Estimating health state utility values for joint health conditions: a conceptual review and critique of the current evidence

Abstract

Background: Analysts frequently estimate the health state utility values (HSUVs) for joint health conditions (JHCs) using data from cohorts with single health conditions. The methods can produce very different results, and there is currently no consensus on the most appropriate technique.

Objective: To conduct a detailed critical review of existing empirical literature to gain an understanding of the reasons for differences in results and identify where uncertainty remains that may be addressed by further research.

Results: Of the 11 studies identified, 10 assessed the additive method, 10 the multiplicative method, 7 the minimum method, and 3 the combination model. Two studies evaluated just 1 of the techniques, whereas the others compared results generated using 2 or more. The range of actual HSUVs can influence general findings, and methods are sometimes compared using descriptive statistics that may not be appropriate for assessing predictive ability. None of the methods gave consistently accurate results across the full range of possible HSUVs, and the values assigned to normal health influence the accuracy of the methods.

Conclusions: Within the limitations of the current evidence base, we would advocate the multiplicative method, conditional on adjustment for baseline utility, as the preferred technique to estimate HSUVs for JHCs when using mean values obtained from cohorts with single conditions. We would recommend that a range of sensitivity analyses be performed to explore the effect on results when using the estimated HSUVs in economic models. Although the linear models appeared to give more accurate results in the studies we reviewed, these models require validating in external data before they can be recommended.