Multinational Evidence of the Applicability and Robustness of Discrete Choice Modeling for Deriving EQ-5D-5L Health-State Values

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. 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. 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. 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.

[1]  Mark Oppe,et al.  A program of methodological research to arrive at the new international EQ-5D-5L valuation protocol. , 2014, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[2]  P. Krabbe,et al.  Quantification of Health by Scaling Similarity Judgments , 2014, PloS one.

[3]  Paul F. M. Krabbe,et al.  A Generalized Measurement Model to Quantify Health: The Multi-Attribute Preference Response Model , 2013, PloS one.

[4]  Mark Oppe,et al.  One-to-one versus group setting for conducting computer-assisted TTO studies: findings from pilot studies in England and the Netherlands , 2013, The European Journal of Health Economics.

[5]  P. Krabbe,et al.  Probabilistic choice models in health-state valuation research: background, theories, assumptions and applications , 2013, Expert review of pharmacoeconomics & outcomes research.

[6]  Aki Tsuchiya,et al.  Binary Choice Health State Valuation and Mode of Administration: Head-to-Head Comparison of Online and CAPI , 2013, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[7]  Alan D. Lopez,et al.  Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010 , 2012, The Lancet.

[8]  M. Herdman,et al.  A comparison of the scaling properties of the English, Spanish, French, and Chinese EQ-5D descriptive systems , 2013, Quality of Life Research.

[9]  J. Brazier,et al.  Using a discrete choice experiment to estimate health state utility values. , 2012, Journal of health economics.

[10]  J. Severens,et al.  Utilities of the EQ-5D , 2012, PharmacoEconomics.

[11]  G. Bonsel,et al.  Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L) , 2011, Quality of Life Research.

[12]  Mark Oppe,et al.  Discrete choice modeling for the quantification of health states: the case of the EQ-5D. , 2010, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[13]  Tara Symonds,et al.  Using DCE and ranking data to estimate cardinal values for health states for deriving a preference-based single index from the sexual quality of life questionnaire. , 2009, Health economics.

[14]  Josep Maria Haro,et al.  Comparison of Population Health Status in Six European Countries: Results of a Representative Survey Using the EQ-5D Questionnaire , 2009, Medical care.

[15]  Paul F. M. Krabbe,et al.  Thurstone Scaling as a Measurement Method to Quantify Subjective Health Outcomes , 2008, Medical care.

[16]  P. Stalmeier,et al.  On the Assessment of Preferences for Health and Duration: Maximal Endurable Time and Better Than Dead Preferences , 2007, Medical care.

[17]  Anthony O'Hagan,et al.  Using rank data to estimate health state utility models. , 2006, Journal of health economics.

[18]  P. Kind Applying paired comparisons models to EQ-5D valuations - deriving TTO utilities from ordinal preference data , 2005 .

[19]  Paul Kind,et al.  EQ-5D concepts and methods : a developmental history , 2005 .

[20]  Christopher McCabe,et al.  Visual Analogue Scales: do they have a role in the measurement of preferences for health states? , 2004 .

[21]  Joshua A Salomon,et al.  Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data , 2003, Population health metrics.

[22]  Aki Tsuchiya,et al.  A single European currency for EQ-5D health states , 2003, The European Journal of Health Economics, formerly: HEPAC.

[23]  L. McKenzie,et al.  Symptom-based outcome measures for asthma: the use of discrete choice methods to assess patient preferences. , 2001, Health policy.

[24]  M Ryan,et al.  Eliciting public preferences for healthcare: a systematic review of techniques. , 2001, Health technology assessment.

[25]  P. Dolan,et al.  Modeling valuations for EuroQol health states. , 1997, Medical care.

[26]  L. Thurstone A law of comparative judgment. , 1994 .

[27]  R. Kane,et al.  Methodology for measuring health-state preferences--II: Scaling methods. , 1989, Journal of clinical epidemiology.

[28]  P. Kind A comparison of two models for scaling health indicators. , 1982, International Journal of Epidemiology.

[29]  P. Zarembka Frontiers in econometrics , 1973 .

[30]  D. McFadden Conditional logit analysis of qualitative choice behavior , 1972 .