Health care impact of implementing a clinical pathway for acute care of pediatric concussion: a stepped wedge, cluster randomised trial
Bibliographic record
Abstract
OBJECTIVES: To test the effects of actively implementing a clinical pathway for acute care of pediatric concussion on health care utilization and costs. METHODS: Stepped wedge, cluster randomized trial of a clinical pathway, conducted in 5 emergency departments (ED) in Alberta, Canada from February 1 to November 30, 2019. The clinical pathway emphasized standardized assessment of risk for persistent symptoms, provision of consistent information to patients and families, and referral for outpatient follow-up. De-identified administrative data measured 6 outcomes: ED return visits; outpatient follow-up visits; length of ED stay, including total time, time from triage to physician initial assessment, and time from physician initial assessment to disposition; and total physician claims in an episode of care. RESULTS: A total of 2878 unique patients (1164 female, 1713 male) aged 5-17 years (median 11.00, IQR 8, 14) met case criteria. They completed 3009 visits to the 5 sites and 781 follow-up visits to outpatient care, constituting 2910 episodes of care. Implementation did not alter the likelihood of an ED return visit (OR 0.77, 95% CI 0.39, 1.52), but increased the likelihood of outpatient follow-up visits (OR 1.84, 95% CI 1.19, 2.85). Total length of ED stay was unchanged, but time from physician initial assessment to disposition decreased significantly (mean change - 23.76 min, 95% CI - 37.99, - 9.52). Total physician claims increased significantly at only 1 of 5 sites. CONCLUSIONS: Implementation of a clinical pathway in the ED increased outpatient follow-up and reduced the time from physician initial assessment to disposition, without increasing physician costs. Implementation of a clinical pathway can align acute care of pediatric concussion more closely with existing clinical practice guidelines while making care more efficient. TRIAL REGISTRATION: ClinicalTrials.gov NCT05095012.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".