Integrating patient safety into health professionals’ curricula: a qualitative study of medical, nursing and pharmacy faculty perspectives
Bibliographic record
Abstract
BACKGROUND: As efforts to integrate patient safety into health professional curricula increase, there is growing recognition that the rate of curricular change is very slow, and there is a shortage of research that addresses critical perspectives of faculty who are on the 'front-lines' of curricular innovation. This study reports on medical, nursing and pharmacy teaching faculty perspectives about factors that influence curricular integration and the preparation of safe practitioners. METHODS: Qualitative methods were used to collect data from 20 faculty members (n=6 medical from three universities; n=6 pharmacy from two universities; n=8 nursing from four universities) engaged in medical, nursing and pharmacy education. Thematic analysis generated a comprehensive account of faculty perspectives. RESULTS: Faculty perspectives on key challenges to safe practice vary across the three disciplines, and these different perspectives lead to different priorities for curricular innovation. Additionally, accreditation and regulatory requirements are driving curricular change in medicine and pharmacy. Key challenges exist for health professional students in clinical teaching environments where the culture of patient safety may thwart the preparation of safe practitioners. CONCLUSIONS: Patient safety curricular innovation depends on the interests of individual faculty members and the leveraging of accreditation and regulatory requirements. Building on existing curricular frameworks, opportunities now need to be created for faculty members to act as champions of curricular change, and patient safety educational opportunities need to be harmonises across all health professional training programmes. Faculty champions and practice setting leaders can collaborate to improve the culture of patient safety in clinical teaching and learning settings.
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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 | 0.026 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".