Adverse Events Related to Emergency Department Care: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To systematically review the literature regarding the prevalence, preventability, severity and types of adverse events (AE) in the Emergency Department (ED). METHODS: We systematically searched major bibliographic databases, relevant journals and conference proceedings, and completed reference reviews of primary articles. Observational studies (cohort and case-control), quasi-experimental (e.g. before/after) studies and randomized controlled trials, were considered for inclusion if they examined a broad demographic group reflecting a significant proportion of ED patients and described the proportion of AE. Studies conducted outside of the ED setting, those examining only a subpopulation of patients (e.g. a specific entrance complaint or receiving a specific intervention), or examining only adverse drug events, were excluded. Two independent reviewers assessed study eligibility, completed data extraction, and assessed study quality with the Newcastle Ottawa Scale. RESULTS: Our search identified 11,624 citations. Ten articles, representing eight observational studies, were included. Methodological quality was low to moderate with weaknesses in study group comparability, follow-up, and outcome ascertainment and reporting. There was substantial variation in the proportion of patients with AE related to ED care, ranging from 0.16% (n = 9308) to 6.0% (n = 399). Similarly, the reported preventability of AE ranged from 36% (n = 250) to 71% (n = 24). The most common types of events were related to management (3 studies), diagnosis (2 studies) and medication (2 studies). CONCLUSIONS: The variability in findings and lack of high quality studies on AE in the high risk ED setting highlights the need for research in this area. Further studies with rigorous, standardized outcome assessment and reporting are required.
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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 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".