Adverse events in the paediatric emergency department: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Understanding adverse events among children treated in the emergency department (ED) offers an opportunity to improve patient safety by providing evidence of where to focus efforts in a resource-restricted environment. OBJECTIVE: To estimate the risk of adverse events, their type, preventability and severity, for children seen in a paediatric ED. METHODS: This prospective cohort study examined outcomes of patients presenting to a paediatric ED over a 1-year period. The primary outcome was the proportion of patients with an adverse event (harm to patient related to healthcare received) related to ED care within 3 weeks of their visit. We conducted structured telephone interviews with all patients and families over a 3-week period following their visit to identify flagged outcomes (such as repeat ED visits, worsening symptoms) and screened admitted patients' health records with a validated trigger tool. For patients with flagged outcomes or triggers, three ED physicians independently determined whether an adverse event occurred. RESULTS: Of 1567 eligible patients, 1367 (87.2%) were enrolled and 1319 (96.5%) reached in follow-up. Median patient age was 4.34 years (IQR 1.5 to 10.57 years) and most (n=1281; 93.7%) were discharged. Among those with follow-up, 33 (2.5%, 95% CI 1.8% to 3.5%) suffered an adverse event related to ED care. None experienced more than one event. Twenty-nine adverse events (87.9%, 95% CI 72.7% to 95.2%) were deemed preventable. The most common types of adverse events (not mutually exclusive) were management issues (51.5%), diagnostic issues (45.5%) and suboptimal follow-up (15.2%). CONCLUSION: One in 40 children suffered adverse events related to ED care. A high proportion of events were preventable. Management and diagnostic issues warrant further study.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".