Self-Valuation and Societal Valuations of Health State Differ With Disease Severity in Chronic and Disabling Conditions

Abstract

This study provides evidence that EQ-5D population valuation estimates of treatment benefit for people with disabling and chronic conditions may well be inaccurate representations of the degree of change actually experienced by the individual with the condition. The varying magnitude of difference between the 2 forms of valuation has important implications for interpreting shifts in health status valuation following interventions for these populations.

Does the correspondence between EQ-5D health state description and VAS score vary by medical condition?

“…The average valuations of hypothetical states made by large numbers of individuals currently in no particular actual state have become, in effect, social health state utilities. It was observed at an early stage of the EQ-5D’s development that when respondents actually existed in the health state which they had been asked to value, their valuations differed significantly from those for whom the state was hypothetical [24,25]. The observed discrepancies between patient and public values stimulated debate over both whose opinions were the most appropriate for HTA purposes [26] and the validity of using the VAS to elicit social preferences [27].…”

Measures of disability: Arthritis Impact Measurement Scales 2 (AIMS2), Arthritis Impact Measurement Scales 2‐Short Form (AIMS2‐SF), The Organization for Economic Cooperation and Development (OECD) Long‐Term Disability (LTD) Questionnaire, EQ‐5D, World Health Organization Disability Assessment Schedule II (WHODASII), Late‐Life Function and Disability Instrument (LLFDI), and Late‐Life Function and Disability Instrument‐Abbreviated Version (LLFDI‐Abbreviated)

“…VAS scores range from 0 (worst imaginable health state) to 100 (best imaginable health state). Researchers have noted that, depending on the item weights and algorithms, widely differing QALY gains and cost‐effectiveness estimations may result (84, 85–94). Where possible, researchers should use the algorithms specific to their country by consulting the EuroQol web site.…”

Comparing EQ-5D Scores for Comorbid Health Conditions Estimated Using 5 Different Methods

“…7 Specific concerns in the literature include the use of 1 generic measure over another, generic versus condition specific, 8 time trade off (TTO) versus other valuation techniques such as standard gamble 9 and general population versus patient values. 10 Differences in these features have been shown to be important in the way they influence HSUVs and hence the results of cost per QALY analyses. However, there has been far less space devoted in the literature to the use of HSUVs in populating decision analytic model to generate cost-effectiveness ratios.…”