Operational Impact of Redirection From the Pediatric Emergency Department: A Matched Cross‐Sectional Study
Bibliographic record
Abstract
BACKGROUND: Programs redirecting patients with non-urgent presentations from Emergency Departments (EDs) to the community (ED2C), by providing them a booked community appointment in lieu of waiting for ED care, may reduce ED crowding. We sought to evaluate the department- and patient-level impact of an ED2C program in an urban tertiary pediatric ED. METHODS: We conducted a matched cross-sectional study to describe patients redirected by a pediatric ED2C program and determine if the program changed ED operations. Days with the program were matched on day type (weekday vs. weekend) and department volume (±10%) to days when ED patients were not being redirected. Measures of ED flow and utilization on days with and without the program were compared using t-tests and linear regression models. RESULTS: Of the 6164 patients eligible for the ED2C program for 53 days that redirection was offered, 900 were redirected (14.6%). On average, 17.7 (SD 8.5) patients were redirected and 92.4 (SD 23.7) eligible patients were not redirected each day the ED2C was in operation. Patients who were redirected had a significantly shorter length of stay (LOS) than those who were eligible but not redirected (2.9 ± 2.0 h vs. 8.5 ± 4.3 h, p-value < 0.0001). Three patients who were redirected (0.3%) and 11 eligible but not redirected (0.2%) returned to the ED and were hospitalized. Average median departmental LOS, time to physician assessment, daily proportion hospitalized patients, proportion of patients left without being seen, and ED return visits did not differ on days with and without the program. CONCLUSIONS: A small proportion of eligible patients were redirected. These patients experienced a lower LOS, without increasing the proportion of return visits. ED operations were unchanged. Refining eligibility criteria for pediatric redirection with an emphasis on patient safety is necessary.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".