The Spanish five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) valuation study was the first to use the EuroQol Valuation Technology protocol, including composite time trade-off (C-TTO) and discrete choice experiments (DCE). In this study, its investigators noticed that some interviewers did not fully explain the C-TTO task to respondents. Evidence from a follow-up study in 2014 confirmed that when interviewers followed the protocol, the distribution of C-TTO responses widened. To handle the data quality issues in the C-TTO responses by estimating a hybrid interval regression model to produce a Spanish EQ-5D-5L value set. Four different models were tested. Model 0 integrated C-TTO and DCE responses in a hybrid model and models 1 to 3 altered the interpretation of the C-TTO responses: model 1 allowed for censoring of the C-TTO responses, whereas model 2 incorporated interval responses and model 3 included the interviewer-specific protocol violations. For external validation, the predictions of the four models were compared with those of the follow-up study using the Lin's concordance correlation coefficient. This stepwise approach to modeling C-TTO and DCE responses improved the concordance between the valuation and follow-up studies (concordance correlation coefficient: 0.948 [model 0], 0.958 [model 1], 0.952 [model 2], and 0.989 [model 3]). We recommend the estimates from model 3, because its hybrid interval regression model addresses the data quality issues found in the valuation study. Protocol violations may occur in any valuation study; handling them in the analysis can improve external validity. The resulting EQ-5D-5L value set (model 3) can be applied to inform Spanish health technology assessments.

Background. Reliably mapping from generic or diseasespecific health status measures into health state utilities would assist health economists. Existing studies mainly use ordinary least squares (OLS) regression equations to predict utility values for particular health states. The authors examine an alternative approach tomap between 2 generic health status instruments, the SF-12 and the EQ-5D. Methods. Multinomial logit regression is used to estimate the probability that a respondent will select a particular level of response to questions in the EQ-5D, using individual question responses and summary scores from the SF-12 as predictors. Monte Carlo simulation methods are used to generate predicted EQ-5D responses, and utility scores (tariffs) are then attached. Results are comparedwithanalternativeapproach based on direct mapping to utility scores using OLS. Data. The authors estimate equations using 12,967 adult survey responses-from the 2000 US Medical Expenditure Panel Survey. They report mean squared error (MSE) andmean absolute error (MAE) of their predicted utilitieswithin this sample, and out-of-sample using 13,304 adults from the 1996 Health Survey for England. Results. The authors obtain an in-sample and out-of-sample MSE of 0.03, compared with 0.02 for the OLS approach. Their MAE of 0.11 is similar to OLS results. The authors’ method predicts groupmean utility scores and differentiates between groups with or without known existing illness. Conclusions. The authors’ approach has higher MSE than the direct OLS approach but givesmore descriptive data on domains of health effects. Further outofsample prediction work will help test the validity of these methods.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Background: The EQ-5D instrument is the most widely used preference-based health-related quality of life questionnaire in cost-effectiveness analysis of health care technologies. Recently, a version called EQ-5D-5L with 5 levels on each dimension was developed. This manuscript explores the performance of a hybrid approach for the modeling of EQ-5D-5L valuation data. Methods: Two elicitation techniques, the composite time trade-off, and discrete choice experiments, were applied to a sample of the Spanish population (n=1000) using a computer-based questionnaire. The sampling process consisted of 2 stages: stratified sampling of geographic area, followed by systematic sampling in each area. A hybrid regression model combining composite time trade-off and discrete choice data was used to estimate the potential value sets using main effects as starting point. The comparison between the models was performed using the criteria of logical consistency, goodness of fit, and parsimony. Results: Twenty-seven participants from the 1000 were removed following the exclusion criteria. The best-fitted model included 2 significant interaction terms but resulted in marginal improvements in model fit compared to the main effects model. We therefore selected the model results with main effects as a potential value set for this methodological study, based on the parsimony criteria. The results showed that the main effects hybrid model was consistent, with a range of utility values between 1 and −0.224. Conclusion: This paper shows the feasibility of using a hybrid approach to estimate a value set for EQ-5D-5L valuation data.

Background. Mapping disease-specific instruments into generic health outcomes or utility values is an expanding field of interest in health economics. This article constructs an algorithm to translate the modified Rankin scale (mRS) into EQ-5D utility values. Methods. mRS and EQ-5D information was derived from stroke or transient ischemic attack (TIA) patients identified as part of the Oxford Vascular study (OXVASC). Ordinary least squares (OLS) regression was used to predict UK EQ-5D tariffs from mRS scores. An alternative method, using multinomial logistic regression with a Monte Carlo simulation approach (MLogit) to predict responses to each EQ-5D question, was also explored. The performance of the models was compared according to the magnitude of their predicted-to-actual mean EQ-5D tariff difference, their mean absolute and mean squared errors (MAE and MSE), and associated 95% confidence intervals (CIs). Out-of-sample validation was carried out in a subset of coronary disease and peripheral vascular disease (PVD) patients also identified as part of OXVASC but not used in the original estimation. Results. The OLS and MLogit yielded similar MAE and MSE in the internal and external validation data sets. Both approaches also underestimated the uncertainty around the actual mean EQ-5D tariff producing tighter 95% CIs in both data sets. Conclusions. The choice of algorithm will be dependent on the study aim. Individuals outside the United Kingdom may find it more useful to use the multinomial results, which can be used with different country-specific tariff valuations. However, these algorithms should not replace prospective collection of utility data.