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

Med Decis Making. 2005 Mar-Apr;25(2):199-209. doi: 10.1177/0272989X04268956.

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.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.
  • Validation Study

MeSH terms

  • Adolescent
  • Adult
  • Algorithms
  • Computer Simulation*
  • Decision Support Techniques*
  • Graft Survival
  • Humans
  • Liver Failure, Acute / mortality
  • Liver Failure, Acute / surgery*
  • Liver Transplantation / mortality
  • Liver Transplantation / statistics & numerical data*
  • Patient Selection*
  • Quality-Adjusted Life Years
  • Registries
  • Resource Allocation / methods
  • Tissue and Organ Procurement / methods*
  • Waiting Lists