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


CONCLUSIONS
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.
Shechter
Steven M
SM
Department of Industrial Engineering, University of Pittsburgh, Pennsylvania, USA.
Bryce
Cindy L
CL
Alagoz
Oguzhan
O
Kreke
Jennifer E
JE
Stahl
James E
JE
Schaefer
Andrew J
AJ
Angus
Derek C
DC
Roberts
Mark S
MS
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D003198:Computer Simulation; D003661:Decision Support Techniques; D006085:Graft Survival; D006801:Humans; D017114:Liver Failure, Acute / Q000401:mortality / Q000601:surgery*; D016031:Liver Transplantation / Q000401:mortality / Q000706:statistics & numerical data*; D018579:Patient Selection; D019057:Quality-Adjusted Life Years; D012042:Registries; D040841:Resource Allocation / Q000379:methods; D009927:Tissue and Organ Procurement / Q000379:methods*; D014850:Waiting Lists