Enhancing maternal and newborn outcomes in Ghana: a comprehensive randomized controlled trial evaluation of obstetric triage effectiveness and midwives training
Bibliographic record
Abstract
BACKGROUND: Ghana has made progress in maternal and newborn health, but significant challenges remain, with maternal mortality at 263 per 100,000 live births and neonatal mortality at 22.8 per 1,000 live births. The Obstetric Triage Implementation Package (OTIP), which includes rapid triage protocols and midwife-led peer training, aims to improve the quality of care in a context of scarce resources. This study evaluates the effectiveness of OTIP in improving maternal and neonatal outcomes and assesses the mechanisms behind the observed effects. METHODS: A cluster randomized controlled trial will assess the impact of OTIP in 25 high-volume hospitals across Ghana during the final phase of its national roll-out. Hospitals will be randomized into early and late intervention groups. A complementary regression discontinuity analysis will assess the impact of OTIP at the national level. Primary outcomes include process improvements and maternal and neonatal outcomes. Secondary outcomes will assess midwives' knowledge and attitudes. Data sources include primary surveys of 1,250 mother-newborn pairs and 750 midwives, and administrative records from the Ghana Health Service, Ministry of Health. DISCUSSION: A rigorous evaluation of OTIP would be crucial, not only to assess the effectiveness of a program in which the Government of Ghana is already investing, but also to assess the potential applicability of this training model to other areas, and to contribute to the academic literature by filling gaps in our understanding of how different training methods can overcome barriers to the diffusion of new practices. TRIAL REGISTRATION: Study protocols have been approved by the Ghana Health Service (GHS) Ethics Review Committee (GHS-ERC: 022/05/24). TRIAL REGISTRATION NUMBER: ISRCTN15629047. Registered on 04/11/2024 while participant enrollment was ongoing, https://doi.org/10.1186/ISRCTN15629047 . The study is hence retrospectively registered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".