Obstetric care navigation: results of a quality improvement project to provide accompaniment to women for facility-based maternity care in rural Guatemala
Bibliographic record
Abstract
BACKGROUND: Many maternal and perinatal deaths in low-resource settings are preventable. Inadequate access to timely, quality care in maternity facilities drives poor outcomes, especially where women deliver at home with traditional birth attendants (TBA). Yet few solutions exist to support TBA-initiated referrals or address reasons patients frequently refuse facility care, such as disrespectful and abusive treatment. We hypothesised that deploying accompaniers-obstetric care navigators (OCN)-trained to provide integrated patient support would facilitate referrals from TBAs to public hospitals. METHODS: This project built on an existing collaboration with 41 TBAs who serve indigenous Maya villages in Guatemala's Western Highlands, which provided baseline data for comparison. When TBAs detected pregnancy complications, families were offered OCN referral support. Implementation was guided by bimonthly meetings of the interdisciplinary quality improvement team where the OCN role was iteratively tailored. The primary process outcomes were referral volume, proportion of births receiving facility referral, and referral success rate, which were analysed using statistical process control methods. RESULTS: Over the 12-month pilot, TBAs attended 847 births. The median referral volume rose from 14 to 27.5, meeting criteria for special cause variation, without a decline in success rate. The proportion of births receiving facility-level care increased from 24±6% to 62±20% after OCN implementation. Hypertensive disorders of pregnancy and prolonged labour were the most common referral indications. The OCN role evolved to include a number of tasks, such as expediting emergency transportation and providing doula-like labour support. CONCLUSIONS: OCN accompaniment increased the proportion of births under TBA care that received facility-level obstetric care. Results from this of obstetric care navigation suggest it is a feasible, patient-centred intervention to improve maternity care.
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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 | 0.002 | 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".