Adverse events among children in Canadian hospitals: the Canadian Paediatric Adverse Events Study
Bibliographic record
Abstract
BACKGROUND: Limited data are available on adverse events among children admitted to hospital. The Canadian Paediatric Adverse Events Study was done to describe the epidemiology of adverse events among children in hospital in Canada. METHODS: We performed a 2-stage medical record review at 8 academic pediatric centres and 14 community hospitals in Canada. We reviewed charts from patients admitted from April 2008 through March 2009, evenly distributed across 4 age groups (0 to 28 d; 29 to 365 d; > 1 to 5 yr and > 5 to 18 yr). In stage 1, nurses and health records personnel who had received training in the use of the Canadian Paediatric Trigger Tool reviewed medical records to detect triggers for possible adverse events. In stage 2, physicians reviewed the charts identified as having triggers and described the adverse events. RESULTS: A total of 3669 children were admitted to hospital during the study period. The weighted rate of adverse events was 9.2%. Adverse events were more frequent in academic pediatric centres than in community hospitals (adjusted odds ratio [OR] 2.98, 95% confidence interval [CI] 1.65-5.39). The incidence of preventable adverse events was not significantly different between types of hospital, but nonpreventable adverse events were more common in academic pediatric centres (adjusted OR 4.39, 95% CI 2.08-9.27). Surgical events predominated overall and occurred more frequently in academic pediatric centres than in community hospitals (37.2% v. 21.5%, relative risk [RR] 1.7, 95% CI 1.0-3.1), whereas events associated with diagnostic errors were significantly less frequent (11.1% v. 23.1%, RR 0.5, 95% CI 0.2-0.9). INTERPRETATION: More children have adverse events in academic pediatric centres than in community hospitals; however, adverse events in the former are less likely to be preventable. There are many opportunities to reduce harm affecting children in hospital in Canada, particularly related to surgery, intensive care and diagnostic error.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".