State-transition modeling: A report of the ISPOR-SMDM modeling good research practices task force-3

Uwe Siebert, Oguzhan Alagoz, Ahmed M. Bayoumi, Beate Jahn, Douglas K. Owens, David J. Cohen, Karen M. Kuntz

Research output: Contribution to journalArticlepeer-review

135 Scopus citations


State-transition modeling (STM) is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling, including both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, STM is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. STMs 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.

Original languageEnglish (US)
Pages (from-to)690-700
Number of pages11
JournalMedical Decision Making
Issue number5
StatePublished - Sep 2012

Bibliographical note

Funding Information:
Source of financial support: This Task Force was supported by ISPOR. U.S. and B.J were supported in part by the Oncotyrol Center for Personalized Cancer Medicine (COMET center).


  • Markov models
  • decision-analytic modeling
  • guidelines
  • state-transition modeling

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