KDPI-Dependent Ranking Policies: Shaping the Allocation of Deceased-Donor Kidneys in the New Era

Baris Ata, Yichuan Ding and Stefanos Zenios
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Baris Ata: University of Chicago
Yichuan Ding: University of British Columbia
Stefanos Zenios: Stanford University

Research Papers from Stanford University, Graduate School of Business

Abstract: The deceased-donor kidney transplant candidates in the US are ranked according to characteristics of both the donor and the recipient. We seek the ranking policy that achieves the best efficiency-equity tradeoff, taking into account patients' strategic choices. Our approach considers a broad class of ranking policies, which provides approximations to the previously and currently used policies in practice. It also subsumes other policies proposed in the literature previously. As such it supports a unified way of characterizing policies that improve the efficiency-equity tradeoff. We use a fluid model to approximate the transplant waitlist. Modeling patients as rational decision makers, we compute the resulting equilibria. We characterize the set of all equilibria under the broad class of ranking policies, namely the achievable region. We develop an algorithm that optimizes the performance over the achievable region. Our results show that the policies that incorporate characteristics of both the donor and the recipient can improve the total quality-adjusted-life-years up to 3.1% based on the fluid model predictions, and may also eliminate kidney wastage in certain parametric settings. We also provide theoretical bounds for the performance gap between the two classes of policies. Our analysis shows that the policies which incorporate donor kidney quality (KDRP) always improve over those do not (KIRP), and the improvement is mainly due to the superior capability of the former in better matching the survival of the donor kidney and the recipient. We point out several conditions under which the performance gap between KDRP and KIRP could be smaller.

Date: 2017-06
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