A Survey of Emergency Department Resources and Strategies Employed in the Treatment of Pediatric Gastroenteritis
Bibliographic record
Abstract
OBJECTIVES: Although leading organizations have developed gastroenteritis management guidelines, little is known about emergency department (ED) use of clinical tools to improve outcomes. Our objective was to describe pediatric gastroenteritis clinical decision tools employed in EDs in the province of Ontario and to determine if a greater number of clinical decision tools are employed in academic, high-volume institutions staffed primarily by emergency medicine (EM)-trained physicians. METHODS: A cross-sectional, Internet-based survey was distributed in the summer of 2010 to medical directors and managers of Ontario EDs. Domains included patient population, general resources, and gastroenteritis-specific strategies. Copies were requested of all gastroenteritis-specific strategies to enable a content review. RESULTS: A total of 133 (83%) of 160 eligible participants responded. Practice guidelines, pathways, or order sets; medical directives; and printed discharge instructions were reported to be in use at 38 of the 133 (29%), 69 of 133 (52%), and 105 of 133 (79%) of the responding institutions, respectively. Oral rehydration therapy (ORT) is routinely initiated at triage in only 51 of the 133 of the EDs (38%). High-volume institutions are more likely to have clinical practice guidelines, pathways, or order sets (p = 0.001) than low- and medium-volume EDs. Physician training in EM was associated with the presence of medical directives for nursing administration of antiemetics and antipyretics (p = 0.04). Review of clinical practice guidelines, pathways, and order sets showed that only six of 27 gastroenteritis-specific strategies reviewed were correctly classified, and 20 (74%) met prespecified quality criteria. CONCLUSIONS: Clinical decision tools designed to improve pediatric gastroenteritis management are not commonly implemented. Such strategies are more common in high-volume EDs and those staffed primarily by physicians with EM training.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".