Estimating Domestic Values for EQ-5D Health States Using Survey Data From External Sources.
BACKGROUND
Health status measures used to quantify outcomes for economic evaluation must be capable of representing health gain in a single index, usually calibrated in terms of the social preferences elicited from "the relevant population." The general problem faced in the majority of countries where social preferences are required for cost-effectiveness analysis is the absence of a value set based on domestic data sources.


OBJECTIVE
This article establishes a methodology for estimating domestic visual analog scale (VAS)-based values for EQ-5D health states by adjusting data sets from countries where valuation studies have been carried out.


METHODS
building upon the relationship between the values for respondents' real health states and hypothetical health states, 2 models are investigated. One assumes that the link between VAS scores for real and hypothetical health state is constant across 2 countries (R1), whereas the other adopts the assumption that the relationship of VAS scores for hypothetical heath states between 2 countries functionally corresponds to variation in scores for real health states (R2). Data from national UK and US population surveys were selected to test both methods.


RESULTS
The R2 model performed better in generating estimated scores that were closer to observed values.


CONCLUSIONS
The R2 model seems to offer a viable method for estimating domestic values of health. Such a method could help to bridge the gap between countries as well as region within a country.
Chuang
Ling-Hsiang
LH
Centre for Health Economics, University of York, York, United Kingdom. lc525@york.ac.uk
Zarate
Victor
V
Kind
Paul
P
D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data; D003431:Cross-Cultural Comparison; D006296:Health Services / Q000191:economics*; D006302:Health Services Research; D006305:Health Status Indicators; D006306:Health Surveys; D006801:Humans; D017059:Models, Econometric; D015233:Models, Statistical; D010147:Pain Measurement / Q000706:statistics & numerical data; D013222:State Medicine / Q000191:economics*; D011795:Surveys and Questionnaires; D006113:United Kingdom; D014481:United States