Theodore Papalexopoulos, James Alcorn, Dimitris Bertsimas, Rebecca Goff, Darren Stewart, Nikolaos Trichakis
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引用次数: 0
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. History: This paper has been accepted for the INFORMS Journal on Applied Analytics Special Issue—2022 Daniel H. Wagner Prize for Excellence in the Practice of Advanced Analytics and Operations Research.
2019年,自1984年以来一直在美国运营器官获取和移植网络(OPTN)的联合共享网络(UNOS)正在寻求设计一项新的国家肺移植分配政策。其目标是建立一个记分系统,将候补名单上的候选人按优先顺序排列,从而产生更有效和公平的结果。我们的麻省理工学院/UNOS联合团队与OPTN肺移植委员会在这些政策设计工作中通力合作。我们讨论了我们的团队如何应用一个新的分析框架,该框架是在麻省理工学院开发的,并利用优化、回归和模拟技术,来阐明结果之间的显著权衡,并指导如何在分配公式中权衡不同点属性的选择。委员会为分配公式选择了在团队分析中突出显示的权重。该团队的建议于2023年3月9日在美国全国范围内作为国家肺分配政策实施。历史:本文已被INFORMS应用分析杂志特刊- 2022年Daniel H. Wagner高级分析和运筹学实践优秀奖所接受。