SynthesisThe European journal of health economics : HEPAC : health economics in prevention and care2025
A systematic review of minimum important changes for generic multi-attribute utility instruments and recommendations for their estimation.
Synthesis in The European journal of health economics : HEPAC : health economics in prevention and care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionMinimum 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.
methodsWe 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.
resultsThe 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.
conclusionsDeficiencies 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.
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