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

doi:10.1177/0272989X12455463

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

^*Corresponding author for this work

Managerial Economics, Decision Sciences and Operations

Research output: Contribution to journal › Article › peer-review

135 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	690-700
Number of pages	11
Journal	Medical Decision Making
Volume	32
Issue number	5
DOIs	https://doi.org/10.1177/0272989X12455463
State	Published - Sep 2012

Keywords

Markov models
decision-analytic modeling
guidelines
state-transition modeling

ASJC Scopus subject areas

Health Policy

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

abstract = "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.",

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author = "Uwe Siebert and Oguzhan Alagoz and Bayoumi, {Ahmed M.} and Beate Jahn and Owens, {Douglas K.} and Cohen, {David J.} and Kuntz, {Karen M.}",

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). ",

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AU - Owens, Douglas K.

AU - Cohen, David J.

AU - Kuntz, Karen M.

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