Implementing the World Health Organization safe childbirth checklist in a district Hospital in Rwanda: a pre- and post-intervention study
Bibliographic record
Abstract
BACKGROUND: Worldwide maternal mortality remains high, with approximately 830 maternal deaths occurring each day. About 90% of these deaths occur in low-income countries. Evidenced-based essential birth practices administered during routine obstetrical care and childbirth are key to reducing maternal and neonatal deaths. The WHO Safe Childbirth Checklist (SCC) is a low-cost tool designed to ensure birth attendants perform 29 essential birth practices (EBP) at four critical periods in the birth continuum. This study aimed to evaluate compliance with EBP in Masaka District Hospital both before and after the implementation of the WHO-SCC. METHODS: This quality improvement project took place in the Masaka District Hospital in Rwanda. Observations of the 29 EBPs were done before and after WHO SCC implementation. The implementation process consisted of providing training in the use of the checklist to all clinical staff and posting SCC posters at different locations in the maternity unit. RESULTS: = 0.005). Significant improvements were seen in 11 out of 29 EBPs. CONCLUSION: The implementation of the WHO SCC improved the overall EBP compliance rate in Masaka District Hospital. Determining the root cause of low compliance rate of some EBP may allow for more successful implementation of EBP interventions in the future. After further study, the SCC should be considered for scale up.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".