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Protocol for a systematic review and meta-analysis of minimal important differences for generic multiattribute
Glen James Henson1, Bruce V Taylor2, Ingrid van der Mei2
1Health Economics, Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.
BMJ Open
|October 25, 2022
Summary
This study proposes guidelines for estimating minimal important differences (MIDs) for health-related quality of life measures. It aims to improve the interpretation of health state utilities (HSUs) from generic multiattribute utility instruments (MAUIs).
Area of Science:
- Health Economics
- Psychometrics
- Biostatistics
Background:
- Generic multiattribute utility instruments (MAUIs) generate health state utilities (HSUs) to assess health-related quality of life.
- Minimal important differences (MIDs) are crucial for interpreting the clinical significance of HSU changes.
- Standardized guidelines for MID estimation are needed to enhance the reliability of MAUI interpretations.
Purpose of the Study:
- To systematically review and meta-analyze existing methods for estimating MIDs for generic MAUIs.
- To develop comprehensive guidelines for robust MID estimation.
- To improve the clinical interpretation of health-related quality of life data.
Main Methods:
- Systematic review and meta-analysis of MIDs for generic MAUIs.
- Comprehensive search of 10 databases.
- Quality appraisal using COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN).
- Narrative analysis of MID calculation methods and heterogeneity.
- Meta-regression to identify sources of heterogeneity.
- Pooling of MIDs using a linear random-effects model.
Main Results:
- The study protocol outlines a rigorous methodology for synthesizing MID data.
- Identification of sources of heterogeneity in MID estimates is a key objective.
- Meta-regression will quantify the impact of heterogeneity on MID values.
Conclusions:
- This systematic review and meta-analysis will provide evidence-based guidelines for MID estimation.
- The findings will enhance the clinical utility and interpretation of generic MAUIs.
- Standardized MID estimation will improve the consistency of health-related quality of life assessments.
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