Who pays for and who benefits from health care services in Uganda?
Bibliographic record
Abstract
BACKGROUND: Equity in health care entails payment for health services according to the capacity to pay and the receipt of benefits according to need. In Uganda, as in many African countries, although equity is extolled in government policy documents, not much is known about who pays for, and who benefits from, health services. This paper assesses both equity in the financing and distribution of health care benefits in Uganda. METHODS: Data are drawn from the most recent nationally representative Uganda National Household Survey 2009/10. Equity in health financing is assessed considering the main domestic health financing sources (i.e., taxes and direct out-of-pocket payments). This is achieved using bar charts and standard concentration and Kakwani indices. Benefit incidence analysis is used to assess the distribution of health services for both public and non-public providers across socio-economic groups and the need for care. Need is assessed using limitations in functional ability while socioeconomic groups are created using per adult equivalent consumption expenditure. RESULTS: Overall, health financing in Uganda is marginally progressive; the rich pay more as a proportion of their income than the poor. The various taxes are more progressive than out-of-pocket payments (e.g., the Kakwani index of personal income tax is 0.195 compared with 0.064 for out-of-pocket payments). However, taxes are a much smaller proportion of total health sector financing compared with out-of-pocket payments. The distribution of total health sector services benefitsis pro-rich. The richest quintile receives 19.2% of total benefits compared to the 17.9% received by the poorest quintile. The rich also receive a much higher share of benefits relative to their need. Benefits from public health units are pro-poor while hospital based care, in both public and non-public sectors are pro-rich. CONCLUSION: There is a renewed interest in ensuring equity in the financing and use of health services. Based on the results in this paper, it would seem that in order to safeguard such equity, there is a need for policy that focuses on addressing the health needs of the poor while continuing to ensure that the burden of financing health services does not rest disproportionately on the poor.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".