Evidence map›Paper›PMID 29937891›Full record

ArticleAfrican health sciences2017

Assessing regional variations in the effect of the removal of user fees on facility-based deliveries in rural Zambia.

Chama-Chiliba Chitalu, Koch Steven

Abstract read
In one paragraph

Article in African health sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Examining the implementation of the Linda Mama free maternity program in Kenya.The International journal of health planning and management · 2021
    Article
  4. Observational
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Chama-Chiliba ChitaluUniversity of Zambia, Department of Economics; University of Pretoria, Department of Economics.
Koch StevenUniversity of Pretoria, Department of Economics.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMaternal health remains a concern in sub-Saharan Africa, where maternal mortality averages 680 per 100,000 live births and almost 50% of the approximately 350,000 annual maternal deaths occur. Improving access to skilled birth assistance is paramount to reducing this average, and user fee reductions could help.

objectiveThe aim of this research was to analyse the effect of user fee removal in rural areas of Zambia on the use of health facilities for childbirth. The analysis incorporates supply-side factors, including quantitative measures of service quality in the assessment.

methodThe analysis uses quarterly longitudinal data covering 2003 (q1)-2008 (q4) and controls for unobserved heterogeneity, spatial dependence and quantitative supply-side factors within an Interrupted Time Series design.

resultsUser fee removal was found to initially increase aggregate facility-based deliveries. Drug availability, the presence of traditional birth attendants, social factors and cultural factors also influenced facility-based deliveries at the national level.

conclusionAlthough user fees matter, to a degree, service quality is a relatively more important contributor to the promotion of facility-based deliveries. Thus, in the short-term, strengthening and improving community-based interventions could lead to further increases in facility-based deliveries.

Indexed as

Fees, MedicalHealth Care CostsDelivery, ObstetricFemaleHealth FacilitiesHumansMaternal Health ServicesMaternal MortalityParturitionPregnancyRural HealthRural PopulationZambiafacility based deliveriesMaternal careruraluser feesZambia

Identifiers

PMID29937891
PMCPMC5870268

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.