Eliciting Patients' Revealed Preferences: An Inverse Markov Decision Process Approach

Zeynep Erkin (), Matthew D. Bailey (), Lisa M. Maillart (), Andrew J. Schaefer () and Mark S. Roberts ()
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Zeynep Erkin: Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
Matthew D. Bailey: School of Management, Bucknell University, Lewisburg, Pennsylvania 17837
Lisa M. Maillart: Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
Andrew J. Schaefer: Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
Mark S. Roberts: Department of Health Policy and Management, University of Pittsburgh, Pittsburgh, Pennsylvania 15261

Decision Analysis, 2010, vol. 7, issue 4, 358-365

Abstract: Estimating patient preferences over various health states is an important problem in health care decision modeling. Direct approaches, which involve asking patients various abstract questions, have significant drawbacks. We propose a new approach that infers patient preferences based on observed decisions via inverse optimization techniques. We illustrate our methods on the timing of a living-donor liver transplant.

Keywords: Markov decision processes; health care; inverse optimization; quality-adjusted life years (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (13)

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