Follow-up After a Pediatric Emergency Department Visit: Telephone Versus E-Mail?
Bibliographic record
Abstract
OBJECTIVE: The Internet has become in recent years an unlimited source of health-related information and revolutionized health information access. Follow-up after an emergency department (ED) visit is important for continuity of care but is difficult to achieve. We conducted this study to determine whether e-mail could become a method for a follow-up contact after leaving the pediatric ED. METHODS: Over a 2-month period, parents who had a telephone line and e-mail access and whose child was discharged from the ED at the Hospital for Sick Children in Toronto were randomized to receive an e-mail or a telephone follow-up. Main outcome measure was the response rates by parents to the telephone or e-mail. RESULTS: A total of 265 (79%) of the 337 families who were approached had Internet access, and the majority (75%) check e-mails at least once a day. Eighty-seven percent (85 of 98) and 53% (53 of 100) of the families who were contacted by telephone or e-mail, respectively, were reached within an average of 17 and 46 hours, respectively. Fourteen percent of families from the study population were unreachable either by telephone or by e-mail. Most (57%) parents who did not respond to the e-mail did not check or did not remember reading the e-mail or had trouble with access. Ten percent of the e-mails were undeliverable. CONCLUSIONS: The telephone is better than e-mail as a follow-up channel with families of children who visit the pediatric ED. The main reason for not responding to e-mails is "technical problems." E-mail could be a mean for follow-up contact for part of our patient population, especially for nonurgent purposes.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".