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ANTIDEPRESSANTMINING AZ AMAZ DESIGNING A WEBBASED ALGORITHM AND VISUAL LANGUAGE FOR ANTIDEPRESSANT DRUG SELECTION TO EDUCATE PRIMARY CARE PRACTITIONERS By Amy Zhong A thesis submitted to Johns Hopkins University in conformity with the requirements for the degree of Master of Arts Baltimore, Maryland March, 2016 © 2016 Amy Zhong All Rights Reserved ABSTRACT Depression is a common mental disorder that affects approximately 14.8 million American adults each year. In addition to being a debilitating condition, depression often occurs in tandem with other medical conditions such as diabetes, heart disease, and cancer. While psychiatric professionals are essential for the management of mental health, majority of patients seek care from their primary care practitioners. This phenomenon is of great concern because diagnosis of depression within primary care settings has only been accurate 25-50% of the time. The antidepressant drug selection algorithm utilizes a unique formula to integrate patient and family medical histories, patient symptoms, and patient preferences to make optimal treatment selections. The development of a visual language explores the use of graphic elements to improve understanding of major pharmacological mechanisms, knowledge essential to making rational DQWLGHSUHVVDQWGUXJVHOHFWLRQV,QFUHDWLQJWKLVPRELOHZHEEDVHGDSSOLFDWLRQZHKRSHWR¿OOD void in resources available to primary care practitioners, and improve management of mental health within the primary care setting. By Amy Zhong Chairpersons of the Supervisory Committee Adam I. Kaplin, M.D., Ph.D., esis Preceptor Assistant Professor, Departments of Psychiatry and Neurology e Johns Hopkins University School of Medicine Kristen Rahn Hollinger, Ph.D., esis Preceptor Instructor, Departments of Psychiatry and Neurology e Johns Hopkins University School of Medicine Jennifer E. Fairman, M.A., C.M.I., F.A.M.I., Departmental Advisor Assistant Professor, Department of Art as Applied to Medicine e Johns Hopkins University School of Medicine ii ACKNOWLEDGEMENTS I would like to take this opportunity to express how eternally grateful I am to have been invited into the Hopkins family two years ago. I am thankful for the aspiring guidance, invaluable constructive criticism and unyielding support that many have shown me over the past few years, all of whom helped bring this thesis into fruition. To Drs. Adam I. Kaplin and Kristen Rahn Hollinger from the Departments of Psychiatry and Neurology, I owe a deep sense of gratitude to both as my thesis preceptors, my guidance counselors and my friends. It was truly an honor to have had the opportunity to work with you both this year. To my faculty advisor, Jennifer E. Fairman, I would like to express a special appreciation for being my rock. Her optimism and enthusiasm helped me stay focused and motivated through the research and writing of this thesis. I would also like to extend my sincere thanks to the rest of the thesis team: Mark Kandrysawtz and Josiah Heigel from Benjamin & Bond and Mike Wang. A shout out to everyone who helped fund my thesis on Experiment.com (Jason Zhong, Kevin G Chen, Joanne Yuan, Steven Chen, Denny Luan, Adam Kaplin, John Sandford, Andrew Kim, Wendy Yuan, Calvin Chan, Minna Chan, Andrew W. Lee, David Dickerman, Ada Lin, Tiffany Liang, Andrew Wu, Rachel Zhou, John Megahan, Weiling Chou, Chris Chen, Claire Vergara, Peter Yeung, Tim Su, Christine Lin, Pamela Krikorian, Wendy Luo, Harry Zhang, Joe Samson, Jeremy Reppy, Lindaanne Donohoe, Patrick Chen, Louise Giam, Andy Li, Ashley Chung, Ashley Jiang, Jeff Lin, Ray Lian, Clarice Chan, Richard Chen, Carmen Loo, Michael Kim, Robin Muccari, Joseph Lee, Jeff G, Xuesi Li, Jeff Day, Ian Suk, Wenjing Wu, Kimberly Stemp, Justine Mirasol, Joshua Gabriel, George Dong, Victoria Tsay, Robert Paul Malchow, Kate Ray, April Koh, Ashley Lau, Tom Liang, Cindy Wu, Douglas A. Mata, Eric Damon Walters, and Adam Davies) and the individuals who helped endorse my project (Corinne Sandone, Justine Mirasol, Lynn Ngai, Felicia Hardi, and Cheri Dijamco). I want to acknowledge the faculty and staff in the Department of Art as Applied to Medicine who were an invaluable support system: Corinne Sandone, Tim Phelps, David Rini, Gary Lees, Juan Garcia, Lydia Gregg, Dacia Balch, Carol Pfeffer, and Ed Philips. I would like to thank my second family in Chicago, whose words of encouragement remind me every day that I am capable of accomplishing anything I put my mind to. Thank you John Sanford, Pamela Krikorian, Robin Muccari, Lindaanne Donohue, and Phil Martin. iii ACKNOWLEDGEMENTS Thank you to my class, the Class of 2016, the classes of 2015 and 2017, and our wonderful alumni Hannah Ahn and James Abraham for the weekly goodies, midnight critiques, spontaneous