Impact of Follow-up Calls From the Pediatric Emergency Department on Return Visits Within 72 Hours
Bibliographic record
Abstract
OBJECTIVES: We compare the rate of return to the emergency department (ED) within 72 hours between families of children receiving a follow-up telephone call by a non-health care provider asking about the child's well-being 12 hours after their visit to the ED and families not receiving a follow-up call. METHODS: This was a prospective, randomized study in which we conducted a follow-up call starting at 12 hours after discharge from the ED versus no call for follow-up. At 96 hours after discharge, we contacted all recruited families. We recorded the rate of return to the ED within 72 hours of discharge. RESULTS: Of 371 families in the data analysis, 46% were in the study group, and 55.5% were male patients. Mean age was 5.7 years. The outcome measure was found to be in contrary to our hypothesis. We found return visits to the ED in 24 (14%) of the children in the study group compared with only 14 (7%) in the control group (P < 0.03). All other parameters were not statistically different between the groups. CONCLUSIONS: Emergency departments practicing follow-up calls by non-health care providers should consider a forecasted increase in return rates.
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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 | 0.004 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".