Organ transplantation policy evaluation

Abstract

This paper on the UNOS Liver Allocation Model (ULAM) describes the building of a simulation model that supports policy evaluation for a national medical problem. The modeling and simulation techniques used in building ULAM include: fitting donor and patient arrival processes having trend and cyclic rate components using non-homogeneous Poisson processes (NHPPs) having exponential rate functions which may include both a polynomial and some trigonometric components; fitting distributions to data on transition times between states of medical urgency; application of variance reduction techniques using common random-number streams and prior information; organizing data structures for efficient file searching and ranking capabilities; the use of bootstrapping techniques for attribute sampling; the building of submodels employing biostatistical procedures such as Kaplan-Meier and logistic regression; and the characterization of performance measures within a complex political, economic and social environment. ULAM provides a means for producing quantitative information to support the selection of a liver allocation policy.