Efficiency in the Endoscopy Unit: Can We ‘Turn Around’ Room Turnover? An Observational Quality Improvement Study
Bibliographic record
Abstract
Background: Endoscopy units are being challenged to provide timely and quality care, despite limited resources and an ever-growing patient population. Decreasing procedure time is unlikely to create sufficient time savings and may compromise quality. Non-procedural factors, such as room turnover, are important contributors to efficiency and represent an ideal target for quality improvement efforts. Aims: The objective of this quality improvement study was to identify practices that will improve endoscopy unit efficiency at our centre. The specific aims were to (a) understand practices at local hospitals that contribute to room turnover efficiency and (b) examine the magnitude and sources of variation in room turnover efficiency across endoscopists and nurses at our centre. Methods: Interviews were conducted with team leads at five local hospitals. Routinely collected data from our centre were analyzed to understand the magnitude and variation in efficiency by provider and reasons for delays. Non-procedure time defined as 'patient 1 scope out' to 'patient 2 scope in' was our primary measure of efficiency. Results: Over the 12-month period, 750 outpatient procedures met inclusion criteria. Median non-procedure time was 19 min (interquartile range: 16-22 min). The variation attributable to endoscopists was 14.7% compared to 80.4% for unmeasured factors. Conclusions: The variation that remains unexplained by our model suggests that unmeasured factors play a substantial role in endoscopy unit efficiency and that our current endoscopy records are not capturing important contributors to efficiency. The next phase will involve focus groups and direct observation with the goal of identifying these unmeasured factors.
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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 | 0.008 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".