Evidence map›Paper›PMID 30594198›Full record

ArticleBMC health services research2018

Bypassing health facilities in rural Mozambique: spatial, institutional, and individual determinants.

Jing Yao, Victor Agadjanian

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
13.1field-weighted citation impact, top 1% of its field
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

36 citing papers in PubMed, 75 citations in OpenAlex.

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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 at 2 institutions in 2 countries.

Jing YaoUrban Big Data Centre, School of Social and Political Sciences, University of Glasgow, 7 Lilybank Gardens, Glasgow, G12 8RZ, UK. Jing.Yao@glasgow.ac.uk.ORCID http://orcid.org/0000-0002-8677-8248
Victor AgadjanianDepartment of Sociology, University of California, Los Angeles, Los Angeles, CA, 90095-1551, USA.
University of California, Los Angeles · USUrban Big Data Centre · GB

Funding

Scientific and Technical CoreP2CHD041022 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HIRAM BELTRAN-SANCHEZ · 2016 to 2026
$6.9M
Childbearing Dynamics in Setting of High HIV Prevalence and Massive ART RolloutR01HD058365 · NICHD · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI AGADJANIAN, VICTOR · 2008 to 2012
$2.0M
Men's Migration and Women's HIV/AIDS Risks in MozambiqueR21HD048257 · NICHD · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI AGADJANIAN, VICTOR · 2006 to 2007
$305k
Economic and Social Research Council ES/P011020/1NICHD NIH HHS P2C HD041022NICHD NIH HHS R01 HD058365NICHD NIH HHS R21 HD048257the Eunice Kennedy Shriver National Institute of Child Health & Human Development R21HD048257; R01HD058365; R01HD058365-03S1
6 · The paper itself

Abstract

backgroundAccess to sexual and reproductive health (SRH) services is critical for such outcomes as pregnancy and birth, prenatal and neonatal mortality, maternal morbidity and mortality, and prevention of vertical transmission of infections like HIV. Health facilities are typically set up where they can efficiently serve the nearby targeted population. However, the actual utilization of health care can be complicated as people sometimes bypass the closest or nearby facilities for various reasons such as service quality. A better understanding of how people actually utilize health services can benefit future health resource allocation as well as health program planning.

methodsIn this study, we use prenatal care as an example of a basic, widely available service to investigate women's choice and bypassing of SRH facilities as well as potential influencing factors at the geographic, clinic, household, and individual levels. The data come from a population-based survey of women of reproductive age in rural Mozambique. The spatial pattern of utilization of health clinics for prenatal care is explored by geographical information system (GIS)-based spatial analysis. Logistic regression is fitted to test the hypotheses regarding the effect of distance, service quality, and household/individual-level factors on the bypassing of the nearest clinic.

resultsThe results indicate that most women living near clinics tend to utilize the closest facilities for prenatal care and those who travel farther mainly do so to seek better services. Further, for women who live far from a clinic (> 5.5 km), service quality still plays an important role in the facility bypassing while the effect of distance is no longer significant. The bypassing of nearest facility is also affected by individual characteristics such as age, HIV status, and household economic conditions.

conclusionsThe findings help to better understand health facility choice and bypassing in developing settings, in general, and in resource-limited Sub-Saharan settings, in particular. They offer valuable guidance for future health resource allocation and health service planning.

Indexed as

AdolescentAdultFemaleHealth Care SurveysHealth FacilitiesHealth Services AccessibilityHumansMaternal Health ServicesMozambiquePatient Acceptance of Health CarePregnancyPrenatal CareRural PopulationSpatial AnalysisYoung AdultGISHealthcare utilizationHospital bypass

Identifiers

PMID30594198
PMCPMC6311024
OpenAlexW2907612806

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.