An Evidence-Based Incentive System for Medicare's End-Stage Renal Disease Program

Donald K. K. Lee () and Stefanos A. Zenios ()
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Donald K. K. Lee: Yale School of Management, Yale University, New Haven, Connecticut 06520
Stefanos A. Zenios: Graduate School of Business, Stanford University, Stanford, California 94305

Management Science, 2012, vol. 58, issue 6, 1092-1105

Abstract: Recent legislations directed Medicare to revamp its decades-old system for reimbursing dialysis treatments, with focus on the risk adjustment of payments and on the transition toward a pay-for-compliance system. To design an optimal payment system that incorporates these features, we develop an empirical method to estimate the structural parameters of the principal-agent model underlying Medicare's dialysis payment system. We use the model and parameter estimates to answer the following questions: Can a pay-for-compliance system based only on the intermediate performance measures currently identified by Medicare achieve first-best? How should patient outcomes be risk adjusted, and what welfare gains can be achieved by doing so? Our main findings are as follows: (1) the current set of intermediate measures identified by Medicare are not comprehensive enough for use alone in a pay-for-compliance system; (2) paying for risk-adjusted downstream outcomes instead of raw downstream outcomes can lengthen the hospital-free life of admitted patients by two weeks per patient per year without increasing Medicare expenditures. This paper was accepted by Christian Terwiesch, operations management.

Keywords: healthcare pay-for-performance; dialysis; evidence-based mechanism design; structural estimation (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (10)

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