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Record W4401891511 · doi:10.1093/heapol/czae082

Stakeholder perspectives on the governance and accountability of Nigeria’s Basic Health Care Provision Fund

2024· article· en· W4401891511 on OpenAlexfundno aff
Mary I Adeoye, A Felix, Emily Adrion

Bibliographic record

VenueHealth Policy and Planning · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsnot available
FundersMastercard Foundation
KeywordsAccountabilityCorporate governanceStakeholderGovernment (linguistics)Health careBusinessCivil societyService delivery frameworkPublic administrationStakeholder engagementPublic relationsSocial accountingFinancePolitical scienceEconomic growthService (business)EconomicsAccountingPoliticsMarketing

Abstract

fetched live from OpenAlex

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.139
GPT teacher head0.362
Teacher spread0.223 · 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".

Quick stats

Citations5
Published2024
Admission routes1
Has abstractyes

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