Don’t let up: implementing and sustaining change in a new post-licensure education model for developing extended role practitioners involved in arthritis care
Bibliographic record
Abstract
Katie Lundon,1,3 Rachel Shupak,1–3 Sonya Canzian,4 Ed Ziesmann,5 Rayfel Schneider,6,71Office of Continuing Professional Development, Faculty of Medicine, University of Toronto, 2Division of Rheumatology, St Michael's Hospital, 3Department of Medicine, University of Toronto, 4Trauma/Neurosurgery and Mobility Programs, St Michael's Hospital, 5Programs and Services, The Arthritis Society, 6Division of Rheumatology, The Hospital for Sick Children, 7Department of Paediatrics, University of Toronto, Toronto, ON, CanadaKey message: Across a 9-year period, the Advanced Clinician Practitioner in Arthritis Care program has achieved a set of short-term “wins” giving direction and momentum to the development of new roles for health care practitioners providing arthritis care.Implications: This is a viable model for post-licensure training offered to multiple allied health professionals to support the development of competent extended role practitioners (extended scope practice). Challenges at this critical juncture include: retain focus, drive, and commitment; develop academic and financial partnerships transferring short-term success to long-term sustainability; advanced, context-driven, system-level evaluation including fiscal outcome; health care policy adaptation to new human health resource development.Supporting evidence: Success includes: completed 2-year health services research evaluating 37 graduates; leadership, innovation, educational excellence, and human health resource benefit awards; influential publications/presentations addressing post-licensure education/outcome, interprofessional collaboration, and improved patient care. Keywords: human health resource development, post-licensure education, arthritis, extended role practitioners, allied health professionals
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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 | 0.027 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".