Modeling SF-6D Health Utilities: Is Bayesian Approach Appropriate?
Int J Environ Res Public Health
; 18(16)2021 08 09.
Article
in English
| MEDLINE | ID: covidwho-1376808
ABSTRACT
BACKGROUND:
Valuation studies of preference-based health measures like SF6D have been conducted in many countries. However, the cost of conducting such studies in countries with small populations or low- and middle-income countries (LMICs) can be prohibitive. There is potential to use results from readily available countries' valuations to produce better valuation estimates.METHODS:
Data from Lebanon and UK SF-6D value sets were analyzed, where values for 49 and 249 health states were extracted from samples of Lebanon and UK populations, respectively, using standard gamble techniques. A nonparametric Bayesian model was used to estimate a Lebanon value set using the UK data as informative priors. The resulting estimates were then compared to a Lebanon value set obtained using Lebanon data by itself via various prediction criterions.RESULTS:
The findings permit the UK evidence to contribute potential prior information to the Lebanon analysis by producing more precise valuation estimates than analyzing Lebanon data only under all criterions used.CONCLUSIONS:
The positive findings suggest that existing valuation studies can be merged with a small valuation set in another country to produce value sets, thereby making own country value sets more attainable for LMICs.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Quality of Life
/
Health Status Indicators
Type of study:
Observational study
/
Prognostic study
/
Randomized controlled trials
Language:
English
Year:
2021
Document Type:
Article
Affiliation country:
Ijerph18168409
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