The need for evolution in healthcare decision modeling

Robert C. Lee*, Cam Donaldson, Linda S. Cook

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

STATEMENT OF PROBLEM. Many Healthcare decisions are difficult because they are complex and have important consequences such as the impact on survival or quality-of-life of individuals and on allocation of limited resources. The present state-of-the-art in healthcare decision modeling is often inadequate to properly assess these decisions. METHODS. Based on a literature search and the experience of the authors, typical methodologies used in healthcare decision analysis modeling are explored and compared with methods used in other practices. An example of hormonal therapy decisions is used. RESULTS. Useful methods that have been developed in other fields are presented. These include methods targeted toward appropriate assessment and representation of the complexity of decisions, assessment of uncertainty, use of nonexpected value decision analysis, and use of multi-attribute decision criteria. CONCLUSION. The state-of-the-art in healthcare decision modeling can be improved through learning from other practices.

Original languageEnglish
Pages (from-to)1024-1033
Number of pages10
JournalMedical Care
Volume41
Issue number9
DOIs
Publication statusPublished - Sept 2003
Externally publishedYes

Keywords

  • Decision analysis
  • Hormonal therapy
  • Uncertainty analysis
  • Utility analysis
  • Women's health

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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