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State-Transition Modeling

Author

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

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.

Suggested Citation

  • Uwe Siebert & Oguzhan Alagoz & Ahmed M. Bayoumi & Beate Jahn & Douglas K. Owens & David J. Cohen & Karen M. Kuntz, 2012. "State-Transition Modeling," Medical Decision Making, , vol. 32(5), pages 690-700, September.
    • Handle: RePEc:sae:medema:v:32:y:2012:i:5:p:690-700
    DOI: 10.1177/0272989X12455463
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    References listed on IDEAS

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    1. Natasha Stout & Sue Goldie, 2008. "Keeping the noise down: common random numbers for disease simulation modeling," Health Care Management Science, Springer, vol. 11(4), pages 399-406, December.
    2. Martin Spielauer, 2007. "Dynamic microsimulation of health care demand, health care finance and the economic impact of health behaviours: survey and review," International Journal of Microsimulation, International Microsimulation Association, vol. 1(1), pages 35-53.
    3. Uwe Siebert, 2003. "When should decision-analytic modeling be used in the economic evaluation of health care?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 4(3), pages 143-150, September.
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    Cited by:

    1. J. Jaime Caro & Jörgen Möller, 2018. "Adding Events to a Markov Model Using DICE Simulation," Medical Decision Making, , vol. 38(2), pages 235-245, February.

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