food adventures and overall good times. I want to thank my godparents Xiaoyu Jing and Kevin Chen for always looking out for me and ensuring that I didn’t starve. I would like to thank my dog Jamie for her unconditional love and enforcement of potty breaks and playtime, which helped maintain my sanity throughout this thesis. To Calvin J. Chan, I am so grateful for his love and support, and extraordinary patience. This thesis is dedicated to my amazing parents Holly Xiong and Pingyu Zhong for whom I owe everything I am today. To my baby brother Arthur Zhong whose creativity and enthusiasm for the arts inspires me to be more fearless. To my grandparents I want to thank for their experiences and words of wisdom. I am so blessed to have such inspiringly hardworking people in my life. You have and will always be my role models. I love you. iv TABLE OF CONTENTS Abstract ii Chairpersons of the Supervisory Committee ii Acknowledgements iii Table of Contents v Index of Tables vii Index of Figures vii Introduction Overview of Mental Healthcare 1 Depression with a capital “D” 2 Psychiatric Consultations 3 Existing Algorithms for Antidepressant Drug Selection 4 Visuals for Teaching Psychopharmacology 5 Potential for a Smartphone Accessible Resource 5 Project Objective 6 Disclaimer 6 Materials & Methods Development of Antidepressant Charts 8 Development of Application Flowchart 11 Development of Drug Selection Algorithm 13 Development of Visual Language 19 Development of Application 22 Results Access to Assets resulting from this thesis 28 Discussion Conclusion v TABLE OF CONTENTS Appendices Appendix A: Antidepressant Charts 32 Appendix B: Drug Selection Flowchart 42 Appendix C: Drug Selection Questions 43 Appendix D: Visual Language 48 Appendix E: Web Application Wireframe & Design 50 Appendix F: Test Scenarios & Results 54 Appendix G: IRB Pre/Post Questionnaires 64 References Vita vi INDEX OF TABLES Table 1 9 Table 2 10 Table 3 14 Table 4 16 Table 5 20 Table 6 21 INDEX OF FIGURES Figure 1 12 Figure 2 17 Figure 3 17 Figure 4 21 Figure 5 22 Figure 6 25 Figure 7 26 vii INTRODUCTION Overview of Mental Healthcare Depression is a life debilitating mood disorder that affects approximately 14.8 million American adults each year (ADAA 2014). In addition to being a chronic mental illness, studies have shown that depression is also a frequent comorbidity of other conditions such as HIV/ AIDS, diabetes, multiple sclerosis, and cancer. Though depression is a treatable condition, it is frequently underdiagnosed and undertreated, and the disease is responsible for a 5-fold increased risk of mortality of comorbid medical conditions (ESC 2015). In 2010, antidepressants were the second most commonly prescribed drug in the US (IMS Health 2011). Between 1988-1994 and 2005-2008 their use increased by 400% (Pratt, et al. 2011). Meanwhile, disturbing evidence shows a steady increase in suicide rates since 2005 with the US suffering nearly 43,000 deaths in 2014 (AFSP 2014). This phenomenon has launched awareness of the increasing involvement of primary care practitioners (PCPs) in mental health – 80% of psychotropic drug prescriptions were made by PCPs in 2013 (Barkil-Oteo 2013) – and the evaluation of their abilities to detect depression and implement the necessary treatment. /LNHRWKHUSV\FKLDWULFGLVRUGHUVGHSUHVVLRQLVDGLI¿FXOWFRQGLWLRQWRUHFRJQL]H'HSUHVVLYH symptoms not only include depressed mood and anhedonia (inability to experience pleasure), but can range from insomnia and anorexia to decreased cognition and suicidal behavior. The SUHYDOHQFHRIV\PSWRPVLVSDWLHQWVSHFL¿FDQGFDQEHVXSHULPSRVHGZLWKV\PSWRPVRIRWKHU comorbid diagnoses. Though screening tools such PHQ-9 and PHQ-2 exist to detect characteristics RIGHSUHVVLRQWKH\DUHQRWPHDQWWRVXEVWLWXWHIRUTXDOL¿HGPHQWDOKHDOWKFDUHSUDFWLWLRQHUV&XWRII points in depression screening questionnaires are typically based off data collected from a variety RIFRQFHSWXDOO\VLPLODUVFLHQWL¿FVWXGLHV7KLVJHQHUDWHVDQH[DJJHUDWHGHVWLPDWHRIDFFXUDF\ leaving room for a margin of error. The situation, as Dr. Ramin Mojtabai, Associate Professor in the Department of Mental Health at the Johns Hopkins Bloomberg School of Public Health describes, “Without enough time to really talk to patients about depression and with some patients increasingly open to the idea of an antidepressant for mild conditions, the primary care setting can be vulnerable to overprescribing” (Katz 2012). Depression with a capital “D” The ability to detect clinical depression manifests in the understanding of the condition. What is depression? Everyone experiences sadness, but what makes a patient clinically depressed? +LSSRFUDWHV %& ¿UVWGHVFULEHGWKHVWDWHRIGHSUHVVLRQDVWKH³DYHUVLRQWRIRRG despondency, sleeplessness, irritability, [and] restlessness” (Kaplin 2014). In a lecture made by