Linking household and health facility surveys to assess obstetric service availability, readiness and coverage: evidence from 17 low- and middle-income countries
Bibliographic record
Abstract
BACKGROUND: Improving access and quality of obstetric service has the potential to avert preventable maternal, neonatal and stillborn deaths, yet little is known about the quality of care received. This study sought to assess obstetric service availability, readiness and coverage within and between 17 low- and middle-income countries. METHODS: We linked health facility data from the Service Provision Assessments and Service Availability and Readiness Assessments, with corresponding household survey data obtained from the Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Based on performance of obstetric signal functions, we defined four levels of facility emergency obstetric care (EmOC) functionality: comprehensive (CEmOC), basic (BEmOC), BEmOC-2, and low/substandard. Facility readiness was evaluated based on the direct observation of 23 essential items; facilities "ready to provide obstetric services" had ≥20 of 23 items available. Across countries, we used medians to characterize service availability and readiness, overall and by urban-rural location; analyses also adjusted for care-seeking patterns to estimate population-level coverage of obstetric services. RESULTS: Of the 111 500 health facilities surveyed, 7545 offered obstetric services and were included in the analysis. The median percentages of facilities offering EmOC and "ready to provide obstetric services" were 19% and 10%, respectively. There were considerable urban-rural differences, with absolute differences of 19% and 29% in the availability of facilities offering EmOC and "ready to provide obstetric services", respectively. Adjusting for care-seeking patterns, results from the linking approach indicated that among women delivering in a facility, a median of 40% delivered in facilities offering EmOC, and 28% delivered in facilities "ready to provide obstetric services". Relatively higher coverage of facility deliveries (≥65%) and coverage of deliveries in facilities "ready to provide obstetric services" (≥30% of facility deliveries) were only found in three countries. CONCLUSIONS: The low levels of availability, readiness and coverage of obstetric services documented represent substantial missed opportunities within health systems. Global and national efforts need to prioritize upgrading EmOC functionality and improving readiness to deliver obstetric service, particularly in rural areas. The approach of linking health facility and household surveys described here could facilitate the tracking of progress towards quality obstetric care.
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 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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 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".