An overview of Internal Medicine Point-of-Care Ultrasound rotations in Canada
Bibliographic record
Abstract
Abstract Background Point-of-care ultrasound (POCUS) is a growing part of internal medicine training programs. Dedicated POCUS rotations are emerging as a particularly effective tool in POCUS training, allowing for longitudinal learning and emphasizing both psychomotor skills and the nuances of clinical integration. In this descriptive paper, we set out to review the state of POCUS rotations in Canadian Internal Medicine training programs. Results We identify five programs currently offering a POCUS rotation. These rotations are offered over two to thirteen blocks each year, run over one to four weeks and support one to four learners. Across all programs, these rotations are set up as a consultative service that offers POCUS consultation to general internal medicine inpatients, with some extension of scope to the hospitalist service or surgical subspecialties. The funding model for the preceptors of these rotations is predominantly fee-for-service using consultation codes, in addition to concomitant clinical work to supplement income. All but one program has access to hospital-based archiving of POCUS exams. Preceptors dedicate ten to fifty hours to the rotation each week and ensure that all trainee exams are reviewed and documented in the patient’s medical records in the form of a consultation note. Two of the five programs also support a POCUS fellowship. Only two out of five programs have established learner policies. All programs rely on In-Training Evaluation Reports to provide trainee feedback on their performance during the rotation. Conclusions We describe the different elements of the POCUS rotations currently offered in Canadian Internal Medicine training programs. We share some lessons learned around the elements necessary for a sustainable rotation that meets high educational standards. We also identify areas for future growth, which include the expansion of learner policies, as well as the evolution of trainee assessment in the era of competency-based medical education. Our results will help educators that are endeavoring setting up POCUS rotations achieve success.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.016 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".