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BACKGROUND: 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. OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Original publication

DOI

10.1016/j.jval.2017.10.023

Type

Journal article

Journal

Value Health

Publication Date

05/2018

Volume

21

Pages

596 - 604

Keywords

economic, health status index, life valuation, quality of life, Choice Behavior, Data Accuracy, Health Status, Humans, Language, Models, Theoretical, Quality of Life, Regression Analysis, Surveys and Questionnaires, Technology Assessment, Biomedical