Simulating Complex Health Systems

Health SOCIETY OF ACTUARIES Section Simulating health behavior A guide to solving complex health system problems with agent-based simulation modeling Prepared by Alan Mills FSA ND Version 1 May 27, 2013 The opinions expressed and conclusions reached by the author are his own and do not represent any official position or opinion of the Society of Actuaries or its members. The Society of Actuaries makes no representation or warranty to the accuracy of the information. ©2013 Society of Actuaries. All rights reserved. It is clear from everyday observation that the behavior of sellers of medical care is different from that of businessmen in general. Kenneth Arrow, 19631 In some one of its numerous forms, the problem of the unanticipated consequences of purposive action has been treated by virtually every substantial contributor to the long history of social thought. The diversity of context and variety of terms by which this problem has been known, however, have tended to obscure the definite continuity in its consideration. In fact, this diversity of context—ranging from theology to technology—has been so pronounced that not only has the substantial identity of the problem been overlooked, but no systematic, scientific analysis of it has as yet been effected. The failure to subject this problem to such thorough-going investigation has perhaps been due in part to its having been linked historically with transcendental and ethical considerations. Obviously, the ready solution provided by ascribing uncontemplated consequences of action to the inscrutable will of God or Providence or Fate precludes, in the mind of the believer, any need for scientific analysis. Whatever the actual reasons, the fact remains that though the process has been widely recognized and its importance equally appreciated, it still awaits a systematic treatment. Robert Merton, 19362 Overall, it seems that agents in the health-care market adopt different decision-making procedures and modes of behavior, depending on the circumstances. I think that health economists have done far too little in trying to understand how exactly the agents’ decision-making procedure is determined in the different situations and how it can be affected. This is precisely where ideas from behavioral economics might be most helpful. 3 Jacob Glazer, 2007 1 From Arrow (1963), page 949. Kenneth Arrow is the youngest person to receive the Nobel Prize in Economics. This quote is from the paper that gave rise to the field of health economics. 2 From Merton (1936), page 894. Robert Merton was a distinguished sociologist who developed the concept “unanticipated consequences” (as well as the terms “role model” and “self-fulfilling prophesy”). Health systems are replete with unanticipated consequences that await a systematic treatment. 3 From Jacob Glazer’s comments about Richard Frank’s chapter titled “Behavioral economics and health economics” in P. A. Diamond & Vartiainen (2007), page 222. Jacob Glazer is a prominent health economist with joint appointments at Boston University and Tel Aviv University. In this work, we will explore how results from behavioral economics can help us better understand the behavior of health system agents. Simulating health behavior CONTENTS Acknowledgments Preface 1 PART I HEALTH BEHAVIOR Introduction 12 ONE Dimensions of behavior 13 A fresh look at behavior TWO Health behavior fields 23 Current health behavior fields and their gaps PART II CLASSIFICATION OF AGENTS AND BEHAVIOR Introduction 36 THREE Classification schemes 37 The varieties of classification, and the health systems ontology FOUR Classification of agents 45 Classification of agent roles FIVE Classification of behavior 50 Classification of agent goals and behavior SIX Using the health systems ontology 54 The potential benefits of the health systems ontology PART III HEALTH BEHAVIOR FACTS Introduction 60 SEVEN Overview of health behavior facts 61 A review of what we know about health behavior EIGHT Behavioral economics and health behavior 66 What behavioral economics says about health behavior Contents Simulating health behavior PART IV HEALTH BEHAVIOR THEORY Introduction 95 NINE Scientific theory 96 What a health behavior theory should be TEN Overview of health behavior theories 102 Survey of current health behavior hypotheses ELEVEN Five useful health behavior hypotheses 111 Detailed descriptions of five useful hypotheses TWELVE One good theory 146 A proposed approach to develop health behavior theory PART V METHODS AND TOOLS Introduction 151 THIRTEEN Agent-based modeling method 152 A complete method for agent-based modeling FOURTEEN Simulation modeling guidelines 164 Seven good practice guidelines for developing simulation models FIFTEEN Agent-based modeling tools 194 Software and hardware for