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Valuation of preference-based measures: can existing preference data be used to select a smaller sample of health states?

Original Paper

Abstract

Background

Different countries have different preferences regarding health, and there are different value sets for popular preference-based measures across different countries. However, the cost of collecting data to generate country-specific value sets can be prohibitive for countries with smaller population size or low- and middle-income countries (LMIC). This paper explores whether existing preference weights could be modelled alongside a small own country valuation study to generate representative estimates. This is explored using a case study modelling UK data alongside smaller US samples to generate US estimates.

Methods

We analyse EQ-5D valuation data derived from representative samples of the US and UK populations using time trade-off to value 42 health states. A nonparametric Bayesian model was applied to estimate a US value set using the full UK dataset and subsets of the US dataset for 10, 15, 20 and 25 health states. Estimates are compared to a US value set estimated using US values alone using mean predictions and root mean square error.

Results

The results suggest that using US data elicited for 20 health states alongside the existing UK data produces similar predicted mean valuations and RMSE as the US value set, while 25 health states produce the exact features.

Conclusions

The promising results suggest that existing preference data could be combined with a small valuation study in a new country to generate preference weights, making own country value sets more achievable for LMIC. Further research is encouraged.

Keywords

Preference-based health measures Nonparametric Bayesian methods Time trade-off EQ-5D 

JEL Classification

C1 I1 

Notes

Acknowledgements

The leading author would like to thank the University Research Bureau (URB) at the American University of Beirut, Lebanon, for funding this study. The authors would particularly like to thank Prof. John E Brazier for all his continual support and useful guidance during their time working on this manuscript. This work was supported by American University of Beirut (103366).

Funding

This study was funded by the University Research Bureau (URB) at the American University of Beirut, Lebanon.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Nutrition and Food Sciences, Faculty of Agricultural and Food SciencesAmerican University of BeirutBeirutLebanon
  2. 2.Health Economics and Decision Science, School of Health and Related ResearchThe University of SheffieldSheffieldUK

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