Patient Safety and Engagement at the Frontlines of Healthcare
Bibliographic record
Abstract
Since the release of the seminal work To Err Is Human in 1999, there has been widespread acknowledgement of the need to change our approach to patient safety in North America.Specifically, healthcare organizations must adopt a systems approach to patient safety, in which organizations take a comprehensive approach aimed at building resilient barriers and ensuring a culture of open communication and learning.Here in Canada, the patient safety movement gained momentum following the publication of the Canadian Adverse Events Study in 2004, which concluded that close to 40% of all hospital-associated adverse events were potentially preventable.Baker et al. (2004) argued for the need to modify the work environment of healthcare professionals to better ensure barriers were in place, as well as the need to improve communication and coordination among healthcare providers.The changes proposed a decade ago required greater healthcare worker engagement in patient safety and the creation of a culture of patient safety.Building a National Dialogue Since the establishment of the Canadian Patient Safety Institute (CPSI) in 2004, the organization endeavoured to provide healthcare organizations with evidence-based interven-Patient Safety and Engagement at the Frontlines of Healthcare
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.001 | 0.018 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".