Determining the acceptance of cadaveric livers using an implicit model of the waiting list

Determining the acceptance of cadaveric livers using an implicit model of the waiting list

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Article ID: iaor20081386
Country: United States
Volume: 55
Issue: 1
Start Page Number: 24
End Page Number: 36
Publication Date: Jan 2007
Journal: Operations Research
Authors: , , ,
Keywords: programming: dynamic, markov processes
Abstract:

The only available therapy for patients with end-stage liver disease is organ transplantation. In the United States, patients with end-stage liver disease are placed on a waiting list and offered livers based on location and waiting time, as well as current and past health. Although there is a shortage of cadaveric livers, 45% of all cadaveric liver offers are declined by the first transplant surgeon and/or patient to whom they are offered. We consider the decision problem faced by these patients: Should an offered organ of a given quality be accepted or declined? We formulate a Markov decision process model in which the state of the process is described by patient state and organ quality. We use a detailed model of patient health to estimate the parameters of our decision model and implicitly consider the effects of the waiting list through our patient-state-dependent definition of the organ arrival probabilities. We derive structural properties of the model, including a set of intuitive conditions that ensure the existence of control-limit optimal policies. We use clinical data in our computational experiments, which confirm that the optimal policy is typically of control-limit type.

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