Improving patient preparedness for the operating room: A quality improvement study in Winchester District Memorial Hospital – A rural hospital in Ontario
Bibliographic record
Abstract
Introduction: Full completion of the pre-operative checklist is important for proper preparation of patients before they enter the operating room (OR), thus increasing OR efficiency. It is also critical for patient safety and successful outcomes. According to various literature, full completion of pre-operative checklists varies widely between institutions and occurs anywhere between 21% and 92% of cases.[1],[2] Our pre-project audits revealed a suboptimal patient preparedness for the Winchester District Memorial Hospital (WDMH) OR, since only 25% of cases arriving at the OR had their pre-operative checklist completed in its entirety, with no omissions. Methods: WDMH performed a 12-month long quality improvement (QI) study to improve patient preparedness for the OR. Multiple QI initiatives were used to induce behavioural change by incorporating process mapping, enabling communication, adjusting the pre-operative checklist based on qualitative staff feedback and implementing a staff education plan. Interventions also included two post-implementation audits. Results: Remarkably, completion of the pre-operative checklist increased from 25% to 67% and finally to 94%. Furthermore, the previous chart's presence and completion of pre-operative orders improved from 87% to 100% and from 82% to 99%, respectively. Another significantly important secondary outcome was improvement in interdepartmental relationships and collaboration. With better communication and checklist completion rates, there came increased patient preparedness and improved efficiency. Conclusions: Multiple significant improvements and many additional minor improvements strongly suggest that the approaches were used were effective at improving patient preparedness.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".