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Record W4405233998 · doi:10.1371/journal.pone.0312906

Determining household out of pocket payments, incidence of catastrophic expenditures and impoverishment among patients with malaria in Zambia’s path towards Universal Health Coverage

2024· article· en· W4405233998 on OpenAlexaff
Patrick Banda, Felix Masiye, Oliver Kaonga, Jesse B. Bump, Peter Berman

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMalariaEnvironmental healthPaymentIncidence (geometry)SocioeconomicsMedicineGeographyDevelopment economicsEconomicsImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: The World Health Organisation (WHO) estimates that about 3.2 billion people which is nearly half of the world's population are at risk of malaria. Annually about 216 million cases and 445,000 deaths of malaria occur globally. Africa accounted for 90% and 91% of the malaria cases and deaths respectively. Zambia has earmarked malaria elimination on its path to Universal Health Coverage (UHC). This paper aims to determine the incidence of Out-of-Pocket Payments (OOP) and Catastrophic Health Expenditures (CHE) and impoverishment among households with malaria patients in Zambia. The paper focusses on the incidence of OOP and impoverishment for malaria in a setting without user fees for accessing primary malaria health care services and virtually no user fees at all levels of care if referred through the referral system. The results of this study will also serve as a baseline for tracking Zambia's path towards achieving malaria financial access on its path towards UHC among patient with malaria. METHODS: The study uses a nationally representative cross-sectional survey of households in both rural and urban areas of Zambia. The study employed probability sampling procedures. A two-stage stratified cluster sample design was used. We analyse a total of 2,005 households that had at least one member suffering from malaria with a recall period of four weeks for out-patients and six months for the in-patient respectively. A logistic regression model was estimated with a Categorical Dependent variable being CHE (CHE = = 1, or otherwise = = 0). A household is considered impoverished if it fell below the poverty line due to OOP. All data was analyzed using Stata version 2013. RESULTS AND DISCUSSION: The results show that although the country has a free malaria policy at primary care level and virtually at all levels if referred through the health system process, households are still incurring costs in accessing health care services. Incidence of CHE and impoverishment were reflected at all levels. In terms of CHE, the poorest contributed almost 30% while the wealthier quintile contributed about 10%. Similarly, impoverishment effects of OOPs are more pronounced in the poorest quintile. The OOP composed mainly of transport, followed by diagnosis and medicines and was lowest for Insecticide-treated bed nets (ITNs) payments. The high costs of transport that the households had to incur when accessing health services could be due to the long distance that the households have to face as they travel to the health facilities as most of the facilities in Zambia are still outside the 5 km radius. The drug expenditure could be explained by the drugs running out of stock. Low expenditure on ITNs could be due to the country's strategy of mass distribution working to give the country's universal financial protection on ITNs for malaria. CONCLUSION AND POLICY IMPLICATIONS: This study sought to address gaps in OOP and the associated incidence of CHE and impoverishment for malaria, distribution of OOP among Social Economic Status (SES) setting and determinants of OOP in Country that has earmarked malaria elimination in the UHC agenda. Understanding household's costs related to malaria will enable targeting intervention to accelerate Zambia's path towards elimination of malaria and therefore contribute to attainment of the Sustainable Development Goals of household's financial access to UHC. Thus, the study will also serve as a baseline for tracking UHC for household financial access to malaria care that the country has embarked on.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.219
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations4
Published2024
Admission routes1
Has abstractyes

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