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Record W1566551647

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

2003· preprint· fr· W1566551647 on OpenAlexaboutno aff
Nathalie de Marcellis-Warin, Geneviève Dufour

Bibliographic record

VenueRePEc: Research Papers in Economics · 2003
Typepreprint
Languagefr
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.068
metaresearch head score (Gemma)0.160
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.841

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.160
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.010
Science and technology studies0.0050.004
Scholarly communication0.0070.002
Open science0.0030.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.101
GPT teacher head0.453
Teacher spread0.351 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2003
Admission routes1
Has abstractyes

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