Optimal Policies for the Acceptance of Living-&Cadaverc-Donor Livers
“Optimal Policies for the Acceptance of Living- and Cadaveric-Donor Livers”
by
Oğuzhan Alagöz
Weatherhead School of Management
Case Western Reserve University
Cleveland, OH, USA
Abstract: Transplantation is the only viable therapy for end-stage liver diseases (ESLD) such as hepatitis B. In the United States, patients with ESLD are placed on a waiting list. When organs become available, they are offered to the patients on this waiting list. This study focuses on the decision problem faced by these patients: which offer to accept and which to refuse? A recent analysis of liver transplant data indicates that 60% of all livers offered to patients for transplantation are declined. We formulate this problem as a discrete-time Markov decision process (MDP). We analyze three MDP models, each representing a different situation. The Living-Donor-Only Model considers the problem of optimal timing of living-donor liver transplantation, which is accomplished by removing an entire lobe of a living donor's liver and implanting it into the recipient. The Cadaveric-Donor-Only Model considers the problem of accepting/refusing a cadaveric liver offer when the patient is on the waiting list but has no available living donor. The Living-and-Cadaveric-Donor Model is the most general model, which combines the first two models, in that the patient is both listed on the waiting list and also has an available living donor. The patient can accept the cadaveric liver offer, decline the cadaveric liver offer and use the living-donor liver, or decline both and continue to wait. We derive structural properties of all three models, including several sets of conditions that ensure the existence of intuitively structured policies such as control-limit policies. The computational experiments use clinical data, and show that the optimal policy is typically of control-limit type.
Biography: Oguzhan Alagoz is currently a Visiting Assistant Professor of Operations at the Weatherhead School of Management of Case Western Reserve University. He received his BS in Industrial Engineering (IE) from Bilkent University in 1997, his MS in IE from Middle East Technical University in 2000 and PhD in IE from the University of Pittsburgh in 2004. His research interests include medical decision making, completely and partially observable Markov decision processes, scheduling, simulation and stochastic programming. His works have appeared in or been accepted by journals such as Management Science, IIE Transactions, Medical Decision Making and European Journal of Operational Research.