PND60 - Comparison of the valuation of treatment alternatives in Parkinson's disease with best-wordt scaling, time trade-off and visual analogue scales

Objectives: Traditional valuation methods are insensitive to small improvements in process and outcome of care. Best-Worst scaling (BWS) was proposed as a sensitive and efficient method to determine the relative value of different treatments for the same disease, which would be desirable to estimate cost-effectiveness. The study objective was to compare the ability of BWS to differentiate between different treatment alternatives to that of Time Trade Off (TTO) and Visual Analogue Scales (VAS). Methods: An online survey was conducted to estimate individual values for six different treatments reflecting the real-life options in the treatment of Parkinson’s Disease with BWS2, BWS3, TTO and VAS (n=592). Pearson correlation coefficient was used to examine the strength of linear dependence between estimated utility scores. Results: Twenty-seven percent of respondents was not willing to trade life years in TTO. Only two percent of the respondent does not differentiate between the value of health states with VAS. When non-traders were excluded from the analysis, the best case scenario was valued significantly higher than the worst case scenario with all methods. Rank reversals among intermediate alternatives were common. The correlation between utility scores was very strong (VAS-BWS2 1,0; VAS-BWS3 0.98; TTO-BWS2 0.99; TTO-BWS3 0.98, BWS2-BWS3 0.96; P<0.000, n=434). Conclusions: The results demonstrate that BWS, TTO and VAS can be used to elicit incremental utility gain of small improvements in care. However, all methods have limitations. VAS does not result in utilities and some respondents do not trade with TTO. While the use of BWS is attractive because of its ability to estimate utilities for many different treatment alternatives, its applicability in CEA is limited because BWS utilities are not anchored on a 0-1 utility scale. We propose to use TTO to estimate utility for extreme health states, and to use BWS to value intermediate health states which differ on process characteristics.