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Health-related quality of life measured using the EQ-5D–5L: South Australian population norms

BACKGROUND: Although a five level version of the widely-used EuroQol 5 dimensions (EQ-5D) instrument has been developed, population norms are not yet available for Australia to inform the future valuation of health in economic evaluations. The aim of this study was to estimate HrQOL normative values...

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Autores principales: McCaffrey, Nikki, Kaambwa, Billingsley, Currow, David C., Ratcliffe, Julie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5028927/
https://www.ncbi.nlm.nih.gov/pubmed/27644755
http://dx.doi.org/10.1186/s12955-016-0537-0
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author McCaffrey, Nikki
Kaambwa, Billingsley
Currow, David C.
Ratcliffe, Julie
author_facet McCaffrey, Nikki
Kaambwa, Billingsley
Currow, David C.
Ratcliffe, Julie
author_sort McCaffrey, Nikki
collection PubMed
description BACKGROUND: Although a five level version of the widely-used EuroQol 5 dimensions (EQ-5D) instrument has been developed, population norms are not yet available for Australia to inform the future valuation of health in economic evaluations. The aim of this study was to estimate HrQOL normative values for the EQ-5D-5L preference-based measure in a large, randomly selected, community sample in South Australia. METHODS: The EQ-5D-5L instrument was included in the 2013 South Australian Health Omnibus Survey, an interviewer-administered, face-to-face, cross-sectional survey. Respondents rated their level of impairment across dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) and global health rating on a visual analogue scale (EQ-VAS). Utility scores were derived using the newly-developed UK general population-based algorithm and relationships between utility and EQ-VAS scores and socio-demographic factors were also explored using multivariate regression analyses. RESULTS: Ultimately, 2,908 adults participated in the survey (63.4 % participation rate). The mean utility and EQ-VAS scores were 0.91 (95 CI 0.90, 0.91) and 78.55 (95 % CI 77.95, 79.15), respectively. Almost half of respondents reported no problems across all dimensions (42.8 %), whereas only 7.2 % rated their health >90 on the EQ-VAS (100 = the best health you can imagine). Younger age, male gender, longer duration of education, higher annual household income, employment and marriage/de facto relationships were all independent, statistically significant predictors of better health status (p < 0.01) measured with the EQ-VAS. Only age and employment status were associated with higher utility scores, indicating fundamental differences between these measures of health status. CONCLUSIONS: This is the first Australian study to apply the EQ-5D-5L in a large, community sample. Overall, findings are consistent with EQ-5D-5L utility and VAS scores reported for other countries and indicate that the majority of South Australian adults report themselves in full health. When valuing health in Australian economic evaluations, the utility population norms can be used to estimate HrQOL. More generally, the EQ-VAS score may be a better measure of population health given the smaller ceiling effect and broader coverage of HrQOL dimensions. Further research is recommended to update EQ-5D-5L population norms using the Australian general population specific scoring algorithm once this becomes publically available.
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spelling pubmed-50289272016-09-22 Health-related quality of life measured using the EQ-5D–5L: South Australian population norms McCaffrey, Nikki Kaambwa, Billingsley Currow, David C. Ratcliffe, Julie Health Qual Life Outcomes Research BACKGROUND: Although a five level version of the widely-used EuroQol 5 dimensions (EQ-5D) instrument has been developed, population norms are not yet available for Australia to inform the future valuation of health in economic evaluations. The aim of this study was to estimate HrQOL normative values for the EQ-5D-5L preference-based measure in a large, randomly selected, community sample in South Australia. METHODS: The EQ-5D-5L instrument was included in the 2013 South Australian Health Omnibus Survey, an interviewer-administered, face-to-face, cross-sectional survey. Respondents rated their level of impairment across dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) and global health rating on a visual analogue scale (EQ-VAS). Utility scores were derived using the newly-developed UK general population-based algorithm and relationships between utility and EQ-VAS scores and socio-demographic factors were also explored using multivariate regression analyses. RESULTS: Ultimately, 2,908 adults participated in the survey (63.4 % participation rate). The mean utility and EQ-VAS scores were 0.91 (95 CI 0.90, 0.91) and 78.55 (95 % CI 77.95, 79.15), respectively. Almost half of respondents reported no problems across all dimensions (42.8 %), whereas only 7.2 % rated their health >90 on the EQ-VAS (100 = the best health you can imagine). Younger age, male gender, longer duration of education, higher annual household income, employment and marriage/de facto relationships were all independent, statistically significant predictors of better health status (p < 0.01) measured with the EQ-VAS. Only age and employment status were associated with higher utility scores, indicating fundamental differences between these measures of health status. CONCLUSIONS: This is the first Australian study to apply the EQ-5D-5L in a large, community sample. Overall, findings are consistent with EQ-5D-5L utility and VAS scores reported for other countries and indicate that the majority of South Australian adults report themselves in full health. When valuing health in Australian economic evaluations, the utility population norms can be used to estimate HrQOL. More generally, the EQ-VAS score may be a better measure of population health given the smaller ceiling effect and broader coverage of HrQOL dimensions. Further research is recommended to update EQ-5D-5L population norms using the Australian general population specific scoring algorithm once this becomes publically available. BioMed Central 2016-09-20 /pmc/articles/PMC5028927/ /pubmed/27644755 http://dx.doi.org/10.1186/s12955-016-0537-0 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
McCaffrey, Nikki
Kaambwa, Billingsley
Currow, David C.
Ratcliffe, Julie
Health-related quality of life measured using the EQ-5D–5L: South Australian population norms
title Health-related quality of life measured using the EQ-5D–5L: South Australian population norms
title_full Health-related quality of life measured using the EQ-5D–5L: South Australian population norms
title_fullStr Health-related quality of life measured using the EQ-5D–5L: South Australian population norms
title_full_unstemmed Health-related quality of life measured using the EQ-5D–5L: South Australian population norms
title_short Health-related quality of life measured using the EQ-5D–5L: South Australian population norms
title_sort health-related quality of life measured using the eq-5d–5l: south australian population norms
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5028927/
https://www.ncbi.nlm.nih.gov/pubmed/27644755
http://dx.doi.org/10.1186/s12955-016-0537-0
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