Facility-Based Maternal Death in Western Africa: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: For exploring maternal death, supply and demand-side factors can be characterized by the three delays model developed by Thaddeus and Maine (1994). The model comprises delay in deciding to seek care (delay 1), delay in reaching the health facility (delay 2), and delay in receiving quality care once at the health facility (delay 3). Few studies have comprehensively dealt with the health systems delays that prevent the receipt of timely and appropriate obstetric care once a woman reaches a health facility (phase III delays). The objective of the present study was to identify facility-level barriers in West African health facilities. METHODS: Electronic databases (Medline, cumulative index to nursing and allied health literature, Centre for Agriculture and Biosciences International Global Health, EMBASE) were searched to identify original research articles from 1996 to 2016. Search terms (and synonyms) related to (1) maternal health care (e.g., obstetric care, perinatal care, maternal health services); (2) facility level (e.g., maternity unit, health facility, phase III, hospital); and (3) Western Africa (e.g., Nigeria, Burkina Faso) were combined. This review followed the preferred reporting items for systematic reviews and meta-analyses. RESULTS: Of the 2103 citations identified, 13 studies were eligible. Studies were conducted in Nigeria, Burkina Faso, Gambia, Guinea, Senegal, and Sierra Leone. 30 facility-level barriers were identified and grouped into 6 themes (human resources, supply and equipment, referral-related, infrastructure, cost-related, patient-related). The most obvious barriers included staff shortages, lack of maternal health services and procedures offered to patients, and lack of necessary medical equipment and supplies in the health-care facilities. CONCLUSION: This review emphasizes that phase I and phase II barriers are not the only factors preventing women from accessing proper emergency obstetric care. Health-care facilities in Western Africa are inadequately equipped to handle the obstetric needs of patients. Supply-side barriers must be addressed to reduce maternal mortality in the region.
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 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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".