The Development of the Canadian Paediatric Trigger Tool for Identifying Potential Adverse Events
Bibliographic record
Abstract
INTRODUCTION Research on adverse events (AEs) has highlighted the need to improve patient safety. The Canadian Adverse Events Study: the incidence of adverse events among hospital patients in Canada (CAES) reported that 7.5% of the annual medical and surgical, adult hospital admissions in Canada are associated with an AE, and close to 2.8% may be preventable (Baker et al. 2004). These data are consistent with the results obtained by many of the international studies that used the same methodology: retrospective chart review using a trigger tool (Brennan et al. 1991; Leape et al. 1991; Wilson et al. 1995; Thomas et al. 2000; Davis et al. 2001; Vincent et al. 2001; Davis et al. 2002; Davis et al. 2003). The CAES focused on patients 19 years of age and older. The rate of AEs in Canadian children remains unknown. The Canadian Association of Paediatric Health Centres (CAPHC) is a national, not-for-profit, organization whose members are multidisciplinary health professionals who provide care for children, youth and families within community, regional and tertiary/quaternary healthcare facilities, rehabilitation centres and community home care services. At the 2004 Canadian Association of Paediatric Hospitals (CAPHC) annual conference, patient safety priorities and recommendations for CAPHC’s Patient Safety Collaborative were identified and developed by a multi-stakeholder National Patient Safety Group. A key recommendation of the workshop was for CAPHC to take the lead in developing a paediatric trigger tool to assess the incidence of AE in paediatric populations. In this article, we will provide background information on the use of trigger tools to detect AEs, and then describe the process used for developing a Canadian paediatric trigger tool and testing its feasibility and validity. Development of this trigger tool is one component of a long-term initiative that will contain several phases and responses to the issue of paediatric patient safety. We believe this project will lead to specific recommendations for improved data collection and event monitoring and will provide a baseline for further intervention studies to reduce AEs in Canadian paediatric acute care hospitals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".