Emergency obstetric care in developing countries: impact of guidelines implementation in a community hospital in Senegal
Bibliographic record
Abstract
OBJECTIVE: To evaluate, with volunteer professionals in a resource-poor setting, an approach of audit and feedback to promote local implementation of emergency obstetric guidelines. DESIGN: Triple cohort observational time series study. SETTING: A 46-bed obstetric unit in an academic-affiliated community hospital in Senegal. POPULATION: All pregnant women with haemorrhagic and hypertensive complications who were admitted to the maternity unit during the study periods. METHODS: To assess the benefits of guidelines implementation, maternal outcomes during the intervention period were compared with those occurring in two one-year periods when staff daily supervision was the main potentially effective action on clinical management. MAIN OUTCOME MEASURES: The intervention strategy was criteria-based audits with regular feedback over a one-year period. The clinical focus was haemorrhage and hypertension the most frequent causes of maternal death in the study population. Hospital charts were audited by external reviewers. The primary outcome was the case fatality rate (CFR) among patients with haemorrhage and hypertension. RESULTS: There was an increase in morbidity diagnoses during the intervention period. In addition, there was a marked increase in obstetric interventions, especially for transfusions and caesarean deliveries. Patients characteristic-adjusted case fatality decreased by 53% between baselines I and II and during the intervention period by 33% and 24%, compared with baseline periods I and II, respectively. Outcome improvements were different for haemorrhage and hypertension. CONCLUSION: While staff daily supervision may have improved maternal outcome before the intervention period, audit and feedback produced marked effects on emergency obstetric care, specially for complications requiring highly trained management (e.g. pre-eclampsia). Audit and feedback are one of the potentially effective guidelines implementation strategies that should be considered for further studies in resource-poor health facilities.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".