Advanced Search
DSpace@MIT

Redesigning liver allocation regions through optimization

Research and Teaching Output of the MIT Community

Show simple item record

dc.contributor.advisor Jónas Oddur Jónasson and Nikolaos Trichakis. en_US
dc.contributor.author Scully, Timothy (Timothy Edward) en_US
dc.contributor.other Massachusetts Institute of Technology. Operations Research Center. en_US
dc.date.accessioned 2017-10-30T15:30:46Z
dc.date.available 2017-10-30T15:30:46Z
dc.date.copyright 2017 en_US
dc.date.issued 2017 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/112083
dc.description Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2017. en_US
dc.description Cataloged from PDF version of thesis. en_US
dc.description Includes bibliographical references (pages 95-97). en_US
dc.description.abstract End-stage liver disease is one of the leading causes of death in the United States, and the only viable treatment is liver transplantation. Since the quality of a donor liver decreases with transportation time, United States organ policy prioritizes transplants within geographic regions. However, the boundaries of these regions were defined mostly by informal relationships between transplant centers many decades ago, which has created local imbalances in supply and demand. As a result, candidates on the waiting list for donor livers face drastically different odds of receiving a transplant. Policy makers have noticed this geographic inequity and are considering proposals for alternative liver allocation approaches. This thesis uses mathematical optimization to redesign liver allocation regions by modeling and including several key elements of the allocation process directly in the optimization formulation. Specifically, we use a fluid approximation to model the dynamics of the wait-list progression and liver allocation. The model is fit using historical data of wait-list candidates and donors. Then, we propose two optimization formulations to reduce geographic inequality. The first directly minimizes the variation in median level of illness at the time of transplant across geographical areas, which is a key metric used by policy makers in addressing geographic inequality. The second approach minimizes the liver transport distance, subject to a certain allowable level of geographic variation. We discuss how these models can flexibly incorporate additional policy constraints to create more realistic models to reduce geographic variation. The region configurations are evaluated on key metrics relating to fairness and system efficiency using a standardized, validated, simulation approach widely accepted by policymakers. Finally, we propose a region design that significantly reduces geographic inequality without any substantial impact on the system's efficiency. en_US
dc.description.statementofresponsibility by Timothy Scully. en_US
dc.format.extent 97 pages en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Operations Research Center. en_US
dc.title Redesigning liver allocation regions through optimization en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Operations Research Center. en_US
dc.identifier.oclc 1006885196 en_US


Files in this item

Name Size Format Description
1006885196-MIT.pdf 7.208Mb PDF Full printable version

This item appears in the following Collection(s)

Show simple item record

MIT-Mirage