A systematic review of minimum important changes for generic multi-attribute utility instruments and recommendations for their estimation
Glen J. Henson,
Ingrid Mei,
Bruce V. Taylor,
Paul Scuffham,
Gang Chen and
Julie A. Campbell ()
Additional contact information
Glen J. Henson: Menzies Institute for Medical Research (University of Tasmania)
Ingrid Mei: Menzies Institute for Medical Research (University of Tasmania)
Bruce V. Taylor: Menzies Institute for Medical Research (University of Tasmania)
Paul Scuffham: Menzies Health Institute Queensland (Griffith University)
Gang Chen: University of Melbourne
Julie A. Campbell: Menzies Institute for Medical Research (University of Tasmania)
The European Journal of Health Economics, 2025, vol. 26, issue 8, No 5, 1383-1399
Abstract:
Abstract Introduction Minimum important changes (MICs) represent thresholds for clinically meaningful change. Multi-attribute utility instruments (MAUIs) generate health state utilities (holistic measures of health-related quality of life). No systematic review of MICs specifically for MAUIs has been conducted. In addition, no guidelines for estimating MICs for MAUIs have been proposed. We aimed to correct these evidence gaps by producing guidelines contextualised by a systematic review. Methods We searched ten databases for relevant records using various search terms. Extracted data were analysed narratively and descriptively. The presence of key reporting items (relating to precision, sensitivity, and concurrent validity) was also evaluated. Guidelines for MIC estimation were informed by the broader MIC literature and contextualised using study results. Results The review identified 5035 non-duplicate records, with 68 entering the study. 282 unique, anchor-based MICs were extracted. Of these MICs, 119 (42.20%) pertained to the EQ-5D-3L, 82 (29.08%) to the EQ-5D-5L, and 50 (17.73%) to the SF-6D.v1. The most common anchor-based method used to estimate MICs (107, 37.94%) involved taking the mean change score for a group considered to have experienced a MIC. Distribution-based methods were also common, appearing in 31 (45.59%) of the included studies. The inclusion of key reporting items was generally deficient. Conclusions Deficiencies in reporting and diverse estimation methods raise concerns regarding the extant MAUI MIC literature. Researchers should exercise caution when using existing MAUI MICs. Recommendations presented in our study may assist researchers in effectively estimating MICs for use in health economics.
Keywords: Minimum important changes; Multi-attribute utility instruments; Health state utility; Health-related quality of life; Systematic review; Mathematic methods (search for similar items in EconPapers)
JEL-codes: C69 I18 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10198-025-01778-3
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