Adherence to the Canadian CT Head Rule in a Nova Scotian Emergency and Trauma Center
Bibliographic record
Abstract
Background and aims Choosing Wisely Nova Scotia (CWNS), an affiliate of Choosing Wisely Canada (CWC), aims to address unnecessary care and tests through literature-informed lists developed by various disciplines. CWC has identified unnecessary head CTs among the top five tests, procedures, and treatments to question within the emergency department setting. The Canadian CT-scan Head Rule (CCHR) has been found to be the most effective clinical decision rule in adults with minor head injuries. This study aimed to better understand the current status of CCHR use in Nova Scotia, we conducted a retrospective audit of patient charts at the Charles V. Keating Emergency and Trauma Center in Halifax, Nova Scotia. Materials and methods Our mixed methods design included a narrative literature review, a retrospective chart audit, and a qualitative audit-feedback component with physicians who work in the emergency department (ED). The chart audit applied the guidelines for adherence to the CCHR and reported on the level of compliance within the ED. Results Analysis of qualitative data is included here, in parallel with in-depth analysis to contextualize findings from the chart audit. A total of 302 charts of patients presenting to the surveyed site were retrospectively reviewed for this study. Of the 37 cases where the CT head was indicated as per the CCHR, a CT was ordered 32 (86.5%) times. Of the 176 cases where a CT head was not indicated as per the CCHR, a CT was not ordered 155 (88.1%) times. Therefore, the CCHR was followed in 187 (87.8%) of the total 213 cases where the CCHR should be applied. Conclusions Our review revealed that the CCHR was adhered in 87.8% of cases at the surveyed ED. Identifying contextual factors that facilitate or hinder the application of CCHR in practice is critical to achieving the goal of reducing unnecessary CTs. This work will be presented to the physician group to engage and understand factors that are enablers in the process of ED minor head injury care.
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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 | 0.008 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".