Emergency obstetric and newborn care signal functions in public and private facilities in Bangladesh
Bibliographic record
Abstract
BACKGROUND: Signal functions for emergency obstetric and newborn care (EmONC) are the major interventions for averting maternal and neonatal mortalities. Readiness of the facilities is essential to provide all the basic and comprehensive signal functions for EmONC to ensure emergency services from the designated facilities. The study assessed population coverage and availability of EmONC services in public and private facilities in Bangladesh. METHODS: An assessment was conducted in all the public and private facilities providing obstetric care in to in-patients 24 districts. Data were collected on the performance of signal functions for EmONC from the study facilities in the last three months prior to the date of assessment. Trained data-collectors interviewed the facility managers and key service providers, along with review of records, using contextualized tools. Population coverage of signal functions was assessed by estimating the number of facilities providing the signal functions for EmONC compared to the United Nations requirements. Availability was assessed in terms of the proportion of facilities providing the services by type of facilities and by district. RESULTS: Caesarean section (CS) delivery and blood transfusion (BT) services (the two major components of comprehensive EmONC) were respectively available in 6.4 (0.9 public and 5.5 private) and 5.6 (1.3 public and 4.3 private) facilities per 500,000 population. The signal functions for basic EmONC, except two (parental anticonvulsants and assisted vaginal delivery), were available in a minimum of 5 facilities (public and private sectors combined) per 500,000 population. A major inter-district variation in the availability of signal functions was observed in each public- and private-sector facility. Among the various types of facilities, only the public medical college hospitals had all the signal functions. The situation was poor in other public facilities at the district and sub-district levels as well as in private facilities. CONCLUSIONS: In the public sector, CS delivery and BT services were available in the minimum required number of facilities. However, to ensure basic EmONC services, participation of the private sector is necessary. Public-private partnership should be promoted for nationwide coverage of signal functions for EmONC in Bangladesh.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".