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Multinational evidence of the applicability and robustness of discrete choice modeling for deriving EQ-5D-5L health-state values.

Authors :
Krabbe PF
Devlin NJ
Stolk EA
Shah KK
Oppe M
van Hout B
Quik EH
Pickard AS
Xie F
Source :
Medical care [Med Care] 2014 Nov; Vol. 52 (11), pp. 935-43.
Publication Year :
2014

Abstract

Aims: To investigate the feasibility of discrete choice experiments for valuing EQ-5D-5L states using computer-based data collection, the consistency of the estimated regression coefficients produced after modeling the preference data, and to examine the similarity of the values derived across countries.<br />Methods: Data were collected in Canada, England, The Netherlands, and the United States (US). Interactive software was developed to standardize the format of the choice tasks across countries, except for face-to-face interviewing in England. The choice task required respondents to choose between 2 suboptimal health states. A Bayesian design was used to generate 200 pairs of states that were randomly grouped into 20 blocks. Each respondent completed 1 block of 10 pairs. A main-effects probit model was used to estimate regression coefficients and to derive values.<br />Results: Approximately 400 respondents participated from each country. The mean time to perform 1 choice task was between 29.2 (US) and 45.2 (England) seconds. All regression coefficients were statistically significant, except level 2 for Usual Activities in The Netherlands (P=0.51). Predictions for the complete set of 3125 EQ-5D-5L health states were similar for the 4 countries. Intraclass correlation coefficients between the countries were high: from 0.80 (England vs. US) through 0.98 (Canada vs.<br />Us) Conclusions: Derivation of value sets from the general population using computer-based choice tasks for the EQ-5D-5L is feasible. Parameter estimates were generally consistent and logical, and health-state values were similar across the 4 countries.

Details

Language :
English
ISSN :
1537-1948
Volume :
52
Issue :
11
Database :
MEDLINE
Journal :
Medical care
Publication Type :
Academic Journal
Accession number :
25100229
Full Text :
https://doi.org/10.1097/MLR.0000000000000178