التفاصيل البيبلوغرافية
| العنوان: |
Reshaping National Organ Allocation Policy. |
| المؤلفون: |
Papalexopoulos, Theodore, Alcorn, James, Bertsimas, Dimitris, Goff, Rebecca, Stewart, Darren, Trichakis, Nikolaos |
| المصدر: |
Operations Research; Jul/Aug2024, Vol. 72 Issue 4, p1475-1486, 12p |
| مصطلحات موضوعية: |
OPERATIONS research, CONTINUOUS distributions, PUBLIC housing, SCHOOL choice, GOVERNMENT policy, PLANNING techniques, BALANCED scorecard, MEDICAL simulation |
| مصطلحات جغرافية: |
UNITED States |
| مستخلص: |
Working with U.S. policymakers to redesign national organ allocation The Organ Procurement & Transplantation Network (OPTN), which manages transplantation activities in the United States, recently partnered with the MIT Operations Research Center to design and implement novel organ allocation policies that are more equitable, efficient, and inclusive. National organ allocation policies need to strike a delicate balance between efficiency and fairness in multiple objectives, reconciling often disparate value judgments and priorities from many different stakeholders. In "Reshaping National Organ Allocation Policy," T. Papalexopoulos, J. Alcorn, and D. Bertsimas et al. introduced a novel optimization- and machine learning-based framework to aid policy design and navigate challenging fairness-efficiency tradeoffs. The authors collaborated with the OPTN to apply the framework to the design of a new national allocation policy for lungs, which was implemented in March 2023 and is anticipated to reduce waitlist mortality by approximately 20%. Based on this success, the authors are now working toward the redesign of the entire U.S. organ allocation system, including kidneys, pancreata, hearts, and livers. The Organ Procurement & Transplantation Network (OPTN) initiated in 2018 a major overhaul of all U.S. deceased-donor organ allocation policies, aiming to gradually migrate them to a so-called continuous distribution model, with the goal of creating an allocation system that is more efficient, more equitable, and more inclusive. Development of policies within this model, however, represents a major challenge because multiple efficiency and fairness objectives need to be delicately balanced. We introduce a novel analytical framework that leverages machine learning, simulation, and optimization to illuminate policy tradeoffs and enable dynamic exploration of the efficient frontier of policy options. In collaboration with the OPTN, we applied the framework to design a new national allocation policy for lungs. Since March 9, 2023, all deceased-donor lungs in the United States have been allocated according to this policy that we helped design, projected to reduce waitlist mortality by approximately 20% compared with current policy based on simulations. We discuss how we extended our collaboration with the OPTN to the redesign of kidney, pancreas, heart, and liver allocation and how our framework can be applied to other application domains, such as school choice or public housing allocation systems. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2022.0035. [ABSTRACT FROM AUTHOR] |
|
Copyright of Operations Research is the property of INFORMS: Institute for Operations Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
