Unscheduled Return Visits to the Pediatric Emergency Department-One-Year Experience
Bibliographic record
Abstract
OBJECTIVES: Patients returning to the emergency department (ED) within 72 hours of their visit may contribute to crowding and might indicate failure to give a proper assessment, treatment, or follow-up instructions. The aim of this study was to describe the rate of return visits in a tertiary care pediatric ED (PED) and find characteristics of children who return to the ED. METHODS: We retrospectively reviewed all records of patients visiting our PED in Toronto during 2003. We collected demographic data, time of visit(s), and acuity. We excluded patients who left without being seen, left against medical advice, or were admitted to the hospital. We conducted univariate and multivariate analyses to determine odds ratio of variables associated with returning. RESULTS: Of 37,725 eligible children, 1990(5.2%) returned within 72 hours. One hundred fifty-six returned for a third visit, and 10 returned for a fourth visit. A quarter of the children who returned were younger than 1 year, and the younger the child, the higher the likelihood of returning; the higher the acuity of the first (index) visit, the higher the likelihood that a patient will return. Patients coming during the busiest hours, between 8 pm and midnight, were more likely to return. We found no significant seasonal differences in univariate or multivariate analysis. CONCLUSIONS: Five percent of our PED visits are return visits of children seen in the 72 hours before the visit. Younger children, with high acuity who come to the ED in the late evening hours, are most likely to return to the ED.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".