Seminar by Burhaneddin Sandıkçı

Seminar by
Burhaneddin Sandıkçı
University of Chicago Booth School of Business, USA

 

 

Abstract:

 

In the United States, patients in need of a liver transplant receive deceased-donor organ offers through joining a waiting list. Accepting or rejecting an offered organ is largely influenced by the patient’s prospects for future offers, which can be ascertained most accurately by knowing the entire composition of the waiting list. We present two stochastic models to help individual patients make optimal accept/reject decisions when faced with an offer. The first model assumes perfect information about the composition of waiting list, whereas the second model contends with partially observable waiting list as available in the current US system. In addition to modeling novelties, we present structural analyses of these models to characterize the optimal decision rule and a detailed numerical study investigating the impact of waiting list information on patients’ life expectancies. We find a significant loss in a patient’s life expectancy, on average, when the patient ignores the waiting list information, and that the currently published partial information is nearly sufficient to eliminate this loss.

Bio:

Burhaneddin Sandıkçı is an Associate Professor of Operations Management at the University of Chicago Booth School of Business. He received his PhD in industrial engineering in 2008 from the University of Pittsburgh. His prior training includes an MS in operations research (University of North Carolina at Chapel Hill), an MS in industrial engineering (Bilkent University), and a BS in industrial egineering (Marmara University). His research interests span decision-making problems under uncertainty with particular focus on problems in medical decision-making and healthcare operations. His methodological interests include Markov decision processes (MDPs), partially observed MDPs, stochastic programming, and simulation. His research has been published in leading academic journals such as Operations Research, Management Science, and Mathematical Programming. His work has also been recognized at various levels by INFORMS Decision Analysis Society, INFORMS Bonder Scholarship, and IIE Pritsker Doctoral Dissertation Award.