Health state valuation using DCEs and best-worst scaling

Health state valuation using discrete choice experiments and best-worst scaling: a comparison of methods

Health utility indices (HUIs) are widely used in economic evaluation. The best–worst scaling (BWS) method is used to value dimensions of HUIs. However, little is known about the properties of this method. We investigate the validity of the BWS method to develop HUI, comparing it to another ordinal valuation method, the discrete choice experiment (DCE). Using a parametric approach we find a low level of concordance between the two methods, with evidence of preference reversals. BWS responses are subject to decision biases, with significant effects on individuals’ preferences. Non-parametric tests indicate BWS data has lower stability, monotonicity and continuity compared to DCE data, suggesting the BWS provides lower quality data.

Outcome and Translation

For both theoretical and technical reasons, practitioners should be cautious both about using the BWS method to measure health-related preferences, and about using HUI based on BWS data. Given existing evidence it seems that the DCE method is a better method, at least because its limitations (and measurement properties) have been extensively researched.

HERU researchers involved in this research project: Nicolas Krucien, Verity Watson and Mandy Ryan


Krucien, N., Watson, V. and Ryan, M. (2017) 'Is best–worst scaling suitable for health state valuation? A comparison with discrete choice experiments', Health Economics, 26(12), e1-e16.


Krucien, N., Watson, V. and Ryan, M. (2014) 'Multi-attribute valuation: a comparison of the discrete choice experiment and best-worse scaling approaches', Health Economists' Study Group, Sheffield, 8-10 January 2014.