Incident Management in Health Care
Bibliographic record
Abstract
BACKGROUND: Nearly 10% of patients experience a harmful patient safety incident in the hospital setting. Current evidence focuses on incident reporting, whereas little is known about how incidents are managed within organizations. PURPOSE: The aim of this study was to explore processes, tools, and resources for incident management in Canadian health care organizations. METHODS: Qualitative focus groups were conducted with key stakeholders, representing clinicians, managers, executives, governors, patients, and families (n = 45). RESULTS: Qualitative data were thematically analyzed and presented as 3 themes: (1) variations in incident reporting and management; (2) simplification of the incident management process; and (3) need for leadership to support just culture and redefine harm. CONCLUSION: The study findings support and inform efforts to create a patient safety culture in Canadian and international health care organizations. There is a need to develop a standardized, accessible incident reporting and management system for use across health care sectors to promote continuous learning and improvement about 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 | 0.016 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".