The McGill University Health Centre Policy on Sentinel Events: Using a Standardized Framework to Manage Sentinel Events, Facilitate Learning and Improve Patient Safety
Bibliographic record
Abstract
Promoting a culture of safety within organizations includes translating the lessons learned from sentinel events into concrete changes that will improve patient safety. In May 2005 the McGill University Health Centre Policy on Sentinel Events was implemented to provide a standardized framework to manage these events and promote that culture of safety. This framework helped implement a number of changes to improve patient safety. The O2 Ticket to Ride project ensures cross-disciplinary responsibility for the transportation of oxygen-dependent patients to diagnostic testing areas. The Code Stroke Algorithm was developed to expedite the sequence of events from the time the stroke symptoms are observed to the time the CT scan is carried out.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.154 | 0.157 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.037 | 0.022 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".