A Comparative Review of Canadian Health Professional Education Accreditation Systems
Bibliographic record
Abstract
Canadian governments and various stakeholder groups are advocating greater interprofessional collaboration amongst health care providers as a fundamental strategy for enhancing coordination and quality of care in the health care system. Interprofessional education for collaborative patient-centred practice (IECPCP) is an educational process by which students/learners (or workers) from different health professions learn together to improve collaboration. The educational system is believed to be a main determinant of interprofessional collaborative practice, yet academic institutions are largely influenced by accreditation, certification and licensure bodies. Accreditation processes have been linked to the continuous improvement of curricula in the health professions, and have also been identified as potential avenues for encouraging educational change and innovation. The purpose of this paper is to summarize the characteristics of the national accreditation systems of select Canadian health professional education programs at both the pre- and post-licensure educational levels and to show how these systems support and/or foster IECPCP. A review of the educational accreditation systems of medicine, nursing, pharmacy, social work, occupational therapy and physiotherapy was undertaken through key informant interviews and an analysis of accreditation process documentation. The results of this comparative review suggest that accreditation systems are more prevalent across the health professions at a pre-licensure level. Accreditation at the post- licensure level, particularly at the continuing professional education level, appears to be less well established across the majority of health professions. Overall, the findings of the review also suggest that current accreditation systems do not appear to promote nor foster interprofessional education for collaborative patient-centred practice in a systematic manner through either accreditation processes or standards. Through a critical adult learning perspective we argue that in order for traditional uni-professional structures within the health professional education system to be challenged, the accreditation system needs to place greater value on interprofessional education for collaborative patient-centred practice.
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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 | 0.024 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.038 | 0.081 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".