Patient Safety - Worker Safety: Building a Culture of Safety to Improve Healthcare Worker and Patient Well-Being
Bibliographic record
Abstract
Patient safety within the Canadian healthcare system is currently a high national priority, which merits a comprehensive understanding of the underlying causes of adverse events. Not least among these is worker health and safety, which is linked to patient outcomes. Healthcare workers have a high risk of workplace injuries and more mental health problems than most other occupational groups. Many healthcare professionals feel fatigued, stressed, in pain, or at risk of illness or injury-factors they feel impede their ability to provide consistent quality care. With this background, the Occupational Health and Safety Agency for Healthcare (OHSAH) in British Columbia, jointly governed by healthcare unions and healthcare employers, launched several major initiatives to improve the healthcare workplace. These included the promotion of safe patient handling, adaptive clothing, scheduled toileting, stroke management training, measures to improve management of aggressive behaviour and, of course, infection control-all intended to improve the safety of workers, but also to improve patient safety and quality of care. Other projects also explicitly promoting physical and mental health at work, as well as patient safety are also underway. Results of the projects are at various stages of completion, but ample evidence has already been obtained to indicate that looking after the well-being of healthcare workers results in safer and better quality patient care. While more research is needed, our work to date suggests that a comprehensive systems approach to promoting a climate of safety, which includes taking into account workplace organizational factors and physical and psychological hazards for workers, is the best way to improve the healthcare workplace and thereby patient safety.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".