Ralph P Insinga1, Dennis G Fryback. 1. University of Wisconsin-Madison, Department of Population Health Sciences, WARF Building, Room 644, 610 Walnut Street, Madison, WI 53726-2397, USA. rpinsinga@students.wisc.edu
Abstract
OBJECTIVE: To examine the source and magnitude of differences between self-ratings for health and ratings of corresponding health state profiles by the general population in the EuroQOL. DATA AND METHODS: EuroQOL data were analysed from the 1993 measurement and valuation of health study (MVH), a sample of 2997 members of the UK adult population, nationally representative by age, gender and social class. Multivariate regression analyses were used to examine the source of differences in visual analogue scores (VAS) between self-ratings and general population ratings. The source of observed differences were investigated with respect to four hypothesized factors: (1) Socio-demographics (age, gender, education, social class); (2) The level of respondent difficulty in completing the rating task; (3) Values for particular EQ-5D health profile attributes; and (4) Differences in the scope of health attributes and levels considered in the rating task (e.g., self-ratings may reflect preferences for attributes not captured by EQ-5D profiles). RESULTS: Overall, mildly ill individuals provided lower self-ratings (3-4 points), and moderately ill individuals higher self-ratings (7 points), than ratings for these states provided by the general population. Socio-demographic characteristics and difficulties in rating task completion did not explain differences between self and general population VAS ratings, contributing differences of 1 point or less in all 15 rating comparisons examined. Rating differences related more closely to a lack of correspondence between health state descriptions and self-raters' actual health experiences (differences in scope) than differences in values for health profile attributes between self-raters and the general population. CONCLUSIONS: EQ-5D health state descriptions may be too sparse to comprehensively describe certain health states. Adding new health state levels or dimensions, or changing the nature and tone of health state descriptions, may be useful steps for improvement.
OBJECTIVE: To examine the source and magnitude of differences between self-ratings for health and ratings of corresponding health state profiles by the general population in the EuroQOL. DATA AND METHODS: EuroQOL data were analysed from the 1993 measurement and valuation of health study (MVH), a sample of 2997 members of the UK adult population, nationally representative by age, gender and social class. Multivariate regression analyses were used to examine the source of differences in visual analogue scores (VAS) between self-ratings and general population ratings. The source of observed differences were investigated with respect to four hypothesized factors: (1) Socio-demographics (age, gender, education, social class); (2) The level of respondent difficulty in completing the rating task; (3) Values for particular EQ-5D health profile attributes; and (4) Differences in the scope of health attributes and levels considered in the rating task (e.g., self-ratings may reflect preferences for attributes not captured by EQ-5D profiles). RESULTS: Overall, mildly ill individuals provided lower self-ratings (3-4 points), and moderately ill individuals higher self-ratings (7 points), than ratings for these states provided by the general population. Socio-demographic characteristics and difficulties in rating task completion did not explain differences between self and general population VAS ratings, contributing differences of 1 point or less in all 15 rating comparisons examined. Rating differences related more closely to a lack of correspondence between health state descriptions and self-raters' actual health experiences (differences in scope) than differences in values for health profile attributes between self-raters and the general population. CONCLUSIONS: EQ-5D health state descriptions may be too sparse to comprehensively describe certain health states. Adding new health state levels or dimensions, or changing the nature and tone of health state descriptions, may be useful steps for improvement.
Authors: Martina Garau; Koonal K Shah; Anne R Mason; Qing Wang; Adrian Towse; Michael F Drummond Journal: Pharmacoeconomics Date: 2011-08 Impact factor: 4.981
Authors: Jeffrey M Pyne; John C Fortney; Shanti Tripathi; David Feeny; Peter Ubel; John Brazier Journal: Health Serv Res Date: 2009-04-21 Impact factor: 3.402