Unlike the other models, discrete event simulation (DES) is based on models of individual patient experiences versus cohorts. This makes DES more flexible and naturalistic than decision tree and Markov models. The use of DES is relatively new to health economics research, but has long been used in operational research. Several of our staff have formal operational research training and have long been working with discrete event simulations. DES is particularly useful when clinical events and outcomes depend on the actual experiences of patients during the model time period and on their individual history or clinical profile (as apposed to a cohort model). DES provides greater granularity and flexibility in the modeling details, which will provide you with very specific information so you can make better decisions. DES is particularly useful for budget impact analyses.
