Stefanos A. Zenios, a professor at Stanford's Graduate School of Business, renowned for his application of Operations Research (O.R.) to tackle some of modern medicine's thorniest problems, has completed new research that could revolutionize kidney allocation for transplant waiting list candidates. The paper, "Recipient Choice Can Address the Efficiency-Equity Trade-Off in Kidney Transplantation: A Mechanism Design Model," was co-written by Zenios with Xuanming Su at Berkeley's Haas School of Business. It was recently published in the journal Management Science.
For over a decade, Zenios has applied O.R., the discipline that uses advanced analytical methods to make better decisions, to find alternative ways to distribute scare resources such as the supply of human kidneys available for transplant. Using optimization, game theory, statistics and queuing theory from the O.R. tool box, Professor Zenios presents a new model which not only gives patients greater choice about their position on the transplant waiting list, but creates a more efficient and equitable system.
Zenios calls for the definition of five distinct quality grades for kidneys. When a patient joins the kidney transplant waiting list, he/she is given information on how long it would take to wait for each of these grades (higher quality is paired with longer waits and vice versa) and what the expected outcomes for transplanting each grade are, given their personal health profile. From there, the patient works with his/her physician to decide on what the minimum grade of kidney they would be willing to accept is.
In essence, Zenios' model creates a sequence of queues for kidneys of various grades and, within these queues, organs that become available are allocated based on waiting time. This contrasts with the present allocation system, determined by the United Network of Organ Sharing (UNOS), whereby kidneys are allocated based on waiting time and certain medical criteria,
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Contact: Barry List
barry.list@informs.org
443-757-3560
Institute for Operations Research and the Management Sciences
3-Jan-2007