Join Zoom Meeting - ORCIBS SEMINAR- Barış Ata

Author: CASE
Time: 17:00


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Seminar speaker: Barış Ata (Booth School of Business, University of Chicago)

Talk title: Structural Estimation of Kidney Transplant Candidates' Quality of Life Scores: Improving National Kidney Allocation Policy Under Endogenous Patient Choice and Geographical Structure

Date: 24 November 2020- Tuesday@ 17:00 pm.

Abstract: This paper develops a framework for assessing the impact of changes to the deceased-donor kidney allocation policy, taking into account the transplant candidates' (endogenous) organ acceptance behavior. To be specific, it advances a dynamic structural model of the transplant candidates' accept/reject decisions for organ offers. Our formulation models the national list (and its geographic structure) which is important for practical implementations, e.g. for incorporating it in the Kidney Pancreas Simulation Allocation Model (KPSAM). Moreover, it allows various important features of the transplant system such as the degree of tissue matching between the donor and the transplant candidate, changes in the health status of the transplant candidates as they wait on the list, organ quality, geographical sharing and cold-ischemia time of the organs as well as the heterogeneity in transplant candidates' quality of life scores. Using United Network of Organ Sharing (UNOS) data on transplant candidates, donors, organ offers, and follow up results on transplant outcomes, we first estimate the transplant candidates' quality of life scores.  Our estimates are based on patient's revealed preferences and yield similar results on average to what is typically assumed in the medical literature. However, they differ significantly when patient and donor characteristics are considered. We then perform various counterfactual studies for assessing the (unintended) consequences of policy changes. In particular, we find that although the current policy increases the total number of transplants by 2.63% and total life years by 4.45%, it decreases total quality adjusted life years by 1.68%. Moreover, it increases the disparity in probability of getting a transplant for patients of different health scores by 69.3%. These happen due to the current prioritization of healthier patients for kidneys of better quality.  We also show that geographical redistricting of the transplant system, as done for the liver allocation system, does not change the system performance significantly.  However, the brevity matching policy which is a last-come-first served distribution policy based on the health scores of the patients, can further increase the total number of transplants by 1.50%.

Joint work with: John J. Friedewald, Northwestern University Transplant Outcomes Research Center, A. Cem Randa, University of California San Francisco Department of Surgery, UC Berkeley Haas School

Short bio: Baris Ata is a Chookaszian Family Professor of Operations Management at The University of Chicago, Booth School of Business. Prior to joining Chicago Booth, he worked for Northwestern’s Kellogg School (2003-2013). He received the B.S. degree in Industrial Engineering from Bilkent University in 1997, and MS degrees in Engineering-Economic Systems and Operations Research (1999), Business Research (2000), Mathematics (2001), and Statistics (2002) and a Ph.D. in Operations, Information, and Technology (2003) from Stanford University. His research takes a problem-driven approach to bridge theory and practice of Operations Management. His current research interests include stochastic networks, healthcare management, and operational problems in the social sector. He received the INFORMS Best Paper in Service Science Award (2009), the William Pierskella Best Paper Award (2015), the MSOM Young Scholar Award (2015), and POMS Wickham Skinner Best Paper Award (2019). He currently serves as a Department Editor for Management Science and the Deputy Editor for Stochastic Systems. He has served as an Associate Editor for Operations Research, Management Science, Mathematics of Operations Research, Manufacturing & Service Operations Management, and Stochastic Systems.