Insights into an innovative point of care ultrasound curriculum for Ontario primary maternity care providers
Bibliographic record
Abstract
Point of care ultrasound (POCUS) has increasingly been used by midwives worldwide. In 2018, the scope of midwifery care in Ontario was expanded to include POCUS to allow practitioners to provide more comprehensive care. In response to the scope expansion, a new continuing POCUS education course was created in collaboration with faculty and clinicians from obstetrics, midwifery, and medical radiation sciences. The continuing education sonography course focused on fostering the knowledge, skills and judgment Ontario midwives required to safely perform these new POCUS skills. The course included online modules, a two-day hands-on bootcamp workshop, and a clinical practicum under the supervision of a sonographer to confirm competency across the three trimesters of pregnancy. The first cohort of 17 learners completed the course in Fall 2019, the new curriculum was well received by learners for its many benefits into learning and applying bedside sonography to clinical care. This paper outlines our process for POCUS curriculum development and implementation in pregnancy care. This POCUS continuing education course should continue to be offered in the future to give more practitioners the ability to perform point of care pregnancy scans.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".