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

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.

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