Association for Public Policy Analysis & Management

In 2013, 6,156 people died waiting for an organ transplant in the U.S.  In the same year, 54,043 people were added to the waiting list, and only 30,040 people on the list received a transplant, 18,458 of which were kidney recipients (OPTN data as of 4/15/2014:  http://optn.transplant.hrsa.gov). 

In the face of the severe shortage, and without the (legal) possibility of buying and selling transplantable kidneys, transplant centers have begun to implement kidney exchange programs.  A patient in need of a kidney transplant and a willing but incompatible living donor (i.e., an incompatible pair) can enter into a exchange program, where an incompatible donor from one pair is matched to a recipient in a second pair, and vice versa.  These arrangements can extend to three or more pairs in self-contained groups or indefinitely through the use of donor chains started by altruistic donors.  They may also occur between an incompatible pair and the deceased donor waiting list.  The main goal of exchange programs is to increase the number of successful transplants that take place.  Exchanges may also have the benefit of improving match quality and length of transplant survival. 

This paper seeks to determine how many additional transplants are generated by exchange mechanisms by exploring patients’ substitution patterns among alternate methods of transplantation, and to explore the impact of exchange on graft survival and match quality for all transplant recipients.  Initial naïve estimates show that more than six out of every ten additional kidney exchange recipients would not have received a living kidney transplant in the absence of such programs.  They also show that receiving a transplant via exchange increases one year graft survival by 1.7 percentage points, increases two year graft survival by 2.6 percentage points, and reduces waiting time by 193 days.  I observe that the level of nearby kidney exchange activity is significantly correlated with the likelihood of receiving a transplant via exchange.  This information motivates two empirical approaches moving forward.  The first is a difference-in-difference approach exploiting variation in paired exchange activity across time and transplant centers while utilizing patients’ zip codes of residence.  The second is the estimation of a discrete choice model of the possible transplant outcomes of patients, taking into consideration both patient- and alternative-specific characteristics.