The impact of an oral rehydration clinical pathway in a paediatric emergency department
Bibliographic record
Abstract
OBJECTIVE: To measure the impact of implementing an oral rehydration clinical pathway for children with mild to moderate dehydration from gastroenteritis in the paediatric emergency department (ED) on the indicators of health care utilization. METHODS: ED charts of children, six months to 17 years of age, meeting the criteria for the oral rehydration clinical pathway were reviewed. There were three 12-month periods of data collection: pre-implementation, transition and postimplementation. The clinical pathway consisted of a standard nursing assessment form and instructions on oral rehydration to be initiated and maintained by caregivers while waiting to see a physician. The primary outcome measure was ED length of visit (LOV) for children treated using the clinical pathway. This was compared with LOV for all other ED visits during the study periods to highlight the effect of the clinical pathway implementation. Secondary outcome measures included rate of intravenous rehydration, unscheduled return visits to the ED and hospital admission. RESULTS: During the three data collection periods, 11,816 children met the eligibility criteria. A decrease in the mean LOV of 24 min (95% CI 17 to 31) was observed, as well as a trivial decrease in the rate of intravenous rehydration therapy (14.6% to 12%) with implementation of the clinical pathway. CONCLUSION: The implementation of an oral rehydration clinical pathway in the ED led to a modest reduction in the ED LOV.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".