The Ottawa Knee Rule: Examining Use in an Academic Emergency Department
Bibliographic record
Abstract
INTRODUCTION: The Ottawa Knee Rule is a validated clinical decision rule for determining whether knee radiographs should be obtained in the setting of acute knee trauma. The objectives of this study were to assess physician knowledge of, barriers to implementation of, and compliance with the Ottawa Knee Rule in academic emergency departments (EDs), and evaluate whether patient characteristics predict guideline noncompliance. METHODS: A 10 question online survey was distributed to all attending ED physicians working at three affiliated academic EDs to assess knowledge, attitudes and self-reported practice behaviors related to the Ottawa Knee Rule. We also performed a retrospective ED record review of patients 13 years of age and older who presented with acute knee trauma to the 3 study EDs during the 2009 calendar year, and we analyzed ED records for 19 variables. RESULTS: ED physicians (n = 47) correctly answered 73.2% of questions assessing knowledge of the Ottawa Knee Rule. The most commonly cited barriers to implementation were "patient expectations" and system issues, such as "orthopedics referral requirement." We retrospectively reviewed 838 records, with 260 eligible for study inclusion. The rate of Ottawa Knee Rule compliance was retrospectively determined to be 63.1%. We observed a statistically significant correlation between Ottawa Knee Rule compliance and patient age, but not gender, insurance status, or provider type, among others. CONCLUSION: Compliance with the Ottawa Knee Rule among academic ED healthcare providers is poor, which was predicted by patient age and not other physician or patient variables. Improving compliance will require comprehensive educational and systemic interventions.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.001 | 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".