Applying Analytics to Design Lung Transplant Allocation Policy

Theodore Papalexopoulos (), James Alcorn (), Dimitris Bertsimas (), Rebecca Goff (), Darren Stewart () and Nikolaos Trichakis ()
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Theodore Papalexopoulos: Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
James Alcorn: United Network for Organ Sharing, Richmond, Virginia 23219
Dimitris Bertsimas: Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
Rebecca Goff: United Network for Organ Sharing, Richmond, Virginia 23219
Darren Stewart: Center for Surgical and Transplant Applied Research, New York University Langone, New York, New York 10016
Nikolaos Trichakis: Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139

Interfaces, 2023, vol. 53, issue 5, 350-358

Abstract: In 2019, the United Network for Sharing (UNOS), which has been operating the Organ Procurement and Transplantation Network (OPTN) in the United States since 1984, was seeking to design a new national lung transplant allocation policy. The goal was to develop a point system that would prioritize candidates on the waiting list in a way that would yield more efficient and equitable outcomes. Our joint Massachusetts Institute of Technology (MIT)/UNOS team joined forces with the OPTN Lung Transplantation Committee in these policy design efforts. We discuss how our team applied a novel analytical framework, which was developed at MIT and utilizes optimization, regression, and simulation techniques, to illuminate salient trade-offs among outcomes and guide the choice of how to weigh different point attributes in the allocation formula. The committee selected for the allocation formula weights that were highlighted in the team’s analysis. The team’s proposal was implemented as the national lung allocation policy on March 9, 2023 across the United States.

Keywords: organ allocation; multiobjective optimization; lung transplantation (search for similar items in EconPapers)
Date: 2023
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