The Waiting Room Assessment to Virtual Emergency Department pathway: Initiating video-based telemedicine in the pediatric emergency department
Bibliographic record
Abstract
The COVID-19 pandemic has presented pediatric emergency departments with unique challenges, resulting in a heightened demand for adapted clinical pathways. In response to this need, the Montreal Children's Hospital pediatric emergency department introduced the WAVE (Waiting Room Assessment to Virtual Emergency Department) pathway, a video-based telemedicine pathway for selected non-critical patients, aiming to reduce safety issues related to emergency department overcrowding, while providing timely care to all children presenting and registering at our emergency department. The objective of the WAVE pilot phase was to evaluate the feasibility and acceptability of telemedicine in our pediatric emergency department, which was previously unfamiliar with this mode of care delivery. During the six-week, three-evening per week deployment, we conducted 18 five-hour telemedicine shifts. In total, 27 patients participated in the WAVE pathway. Results from this pilot phase met four of five a priori feasibility and acceptability criteria. Overall, participating families were satisfied with this novel care pathway and reported no disruptive technological barriers.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".