A clinically based discrete-event simulation of end-stage liver disease and the organ allocation process

Steven M. Shechter, Cindy L. Bryce, Oguzhan Alagoz, Jennifer E. Kreke, James E. Stahl, Andrew J. Schaefer, Derek C. Angus, Mark S. Roberts*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

70 Scopus citations

Abstract

Background. The optimal allocation of scarce donor livers is a contentious health care issue requiring careful analysis. The objective of this article was to design a biologically based discrete-event simulation to test proposed changes in allocation policies. Methods. The authors used data from multiple sources to simulate end-stage liver disease and the complex allocation system. To validate the model, they compared simulation output with historical data. Results. Simulation outcomes were within 1% to 2% of actual results for measures such as new candidates, donated livers, and transplants by year. The model overestimated the yearly size of the waiting list by 5% in the last year of the simulation and the total number of pretransplant deaths by 10%. Conclusion. The authors created a discrete-event simulation model that represents the biology of end-stage liver disease and the health care organization of transplantation in the United States.

Original languageEnglish (US)
Pages (from-to)199-209
Number of pages11
JournalMedical Decision Making
Volume25
Issue number2
DOIs
StatePublished - Mar 2005
Externally publishedYes

Keywords

  • Discrete-event simulation
  • Graft survival
  • Liver transplantation
  • Monte Carlo simulation
  • Organ allocation
  • Patient survival
  • Policy analysis
  • Simulation modeling

ASJC Scopus subject areas

  • Health Policy

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