However, identifying utilities associated with major clinical events directly from patients rating their own health would be impractical for two reasons.
A key advantage of vignette-based utility assessment is that it can be used to identify utilities of specific factors that may be difficult to isolate in a patient sample.
Given that these treatments vary widely in terms of treatment burden and adverse event profile, it may be important to identify utilities associated with these attributes so that they can be represented accurately in cost-utility models comparing treatments.
The importance of such a feature for valid exposure assessment in epidemiologic studies is underscored by recent research to develop methods to identify utilities that have low spatial variability of DBP (Hinckley et al. 2005a).
For situations when the EQ-5D is unlikely to be relevant or sensitive, there are methods for identifying utilities associated with specific diseases or treatments, such as condition-specific preference-based measures [ 27] and studies in which respondents value health state descriptions (i.e., vignettes) designed to represent specific relevant characteristics.
While the 2013 NICE guide suggests that content validity of the EQ-5D should be considered when deciding whether the instrument is appropriate for identifying utilities of a specific patient population, the guide does not discuss the level of content validity that should be considered acceptable.
If the missing content truly appears to be important, the qualitative findings can be used as justification for considering the EQ-5D to be "inappropriate" for the specific patient group and using another method to identify utilities or to measure the health status of a specific patient group.
In this paper, we introduce a quantitative method for identifying utility thresholds.
To assist resource managers and policymakers in developing EBM decision criteria, we introduce a quantitative, transferable method for identifying utility thresholds.
The development of these health states is described further in a direct preference elicitation study designed to identify utility values attributable to each health state.
A more rigorous approach to obtain a single overall summary would be to identify utility weights for the different outcomes to provide a weighted average.
