Understanding and Managing the Complexity of Healthcare

Preface

We both came to this topic having had many experiences, some of them profound, with the healthcare delivery system in the United States. These experiences have caused us to believe that the system could be much better. Indeed, we believe that high quality, affordable care for everyone is doubtlessly achievable. We inherently address this possibility from rather different perspectives, one being engineering (W.R.) and the other statistics (N.S.). The engineering approach begins with first principles (e.g., laws of physics or economics ) and builds structural models of the phenomena of interest. The models are used to deduce the likely effects of different design choices. These predictions are then compared to either existing data or measurements made for this purpose. The statistical approach starts with the data and uses a range of methods to infer underlying structures and assess how well these structures fit the data. The identified structures can then inform efforts to design systems that will yield better outcomes. These outcomes are captured in new data sets, which are then subject to additional types of analyses. We have found that the creative clash of the model-driven and datadriven perspectives can yield insights not possible from any single point of view. Transformation of the U.S. system of healthcare delivery will not succeed if one point of view dominates. This book is intended to illustrate how different perspectives can be woven together to synthesize ways to contribute to this transformation. We are pleased to acknowledge many colleagues who have worked with us on one or more of the research projects discussed in this book. These colleagues include Rahul Basole, Mark Braunstein, Ken Brigham, Trustin Clear, Lynn Cunningham, Eser Kirkizlar, Mallory Nobles, Hyunwoo Park, Jessica Heir Stamm, Julie Swann, and Annie Yu. We also want to thank several mentors who helped tremendously as we immersed ourselves in the complexity of healthcare delivery. We are very grateful for the advice and guidance of Raymond Carroll, Denis Cortese, Mike Johns, Bob Smoldt, and Bill Stead. Preface ...