Examining the Appropriateness and Motivations Behind Low-Acuity Pediatric Emergency Department Visits
Bibliographic record
Abstract
OBJECTIVES: High patient volumes have a deleterious effect on care in the pediatric emergency department (PED). Our study assessed the motivation for PED visits that could have been assessed by a primary care physician. METHODS: We identified a convenience sample of patients presenting to the SickKids Hospital PED in June and July 2011 with a Paediatric Canadian Triage and Acuity Score 4 or 5. Patients completed a forced answer yes/no survey describing potential motivators for visiting the PED. Visit appropriateness was determined by a modified version of the DeAngelis tool, an explicit criteria-based tool frequently used for this purpose. RESULTS: Of the included 635 patients with Paediatric Canadian Triage and Acuity Score 4 and 5, 25% were truly inappropriate as per DeAngelis criteria. Of these, perceived expertise at the tertiary care hospital (93.1%) and ease of getting tests (80.8%) were the most common reasons behind PED presentation. CONCLUSIONS: Patients presenting to our PED typically have primary care physicians; however, access to their physicians during off-hours and availability of off-site testing is limited. Public policy aimed at decreasing overcrowding in the PED should address these themes.
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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 | 0.016 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".