DIAGNOSING DIZZINESS IN THE EMERGENCY DEPARTMENT Why “What do you mean by ‘dizzy’?” Should Not Be the First Question You Ask by David Edward Newman-Toker, M.D. A dissertation submitted to the Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland March, 2007 © 2007 David E. Newman-Toker All Rights Reserved Abstract Dizziness is a complex neurologic symptom reflecting a perturbation of normal balance perception and spatial orientation. It is one of the most common symptoms encountered in general medical practice. Considering the dual impact of symptom-related morbidity (e.g., falls with hip fractures) and direct medical expenses for diagnosis and treatment, dizziness represents a major healthcare burden for society. However, perhaps the dearest price is paid by those individuals who are misdiagnosed, with devastating consequences. Dizziness can be caused by numerous diseases, some of which are dangerous and manifest symptoms almost indistinguishable from benign causes. The risk appears highest among patients with new or severe symptoms, particularly those seeking medical attention in acute-care settings such as the emergency department. Nevertheless, even acute dizziness is more often caused by benign inner ear or cardiovascular disorders. Thus, a major challenge faced by frontline providers is to efficiently identify those patients at high risk of harboring a dangerous underlying disorder. Unfortunately, diagnostic performance in the assessment of dizzy patients is poor. In part, this simply reflects the generally high rates of medical misdiagnosis encountered in frontline settings. However, misdiagnosis of dizziness is disproportionately frequent. Although possible explanations are myriad, I propose that an important cause stems from the pervasive use of an antiquated, oversimplified clinical heuristic to drive diagnostic reasoning in the assessment of dizzy patients. In this dissertation, I contend that the commonly-applied bedside rule that dizziness symptom quality, when grouped into one of four dizziness “types” (vertigo, presyncope, disequilibrium, or ill-defined dizziness), ii predicts the underlying cause, is false and potentially misleading. The argument supporting this theory is developed in the chapters that follow. Chapter 1 focuses on why dizziness diagnosis presents a significant challenge worthy of our concerted attention. Chapter 2 describes a multi-institutional survey of emergency physicians confirming that the “quality-of-symptoms” approach to dizziness is the dominant paradigm for diagnosis. Chapter 3 describes a cross-sectional study of emergency department dizzy patients demonstrating how this approach is fundamentally flawed. Chapter 4 concludes with a discussion of why this flawed paradigm might have garnered and maintained such widespread acceptance for over three decades. Keywords from the Medical Subject Headings (MeSH) Database 1. dizziness 2. diagnosis 3. diagnostic errors 4. medical history taking 5. emergency service, hospital Dissertation Readers Serving on the Final Oral Examination Committee David S. Zee, MD (Mentor, Committee Chair, Non-Departmental Voting Member) Frederick L. Brancati, MD, MHS (Advisor, Departmental Voting Member) Harold P. Lehmann, MD, PhD (Non-Departmental Voting Member) Scott L. Zeger, PhD (Departmental Voting Member) Richard E. Rothman, MD, PhD (Optional Member) iii Preface Publication of this dissertation marks the culmination of seven years of study and effort devoted to changing the way physicians approach the diagnostic assessment of dizzy patients. It also signals the start of a career dedicated to reducing misdiagnosis in frontline healthcare settings, using the tools of clinical investigation, medical informatics, and physician education. It is my belief that, by changing the way providers seek, solicit, and synthesize a patient’s illness-related symptoms for the purpose of diagnosis, we can improve diagnostic accuracy, without sacrificing efficiency. Thus, it is my hope that this dissertation represents the first major milestone in a career-long journey intended to help bring science to the “art” of bedside diagnosis. Even the inception of this journey would not have been possible without the substantial and ongoing support of others. I am deeply indebted to all of my mentors, collaborators, co-authors, employees, and funding agencies who have made possible the research described in this dissertation. Many of these important individuals are named below, although there are many more who have contributed than those I am able to list in these pages. I am also profoundly thankful for the knowledge and skills imparted to me by all of my former teachers, mentors, and role models throughout the various stages of my education and post-graduate career. Most of all, I