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Record W2953025399 · doi:10.1186/s13561-019-0235-9

Aligning public financial management system and free healthcare policies: lessons from a free maternal and child healthcare programme in Nigeria

2019· article· en· W2953025399 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

VenueHealth Economics Review · 2019
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersAfrican Population and Health Research CenterUniversity of OxfordInternational Development Research Centre
KeywordsVettingHealth careBusinessDescriptive statisticsRevenueHealth administrationPublic healthFinanceFinancial managementPaymentHealth informaticsPublic economicsEconomicsEconomic growthMedicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Relatively little is known about how public financial management (PFM) systems and health financing policies align in low- and middle-income countries. This study assessed the alignment of PFM systems with health financing functions in the free maternal and child healthcare programme (FMCHP) of Enugu State, Nigeria. METHODS: Data were collected through quantitative and qualitative document review, and semi-structured, in-depth interview with 16 purposively selected policymakers involved in FMCHP. Data collection and analysis were by guided a framework for assessing alignment of PFM systems and health financing policies. Revenue and expenditure trend analyses were done using descriptive statistics and analysis of variance (ANOVA). Level of significance was set at ρ < 0.05. Qualitative data were analysed using a framework approach. RESULTS: The results showed that no more than 50% of FMCHP fund were collected despite that the promised fund remained unchanged since inception. Revenue generation significantly varied between 2010 and 2016 (ρ < 0.05). Level of pooling was limited by non-compliance with contribution rules, recurrent unauthorised expenditure and absence of expenditure caps. The unauthorised expenditure significantly varied between 2010 and 2016 (ρ < 0.05). Misalignment of budget monitoring and purchasing revealed absence of auditing and delays in provider payment. Refunds to providers significantly varied between 2010 and 2016 (ρ < 0.05) due to weak Steering Committee, weak vetting team, paper-based claims management and institutional conflicts between Ministry of Health and district-level officials. CONCLUSIONS: This study identified important lessons to align PFM systems and FMCHP. A realistic and evidence-informed budget and enforcement of contribution rules are critical to adequate and sustainable revenue generation. Clarity of roles for various FMCHP committees and use of clear resource allocation strategy would strengthen pooling and fund management. Enforcement of provider payment standards, regular auditing, and a stronger role for the parliament in budgetary processes are warranted.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.035
GPT teacher head0.308
Teacher spread0.273 · 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