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Related Experiment Videos

Measuring improved patient choice.

M Holmes-Rovner1, D R Rovner

  • 1Department of Medicine, College of Human Medicine, Michigan State University, USA.

Journal of Evaluation in Clinical Practice
|November 18, 2000
PubMed
Summary
This summary is machine-generated.

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Patient decision support (PDS) tools aid evidence-based choices. This paper suggests subjective expected utility (SEU) is the optimal primary endpoint for PDS trials, measuring decision consistency.

Area of Science:

  • Health Informatics
  • Decision Analysis
  • Behavioral Science

Background:

  • Patient decision support (PDS) tools enhance clinical encounters by facilitating evidence-based patient choices.
  • Current PDS trials utilize diverse outcome measures like knowledge, satisfaction, health status, and choice-value consistency.
  • There is a need for a standardized, theoretically robust primary endpoint for PDS efficacy trials.

Purpose of the Study:

  • To propose 'subjective expected utility' (SEU) as the optimal primary endpoint for evaluating patient decision support tools.
  • To explore the application of decision analysis within PDS tools for structuring evidence presentation and guiding decision-making.
  • To differentiate the utility of SEU versus expected utility (EU) based on trial objectives (decision consistency vs. population health status).

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Main Methods:

  • Review of existing literature on patient decision support tools and their efficacy outcome measures.
  • Description of how decision analysis can be integrated into PDS tools.
  • Theoretical argument for SEU as a primary endpoint in behavioral decision theory.

Main Results:

  • The paper posits that the correlation between SEU and patient decision is the most suitable primary endpoint for PDS trials.
  • Decision analysis can structure evidence presentation in PDS tools.
  • EU is suitable for PDS tools aiming to improve population health status, while SEU is better for assessing internal choice consistency.

Conclusions:

  • Subjective expected utility (SEU) offers a theoretically sound and empirically measurable primary endpoint for patient decision support tool trials.
  • Integrating decision analysis principles can enhance the design and effectiveness of PDS tools.
  • The choice of outcome measure (SEU vs. EU) should align with the specific objectives of PDS tool evaluation.