Mathematical Optimization and Simulation Analyses for Optimal Liver Allocation Boundaries

The US transplant community has long been concerned about geographic disparities in access to and outcomes of transplantation. While several policies have been introduced to address the discrepancies, transplant researchers still report that a number of key elements that determine equity in transplantation vary significantly depending on the location of a patient. One of the alleged causes of disparity is administratively determined organ allocation boundaries that limit organ sharing across regions. Currently, the US liver allocation system consists of three layers of boundaries known as, from the smallest to the largest, the Organ Procurement Organization (OPO) areas, UNOS regions, and the national (i.e., US ) boundary. This study used a mathematical programming model to explore the following: (i) optimal locations of liver transplant centers; and (ii) optimal lowest boundaries as an alternative to the existing OPO boundaries across the contiguous United States. The optimal boundaries derived a priori were evaluated a posteriori using discrete-event simulation to examine whether the new boundaries perform better in a realistic setting with more complex allocation protocols and liver-candidate matching criteria. Our results confirmed that the mathematically driven optimal boundaries could reduce average waiting time and graft transfer distance and increase access to transplant across OPOs .