An Achievable-Region-Based Approach for Kidney Allocation Policy Design with Endogenous Patient Choice

Manufacturing & Service Operations Management · 2020 · 30 citations

• Computer Science
• Machine Learning
• Computer Science

Problem definition: Deceased-donor kidney transplant candidates in the United States are ranked according to characteristics of both the donor and the recipient. We seek the ranking policy that optimizes the efficiency–equity tradeoff among all such policies, taking into account patients’ strategic choices. Academic/practical relevance: 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 facilitates a unified way of characterizing good policies. Methodology: We use a fluid model to approximate the transplant waitlist. Modeling patients as rational decision makers, we compute the resulting equilibria under a broad class of ranking policies, namely the achievable region. We then develop an algorithm that optimizes the system performance over the achievable region. Results: We show analytically that it suffices to restrict attention to priority scores that are affine in the patient’s waiting time. We also show through a numerical study that the total quality-adjusted life-years can be increased substantially by allowing patient rankings to depend on the kidney quality. Last, we observe that there is almost no improvement if only the healthier patients are prioritized for certain kidney types. Managerial implications: Our results verify that ranking patients differently for kidneys of different quality can reduce the survival mismatch and the kidney wastage significantly. Consequently, the policy change in 2014, that implemented prioritizing the healthiest patients when allocating the highest 20% quality organs, is a step in the right direction. For further improvement, one may consider revising the new policy by also prioritizing the least healthy patients on the waitlist for the lowest-quality organs.