Mathematical models in decision analysis.


Journal Article (Review)

Decision analysis offers powerful techniques to understand and evaluate uncertain clinical situations better. Decision analytic models are appearing with increasing frequency in health policy planning, clinical information and decision-support computer systems, evaluations of clinical pathways, development of clinical practice or utilization review guidelines, and epidemiologic research. This article describes the structure, application, and limitations of the more popular decision analytic methods, including decision trees, Markov models, Monte Carlo simulation, survival and hazard functions, fuzzy logic, and sensitivity analysis. Understanding the nature of these methods will help readers to assess better the appropriateness of their use in published reports.

Full Text

Cited Authors

  • Tom, E; Schulman, KA

Published Date

  • January 1997

Published In

Volume / Issue

  • 18 / 1

Start / End Page

  • 65 - 73

PubMed ID

  • 9013249

Pubmed Central ID

  • 9013249

Electronic International Standard Serial Number (EISSN)

  • 1559-6834

International Standard Serial Number (ISSN)

  • 0899-823X

Digital Object Identifier (DOI)

  • 10.1086/647503


  • eng