Evidence map›Paper›PMID 36348362›Full record

Observational studyBMC pregnancy and childbirth2022

The impact of professional midwives and mentoring on the quality and availability of maternity care in government sub-district hospitals in Bangladesh: a mixed-methods observational study.

Rondi Anderson, Anna Williams, Nicole Jess, Jonathan M Read, Mark Limmer

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.7field-weighted citation impact, top 4% 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

13 citing papers in PubMed, 15 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

5 authors at 2 institutions in 2 countries.

Rondi AndersonUNFPA, Dhaka, Bangladesh. sakapana@gmail.com.
Anna WilliamsData, Design + Writing, Oregon, USA.
Nicole JessCenter for Statistical Training & Consulting, Measurement & Quantitative Methods, Michigan State University, Michigan, USA.
Jonathan M ReadCentre for Health Inequalities Research, Division of Health Research, Faculty of Health and Medicine, Lancaster University, Lancaster, UK.
Mark LimmerCentre for Health Inequalities Research, Division of Health Research, Faculty of Health and Medicine, Lancaster University, Lancaster, UK.
Lancaster University · GBMichigan State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study compared government sub-district hospitals in Bangladesh without globally standard midwives, with those with recently introduced midwives, both with and without facility mentoring, to see if the introduction of midwives was associated with improved quality and availability of maternity care. In addition, it analysed the experiences of the newly deployed midwives and the maternity staff and managers that they joined.

methodsThis was a mixed-methods observational study. The six busiest hospitals from three pre-existing groups of government sub-district hospitals were studied; those with no midwives, those with midwives, and those with midwives and mentoring. For the quantitative component, observations of facility readiness (n = 18), and eight quality maternity care practices (n = 641) were carried out using three separate tools. Willing maternity staff (n = 237) also completed a survey on their knowledge, perceptions, and use of the maternity care interventions. Descriptive statistics and logistic regression were used to identify differences between the hospital types. The qualitative component comprised six focus groups and 18 interviews involving midwives, other maternity staff, and managers from the three hospital types. Data were analysed using an inductive cyclical process of immersion and iteration to draw out themes. The quantitative and qualitative methods complemented each other and were used synergistically to identify the study's insights.

resultsQuantitative analysis found that, of the eight quality practices, hospitals with midwives but no mentors were significantly more likely than hospitals without midwives to use three: upright labour (94% vs. 63%; OR = 22.57, p = 0.001), delayed cord clamping (88% vs. 11%; OR = 140.67, p < 0.001), skin-to-skin (94% vs. 13%; OR = 91.21, p < 0.001). Hospitals with mentors were significantly more likely to use five: ANC card (84% vs. 52%; OR = 3.29, p = 0.002), partograph (97% vs. 14%; OR = 309.42, p = 0.002), upright positioning for labour (95% vs. 63%; OR = 1850, p < 0.001), delayed cord clamping (98% vs. 11%; OR = 3400, p = 0.003), and skin-to-skin contact following birth (93% vs. 13%; OR = 70.89, p < 0.001) Qualitative analysis identified overall acceptance of midwives and the transition to improved quality care; this was stronger with facility mentoring. The most resistance to quality care was expressed in facilities without midwives. In facilities with midwives and mentoring, midwives felt proud, and maternity staff conveyed the greatest acceptance of midwives.

conclusionFacilities with professional midwives had better availability and quality of maternity care across multiple components of the health system. Care quality further improved with facility mentors who created enabling environments, and facilitated supportive relationships between existing maternity staff and managers and the newly deployed midwives.

Indexed as

Maternal Health ServicesMentoringMidwiferyAttitude of Health PersonnelBangladeshFemaleGovernmentHospitals, DistrictHumansPregnancyBangladeshHealth system strengtheningICM standard midwivesMentorshipQuality of careRespectful maternity care

Identifiers

PMID36348362
PMCPMC9644636
OpenAlexW4308509783

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.