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

Oguzhan Alagoz*, Lisa M. Maillart, Andrew J. Schaefer, Mark S. Roberts

*Corresponding author for this work

Research output: Contribution to journalArticle

63 Scopus citations

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 patientstate-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.

Original languageEnglish (US)
Pages (from-to)24-36
Number of pages13
JournalOperations Research
Volume55
Issue number1
DOIs
StatePublished - Jan 1 2007
Externally publishedYes

Keywords

  • Applications and markov: infinite horizon
  • Dynamic programming/optimal control
  • Health care, treatment

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research

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