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A Systematic Review of the Methodologies and Modelling Approaches Used to Generate International EQ-5D-5L Value Sets
Donna Rowen1, Clara Mukuria2, Emily McDool2
1School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK. d.rowen@sheffield.ac.uk.
Background:
The international protocol for valuing EQ-5D-5L focuses upon prescribed preference elicitation methods and design. However, there are no recommendations around sampling, recruitment, data analysis or modelling to generate the EQ-5D-5L value set. This review examines methods used to generate international EQ-5D-5L values sets, across sampling, recruitment, data analysis, modelling, assessing model performance and selection of the recommended value set.
Methods:
All published EQ-5D-5L value sets were identified by a systematic search and confirmed by the EuroQol Group. Data were extracted to assess sampling, recruitment, preference elicitation techniques and design, data analysis, modelling, assessing model performance, and vale set selection. These are summarised in tables.
Results:
The review included 29 studies with 27 value sets generated using time-trade-off (TTO) data (n = 10) only or using a hybrid model that combines TTO and discrete choice experiment data (n = 17). TTO data were most commonly estimated using a heteroscedastic Tobit model with censoring at - 1, and the hybrid model using a specially created program. Model performance was generally assessed using goodness of fit, logical consistency and significance of coefficients, suitability of the model for the data characteristics and parsimony, though not all selected models account for the specific characteristics of the data.
Discussion:
Different assessments of model performance and reasoning are provided for the selection of the recommended value set for a country. This raises the question of valid criteria for selecting a recommended value set and whether this should rely upon researchers' recommendations when value sets are often used to inform public policy.
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