G-2 TIME OUT FOR TIME TRADE-OFF: REDUNDANT OR INVALID MEASURES IN US, UK AND DANISH EQ-5D VALUATION STUDIES

Tuesday, October 20, 2009: 4:15 PM
Grand Ballroom, Salon 4 (Renaissance Hollywood Hotel)
Kim Rand-Hendriksen, Cand.Psychol1, Liv Ariane Augestad, MD1, Knut Stavem, MD, PhD1 and Ivar Sønbø Kristiansen, MD, PhD, MPH2, (1)Akershus University Hospital, Lørenskog, Norway, (2)Institute of Health Economics, N-0317 Oslo, Denmark Norway

Purpose: Most prominent national EQ-5D valuation studies employ the Time Trade-Off (TTO) preference elicitation method, using sequential choice tasks to model a trade-off between health and longevity. In the US, UK and Danish EQ-5D valuation studies, the first choice task was the most significant, categorizing health states as being worse than death (wtd), equal to death (etd) or better than death (btd). Adding the special case of respondents unwilling to trade (utt) any lifetime to achieve perfect health, valuations fall into four qualitatively distinct categories. The purpose of the study was to test to which extent the final tariffs are determined by these categories; how much is gained by continuing the TTO task after the initial choice.

Method: We performed separate analyses on TTO data from the US, UK and Danish valuation studies using two transformations of negative utilities corresponding to the US and UK methods. Original valuation study exclusion criteria were used. TTO values were collapsed onto four equidistant points corresponding to the four distinct categories (utt, btd, etd, wtd). Averages for each directly measured health state were correlated between full and collapsed TTO values. We calculated Pearson’s correlations between predicted values based on full and collapsed TTO for all 243 health states using both the D1 and N3 regression specifications.

Result: Pearson’s r between averaged health states for full and collapsed TTO were >.998 (p<.001) for all three datasets. Correlations between predicted values for all 243 states based on full and collapsed TTO using the same transformation and regression model were all >.999 (p<.001). Using three national valuation datasets, two different transformations of negative utilities and two different regression specifications, the patterns of distances between averaged health state values were conserved (r2>.998 for all measures) when collapsing the TTO onto four points.

Conclusion: There was no gain from continuing the valuation task after the initial choice. The resulting population tariffs appear to be determined by patterns in the proportion of the population electing each of the four categories. Depending on whether we consider the first choice task alone to be a valid measure of health state severity, the TTO method could be radically simplified, revised or should possibly be abandoned.

Candidate for the Lee B. Lusted Student Prize Competition