Examining Approaches to Estimate the Prevalence of Catastrophic Costs Due to Tuberculosis from Small-Scale Studies in South Africa.
Adult
Catastrophic Illness
/ economics
Cohort Studies
Cost of Illness
Datasets as Topic
Female
Health Care Costs
/ statistics & numerical data
Humans
Income
/ statistics & numerical data
Male
Middle Aged
Models, Economic
Policy Making
Prevalence
South Africa
/ epidemiology
Tuberculosis
/ economics
Uncertainty
Journal
PharmacoEconomics
ISSN: 1179-2027
Titre abrégé: Pharmacoeconomics
Pays: New Zealand
ID NLM: 9212404
Informations de publication
Date de publication:
06 2020
06 2020
Historique:
pubmed:
3
4
2020
medline:
24
4
2021
entrez:
3
4
2020
Statut:
ppublish
Résumé
In context of the End TB goal of zero tuberculosis (TB)-affected households encountering catastrophic costs due to TB by 2020, the estimation of national prevalence of catastrophic costs due to TB is a priority to inform programme design. We explore approaches to estimate the national prevalence of catastrophic costs due to TB from existing datasets as an alternative to nationally representative surveys. We obtained, standardized and merged three patient-level datasets from existing studies on patient-incurred costs due to TB in South Africa. A deterministic cohort model was developed with the aim of estimating the national prevalence of catastrophic costs, using national data on the prevalence of TB and likelihood of loss to follow-up by income quintile and HIV status. Two approaches were tested to parameterize the model with existing cost data. First, a meta-analysis summarized study-level data by HIV status and income quintile. Second, a regression analysis of patient-level data also included employment status, education level and urbanicity. We summarized findings by type of cost and examined uncertainty around resulting estimates. Overall, the median prevalence of catastrophic costs for the meta-analysis and regression approaches were 11% (interquartile range [IQR] 9-13%) and 6% (IQR 5-8%), respectively. Both approaches indicated that the main burden of catastrophic costs falls on the poorest households. An individual-level regression analysis produced lower uncertainty around estimates than a study-level meta-analysis. This paper presents a novel application of existing data to estimate the national prevalence of catastrophic costs due to TB. This type of model could be useful for researchers and policy makers looking to inform certain policy decisions; however, some uncertainties remain due to limitations in data availability. There is an urgent need for standardized reporting of cost data and improved guidance on methods to collect income data to improve these estimates going forward.
Sections du résumé
BACKGROUND AND OBJECTIVE
In context of the End TB goal of zero tuberculosis (TB)-affected households encountering catastrophic costs due to TB by 2020, the estimation of national prevalence of catastrophic costs due to TB is a priority to inform programme design. We explore approaches to estimate the national prevalence of catastrophic costs due to TB from existing datasets as an alternative to nationally representative surveys.
METHODS
We obtained, standardized and merged three patient-level datasets from existing studies on patient-incurred costs due to TB in South Africa. A deterministic cohort model was developed with the aim of estimating the national prevalence of catastrophic costs, using national data on the prevalence of TB and likelihood of loss to follow-up by income quintile and HIV status. Two approaches were tested to parameterize the model with existing cost data. First, a meta-analysis summarized study-level data by HIV status and income quintile. Second, a regression analysis of patient-level data also included employment status, education level and urbanicity. We summarized findings by type of cost and examined uncertainty around resulting estimates.
RESULTS
Overall, the median prevalence of catastrophic costs for the meta-analysis and regression approaches were 11% (interquartile range [IQR] 9-13%) and 6% (IQR 5-8%), respectively. Both approaches indicated that the main burden of catastrophic costs falls on the poorest households. An individual-level regression analysis produced lower uncertainty around estimates than a study-level meta-analysis.
CONCLUSIONS
This paper presents a novel application of existing data to estimate the national prevalence of catastrophic costs due to TB. This type of model could be useful for researchers and policy makers looking to inform certain policy decisions; however, some uncertainties remain due to limitations in data availability. There is an urgent need for standardized reporting of cost data and improved guidance on methods to collect income data to improve these estimates going forward.
Identifiants
pubmed: 32239479
doi: 10.1007/s40273-020-00898-3
pii: 10.1007/s40273-020-00898-3
pmc: PMC7307451
mid: EMS86550
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Pagination
619-631Subventions
Organisme : Wellcome Trust
ID : 201433
Pays : United Kingdom
Organisme : Bill & Melinda Gates Foundation
ID : OPP1109722
Pays : United States
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