Optimal Design of the Liver Allocation System Considering Patient Preferences

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

The objective of this research is to design a new organ allocation policy considering patient preferences that will improve the efficiency of the liver allocation system, which is measured by the total number of organs wasted and the total expected quality-adjusted life years. The only viable therapy for patients with end-stage liver diseases (ESLD) is organ transplantation. These patients are listed on a waiting list, in which they are prioritized based on their location, medical urgency, blood type, and waiting time. When an organ is harvested, it is offered to these patients sequentially. Patients and/or their transplant surgeons have the right to decline an organ offer without penalty. This research will use stochastic models and simulation to optimize the liver allocation system. There are many interesting and controversial policy questions associated with the design of a new liver allocation system. What should be the primary criterion for prioritizing patients, medical urgency of the patients or the marginal benefit of transplanting an organ? Should we penalize patients if they decline an organ offer? What would be the potential benefits of requiring patients to specify their organ acceptance preferences in advance? There is strong evidence that the current liver allocation system is not operating effectively. The proposed research will not only improve the current liver allocation system, but will also provide insights for designing a better allocation system for other organs such as hearts. Any improvement on the organ allocation system would reduce the number of wasted organs, which is equivalent to saving many lives. Hence, the proposed work will directly affect the lives of thousands of transplant patients that are currently waiting for an organ. This research will have an immediate impact on education. PhD student(s) will be trained to utilize operations research techniques to solve complicated decision problems in medicine. The results of this research will be integrated into new courses developed by the PI. The proposed research will introduce operations research tools to medical community through a successful application of these tools to a complicated and controversial problem in medicine.