Heterogeneous uncertainties in cholesterol management

Yakov Ben-Haim, Clifford C. Dacso, Jonathon Carrasco, Nithin Rajan

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Physicians use clinical guidelines to inform judgment about therapy. Clinical guidelines do not address three important uncertainties: (1) uncertain relevance of tested populations to the individual patient, (2) the patient's uncertain preferences among possible outcomes, and (3) uncertain subjective and financial costs of intervention. Unreliable probabilistic information is available for some of these uncertainties; no probabilities are available for others. The uncertainties are in the values of parameters and in the shapes of functions. We explore the usefulness of info-gap decision theory in patient-physician decision making in managing cholesterol level using clinical guidelines. Info-gap models of uncertainty provide versatile tools for quantifying diverse uncertainties. Info-gap theory provides two decision functions for evaluating alternative therapies. The robustness function assesses the confidence-in light of uncertainties-in attaining acceptable outcomes. The opportuneness function assesses the potential for better-than-anticipated outcomes. Both functions assist in forming preferences among alternatives. Hypothetical case studies demonstrate that decisions using the guidelines and based on best estimates of the expected utility are sometimes, but not always, consistent with robustness and opportuneness analyses. The info-gap analysis provides guidance when judgment suggests that a deviation from the guidelines would be productive. Finally, analysis of uncertainty can help resolve ambiguous situations.

Original languageEnglish (US)
Pages (from-to)1046-1065
Number of pages20
JournalInternational Journal of Approximate Reasoning
Volume50
Issue number7
DOIs
StatePublished - Jul 1 2009

Keywords

  • Cholesterol management
  • Clinical guidelines
  • Info-gap decision theory
  • Judgment under uncertainty
  • Patient satisfaction

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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