Valuation of preference-based measures: can existing preference data be used to generate better estimates?

Samer A. Kharroubi

doi:10.1186/s12955-018-0945-4

Abstract

BackgroundExperimental studies to develop valuations of health state descriptive systems like EQ-5D or SF-6D need to be conducted in different countries, because social and cultural differences are likely to lead to systematically different valuations. There is a scope utilize the evidence in one country to help with the design and the analysis of a study in another, for this to enable the generation of utility estimates of the second country much more precisely than would have been possible when collecting and analyzing the country’s data alone.MethodsWe analyze SF-6D valuation data elicited from representative samples corresponding to the Hong Kong (HK) and United Kingdom (UK) general adult populations through the use of the standard gamble technique to value 197 and 249 health states respectively. We apply a nonparametric Bayesian model to estimate a HK value set using the UK dataset as informative prior to improve its estimation. Estimates are compared to a HK value set estimated using HK values alone using mean predictions and root mean square error.ResultsThe novel method of modelling utility functions permitted the UK valuations to contribute significant prior information to the Hong Kong analysis. The results suggest that using HK data alongside the existing UK data produces HK utility estimates better than using the HK study data by itself.ConclusionThe promising results suggest that existing preference data could be combined with valuation study in a new country to generate preference weights, making own country value sets more achievable for low and middle income countries. Further research is encouraged.

Highlights

Experimental studies to develop valuations of health state descriptive systems like The EuroQol (EQ-5D) or Short form 6 dimensions health survey (SF-6D) need to be conducted in different countries, because social and cultural differences are likely to lead to systematically different valuations
The new modelling approach is applied to the analysis of SF-6D Hong Kong (HK) study using the previously existing United Kingdom (UK) study
The estimates are compared to those estimated using the HK data excluding the UK data using different prediction criterion, including predicted versus actual mean health states valuations, mean predicted error, root mean square error along with the Bland-Altman agreement plots [21]

Summary

Introduction

Experimental studies to develop valuations of health state descriptive systems like EQ-5D or SF-6D need to be conducted in different countries, because social and cultural differences are likely to lead to systematically different valuations. Kharroubi et al [9] use a novel nonparametric Bayesian approach to model the disparities between the United States (US) and UK which is simpler, better fitting and more appropriate for the data than the previously adopted conventional parametric model of Johnson et al [10]. Such an approach has been applied to the joint UK-Hong Kong and UK-Japan SF-6D data set ([11], [12]). The nonparametric Bayesian model offers a major added advantage as it permits the utilization of findings of country 1 to improve those of country 2, and as such generated utility estimates of the second country will be more precise than would have been the case if that country’s data was collected and analyzed on its own

Methods

Results

Discussion

Conclusion