Low-volume obstetrics. Characteristics of family physicians' practices in Alberta.
Bibliographic record
Abstract
OBJECTIVE: To compare the obstetric practices of family physicians who attended fewer than 25 births per year (low-volume) with the practices of family physicians who attended more than 25 births per year (high-volume) and the practices of obstetricians. DESIGN: Retrospective cohort study using data from administrative databases. SETTING: Alberta. PARTICIPANTS: All physicians who provided intrapartum care between April 1, 1997, and March 31, 2000. MAIN OUTCOME MEASURES: Type of delivery, size of hospitals where deliveries took place, characteristics of patients, and number of medical interventions. RESULTS: Of 1026 family physicians, 543 (53%) were low-volume providers of intrapartum care. In 1997-1998, low-volume family physicians (LVFPs) attended 24% of all vaginal and cesarean births attended by family physicians; by 1998-1999, that percentage had decreased to 9%; and by 1999-2000, to 5%. In contrast, the number of births attended by all family physicians remained relatively constant at 43% during the 3 years. In hospitals that had fewer than 50 deliveries a year, LVFPs attended almost half the births. Although LVFPs did fewer medical inductions, vacuum extractions, and epidural anesthetics and more forceps extractions, episiotomies, and cesarean sections than high-volume family physicians (HVFPs), the differences between their practices were much smaller than the differences between all family physicians' practices and the practices of obstetricians (who treat higher-risk mothers and newborns). CONCLUSION: The decrease in LVFPs' obstetric practices could make a pronounced difference at smaller hospitals where most low-volume practice occurs.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".