Estimating the EQ-5D-5L value set for the Philippines.
Developing countries
EQ-5D-5L
Hybrid mathematical modeling
QALY
Utility weights
Journal
Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation
ISSN: 1573-2649
Titre abrégé: Qual Life Res
Pays: Netherlands
ID NLM: 9210257
Informations de publication
Date de publication:
Sep 2022
Sep 2022
Historique:
accepted:
05
04
2022
pubmed:
10
5
2022
medline:
10
8
2022
entrez:
9
5
2022
Statut:
ppublish
Résumé
The Philippines has recommended the use of Quality-Adjusted Life Years (QALYs) in government health technology assessments (HTA). We aimed to develop a value set for the EQ-5D-5L based on health preferences of the healthy general adult population in the Philippines. Healthy, literate adults were recruited from the Philippine general population with quota targets based on age, sex, administrative region, type of residence, education, income, and ethnolinguistic groups. Each participant's preference was elicited by completing Composite Time Trade-Off (C-TTO) and Discrete Choice Experiment (DCE) tasks. Tasks were computer-assisted using the EuroQol Valuation Technology 2.0. To estimate the value set, we explored 20- and 8-parameter models that either use c-TTO-only data or both c-TTO and DCE (also called hybrid models). Final model choice was guided by principles of monotonicity, out-of-sample likelihood, model fit, and parsimony. We recruited 1000 respondents with demographic characteristics that approximate the general population such as 49.6% Female, 82% Roman Catholic, 40% in urban areas, and 55% finished high school. None of the 20-parameter models demonstrated monotonicity (logical worsening of coefficients with increasing severity). From the 8-parameter models, the homoscedastic TTO-only model exhibited the best fit. From this model, mobility and pain/ discomfort had the highest effect on utilities. The selected model for representing the Philippine general population preferences for EQ-5D-5L health states was an 8-parameter homoscedastic TTO-only model. This value set is recommended for use in QALY calculations in support of HTA-informed coverage decisions in the Philippines.
Sections du résumé
BACKGROUND
BACKGROUND
The Philippines has recommended the use of Quality-Adjusted Life Years (QALYs) in government health technology assessments (HTA). We aimed to develop a value set for the EQ-5D-5L based on health preferences of the healthy general adult population in the Philippines.
METHODS
METHODS
Healthy, literate adults were recruited from the Philippine general population with quota targets based on age, sex, administrative region, type of residence, education, income, and ethnolinguistic groups. Each participant's preference was elicited by completing Composite Time Trade-Off (C-TTO) and Discrete Choice Experiment (DCE) tasks. Tasks were computer-assisted using the EuroQol Valuation Technology 2.0. To estimate the value set, we explored 20- and 8-parameter models that either use c-TTO-only data or both c-TTO and DCE (also called hybrid models). Final model choice was guided by principles of monotonicity, out-of-sample likelihood, model fit, and parsimony.
RESULTS
RESULTS
We recruited 1000 respondents with demographic characteristics that approximate the general population such as 49.6% Female, 82% Roman Catholic, 40% in urban areas, and 55% finished high school. None of the 20-parameter models demonstrated monotonicity (logical worsening of coefficients with increasing severity). From the 8-parameter models, the homoscedastic TTO-only model exhibited the best fit. From this model, mobility and pain/ discomfort had the highest effect on utilities.
CONCLUSION
CONCLUSIONS
The selected model for representing the Philippine general population preferences for EQ-5D-5L health states was an 8-parameter homoscedastic TTO-only model. This value set is recommended for use in QALY calculations in support of HTA-informed coverage decisions in the Philippines.
Identifiants
pubmed: 35532835
doi: 10.1007/s11136-022-03143-w
pii: 10.1007/s11136-022-03143-w
pmc: PMC9356948
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2763-2774Informations de copyright
© 2022. The Author(s).
Références
Value Health. 2018 May;21(5):596-604
pubmed: 29753358
Value Health. 2009 Mar;12 Suppl 1:S5-9
pubmed: 19250132
Health Econ. 2018 Jan;27(1):7-22
pubmed: 28833869
Value Health. 2017 Apr;20(4):662-669
pubmed: 28408009
Pharmacoeconomics. 2016 Oct;34(10):993-1004
pubmed: 27084198
Health Econ. 2014 Sep;23(9):1098-114
pubmed: 24943827
Qual Life Res. 2011 Dec;20(10):1727-36
pubmed: 21479777
Health Econ. 2018 Jan;27(1):23-38
pubmed: 28833854
Pharmacoeconomics. 2017 Nov;35(11):1153-1165
pubmed: 28695543
Med Care. 2016 Jan;54(1):98-105
pubmed: 26492214
Int J Technol Assess Health Care. 2020 Apr;36(2):96-103
pubmed: 32340631
Expert Rev Pharmacoecon Outcomes Res. 2018 Oct;18(5):551-558
pubmed: 29958008
Med Care. 2017 Jul;55(7):e51-e58
pubmed: 25521503
Pharmacoeconomics. 2019 May;37(5):715-725
pubmed: 30535779
Value Health. 2014 Nov;17(7):A737
pubmed: 27202647
Hum Vaccin Immunother. 2017 May 4;13(5):1158-1166
pubmed: 28075249
Value Health. 2019 Jan;22(1):23-30
pubmed: 30661630
Value Health. 2018 Jun;21(6):732-741
pubmed: 29909879
Value Health. 2016 Jul-Aug;19(5):648-54
pubmed: 27565282
Eur J Health Econ. 2013 Jul;14 Suppl 1:S5-13
pubmed: 23900660
PLoS One. 2017 Sep 21;12(9):e0184883
pubmed: 28934266
Health Policy Plan. 2006 Sep;21(5):402-8
pubmed: 16877455
PLoS One. 2015 Jul 01;10(7):e0131156
pubmed: 26131961
Qual Life Res. 2016 Feb;25(2):323-333
pubmed: 26242249
Value Health. 2014 Jan-Feb;17(1):70-6
pubmed: 24438719
Patient. 2018 Apr;11(2):235-247
pubmed: 29019161
Pharmacoeconomics. 2018 Jun;36(6):663-674
pubmed: 29460066
Value Health. 2017 Jul - Aug;20(7):945-952
pubmed: 28712624
Qual Life Res. 2016 Jul;25(7):1845-52
pubmed: 26961008
Value Health. 2016 Jun;19(4):343-52
pubmed: 27325326
Value Health. 2014 Jun;17(4):445-53
pubmed: 24969006