Fairness , Efficiency and Flexibility in Organ Allocation for Renal Transplantation

We propose a scalable, data-driven method for designing national policies for the allocation of deceased donor kidneys to patients on a waiting list, in a fair and efficient way. We focus on policies that have the same form as the one currently used in the U.S. In particular, we consider policies that are based on a point system, which ranks patients according to some priority criteria, e.g., waiting time, medical urgency, etc., or a combination thereof. Rather than making specific assumptions about fairness principles or priority criteria, our method offers the designer the flexibility to select her desired criteria and fairness constraints from a broad class of allowable constraints. The method then designs a point system that is based on the selected priority criteria, and approximately maximizes medical efficiency, i.e., life year gains from transplant, while simultaneously enforcing selected fairness constraints. Using our method, we design a point system that has the same form, uses the same criteria and satisfies the same fairness constraints as the point system that was recently proposed by U.S. policymakers. In addition, the point system we design delivers an 8% increase in extra life year gains illustrating the value of our approach. We perform a sensitivity analysis which demonstrates that the increase in extra life year gains by relaxing certain fairness constraints can be as high as 30%. We evaluate the performance of all policies under consideration using the same statistical and simulation tools currently used by U.S. policymakers. Sloan School and Operations Research Center, Massachusetts Institute of Technology, dbertsim@mit.edu Sloan School and Operations Research Center, Massachusetts Institute of Technology, vivekf@mit.edu Operations Research Center, Massachusetts Institute of Technology, nitric@mit.edu