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 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".