Modelling Approaches: The Case of Schizophrenia
2008
This article, published in Pharmacoeconomics, evaluates three modelling techniques including decision trees, Markov models (using both cohort and microsimulation approaches) and discrete event simulation models in the case of schizophrenia. Schizophrenia is a complex disease with considerable variation in the course of disease between individual patients. The three modelling techniques are compared in terms of their ability to deal with this patient heterogeneity, building time, data requirements, medico-scientific experience, simulation time, clinical representation, the timing of events, prior events, patient interaction, interaction between covariates, and variability (first-order uncertainty).
Based on their evaluation, the authors conclude that a discrete event simulation model may be optimal if a microsimulation is required for the cost-effectiveness analysis of schizophrenia treatments. The optimal modeling approach should be selected based on the expected differences between the comparators, the number of covariates, the number of patient subgroups, the interactions between covariates, and simulation time.
Modelling Approaches: The Case of Schizophrenia
Source:
Heeg BMS, Damen J, Buskens E et al. Modelling Approaches: The Case of Schizophrenia. Pharmacoeconomics 2008; 26 (8): 633-648. https://doi.org/10.2165/00019053-200826080-00002
Not open access.