Outcomes for the First Year of Ontario's Birth Center Demonstration Project
Bibliographic record
Abstract
INTRODUCTION: In 2014, Ontario opened 2 stand-alone midwifery-led birth centers. Using mixed methods, we evaluated the first year of operations for quality and safety, client experience, and integration into the maternity care community. This article reports on our study of safety and quality of care. METHODS: This descriptive evaluation focused on women admitted to a birth center at the beginning of labor. For context, we matched this cohort (on a 1:4 basis) with similar low-risk midwifery clients giving birth in a hospital. Data sources included Ontario's Better Outcomes Registry and Network (BORN) Information System, the Canadian Institute for Health Information, Ontario census data, and birth center records. RESULTS: Of 495 women admitted to a birth center, 87.9% experienced a spontaneous vaginal birth, regardless of the eventual location of birth, and 7.7% had a cesarean birth. The transport rate to a hospital was 26.3%. When compared with midwifery clients with a planned hospital birth, rates of intervention (epidural analgesia, labor augmentation, assisted vaginal birth, and cesarean birth) were significantly lower in the planned birth center group, even when controlled for previous cesarean birth and body mass index. Markers of potential morbidity were identified in about 10% of birth center births; however, there were no short-term health impacts up to discharge from midwifery care at 6 weeks postpartum. Care was low in intervention and safe (minimal negative outcomes and transport rates comparable to the literature). DISCUSSION: In the first year of operation, care was consistent with national guidelines, and morbidity and mortality rates and intervention rates were low for women with low-risk pregnancies seeking a low-intervention approach for labor and birth. Further evaluation to confirm these findings is required as the number of births grows.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".