EQ-5D and Health-Related Quality of Life

Versteegh MM, Vermeulen KM, Evers SMAA, de Wit GA, Prenger R, Stolk EA
Value in Health. 2016;19(4):343-352.

BACKGROUND

In 2009, a new version of the EuroQol five-dimensional questionnaire (EQ-5D) was introduced with five rather than three answer levels per dimension. This instrument is known as the EQ-5D-5L. To make the EQ-5D-5L suitable for use in economic evaluations, societal values need to be attached to all 3125 health states.

OBJECTIVES

To derive a Dutch tariff for the EQ-5D-5L.

METHODS

Health state values were elicited during face-to-face interviews in a general population sample stratified for age, sex, and education, using composite time trade-off (cTTO) and a discrete choice experiment (DCE). Data were modeled using ordinary least squares and tobit regression (for cTTO) and a multinomial conditional logit model (for DCE). Model performance was evaluated on the basis of internal consistency, parsimony, goodness of fit, handling of left-censored values, and theoretical considerations.

RESULTS

A representative sample (N = 1003) of the Dutch population participated in the valuation study. Data of 979 and 992 respondents were included in the analysis of the cTTO and the DCE, respectively. The cTTO data were left-censored at −1. The tobit model was considered the preferred model for the tariff on the basis of its handling of the censored nature of the data, which was confirmed through comparison with the DCE data. The predicted values for the EQ-5D-5L ranged from −0.446 to 1.

CONCLUSIONS

This study established a Dutch tariff for the EQ-5D-5L on the basis of cTTO. The values represent the preferences of the Dutch population. The tariff can be used to estimate the impact of health care interventions on quality of life, for example, in context of economic evaluations.

Luo N, Liu G, Li M, Guan H, Jin X, Rand-Hendriksen K.
Value in Health. 2017;20(4):662-669.

OBJECTIVES

To estimate a five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) value set for China using the health preferences of residents living in the urban areas of the country.

METHODS

The values of a subset of the EQ-5D-5L–defined health states (n = 86) were elicited using the time trade-off (TTO) technique from a sample of urban residents (n = 1271) recruited from five Chinese cities. In computer-assisted personal interviews, participants each completed 10 TTO tasks. Two additive and two multiplicative regression models were evaluated for their performance in describing the relationship between TTO values and health state characteristics using a cross-validation approach. Final values were generated using the best-performed model and a rescaling method.

RESULTS

The 8- and 9-parameter multiplicative models unanimously outperformed the 20-parameter additive model using a random or fixed intercept in predicting values for out-of-sample health states in the cross-validation analysis and their coefficients were estimated with lower standard errors. The prediction accuracies of the two multiplicative models measured by the mean absolute error and the intraclass correlation coefficient were very similar, thus favoring the more parsimonious model.

CONCLUSIONS

The 8-parameter multiplicative model performed the best in the study and therefore was used to generate the EQ-5D-5L value set for China. We recommend using rescaled values whereby 1 represents the value of instrument-defined full health in economic evaluation of health technologies in China whenever the EQ-5D-5L data are available.

Shiroiwa T, Ikeda S, Noto S, Igarashi A, Fukuda T, Saito S, Shimozuma K.
Value in Health. 2016;19(5):648-654.

BACKGROUND

The valuation study of the five-level version of the EuroQol five-dimensional questionnaire (EQ-5D-5L) involved composite time trade-off (cTTO) and a discrete choice experiment (DCE). The DCE scores must be anchored to the quality-of-life scale from 0 (death) to 1 (full health). Nevertheless, the characteristics of the statistical methods used for converting the EQ-5D-5L DCE results by using TTO information are not yet clearly known.

OBJECTIVES

To present the Japanese DCE value set of the EQ-5D-5L and compare three methods for converting latent DCE values.

METHODS

The survey sampled the general population at five locations in Japan. 1098 respondents were stratified by age and sex. To obtain and compare the value sets of the EQ-5D-5L, the cTTO and DCE data were analyzed by a linear mixed model and conditional logit, respectively. The DCE scores were converted to the quality-of-life scale by anchoring to the worst state using cTTO, mapping DCE onto cTTO, and a hybrid model.

