22 Patients who leave the Paediatric Emergency Department without Being Seen: Why don't they Stay and Where do they go?
Bibliographic record
Abstract
Numerous children visiting Paediatric Emergency Departments (EDs) leave prior to being seen by a physician (LWBS). Of potential concern is the inability to provide them with a timely assessment and treatment. The population of children who LWBS has not been adequately characterized. The objective of this study was to examine the acuity (triage score) of children who LWBS compared to children who have stayed to be seen in the ED. We also examined variables related to LWBS and follow up healthcare use. We conducted a prospective cohort study during a 3-month period in the ED of a tertiary paediatric hospital in Toronto, Ontario. All families who LWBS were contacted and asked questions about their child's condition, use of follow-up health services, and sociodemographic variables. Logistic regression analysis was used to compare LWBS children with controls matched for age and gender. During the study period, 289 (2.6%) of families left the ED, of whom 180 (62%) consented to participate in the study. The study and control groups consisted of 158 and 316 children respectively. Waiting for too long and improved symptoms accounted for 58% and 37% of premature leaving. Of the LWBS, 14% were triaged as “urgent” and two-thirds of them sought further medical care, of whom one child was admitted. Multivariable analysis showed that patients who left had a lower acuity, compared to those who stayed (OR 4.95, 95% CI: 2.6–9.4). Most of them sought further medical attention after leaving (OR 4.63, 95% CI: 2.8–7.8), and were more likely to register in the ED between midnight and 4 am (OR 4.86, 95% CI: 2.2–10.5). Children who LWBS have a lower acuity level, seek follow-up care elsewhere, and usually leave because they get better or the wait is too long. A small proportion is triaged as “urgent” but their outcome is favorable. Further studies are recommended to address possible solutions including improving patient flow in the ED and increasing staff at peak times.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".