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Record W3012509810 · doi:10.1186/s12913-020-5065-2

Assessing quality of newborn care at district facilities in Malawi

2020· article· en· W3012509810 on OpenAlexafffund
Kondwani Kawaza, Mai‐Lei Woo Kinshella, Tamanda Hiwa, Jenala Njirammadzi, Mwai Banda, Marianne Vidler, Laura Newberry, Alinane Linda Nyondo‐Mipando, Queen Dube, Elizabeth Molyneux, David A. Goldfarb

Bibliographic record

VenueBMC Health Services Research · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchGlobal Affairs CanadaInternational Development Research Centre
KeywordsMedicineHealth administrationHealth careNursing researchHealth facilityLikert scaleQuality (philosophy)Health informaticsEnvironmental healthPublic healthNursingMedical emergencyPopulationEconomic growthHealth services

Abstract

fetched live from OpenAlex

BACKGROUND: Malawi is celebrated as one of the few countries in sub-Saharan Africa to meet the Millennium Development Goal of reducing under-5 mortality by two-thirds between 1990 and 2015. However, within this age range neonatal mortality rates are the slowest to decline, even though rates of facility births are increasing. Examining the quality of neonatal care at district-level facilities where most deliveries occur is warranted. OBJECTIVE: The objective of this paper is to evaluate the quality of neonatal care in three district hospitals and one primary health centre in southern Malawi as well as to report the limitations and lessons learned on using the WHO integrated quality of care assessment tool. METHODS: These facility assessments were part of the "Integrating a neonatal healthcare package for Malawi" project, a part of the Innovating for Maternal and Child Health in Africa (IMCHA) initiative. The WHO integrated quality of care assessment tool was used to assess quality of care and availability and quantity of supplies and resources. The modules on infrastructure, neonatal care and labour and delivery were included. Facility assessments were administered in November 2017 and aspects of care were scored on a Likert scale from one to five (a score of 5 indicating compliance with WHO standards of care; one as lowest indicating inadequate care). RESULTS: The continuum of labour, delivery and neonatal care were assessed to identify areas that required improvements to meet standards of care. Critical areas for improvements included infection control (mean score 2.9), equipment, supplies and setup for newborn care in the labor ward (2.3), in the surgical theater (3.3), and nursery (3.4 nursery facilities, 3.0 supplies and equipment), as well as for management of sick newborns (3.2), monitoring and follow-up (3.6). Only one of the 12 domains, laboratory, met the standards of care with only minor improvements needed (4.0). CONCLUSION: The WHO integrated quality of care assessment tool is a validated tool that can shed light on the complex quality of care challenges faced by district-level health facilities. The results reveal that the quality of care needs improvement, particularly for sick and vulnerable newborns.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.179
GPT teacher head0.498
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations39
Published2020
Admission routes2
Has abstractyes

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