RESULTS

The data from 1026 respondents were analyzed. All the coefficients in the cTTO and DCE value sets were consistent throughout all the analyses. Compared with the cTTO algorithm, the mapping and hybrid methods yielded very similar scoring coefficients. The hybrid model results, however, produced a lower root mean square error and fewer health states with errors exceeding 0.05 than did the other models. The DCE anchored to the worst state overestimated the cTTO scores of almost all the health states.

CONCLUSIONS

Japanese value sets based on DCE were demonstrated. On comparing the observed cTTO scores, we found that the hybrid model was slightly superior to the simpler methods, including the TTO model.

Ramos-Goñi JM, Oppe M, Slaap B, Busschbach JJV, Stolk E.
Value in Health. 2017;20(3):466-473.

BACKGROUND

The values of the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) are elicited using composite time trade-off and discrete choice experiments. Unfortunately, data quality issues and interviewer effects were observed in the first few EQ-5D-5L valuation studies. To prevent these issues from occurring in later studies, the EuroQol Group established a cyclic quality control (QC) process.

OBJECTIVES

To describe this QC process and show its impact on data quality.

METHODS

A newly developed QC tool provided information about protocol compliance, interviewer effects, and mean values by health state severity. In a cyclic process, this information is initially used to evaluate whether new interviewers meet minimal quality requirements and later to provide feedback about how their performance may be improved. To investigate the impact of this cyclic process, we compared the quality of the data in Dutch and Spanish valuation studies that did not have this QC process with that in the follow-up studies in the same countries that used the QC process. Data quality was measured using protocol violations, variability between interviewers, the proportion of inconsistent responders, and clustering of composite time trade-off values.

RESULTS

In Spain, protocol violations were reduced from 87% in the valuation study to 5% in the follow-up study and in the Netherlands from 20% to 8%. In both countries, interviewers performed more homogeneously in the follow-up studies. The number of inconsistent respondents was reduced by 23.2% in Spain and 23.6% in the Netherlands. Values were less clustered in the follow-up studies.

CONCLUSIONS

The implementation of a strict QC process in EQ-5D-5L valuation studies increases interviewer protocol compliance and promotes data quality.

Hernandez Alava M, Wailoo A, Grimm S, Pudney S, Gomes M, Sadique Z, Meads D, O’Dwyer J, Barton G, Irvine L.
Value in Health. 2018;21(1):49-56.

OBJECTIVES

To model the relationship between the three-level (3L) and the five-level (5L) EuroQol five-dimensional questionnaire and examine how differences have an impact on cost effectiveness in case studies.

METHODS

We used two data sets that included the 3L and 5L versions from the same respondents. The EuroQol Group data set (n = 3551) included patients with different diseases and a healthy cohort. The National Data Bank data set included patients with rheumatoid disease (n = 5205). We estimated a system of ordinal regressions in each data set using copula models to link responses of the 3L instrument to those of the 5L instrument and its UK tariff, and vice versa. Results were applied to nine cost-effectiveness studies.

RESULTS

Best-fitting models differed between the EuroQol Group and the National Data Bank data sets in terms of the explanatory variables, copulas, and coefficients. In both cases, the coefficients of the covariates and latent factors between the 3L and the 5L instruments were significantly different, indicating that moving between instruments is not simply a uniform re-alignment of the response levels for most dimensions. In the case studies, moving from the 3L to the 5L caused a decrease of up to 87% in incremental quality-adjusted life-years gained from effective technologies in almost all cases. Incremental cost-effectiveness ratios increased, often substantially. Conversely, one technology with a significant mortality gain saw increased incremental quality-adjusted life-years.

CONCLUSIONS

The 5L shifts mean utility scores up the utility scale toward full health and compresses them into a smaller range, compared with the 3L. Improvements in quality of life are valued less using the 5L than using the 3L. The 3L and the 5L can produce substantially different estimates of cost effectiveness. There is no simple proportional adjustment that can be made to reconcile these differences.