Background: Geographic disparities persist in access to liver transplantation. Candidates with similar urgency experience varying opportunities for transplants across the US. Policymakers are poised to act and one proposal entails reorganizing the current OPTN of 11 regions into 8 districts. However, redistricting has the shortcomings that OPOs are disconnected from their immediate neighbors by district borders and that it is not easily responsive to uncertainty resulting from variability in donor and listing rates.

Methods: We introduce the notion of an OPO's neighborhood – a collection of DSAs surrounding the OPO that acts as the OPO's region in the current local-regional-national framework. Districts and concentric circles are special cases. We design 58 neighborhoods for the DSAs with several attractive properties and optimize them to balance supplies and demands using 10 years of OPTN data. We conduct a simulation experiment comparing current allocation, redistricting, and neighborhoods under current sharing policies with respect to the following metrics: total mortalities, DSA-average MELD at transplant, DSA-average MELD standard deviation, and average organ transport distance. LSAM cannot accommodate neighborhoods, so we programmed a discrete-event simulator, LivSim, to approximate LSAM.

Results: We exhibited a neighborhood solution. Compared to the current allocation, simulation results showed that neighborhoods reduce the DSA-average MELD standard deviation by 29% and save about 65 lives annually. Compared to redistricting, the neighborhoods had a smaller average transport distances that were more uniform across DSAs, saved about 20 additional lives, and reduced DSA-average MELD standard deviation by an additional 17%.

Conclusions: Alternatives to redistricting with desirable properties and performance are possible and should be considered.

CITATION INFORMATION: Mehrotra S, Kilambi V. Improving Liver Allocation Using Optimized Neighborhoods. Am J Transplant. 2017;17 (suppl 3).

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