Availability and Distribution of Emergency Obstetric Care Services in Karnataka State, South India: Access and Equity Considerations
Bibliographic record
Abstract
BACKGROUND: As part of efforts to reduce maternal deaths in Karnataka state, India, there has been a concerted effort to increase institutional deliveries. However, little is known about the quality of care in these healthcare facilities. We investigated the availability and distribution of emergency obstetric care (EmOC) services in eight northern districts of Karnataka state in south India. METHODS & FINDINGS: We undertook a cross-sectional study of 444 government and 422 private health facilities, functional 24-hours-a-day 7-days-a-week. EmOC availability and distribution were evaluated for 8 districts and 42 taluks (sub-districts) during the year 2010, based on a combination of self-reporting, record review and direct observation. Overall, the availability of EmOC services at the sub-state level [EmOC = 5.9/500,000; comprehensive EmOC (CEmOC) = 4.5/500,000 and basic EmOC (BEmOC) = 1.4/500,000] was seen to meet the benchmark. These services however were largely located in the private sector (90% of CEmOC and 70% of BemOC facilities). Thirty six percent of private facilities and six percent of government facilities were EmOC centres. Although half of eight districts had a sufficient number of EmOC facilities and all eight districts had a sufficient number of CEmOC facilities, only two-fifths of the 42 taluks had a sufficient number of EmOC facilities. With the private facilities being largely located in select towns only, the 'non-headquarter' taluks and 'backward' taluks suffered from a marked lack of coverage of these services. Spatial mapping further helped identify the clustering of a large number of contiguous taluks without adequate government EmOC facilities in northeastern Karnataka. CONCLUSIONS: In conclusion, disaggregating information on emergency obstetric care service availability at district and subdistrict levels is critical for health policy and planning in the Indian setting. Reducing maternal deaths will require greater attention by the government in addressing inequities in the distribution of emergency obstetric care services.
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 | 0.000 | 0.002 |
| 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".