An optimization framework to determine an optimal local sharing variance for organ allocation
Publication Title
Operations Research for Health Care
ISSN
22116923
Document Type
Article
Abstract
One of the main elements affecting the performance of the organ transplantation system is the set of organ allocation boundaries that limits the number of organs shared among regions. To overcome these boundary limits, members of the Organ Procurement Transplant Network - OPTN - (including, transplant hospitals, Organ Procurement Organizations (OPO), medical/scientific members, among others) can propose a variance to the current allocation system to allocate organs differently than the OPTN policies. Over the years, several variances have been enacted by different members for various organs. In this study, we focus on the analysis of sharing variances which allow allocating organs within participating members before offering them at other levels. This type of variance has been successfully implemented in the past. For example, Florida and Tennessee created the Statewide Sharing program whereby kidneys are made available within-state donor service areas before they are made available for regional or national allocation. This program removed geographic disparities within those two states and resulted in better performance of the system in the states. Given these success stories, we propose a multi-period optimization model that can be used to determine the best policy for a local sharing program for any given OPO. We use liver allocation for the GALL OPO (i.e., LifeLink of Georgia) in the state of Georgia (USA) as a test case; however, our approach could be used for a variety of organs in any OPO.
Publication Date
3-1-2020
DOI
10.1016/j.orhc.2019.100242
Recommended Citation
Mohammadi, Mohsen; Koli, Vikram; Gentili, Monica; and Muthuswamy, Shanthi, "An optimization framework to determine an optimal local sharing variance for organ allocation" (2020). NIU Bibliography. 544.
https://huskiecommons.lib.niu.edu/niubib/544
Department
Department of Industrial and Systems Engineering; Department of Engineering Technology