Are Health State Valuations from the General Public Biased? A Test of Health State Reference Dependency Using Self‐assessed Health and an Efficient Discrete Choice Experiment. (27th October 2016)

• Record Type: Journal Article
• Authors: Jonker, Marcel F.; Attema, Arthur E.; Donkers, Bas; Stolk, Elly A.; Versteegh, Matthijs M.
• Is Part Of: Health economics. Volume 26:Number 12(2017)
• Page Start: 1534
• Page End: 1547
• Publication Date: 2016-10-27
• Subjects: health state valuation -- prospect theory -- discrete choice experiment -- EQ‐5D; Medical economics -- Periodicals; Economics, Medical -- Periodicals; Health Care Costs -- Periodicals; Health Policy -- economics -- Periodicals; Health Services -- economics -- Periodicals; 362.1
• DOI: 10.1002/hec.3445
• Languages: English
• ISSNs: 1057-9230

Abstract

Abstract: Health state valuations of patients and non‐patients are not the same, whereas health state values obtained from general population samples are a weighted average of both. The latter constitutes an often‐overlooked source of bias. This study investigates the resulting bias and tests for the impact of reference dependency on health state valuations using an efficient discrete choice experiment administered to a Dutch nationally representative sample of 788 respondents. A Bayesian discrete choice experiment design consisting of eight sets of 24 (matched pairwise) choice tasks was developed, with each set providing full identification of the included parameters. Mixed logit models were used to estimate health state preferences with respondents' own health included as an additional predictor. Our results indicate that respondents with impaired health worse than or equal to the health state levels under evaluation have approximately 30% smaller health state decrements. This confirms that reference dependency can be observed in general population samples and affirms the relevance of prospect theory in health state valuations. At the same time, the limited number of respondents with severe health impairments does not appear to bias social tariffs as obtained from general population samples. Copyright © 2016 John Wiley & Sons, Ltd.