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

Abstract

The additive and minimum methods performed very poorly in our data. Although the simple linear model gave the most accurate results, the model requires validating in external data obtained from the EQ-5D and other preference-based measures. Based on the current evidence base, we would recommend the multiplicative method is used together with a range of univariate sensitivity analyses.

Estimating Health State Utility Values for Comorbid Health Conditions Using SF-6D Data

“…Our results may not generalize to all other preference-based instruments and datasets, and the observed hierarchy of the five methods is equivalent to that reported in an article describing similar research on EQ-5D data [23]. One area where additional research would be particularly informative would be in evaluating the different techniques on subgroups of combinations of specific health conditions.…”

Using Health State Utility Values in Models Exploring the Cost-Effectiveness of Health Technologies

“…For example, although the minimum outperformed the additive and multiplicative methods in one study [22], the data estimated covered a very narrow range (0.611-0.742) and two of the other studies demonstrated that the magnitude of the errors for the minimum method increased substantially when estimating lower utility values [12,17]; thus, the findings of the first study cannot be generalized beyond their data set without additional research. On a similar theme, the authors noted that the use of mean errors when comparing methods was insufficient because these masked bias in the errors [12,17]. Finally, the accuracy of the method used was influenced by the value assigned to normal health, and the errors in estimated values increased when full health (EQ-5D questionnaire ϭ 1) was used to determine the decrement associated with the single health conditions.…”

“…These assign a constant absolute decrement, a constant relative decrement, and no additional decrement over that observed for the condition with the lowest HSUV, respectively. A variation of the minimum method (the adjusted decrement estimator) has been suggested, and linear models incorporating terms to represent the three traditional methods (additive, multiplicative, and minimum) and obtained using ordinary least square regressions have been presented [12,[15][16][17]. Specific details of the five methods are provided online.…”

“…The remaining eight used HSUVs obtained by using generic questionnaires (EQ-5D questionnaire ϭ 4 [15,17,21,22], six-dimensional health state short form [derived from short form 36 health survey] ϭ 3 [12,23,24], health utilities index 3 ϭ 1 [25]) collected during surveys (range 5,224 -131,535 respondents). Two of the studies evaluated just one method, and the others compared results generated by using two, three, or more methods.…”

Accounting for multimorbidity can affect the estimation of the Burden of Disease: a comparison of approaches

“…This so-called adjusted decrement estimator method is a variation on the maximum limit method ([11, 13]). However, many studies [13, 25, 26] use utility measures such as EQ-5D scores or Health Utilities Index Mark 3 (HUI3) instead of Disability Weights, resulting in profound differences. Haagsma et al [12] compared three comorbidity approaches in patients with temporary injury consequences as well as comorbid chronic conditions with non-trivial health impacts.…”