Evidence map›Paper›PMID 33882968›Full record

SynthesisHuman resources for health2021

How can human resources for health interventions contribute to sexual, reproductive, maternal, and newborn healthcare quality across the continuum in low- and lower-middle-income countries? A systematic review.

Melese Girmaye Negero, David Sibbritt, Angela Dawson

Abstract readSystematic Review
In one paragraph

Synthesis in Human resources for health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
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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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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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

3 authors.

Melese Girmaye NegeroSchool of Public Health, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia. melesegirmaye@gmail.com.ORCID 0000-0002-1640-9631
David SibbrittSchool of Public Health, Faculty of Health, University of Technology Sydney, Sydney, Australia.
Angela DawsonSchool of Public Health, Faculty of Health, University of Technology Sydney, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWell-trained, competent, and motivated human resources for health (HRH) are crucial to delivering quality service provision across the sexual, reproductive, maternal, and newborn health (SRMNH) care continuum to achieve the 2030 Sustainable Development Goals (SDGs) maternal and neonatal health targets. This review aimed to identify HRH interventions to support lay and/or skilled personnel to improve SRMNH care quality along the continuum in low- and lower-middle-income countries (LLMICs).

methodsA structured search of CINAHL, Cochrane Library/trials, EMBASE, PubMed, SCOPUS, Web of Science, and HRH Global Resource Centre databases was undertaken, guided by the PRISMA framework. The inclusion criteria sought to identify papers with a focus on 1. HRH management, leadership, partnership, finance, education, and/or policy interventions; 2. HRH interventions' impact on two or more quality SRMNH care packages across the continuum from preconception to pregnancy, intrapartum and postnatal care; 3. Skilled and/or lay personnel; and 4. Reported primary research in English from LLMICs. A deductive qualitative content analysis was employed using the World Health Organization-HRH action framework.

resultsOut of identified 2157 studies, 24 intervention studies were included in the review. Studies where ≥ 4 HRH interventions had been combined to target various healthcare system components, were more effective than those implementing ≤ 3 HRH interventions. In primary care, HRH interventions involving skilled and lay personnel were more productive than those involving either skilled or lay personnel alone. Results-based financing (RBF) and its policy improved the quality of targeted maternity services but had no impact on client satisfaction. Local budgeting, administration, and policy to deliver financial incentives to health workers and improve operational activities were more efficacious than donor-driven initiatives. Community-based recruitment, training, deployment, empowerment, supportive supervision, access to m-Health technology, and modest financial and non-financial incentives for community health workers (CHWs) improved the quality of care continuum. Skills-based, regular, short, focused, onsite, and clinical simulation, and/or mobile phone-assisted in-service training of skilled personnel were more productive than knowledge-based, irregular, and donor-funded training. Facility-based maternal and perinatal death reviews, coupled with training and certification of skilled personnel, positively affected SRMNH care quality across the continuum. Preconception care, an essential component of the SRMNH care continuum, lacks studies and services in LLMICs.

conclusionsWe recommend maternal and perinatal death audits in all health facilities; respectful, woman-centered care as a critical criterion of RBF initiatives; local administration of health worker allowances and incentives; and integration of CHWs into the healthcare system. There is an urgent need to include preconception care in the SRMNH care continuum and studies in LLMICs.

Indexed as

Community Health WorkersDeveloping CountriesFemaleHumansInfant, NewbornPovertyPregnancyQuality of Health CareWorkforceAnd newborn healthDeductive qualitative content analysisHuman resources for health interventionLay personnelLow- and lower-middle-income countriesMaternalQuality of careReproductiveSexualSkilled personnelThe continuum of care

Identifiers

PMID33882968
PMCPMC8061056

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.