The impact of pediatric emergency department crowding on patient and health care system outcomes: a multicentre cohort study
Bibliographic record
Abstract
BACKGROUND: Emergency department overcrowding has been associated with increased odds of hospital admission and mortality after discharge from the emergency department in predominantly adult cohorts. The objective of this study was to evaluate the association between crowding and the odds of several adverse outcomes among children seen at a pediatric emergency department. METHODS: We conducted a retrospective cohort study involving all children visiting 8 Canadian pediatric emergency departments across 4 provinces between 2010 and 2014. We analyzed the association between mean departmental length of stay for each index visit and hospital admission within 7 days or death within 14 days of emergency department discharge, as well as hospital admission at index visit and return visits within 7 days, using mixed-effects logistic regression modelling. RESULTS: A total of 1 931 465 index visits occurred across study sites over the 5-year period, with little variation in index visit hospital admission or median length of stay. Hospital admission within 7 days of discharge and 14-day mortality were low across provinces (0.8%-1.5% and < 10 per 100 000 visits, respectively), and their association with mean departmental length of stay varied by triage categories and across sites but was not significant. There were increased odds of hospital admission at the index visit with increasing departmental crowding among visits triaged to Canadian Triage and Acuity Scale (CTAS) score 1-2 (odds ratios [ORs] ranged from 1.01 to 1.08) and return visits among patients with a CTAS score of 4-5 discharged at the index visit at some sites (ORs ranged from 1.00 to 1.06). INTERPRETATION: Emergency department crowding was not significantly associated with hospital admission within 7 days of the emergency department visit or mortality in children. However, it was associated with increased hospital admission at the index visit for the sickest children, and with return visits to the emergency department for those less sick.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".