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Record W7064980681

Delivery Care at Mangochi District Hospital, Malawi

2020· dissertation· en· W7064980681 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSkemman · 2020
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)LaggingChildbirthBirth attendantDistrict hospitalHealth careMillennium Development GoalsPopulationMaternity careStandardized mortality ratio
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Maternal mortality is a significant disease burden in many countries. Despite global progress, it in unevenly spread with sub-Saharan Africa particularly lagging behind. The Sustainable Development Goal 3.1 aims for maternal mortality ratio (MMR) reduction to less than 70 maternal deaths per 100,00 live births, and all deliveries to be assisted by skilled birth attendants (SBA). The aim of this study was to identify key challenges in labour and delivery care in a low-income sub-Saharan setting.
\nMethods: The study was conducted in Mangochi District, Malawi. It included participant observation to better understand the setting of delivery care in the district, in particular at the new maternity wing at the Mangochi District Hospital (MDH) which was inaugurated in January 2019. The Health Management Information System (HMIS) in Malawi provided district level maternity care data for the years 2015-2019. Two additional datasets were created based on registration books in the labour ward and its surgical theatre at MDH. These include all delivery services at MDH from 19 February to 17 March 2020. Interviews were conducted with eight staff members at the maternity wing. The data were analysed in RStudio and the Mangochi Health Research Committee granted the study a permission.
\nResults: From 2015 to 2019, on average about two out of three deliveries in Mangochi District took place in health facilities; the Caesarean-section (C-section) rate was 4%. A quarter of the district’s institutional deliveries and nearly two thirds of the district’s C-sections took place at MDH. Institutional MMR in the district decreased from 162 to 64 per 100,000 live births in the period. MDH registers annually on average 34 maternal deaths. During the data collection period in 2020, 797 women received delivery care at MDH; 27 of the women had delivered before admission out of whom just less than one third delivered by SBA. All women who delivered at MDH were assisted during the delivery with SBA. Out of all admissions, 18% had obstetric complications and 6% received emergency obstetric care; about one in five of deliveries at MDH were C-sections. Nine out of 10 operations at the maternity wing were C-sections and 97% of the operations were emergencies. Overall, the staff were happy with the new facility, staffing had improved, and patients were better accommodated. However, having only one surgical theatre caused delays for C-sections. Further, lack of equipment was reported as well as deficient maintenance, especially for anaesthesia. Supply of drugs and single use items was also often reported as insufficient and unaccountable. Although teamwork was good and staffing had improved, there was still shortage of anaesthetists, Clinical Officers, and nurses.
\nConclusion: To decrease maternal mortality rate still further in Mangochi District, SBA needs to be improved with better and timely access to C-sections. While the new maternity wing at MDH was a quality improvement in delivery services, the option for a second theatre should be considered, coupled with improved maintenance, better staffing and stable supply of equipment and drugs to further decrease maternal mortality ratio in Mangochi District. These results may have implications for other similar settings.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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