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A guide to handling missing data in cost-effectiveness analysis conducted within randomised controlled trials.

Rita Faria1, Manuel Gomes, David Epstein

  • 1Centre for Health Economics, University of York, Heslington, York, YO10 5DD, UK, rita.nevesdefaria@york.ac.uk.

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Summary

Handling missing data in cost-effectiveness analysis (CEA) is crucial for accurate results. This guide offers a principled approach for within-trial CEAs, ensuring interventions are evaluated as good value for money.

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Area of Science:

  • Health Economics
  • Biostatistics
  • Clinical Trials

Background:

  • Missing data frequently complicate cost-effectiveness analysis (CEA) within randomized controlled trials.
  • Inadequate handling of missing data can yield misleading economic evaluations and impact value-for-money decisions.
  • Robust methods are essential for reliable within-trial CEA.

Purpose of the Study:

  • To provide practical guidance on managing missing data in within-trial cost-effectiveness analyses.
  • To outline a principled approach for handling missing data, ensuring accurate economic evaluations.
  • To enhance the reliability of decisions regarding the value for money of health interventions.

Main Methods:

  • Adopting a principled approach based on plausible assumptions about the missing data mechanism (e.g., missing at random).
  • Selecting base-case analysis methods aligned with the assumed missing data mechanism.
  • Conducting sensitivity analyses to assess the impact of different missing data assumptions on results.

Main Results:

  • A three-stage implementation process is detailed: descriptive analysis for mechanism assumption, method selection based on assumptions, and sensitivity analysis techniques.
  • A case study demonstrates practical application, including software code for handling missing data in CEA.
  • The approach facilitates informed decision-making by clarifying the impact of missing data.

Conclusions:

  • Implementing a principled approach to missing data handling is vital for credible within-trial CEAs.
  • Recommendations for practice and future research directions are provided to improve economic evaluations.
  • Accurate handling of missing data ensures reliable assessments of intervention cost-effectiveness.