Models based on value and probability in health improve shared decision making

J Eval Clin Pract. 2008 Oct;14(5):714-7. doi: 10.1111/j.1365-2753.2007.00931.x.

Abstract

Rationale, aims and objectives: Diagnostic reasoning and treatment decisions are a key competence of doctors. A model based on values and probability provides a conceptual framework for clinical judgments and decisions, and also facilitates the integration of clinical and biomedical knowledge into a diagnostic decision.

Method: Both value and probability are usually estimated values in clinical decision making. Therefore, model assumptions and parameter estimates should be continually assessed against data, and models should be revised accordingly. Introducing parameter estimates for both value and probability, which usually pertain in clinical work, gives the model labelled subjective expected utility. Estimated values and probabilities are involved sequentially for every step in the decision-making process.

Results: Introducing decision-analytic modelling gives a more complete picture of variables that influence the decisions carried out by the doctor and the patient.

Conclusion: A model revised for perceived values and probabilities by both the doctor and the patient could be used as a tool for engaging in a mutual and shared decision-making process in clinical work.

Publication types

  • Case Reports
  • Review

MeSH terms

  • Adult
  • Arthritis, Rheumatoid / diagnosis
  • Arthritis, Rheumatoid / psychology
  • Arthritis, Rheumatoid / therapy
  • Attitude of Health Personnel*
  • Attitude to Health*
  • Choice Behavior
  • Clinical Competence
  • Cooperative Behavior
  • Decision Support Techniques*
  • Evidence-Based Medicine / methods*
  • Female
  • Humans
  • Judgment
  • Male
  • Middle Aged
  • Myocardial Infarction / diagnosis
  • Myocardial Infarction / psychology
  • Myocardial Infarction / therapy
  • Patient Participation* / methods
  • Patient Participation* / psychology
  • Patient Selection
  • Physician-Patient Relations
  • Predictive Value of Tests
  • Probability*