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Testing a discrete choice experiment including duration to value health states for large descriptive systems: Addressing design and sampling issues

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  • Bansback, Nick
  • Hole, Arne Risa
  • Mulhern, Brendan
  • Tsuchiya, Aki

Abstract

There is interest in the use of discrete choice experiments that include a duration attribute (DCETTO) to generate health utility values, but questions remain on its feasibility in large health state descriptive systems. This study examines the stability of DCETTO to estimate health utility values from the five-level EQ-5D, an instrument with depicts 3125 different health states. Between January and March 2011, we administered 120 DCETTO tasks based on the five-level EQ-5D to a total of 1799 respondents in the UK (each completed 15 DCETTO tasks on-line). We compared models across different sample sizes and different total numbers of observations. We found the DCETTO coefficients were generally consistent, with high agreement between individual ordinal preferences and aggregate cardinal values. Keeping the DCE design and the total number of observations fixed, subsamples consisting of 10 tasks per respondent with an intermediate sized sample, and 15 tasks with a smaller sample provide similar results in comparison to the whole sample model. In conclusion, we find that the DCETTO is a feasible method for developing values for larger descriptive systems such as EQ-5D-5L, and find evidence supporting important design features for future valuation studies that use the DCETTO.

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  • Bansback, Nick & Hole, Arne Risa & Mulhern, Brendan & Tsuchiya, Aki, 2014. "Testing a discrete choice experiment including duration to value health states for large descriptive systems: Addressing design and sampling issues," Social Science & Medicine, Elsevier, vol. 114(C), pages 38-48.
    • Handle: RePEc:eee:socmed:v:114:y:2014:i:c:p:38-48
    DOI: 10.1016/j.socscimed.2014.05.026
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    3. Osman, Ahmed M.Y. & Wu, Jing & He, Xiaoning & Chen, Gang, 2021. "Eliciting SF-6Dv2 health state utilities using an anchored best-worst scaling technique," Social Science & Medicine, Elsevier, vol. 279(C).

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