Stakeholder perspectives on the governance and accountability of Nigeria’s Basic Health Care Provision Fund
Bibliographic record
Abstract
In recent decades, Nigeria has implemented a number of health financing reforms, yet progress towards Universal Health Coverage (UHC) has remained slow. In particular, the introduction of the Basic Health Care Provision Fund (BHCPF) through the National Health Act of 2014 sought to increase coverage of basic health services in Nigeria. However, recent studies have shown that health financing schemes like the BHCPF in Nigeria are suboptimal and have frequently attributed this to weak accountability and governance of the schemes. However, little is known about the accountability and governance of health financing in Nigeria, particularly from the perspective of key actors within the system. This study explores perceptions around governance and accountability through qualitative in-depth interviews with key BHCPF actors, including high-level government officers, academics and Civil Society Organizations. Thematic analysis of the findings reveals broad views among respondents that financial processes are appropriately ring-fenced, and that financial mismanagement is not the most pressing accountability gap. Importantly, respondents report that accountability processes are unclear and weak in subnational service delivery, and cite low utilization, implicit priority setting and poor quality as issues. To accelerate UHC progress, the accountability framework must be redesigned to include greater strategic participation and leadership from subnational governments.
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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 | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".