agent-based modeling SIXTEEN Sample agent-based models 209 Overview of three sample agent-based simulation models PART VI FILLING THE GAPS Introduction 257 SEVENTEEN Seven health behavior gaps 259 Seven major gaps in the field of health behavior EIGHTEEN Eight health behavior challenges 264 Eight challenges to start filling the gaps Glossary Resources Notes Appendix A: Physician network model Appendix B: Workplace wellness model Appendix C: Adverse selection model Contents Simulating health behavior ACKNOWLEDGMENTS Good work is seldom done in isolation. For this project, I am grateful to many for their foresight, wise counsel, generous support, creativity, and encouragement: . John Stark initiated the project. He recognized the need for it and recommended that the Society of Actuaries (SOA) Health Section consider it for funding. During the project, he was an enthusiastic member of the Project Oversight Group, generously offering sound guidance and creative suggestions for improvement. Kevin Law, head of the SOA Health Section in 2012, foresaw the potential benefits of the project and invited John Stark to present it to the Health Section Council. Members of the SOA Health Section Council, particularly Joan Barrett, Pat Kinney, and other members of its research committee, agreed about the importance of the project and agreed to fund it. Members of the SOA Research Executive Committee, particularly Tom Getzen, offered to fund the project as part of the Research Expanding Boundaries Pool. Members of the Project Oversight Group: – Steve Cyboran – Bill Dimmock – Tom Getzen – Pat Kinney – Syed Mehmud – Evan Morgan – Sandee Schuster – John Stark – Steel Stewart – Steve Siegel, SOA Research Actuary – Barbara Scott, SOA Research Administrator It is hard to imagine a more helpful oversight group. During each stage of the project, each member actively participated, probing successive report drafts, offering insightful critiques, sharing rich experiences to help clarify my thinking, introducing me to helpful colleagues, and encouraging me to innovate. Members reviewed more than eight hundred pages of project material and examined simulation models with tens of thousands of lines of computer code. Not only did members participate in the project’s conference calls, they communicated with me separatelyoften at lengthby phone and email. Such stimulating company was glorious fun. Steve Siegel expertly navigated the project and the oversight group past each potential obstacle, and was always ready with enthusiasm and gentle suggestions that inspired group members to shine. And Barbara Scott cheerfully handled a thousand details in ways that seemed effortless. Acknowledgments Simulating health behavior ACKNOWLEDGMENTS continued . David Gochman graciously shared his extensive knowledge and experience about health behavior research. It was during a conversation in his beautiful home that it dawned on me how urgent and important it is to fill the gaps in health behavior research. Bob Daugherty generously provided his insights about the current state of health behavior research. Howard Bolnick suggested improvements in the design of the Workplace Wellness Model described in Chapter sixteen (Sample agent-based models). Members of the RAND COMPARE Strategic Policy Advisory Committee and Federico Girosi supported and critiqued early versions of Chapter fourteen (Simulation modeling guidelines). Lin Padgham kindly shared her knowledge about agent-based modeling in general, as well as the Belief- Desire-Intention model of behavior and the Prometheus agent-based modeling method and design tool in particular. Members of the Argonne Repast Simphony teamespecially Mike North, Eric Tatara, and Nick Colliergenerously shared their knowledge about Repast Simphony and agent-based modeling. Many times they took great pains to help me improve the sample models described in Chapter sixteen, and to make them accessible for students of agent-based modeling. Qiang Hou carefully reviewed the project’s sample models (described in Chapter sixteen) to make sure they work properly and are useful examples for students of agent-based modeling. He also suggested many innovations to improve the models. Lisa Canar, my wife, read every word of the project’s reportsmany timesand each time offered helpful suggestions. During the long periods of my absence while I worked on the project, she and our children, Calun and Ariana, stayed consistently and patiently supportive. But when Ariana, my six year old daughter, saw the finished product, she pinned me with a quizzical look, shook her head, and said, “Why didn’t you draw more pictures? It would have taken a lot less time.” To you all, my heartfelt thanks. Acknowledgments Simulating health behavior PREFACE

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