Student-observed surgical safety practices across an urban regional health authority: Table 1
Bibliographic record
Abstract
BACKGROUND AND AIM: Recognising the global push for patient safety in healthcare, students in medicine and nursing participated in a project to compare surgical safety practices in the Winnipeg Regional Health Authority (WRHA) with the WHO surgical safety checklist. METHODOLOGY: Students volunteered to participate and were oriented to operating room (OR) protocol and the WHO surgical safety checklist. Over a 1-month period, 130 students visited 65 ORs across the WRHA in interprofessional pairs, and documented the surgical safety measures employed. Feedback was solicited from OR staff. Qualitative observations were obtained during two student focus groups. Regional policy documents pertaining to OR safety were reviewed. RESULTS: The WRHA does not employ a surgical checklist, although policy mandates several practices included in the WHO document, with a student-observed adherence rate of 75-86%. Remaining checklist items are mandated by the Canadian Anaesthesia Society and Canadian Medical Protective Association. Students observed five errors in patient care with potential for injury. No adverse events resulting in patient harm occurred. CONCLUSIONS AND DISCUSSION: Surgical safety practices in ORs across the WRHA are consistent with the guidelines established by the WHO in 2007, but most are not monitored or enforced. The use of a checklist in the preoperative briefing period may improve adherence to these guidelines and facilitate surgical team interaction, resulting in standardisation of practice and improvements in team communication. Student interprofessional team observers are an effective tool for monitoring safety and teamwork.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".