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A growing number of published articles report estimates from meta-analysis or meta-regression on health state utility values (HSUVs), with a view to providing input into decision-analytic models. Pooling HSUVs is problematic because of the fact that different valuation methods and different preference-based measures (PBMs) can generate different values on exactly the same clinical health state. Existing meta-analyses of HSUVs are characterised by high levels of heterogeneity, and meta-regressions have identified significant (and substantial) impacts arising from the elicitation method used. The use of meta-regression with few utility values and inclusion criteria that extend beyond the required utility value has not helped. There is the potential to explore greater use of mapping between different PBMs and valuation methods prior to data synthesis, which could support greater use of pooling values. Researchers wishing to populate decision-analytic models have a responsibility to incorporate all high-quality evidence available. In relation to HSUVs, greater understanding of the differences between different methods and greater consistency of methodology is required before this can be achieved.

Is Meta-Analysis for Utility Values Appropriate Given the Potential Impact Different Elicitation Methods Have on Values?