title: State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--3.
abstract: State-transition modeling is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling including both Markov model cohort simulation and individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, state-transition modeling is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. State-transition models have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. The goal of this article was to provide consensus-based guidelines for the application of state-transition models in the context of health care. We structured the best practice recommendations in the following sections: choice of model type (cohort vs. individual-level model), model structure, model parameters, analysis, reporting, and communication. In each of these sections, we give a brief description, address the issues that are of particular relevance to the application of state-transition models, give specific examples from the literature, and provide best practice recommendations for state-transition modeling. These recommendations are directed both to modelers and to users of modeling results such as clinicians, clinical guideline developers, manufacturers, or policymakers.
authors.affiliation: UMIT-University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria. uwe.siebert@umit.at
authors.forename: Uwe
authors.initials: U
authors.lastname: Siebert
authors.forename: Oguzhan
authors.initials: O
authors.lastname: Alagoz
authors.forename: Ahmed M
authors.initials: AM
authors.lastname: Bayoumi
authors.forename: Beate
authors.initials: B
authors.lastname: Jahn
authors.forename: Douglas K
authors.initials: DK
authors.lastname: Owens
authors.forename: David J
authors.initials: DJ
authors.lastname: Cohen
authors.forename: Karen M
authors.initials: KM
authors.lastname: Kuntz
mesh_terms: D026683:Advisory Committees; D057186:Comparative Effectiveness Research; D032921:Consensus; D003658:Decision Making, Computer-Assisted; D055317:Evidence-Based Practice; D017408:Guidelines as Topic; D008390:Markov Chains; D008962:Models, Theoretical