State-Transition Modeling- A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3

Sep 1, 2012, 00:00
10.1016/j.jval.2012.06.014
https://www.valueinhealthjournal.com/article/S1098-3015(12)01654-3/fulltext
Title : State-Transition Modeling- A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3
Citation : https://www.valueinhealthjournal.com/action/showCitFormats?pii=S1098-3015(12)01654-3&doi=10.1016/j.jval.2012.06.014
First page : 812
Section Title : ISPOR Task Force Reports
Open access? : No
Section Order : 3

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.

Categories :
  • Best Research Practices
  • Methodological & Statistical Research
  • Modeling and simulation
  • Organizational Practices
Tags :
  • decision-analytic modeling
  • guidelines
  • Markov models
  • state-transition modeling
Regions :
  • Global
  • North America
ViH Article Tags :