to provide patient care.14 This effect overwhelms the fact that one could probably argue that the hazards that a patient may encounter have at worst changed little or at best diminished somewhat thanks to better operative, peri-operative techniques and safer drugs.

Can We Predict Hospital Iatrogenic Death? Implicit in the prediction of iatrogenic hospital death is the fact that there would need to be a number of easily identifiable simple clinical markers or factors that predict death. Unfortunately, there are no such markers or factors. In an attempt to look for such markers and risk factors, three types of study have been used. First, the large retrospective epidemiological case note review studies used to determine incidence and outcome from hospital adverse events have shed some light on factors that may predispose a patient to iatrogenic hospital death.1,5,10,15–18 The Harvard Medical Practice Study (HMPS) and the QAHCS both performed a separate analysis of the documented adverse events, by an iterative process with expert reviewers, to look for causative factors, degrees of preventability and with HMPS-associated negligence. The HMPS found that age, operative status, and negligence were associated with poor outcomes (death and permanent disability) from adverse events with associated high degrees of preventability. The HMPS documented that patients over 65 years of age had double the risk of an adverse event than patients between 16 and 44.15,16 It also estimated that 51.3% of the deaths from adverse events were caused by negligence. In a re-examination of the 2,351 adverse events from the QAHCS, 34.6% of the adverse events were categorized as “a complication of, or the failure in the technical performance of an indicated procedure or operation.”10 However, of more significance, 81.8% of events were associated with human error and cognitive failure as discussed above.10 The QAHCS also found that “delay,” both diagnostic and treatment was associated with 20% of adverse events and that 86–90% of these events were assessed to be highly preventable.10 A second methodology is the case or case-control study, which retrospectively examines features of care received by patients who had an unexpected in-hospital death, or other high risk event (in hospital cardiac arrest or unplanned ICU admission).A retrospective case note review at the Jackson Memorial Medical Center in Florida, documented, over a 4-month period in 1987, 64 consecutive ­in-hospital cardiac arrests in the general ward areas.19 Of these, 54 (84%), had

98

M. Buist

documented observations of clinical deterioration or new complaints within 8 h of the arrest. In a similar study performed at the Cook County Hospital in Illinois, 150 cardiac arrests were observed in the medical wards over a 20-month period from 1990 to 1991.20 In 99 of these (64%), a nurse or physician documented deterioration in the patient’s condition within 6 h of the cardiac arrest. The hospital mortality rate of the 150 cardiac arrests was 91%. Again, in a 28-week period at the Manchester Royal Infirmary, reported in 1999, 47 cardiac arrest calls in the general ward areas were analyzed.21 Twenty-four (51%) had premonitory signs prior to the cardiac arrest call. Similarly, in a study in a tertiary care hospital in metropolitan Melbourne over the 1997 calendar year, there was a median period of documented clinical instability of 6.5 h (range 0–432 h) prior to either cardiac arrest call or intensive care unit referral among 122 in-hospital patients.22 This was despite the fact that over the period of instability, these patients were reviewed, on average, twice by junior medical staff.22 In a case-control study of 118 consecutive cardiac arrests in 1999 performed at Selly Oak Hospital in Birmingham, multivariate analysis identified abnormal breathing, abnormal pulse and abnormal systolic blood pressure in the hours prior to the cardiac arrest as being positively associated with the event.23 More simply, Goldhill and Summer made the observation, across a group of UK hospitals, that admission to the intensive care unit from the general ward areas, as compared to ICU admission from the operating room or emergency department resulted in significantly higher mortality.24 Furthermore, in a study of 7,190 ICU admissions across 24 UK hospitals, the actual length of stay in a general hospital ward was an independent predictor of hospital mortality.25 This study documented a hospital mortality rate of 67.2% for patients who were on the ward for more than 15 days. An analysis of 1,047 general ward patients in a UK Trust Hospital that were assessed by an intensive care outreach team in 2005 found an association between all physiological variables except temperature and heart rate with hospital mortality.26 Looking at 321 in-hospital cardiac arrests in a single Finnish Hospital between 1993 and 2002 found that documented abnormal clinical observations, an initial rhythm at arrest that was nonshockable, unwitnessed arrest, and delay in resuscitation team response were all independent risk factors for mortality at hospital discharge.27 There are only two multi-center case or case control studies. In the ACADEMIA study undertaken jointly by the UK Intensive Care Society and the Australia and New Zealand Intensive Care Society clinical trials group,28 data was collected on the incidence of serious physiological abnormalities that preceded in-hospital death, cardiac arrest or unanticipated ICU admission over 3 consecutive days in 90 hospitals in the three study countries. Over the 3 days of the study, there were 638 such events, of which 60% had a total of 1,032 serious physiological abnormalities prior to the index event. In the second case control study, Cretikos29 conducted a nested case control study in seven Australian public hospital during the MERIT study.30 There were 450 cases as defined by ICU/HDU admission, cardiac arrest and death in hospital patients without a “do not resuscitate” order and 520 sex-, age- and locationmatched controls. In this analysis, various abnormal observations for activation of

10  The Challenge of Predicting In-Hospital Cardiac Arrests and Deaths

99

the medical emergency team were applied to determine the criteria with highest sensitivity and specificity and hence positive predictive value for a case event. The most predictable criteria was a combination of a heart rate greater than 140 bpm, respiratory rate greater than 36/min, systolic blood pressure of less than 90 mmHg, and a greater than two-point reduction in the Glasgow Coma Scale (sensitivity of 49% and specificity of 94% and a positive predictive value of only 10%.) Thirdly, there are prospective cohort studies. These studies look at a population of patients over time and try to determine risk factors from the patients who have sentinel events. A New South Wales (NSW) study of 50,942 acute-care admissions to three hospitals, performed over a 6-month study period in 1996, documented the antecedents of 778 deaths.31 Of these, only 66 were classified as unexpected in that they did not have a “do not resuscitate” order or were preceded by a cardiac arrest or intensive care unit admission. In the 8 h prior to the deaths of these patients, 50% had documented severe abnormalities in the observation charts or concerns noted in the nursing or medical record. Furthermore, 33% of these patients had abnormal observations, or concerns noted up to 48 h prior to their deaths. The most common abnormal observations were hypotension (systolic blood pressure 36/min). In another study, Bellomo et al followed 1,125 patients admitted for more than 48  h (excluding day case surgical admissions) to the surgical units at the Austin Hospital over a 6-month period in 1999.32 They documented 414 serious adverse events including 80 patient deaths (7.1%). This study also identified increased age as a risk factor for death from adverse events. The mortality rate for patients aged more than 75 years who underwent unscheduled surgery was 20%. The major limitation of this study was that the definition of serious adverse events included postoperative complications such as sepsis, pulmonary edema and acute myocardial infarction, events that although serious and adverse, may not have been preventable. Similarly, a study of 6,303 patients33 admitted to Dandenong Hospital in Melbourne, over a 33-week period in 1999, 564 (8.9%) experienced a total of 1,598 abnormal observations. The two commonest abnormal observations were desaturation to less than 90% (51% of all events), and hypotension (17.3%). One hundred and forty-six patients died during the study. When the abnormal observations were considered simultaneously in a multiple linear logistic regression model, the following events were found to be significant predictors of mortality: decrease of consciousness, loss of consciousness, hypotension, respiratory rate