Dynamic allocation of kidneys to candidates on the transplant waiting list
成果类型：
Article
署名作者：
Zenios, SAA; Chertow, GM; Wein, LM
署名单位：
Stanford University; University of California System; University of California San Francisco; Massachusetts Institute of Technology (MIT)
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.48.4.549.12418
发表日期：
2000
页码：
549-569
关键词：
摘要：
The crux of the kidney allocation problem is the trade-off between clinical efficiency and equity. We consider a dynamic resource allocation problem with the tri-criteria objective of maximizing the quality-adjusted life expectancy of transplant candidates (clinical efficiency) and minimizing two measures of inequity: a linear function of the likelihood of transplantation of the various types of patients, and a quadratic function that quantities the differences in mean waiting times across patient types. The dynamic status of patients is modeled by a set of linear differential equations, and an approximate analysis of the optimal control problem yields a dynamic index policy. We construct a large-scale simulation model using data from over 30,000 transplants, and the simulation results demonstrate that, relative to the organ allocation policy currently employed in the United States, the dynamic index policy increases the quality-adjusted life expectancy and reduces the mean waiting time until transplantation for all six demographic groups (two sexes, races, and age groups) under consideration.