A Stochastic Game Analysis of Incentives and Behavioral Barriers in Chronic Disease Management

Hui Zhang (), Christian Wernz () and Danny Hughes
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Hui Zhang: The Center for Health and the Social Sciences, The University of Chicago, Chicago, Illinois 60637
Christian Wernz: Department of Health Administration, Virginia Commonwealth University, Richmond, Virginia 23298

Service Science, 2018, vol. 10, issue 3, 302-319

Abstract: Chronic diseases can be prevented or mitigated by changing the behavior of patients and physicians. Incentives are one of the mechanisms to motivate such change. We present a two-player, multiperiod stochastic game model in which patients and primary care physicians jointly decide on chronic disease management activities. The model accounts for the decisions of patients regarding primary care engagement and lifestyle, as well as physicians’ choice of effort spent in clinical encounters. We capture the behavioral aspects of patients’ decisions by incorporating the health belief model. The physician-patient interaction is modeled as a general-sum stochastic game with switching control structure. A nonlinear programming (NLP) approach is used to find the agents’ optimal strategies. Using data on coronary heart disease, we provide a numerical example that quantifies how behavioral barriers and incentives affect patients’ and physicians’ decisions. Our results provide insights for health policy makers on how to design incentive mechanisms that contribute to more effective chronic disease management.

Keywords: stochastic games; chronic disease management; nonlinear programming; healthcare incentives; behavioral barriers; health belief model (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:orserv:v:10:y:2018:i:3:p:302-319

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