Modeling Kidney Allocation: A Data-Driven Optimization Approach

STATISTICAL METHODS IN HEALTHCARE, F. Faltin, R. Kenett & F. Ruggeri, eds., Wiley, 2011

14 Pages Posted: 10 Oct 2011

See all articles by Inbal Yahav

Inbal Yahav

Bar-Ilan University - Graduate School of Business Administration

Date Written: October 10, 2011

Abstract

In the United States, more than 90,000 candidates are currently waiting for kidney transplantation, with an annual increase of about 20,000 candidates. The current allocation policy poorly matches donors with recipients. We present a two-phase allocation policy that combines an integer programming-based learning phase and a data-mining, real-time phase. Our policy outperforms the current system in multiple respects, such as increased life-year gained from kidney allocation and lower better match between organs and recipients.

Keywords: kidney Allocation, optimization, KAS, Stochastic Optimization

Suggested Citation

Yahav, Inbal, Modeling Kidney Allocation: A Data-Driven Optimization Approach (October 10, 2011). STATISTICAL METHODS IN HEALTHCARE, F. Faltin, R. Kenett & F. Ruggeri, eds., Wiley, 2011. Available at SSRN: https://ssrn.com/abstract=1941847

Inbal Yahav (Contact Author)

Bar-Ilan University - Graduate School of Business Administration ( email )

Ramat Gan
Israel
97235318913 (Phone)

HOME PAGE: http://faculty.biu.ac.il/~yahavi1

Register to save articles to
your library

Register

Paper statistics

Downloads
95
rank
264,938
Abstract Views
489
PlumX Metrics