Evidence map›Paper›PMID 36726073›Full record

ArticleBMC pregnancy and childbirth2023

A qualitative evaluation and conceptual framework on the use of the Birth weight and Age-at-death Boxes for Intervention and Evaluation System (BABIES) matrix for perinatal health in Uganda.

Michelle M Dynes, Gaea A Daniel, Valerie Mac, Brenda Picho, Alice Asiimwe, Agnes Nalutaaya, Gregory Opio, Vincent Kamara, Frank Kaharuza, Florina Serbanescu

Open access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Review
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

10 authors at 8 institutions in 3 countries.

Michelle M Dynes *Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA, USA. wvu8@cdc.gov.
Gaea A Daniel *Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.
Valerie Mac *Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.
Brenda PichoInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Alice AsiimweBaylor College of Medicine Children's Foundation, Kampala, Uganda.
Agnes NalutaayaInfectious Diseases Institute, Makerere University, Kampala, Uganda.
Gregory OpioBaylor College of Medicine Children's Foundation, Kampala, Uganda.
Vincent KamaraUganda Ministry of Health, Kampala, Uganda.
Frank KaharuzaKampala International University, Western Campus, Ishaka Bushenyi, Uganda.
Florina SerbanescuDivision of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Baylor College of Medicine Children’s Foundation · UGEmory University · USCenters for Disease Control and Prevention · USInfectious Diseases Institute · UGKampala International University · UGMakerere University · UGMinistry of Health · UGThe Centers · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPerinatal mortality (newborn deaths in the first week of life and stillbirths) continues to be a significant global health threat, particularly in resource-constrained settings. Low-tech, innovative solutions that close the quality-of-care gap may contribute to progress toward the Sustainable Development Goals for health by 2030. From 2012 to 2018, the Saving Mothers, Giving Life Initiative (SMGL) implemented the Birth weight and Age-at-Death Boxes for Intervention and Evaluation System (BABIES) matrix in Western Uganda. The BABIES matrix provides a simple, standardized way to track perinatal health outcomes to inform evidence-based quality improvement strategies.

methodsIn November 2017, a facility-based qualitative evaluation was conducted using in-depth interviews with 29 health workers in 16 health facilities implementing BABIES in Uganda. Data were analyzed using directed content analysis across five domains: 1) perceived ease of use, 2) how the matrix was used, 3) changes in behavior or standard operating procedures after introduction, 4) perceived value of the matrix, and 5) program sustainability.

resultsValues in the matrix were easy to calculate, but training was required to ensure correct data placement and interpretation. Displaying the matrix on a highly visible board in the maternity ward fostered a sense of accountability for health outcomes. BABIES matrix reports were compiled, reviewed, and responded to monthly by interprofessional teams, prompting collaboration across units to fill data gaps and support perinatal death reviews. Respondents reported improved staff communication and performance appraisal, community engagement, and ability to track and link clinical outcomes with actions. Midwives felt empowered to participate in the problem-solving process. Respondents were motivated to continue using BABIES, although sustainability concerns were raised due to funding and staff shortages.

conclusionsDistrict-level health systems can use data compiled from the BABIES matrix to inform policy and guide implementation of community-centered health practices to improve perinatal heath. Future work may consider using the Conceptual Framework on Use of the BABIES Matrix for Perinatal Health as a model to operationalize concepts and test the impact of the tool over time.

Indexed as

Maternal DeathMaternal Health ServicesPerinatal DeathBirth WeightFemaleHumansInfantInfant, NewbornParturitionPregnancyUgandaBABIES matrixBirth weightMaternal healthNeonatal healthNewbornPerinatal mortalitySaving mothers, giving lifeStillbirthsSurveillance systemsUganda

Identifiers

PMID36726073
PMCPMC9890791
OpenAlexW4318924229

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.