Assessing catastrophic and impoverishing effects of health care payments in Uganda
Bibliographic record
Abstract
BACKGROUND: Direct out-of-pocket payments for health care are recognised as limiting access to health care services and also endangering the welfare of households. In Uganda, such payments comprise a large portion of total health financing. This study assesses the catastrophic and impoverishing impact of paying for health care out-of-pocket in Uganda. METHODS: Using data from the Uganda National Household Surveys 2009/10, the catastrophic impact of out-of-pocket health care payments is defined using thresholds that vary with household income. The impoverishing effect of out-of-pocket health care payments is assessed using the Ugandan national poverty line and the World Bank poverty line ($1.25/day). RESULTS: A high level and intensity of both financial catastrophe and impoverishment due to out-of-pocket payments are recorded. Using an initial threshold of 10% of household income, about 23% of Ugandan households face financial ruin. Based on both the $1.25/day and the Ugandan poverty lines, about 4% of the population are further impoverished by such payments. This represents a relative increase in poverty head count of 17.1% and 18.1% respectively. CONCLUSION: The absence of financial protection in Uganda's health system calls for concerted action. Currently, out-of-pocket payments account for a large share of total health financing and there is no pooled prepayment system available. There is therefore a need to move towards mandatory prepayment. In this way, people could access the needed health services without any associated financial consequence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".