How Game Theory Revolutionized Kidney Donation

In the early 2000’s, renowned economist and Stanford University professor Alvin Roth created a revolutionary system to change the way patients were matched with kidney donors. His method, originally implemented as the New England Program for Kidney Exchange (NEPKE), was made possible by leveraging of the principles of game theory. Before the implementation of the system designed by Roth, “donors and patients mostly worked through a single transplant center” and successful matches would mostly rely on the compatibility of a friend or family member (Reuters). This created a situation where hundreds of patients in need of a kidney donations had compatible and willing donors but were not matched up with them due to the lack of an effective matching program that could sort through donor and patient lists and create an optimal outcome.

The algorithm that served as the basis for NEPKE “[allowed] patients to effectively swap incompatible donors with compatible ones from other donor-patient pairs” (Reuters). Before the program, there were numerous pairs of “unrelated donors and recipients” that were never matched to each other. This was because donors who tested and were deemed incompatible for the original patient were taken off the donor list entirely. With the new system, individuals who were willing to donate to patients they didn’t know directly would still be included in the system to broaden the donor base and create more possible matches. The program would then use the current information on the list of donors and prospective recipients as inputs to achieve the best possible cumulative outcome based on the given circumstances. In a way, this is very similar to several of the fundamental game theory setups studied in this course. Roth’s program set up a very sophisticated and large matrix of payoff that depended on the compatibility of patient x to donor y and ran an algorithm that tested different matching setups to determine the optimal societal payoff.

The output maximizing algorithm created an extremely quick and effective way to create matches that would have never happened otherwise. The algorithm was incorporated into the United Network for Organ Sharing soon after the news of its immediate success in New England had been confirmed. In just under a decade, the program took nationwide kidney donations from live donors from 19 per year to over 440 per year, an increase of over 2000% (Reuters).

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