am grateful to my family — in particular, to my wife, Julie, for the tremendous, unflagging, loving support she has provided throughout this challenging endeavor. Without her boundless strength and the love of my parents Karen and Cyril, grandmother Nedra, sister Rachel, daughters Maya and Adina, and dear friends, I could not have completed the task. I love you all more than I could ever express in words. iv Dedication This dissertation is for my grandparents who remain with us in spirit (Fay Toker, Philip Toker, and Victor Monroe Harkavy). In particular, this work is dedicated to the loving memory of Victor (“Grandaw” as I knew him): grandfather, engineer, role model, true mensch, and wellspring of personal inspiration for me. Acknowledgements Mentors & Advisors Primary Mentors & Advisors Secondary Mentors & Advisors • David S. Zee, MD (mentor) • Eric B. Bass, MD, MPH • Frederick L. Brancati, MD, MHS (advisor) • David R. Cornblath, MD • Harold P. Lehmann, MD, PhD • Steven N. Goodman, MD, MHS, PhD • Justin C. McArthur, MBBS, MPH • Gabor D. Kelen, MD • David G. Nichols, MD • Guohua Li, MD, DrPH • Richard E. Rothman, MD, PhD • Albert W. Wu, MD, MPH • Scott L. Zeger, PhD v Co-Authors & Collaborators Chapter 2 Chapter 3* • Victoria Stanton, BA, MSII • Lisa M. Guardabascio, MD • Yu-Hsiang Hsieh, PhD • Matthew E. Stofferahn, BM, MSIV • Carlos A. Camargo, Jr., MD, DrPH • Richard E. Rothman, MD, PhD • Jonathan A. Edlow, MD • Yu-Hsiang Hsieh, PhD, MS • Paris Lovett, MD, MBA • David S. Zee, MD • Joshua N. Goldstein, MD, PhD • Stephanie Abbuhl, MD • Michelle Lin, MD • Arjun Chanmugam, MD, MBA • Richard E. Rothman, MD, PhD * We also wish to thank the entire Emergency Department staff (especially Judy Shahan, RN, MBA, Research Associate and Michael Levi, Administrative Assistant) at both Johns Hopkins Hospital and Johns Hopkins Bayview Medical Center, for their support and patience in helping us to conduct this research in their patient care area. vi Sources of Funding • National Institutes of Health — National Center for Research Resources (NCRR) K23 RR17324-01, “Building a New Model for Diagnosis of ED Dizzy Patients” Funded 75% of Dr. Newman-Toker’s effort (2002-2007), and provided the principal support for the work presented in this dissertation, and its written preparation. • University of California at San Francisco, School of Medicine, Dean’s Summer Student Research Fellowship Program 2006, “Current Emergency Department Management of Dizzy Patients” Provided medical student Stanton’s stipend/support (summer 2006) for assisting in the design and conduct of the survey research study presented in Chapter 2. • Other Funding Sources The development and design of the study presented in Chapter 3 was supported, in part, by grants from the Arnold-Chiari Foundation (training grant, Dr. David Zee), the Albert Pennick Fund (training grant, Dr. David Zee), and the Biomedical Engineering Training Grant for Vestibular Research (NRSA 5 T32 DC00023, Dr. Murray Sachs). Together, these grants provided funding support for Dr. Newman-Toker’s effort over a 2-year period leading to eventual K23 submission and award. vii Other Acknowledgments Chapter 2: We thank Dr. Elizabeth Elliott of the Johns Hopkins Bloomberg School of Public Health for her invaluable help with the survey design, and Dr. Adam Stubblefield of the Johns Hopkins University Department of Computer Science for his help in developing the web portal to randomly assign participants to one of two survey versions. Elizabeth Elliott, ScD Adam Stubblefield, PhD Adjunct Assistant Professor of Epidemiology Assistant Research Professor of Computer Science Johns Hopkins Bloomberg School of Public Health Johns Hopkins University Chapter 3: We thank Drs. Julie R. Newman-Toker and Joshua M. Sharfstein for critically reviewing the text and providing invaluable editorial advice. We would also like to extend our deepest gratitude to Jakob and Elisabeth Scherer of Diatouch, Inc. for their generous assistance in optimizing their software for use in a clinical research setting, without which this study would not have been possible. Finally, we would like to thank the dedicated research assistants* whose hard work is reflected in the results of this study. Julie R. Newman-Toker, MD Joshua M. Sharfstein, MD Private practice, Baltimore, MD Baltimore City Health Commissioner Jakob Scherer Elisabeth Scherer Diatouch, Inc. Diatouch, Inc. * Research Assistants (in alphabetical order): Christopher Belknap, Allison Berken, Emmanuella Eastman, Katina Fox, Michael Green, Kareem Idrees, Julia Loux, Jessica Lozier, Maura McTague, Avantika Mishra, Jamia Saunders, Skylar Turner viii Table of Contents Chapter Pages Front Matter....................................................................................................