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Record W2805505463 · doi:10.1186/s12913-018-2974-4

Porous safety net: catastrophic health expenditure and its determinants among insured households in Togo

2018· article· en· W2805505463 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBMC Health Services Research · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsnot available
FundersAfrican Population and Health Research CenterInternational Development Research Centre
KeywordsMedicineEnvironmental healthCatastrophic illnessHealth carePublic healthNational Health Interview SurveyHealth administrationHealth economicsSocioeconomic statusHousehold incomeMedical Expenditure Panel SurveyPaymentSocioeconomicsHealth insuranceBusinessPopulationGeographyEconomic growthNursingEconomicsFinance

Abstract

fetched live from OpenAlex

BACKGROUND: In Togo, about half of health care costs are paid at the point of service, which reduces access to health care and exposes households to catastrophic health expenditure (CHE). To address this situation, the Togolese government introduced a National Health Insurance Scheme (NHIS) in 2011. This insurance currently covers only employees and retirees of the State as well as their dependents, although plans for extension exist. This study is the first attempt to examine the extent to which Togo's NHIS protects its members financially against the consequences of ill-health. METHODS: Data was obtained from a cross-sectional representative households' survey involving 1180 insured households that had reported illness in the household in the 4 weeks preceding the survey or hospitalization in the 12 months preceding the survey. The incidence and intensity of CHE were measured by the catastrophic health payment method. A logistic regression was used to analyse determinants of CHE. RESULTS: The results indicate that the proportion of insured households with CHE varies widely between 3.94% and 75.60%, depending on the method and the threshold used. At the 40% threshold, health care cost represents 60.95% of insured households' total monthly non-food expenditure. This study showed that the socioeconomic status, the type of health facility used, hospitalization and household size were the highest predictors of CHE. Whatever the chosen threshold, care in referral and district hospitals significantly increases the likelihood of CHE. In addition, the proportion of households facing CHE is higher in the lowest income groups. The behaviour of health care providers, poor quality of care and long waiting time were the main factors leading to CHE. CONCLUSION: A sizable proportion of insured households face CHE, suggesting gaps in the coverage. To limit the impoverishment of insured households with low income, policies for free or heavily subsidized hospital services should be considered. The results call for an equitable health insurance scheme, which is affordable for all insured households.

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.

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)0.007
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 score0.015
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.079
GPT teacher head0.364
Teacher spread0.285 · 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