Déclaration des incidents et des accidents dans les centres hospitaliers - Analyse critique du rapport d'incident/accident AH-223 et évaluation de la structure de gestion des rapports
Bibliographic record
Abstract
Reporting incidents and accidents is part of a continuous quality improvement process. The data collected through that process must be genuine and usable in order to understand what has really happened and to put forward adapted corrective measures. In the first part of this report, we will define the methodology of our critical analysis of the incidents and accidents report in Quebec hospitals. We will then briefly overview the history of the AH-223 incident/accident report and discuss its original purpose. Third, we will review section by section the AH-223 form originally proposed by MSSS. We will analyze the information that it collects and its uses, and we will also suggest several modifications. In conclusion, we will make recommendations and propose some leads to review form AH-223 as well as the report management system. The complete version of this publication is confidential. La démarche de déclaration des incidents et accidents s'insère dans un processus continu d'amélioration de la qualité. Les informations recueillies doivent être de qualité et utilisables pour permettre de comprendre ce qui s'est passé et mettre en place les mesures de prévention adaptées. Dans la première partie de ce rapport, nous définirons la méthodologie sur laquelle est basée notre analyse critique du report des incidents et des accidents dans le milieu hospitalier au Québec. Nous ferons ensuite un bref historique du rapport d'incident/accident AH-223 et des objectifs prévus lors de sa conception. Dans la troisième partie, nous détaillerons section par section le formulaire AH-223 actuellement proposé par le MSSS. Nous analyserons l'information demandée, son utilisation et nous proposerons un certain nombre de modifications. Nous conclurons par des recommandations et des pistes de réflexion sur les possibilités de révision du formulaire AH-223 et de l'ensemble de la démarche de report des incidents/accidents. La version complète de cette publication est confidentielle.
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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 | 0.068 | 0.160 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".