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Protocol for a systematic review and meta-analysis of minimal important differences for generic multiattribute utility instruments

Citation

Henson, GJ and Taylor, BV and van der Mei, I and Claflin, SB and Simpson-Yap, S and Palmer, AJ and Xia, Q and Antony, B and Singh, Ambrish and Campbell, JA, Protocol for a systematic review and meta-analysis of minimal important differences for generic multiattribute utility instruments, BMJ Open, 12, (10) Article e062703. ISSN 2044-6055 (2022) [Refereed Article]


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The Author(s) 2022. This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License (https://creativecommons.org/licenses/by-nc/4.0/). This license allows re-users to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

Official URL: https://bmjopen.bmj.com/content/12/10/e062703

DOI: doi:10.1136/bmjopen-2022-062703

Abstract

Introduction:Generic multiattribute utility instruments (MAUIs) are efficient tools for determining and enumerating health-related quality of life. MAUIs accomplish this by generating health state utilities (HSUs) via algorithms. Minimal important differences (MIDs) assist with the interpretation of HSUs by estimating minimum changes that are clinically significant. The overall goal of the proposed systematic review and meta-analysis is the development of comprehensive guidelines for MID estimation.

Methods and analysis: This protocol defines a systematic review and meta-analysis of MIDs for generic MAUIs. The proposed research will involve a comprehensive investigation of 10 databases (EconLit, IDEAs database, INAHTA database, Medline, PsycINFO, Embase, Emcare, JBIEBP and CINAHL) from 1 June 2022 to 7 June 2022, and will be performed and reported in accordance with several validated guidelines, principally the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The quality of papers, considered for inclusion in the review, will be appraised using the COnsensus-based Standards for the selection of health Measurement INstruments, inter alia.

Narrative analysis will involve identifying the characteristics of MIDs including methods of calculation, sources of heterogeneity, and validation. Meta-analysis will also be conducted. The descriptive element of meta-analysis will involve the generation of I2 statistics and Galbraith plots of MID heterogeneity. Together with narrative analysis, this will allow sources of MID heterogeniety to be identified. A multilevel mixed model, estimated via restricted maximum likelihood estimation, will be constructed for the purposes of meta-regression. Meta-regression will attempt to enumerate the effects of sources of heterogeneity on MID estimates. Meta-analysis will be concluded with pooling of MIDs via a linear random-effects model.

Ethics and dissemination:Ethics approval is not required for this review, as it will aggregate data from published literature. Methods of dissemination will include publication in a peer-reviewed journal, as well as presentation at conferences and seminars.

Item Details

Item Type:Refereed Article
Keywords:health economics, quality of life, multi-attribute utility instrument, minimal important difference
Research Division:Economics
Research Group:Applied economics
Research Field:Health economics
Objective Division:Health
Objective Group:Evaluation of health and support services
Objective Field:Health policy evaluation
UTAS Author:Henson, GJ (Mr Glen Henson)
UTAS Author:Taylor, BV (Professor Bruce Taylor)
UTAS Author:van der Mei, I (Professor Ingrid van der Mei)
UTAS Author:Claflin, SB (Dr Suzi Claflin)
UTAS Author:Palmer, AJ (Professor Andrew Palmer)
UTAS Author:Xia, Q (Miss Qing Xia)
UTAS Author:Antony, B (Dr Benny Eathakkattu Antony)
UTAS Author:Singh, Ambrish (Mr Ambrish Singh)
UTAS Author:Campbell, JA (Dr Julie Campbell)
ID Code:154068
Year Published:2022
Deposited By:Menzies Institute for Medical Research
Deposited On:2022-10-26
Last Modified:2022-11-18
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