Liver transplantation is currently the only known medical restorative therapy for End-stage Liver Disease with established survival benefits. In the United States, liver organs procured from deceased donors for the purpose of transplantation are allocated based on the geographic partitioning of the country. There continues to be disparities in a number of metrics, including the fraction of patients dying on the waitlist. In response to disparities in patient access to liver transplant across the country, a proposal for repartitioning the country has garnered interest. The repartitioning structure appears to have limitations in achieving its intended goals, particularly in the presence of uncertainties in the organ demand, and changes in organ allocation policies. A suboptimal policy change may have long term implications on patient welfare. Alternative modeling approaches might respond more effectively to uncertainty. However, development and solution of these models require additional research. The proposed work will develop stochastic optimization models and test the effectiveness of model based solutions towards reducing disparities in liver transplantation. If successful, the research will inform the liver transplantation policy on an issue requiring a rapid resolution.
|Effective start/end date||7/15/17 → 6/30/19|
- National Science Foundation (CMMI-1743886)
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