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Updated: Jun 23, 2025

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Identifying target populations to align with decision-makers' needs.

Jennifer L Lund1, Anthony A Matthews2

  • 1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.

American Journal of Epidemiology
|June 19, 2024
PubMed
Summary
This summary is machine-generated.

Randomized trials provide average treatment effects, but decision-makers need evidence tailored to specific populations. Researchers should align trial design with decision-maker needs for relevant real-world data and analysis.

Keywords:
causal inferencedecision-makerstarget populations

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Area of Science:

  • Clinical Trials
  • Pharmacoepidemiology
  • Health Services Research

Background:

  • Randomized trials (RCTs) assess average treatment effects in enrolled participants.
  • Decision-makers require evidence applicable to their specific target populations, which often differ from RCT populations.

Purpose of the Study:

  • To guide researchers in aligning evidence generation with decision-maker needs.
  • To identify decision-maker groups and their target populations for specific health interventions.
  • To determine when RCTs alone suffice versus when real-world data is needed.

Main Methods:

  • Outlined 5 key decision-maker groups: policymakers, payers, purchasers, providers, and patients.
  • Specified target populations for beta-blocker effectiveness post-myocardial infarction with preserved ejection fraction.
  • Summarized scenarios where RCT results apply and suggested analytic approaches.

Main Results:

  • RCT generalizability varies depending on the alignment between trial and target populations.
  • Real-world data and complementary analyses are often necessary to inform specific decision-maker needs.
  • A structured approach is needed to bridge the gap between trial evidence and policy application.

Conclusions:

  • Researchers must proactively identify decision-makers and their target populations early in the research process.
  • Tailoring evidence generation to specific decision-maker contexts enhances the utility of research findings.
  • Integrating RCTs with real-world data analysis is crucial for informing diverse healthcare decisions.