Health facilities’ capability to provide comprehensive postabortion care in Sub‐Saharan Africa: Evidence from a cross‐sectional survey across 210 high‐volume facilities
Bibliographic record
Abstract
OBJECTIVE: To evaluate the capability of high-volume comprehensive emergency obstetric care (CEmOC) health facilities on the provision of comprehensive postabortion care (PAC) in Sub-Saharan Africa and to determine the frequency of women with severe abortion-related complications in high capability facilities. METHODS: A cross-sectional analysis conducted across 11 countries in Sub-Saharan Africa, using facility-level information from the World Health Organization (WHO) Multi-Country Survey on Abortion-related morbidity (MCS-A) between 2017 and 2018. PAC signal functions were adapted to assess facilities' capability to deliver comprehensive PAC through infrastructure, standard comprehensive capability, and extended comprehensive capability to provide PAC. The percentage of facilities with each signal function and distribution of facilities by number of signal functions were calculated for the three capability categories. Distribution of severe abortion complications by facility capability score was assessed. RESULTS: Of 210 high-volume CEmOC facilities included, 47.9% (n = 100) had capability to provide all facility infrastructure signal functions, 54.4% (n = 105) for standard comprehensive PAC, reducing to 17.7% (n = 34) for extended comprehensive PAC capability. Overall, there were gaps in extended capabilities including availability of a functioning ICU (available in 37.3% of facilities) and providers 24/7 (65.5% of facilities reported an obstetrician available 24/7 dropping to 41.3% for anesthesiologists). Facilities' PAC capability varied across regions. Overall, 34.6% (n = 614) of women with severe abortion-related complications were treated in facilities with the maximum capability score for extended comprehensive PAC. CONCLUSION: Although high levels of capability to provide abortion-related care for most signal functions were evident, significant gaps that impact on the management of severe abortion-related complications remain, particularly related to extended facility capabilities including specialized human resources and ICU.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".