An evolving strategy known as kidney paired donation (KPD) employs a technological solution to overcome the barriers faced by many patients with kidney failure who present with willing, but immunologically or blood type incompatible living donors. Kidney paired donation uses a computerized algorithm to match one incompatible donor/recipient pair to another pair with a complementary incompatibility, such that the donor of the first pair gives to the recipient of the second, and vice versa. We also consider more complex exchanges of organs involving three or more pairs. In addition, we allow for altruistic donors who donate a kidney voluntarily and thereby have the potential to create a chain of kidney transplants. A fundamental problem in managing a KPD program is selecting the "optimal" set of transplants from among the many mathematically possible alternative combinations that could be generated. The choice of an optimal allocation depends in part on the assigned utility of a specific transplant. We show that this choice should also depend on stochastic elements and define new and better methods for optimization. We will develop a data-based micro-simulation model of KPD program, and utilize that model to evaluate different allocation strategies, to compare the impact of these strategies on performance outcomes, and to assess effects of different utility assignments. In addition, we will develop a user-friendly version of these models to provide decision support to individuals charged with managing KPD programs. To accomplish these tasks, we propose the following specific aims:
Aim 1 : Develop optimization methods for selecting exchanges and chains in a KPD program that take account of utility and uncertainty, and to compare these new methods with those currently in use that are based solely on utility. This includes testing and refining these methods through their implementation in existing KPD programs.
Aim 2 : To develop a holistic approach to the modeling of all aspects of a KPD program using simulation methods based on multiple data sources, and the use of this micro simulation model to assess the effects of policy decisions and approaches on key performance measures of a KPD.
Aim 3 : To develop a user friendly interface to enable the use of the micro simulation model for decision support in active KPD programs.

Public Health Relevance

The USRDS reports that for the 2009 year, Medicare spent nearly $24 billion to care for patients with End Stage Renal Disease (ESRD), or nearly 5.8 percent of all Medicare spending. When non-Medicare spending is factored in, total ESRD costs reached $35.3 billion or 1.6% of the $2.2 trillion the US spent on healthcare in 2007. Both in terms of patient outcomes and in terms of medical costs, transplantation, and especially living-donor transplantation is the preferred treatment of ESRD. This project would seek to optimize the potential of Kidney Paired Donation Programs to increase the number and quality of living donor transplants and so improve patient outcomes while also reducing health care costs substantially.

National Institute of Health (NIH)
Research Project (R01)
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Biostatistical Methods and Research Design Study Section (BMRD)
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Abbott, Kevin C
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University of Michigan Ann Arbor
Schools of Public Health
Ann Arbor
United States
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Li, Yijiang; Song, Peter X-K; Leichtman, Alan B et al. (2014) Decision Making in Kidney Paired Donation Programs with Altruistic Donors. Sort (Barc) 38:53-72
Li, Yijiang; Song, Peter X-K; Zhou, Yan et al. (2014) Optimal Decisions for Organ Exchanges in a Kidney Paired Donation Program. Stat Biosci 6:85-104