Population‐based cohort study of hospital delivery volume, geographic accessibility, and obstetric outcomes
Bibliographic record
Abstract
OBJECTIVE: To determine associations between geographic accessibility, delivery volume, and obstetric outcomes. METHODS: Population-based cohort study of linked hospital administrative, census, and geospatial data (2006-2009) from all Canadian jurisdictions except Quebec. Perinatal mortality and major maternal morbidity/mortality were compared across categories of road distance and hospital delivery volume. RESULTS: Among 820 761 mothers delivering 827 504 neonates, travel distance had minimal effect on perinatal mortality. Compared with mothers travelling 0-9 km, the odds of adverse maternal outcomes was decreased for women travelling modest distances (20-49 km, odds ratio, 0.80 [95% confidence interval, 0.75-0.86]), and increased thereafter (50-99 km, 0.99 [0.89-1.10]; 200-299 km, 1.44 [1.10-1.87]; >400 km, 2.22 [1.06-4.63]). Relative to high-volume hospitals (>2500 deliveries/year), adverse maternal outcomes were less likely for hospitals with 1000-2499 (0.90 [0.86-0.95]), and roughly equivalent for hospitals with 200-499 (1.34 [1.22-1.48]) and 500-999 (1.27 [1.17-1.39]) deliveries/year. Odds of perinatal mortality ranged from 1.04 (0.73-1.49; 100-199 deliveries/year) to 1.50 (1.04-2.16; 50-99 deliveries/year); the pattern did not suggest causality. CONCLUSION: Maternal outcomes worsen when travel distance is greater than 200 km, and improve when delivery volume exceeds 1000 deliveries per year.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".