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Related Experiment Videos

Selecting a decision model for economic evaluation: a case study and review.

J Karnon1, J Brown

  • 1Health Economics Research Group, Brunel University, Uxbridge, Middlesex, UK. jonathan.karnon@brunel.ac.uk

Health Care Management Science
|August 1, 2000
PubMed
Summary

This study compares decision trees, Markov chain models, and discrete event simulation for health economic evaluations. Discrete event simulation offers greater flexibility for complex health technology assessments.

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Area of Science:

  • Health economics
  • Mathematical modeling
  • Health technology assessment

Background:

  • Economic evaluations of health technologies increasingly use modeling.
  • Decision trees and Markov chain models are common, but discrete event simulation is less developed.
  • Adjuvant therapies for breast cancer serve as an example.

Purpose of the Study:

  • To describe the construction of decision tree, Markov chain, and discrete event simulation models.
  • To discuss the benefits and drawbacks of each modeling approach.
  • To assess the suitability of these techniques for general health program economic evaluations.

Main Methods:

  • Comparative analysis of three modeling techniques: decision trees, Markov chain models, and discrete event simulation.

Related Experiment Videos

  • Illustrative application using economic evaluation of adjuvant therapies for breast cancer.
  • Discussion of model construction, benefits, and limitations.

    • Main Results:

    • Decision trees are suitable for simple, short-term scenarios.
    • Markov chain models handle longer timeframes with uncertain event timing.
    • Discrete event simulation provides greater flexibility for complex evaluations.

    Conclusions:

    • Each modeling technique has specific strengths and weaknesses.
    • Discrete event simulation may offer advantages for complex health economic evaluations.
    • The choice of model should align with the specific characteristics of the health program being evaluated.