A148 EFFICIENCY IN THE ENDOSCOPY UNIT: CAN WE ‘TURN AROUND’ ROOM TURNOVER?
Bibliographic record
Abstract
Abstract Background Endoscopy units across Canada are being challenged to meet the growing demand for procedures despite limited resources, highlighting the need to optimize endoscopy unit efficiency. Earlier studies have found that non-procedural factors, such as room turnover, represent an ideal target to improve efficiency. Aims The objective of this research project was to identify practices that will improve efficiency for routine outpatient gastrointestinal (GI) procedures at Sunnybrook Health Sciences Centre (SHSC). There were 2 sub-aims: 1) to understand practices at Toronto hospitals that shorten room turnover time and 2) to describe the variation in room turnover time at SHSC. Methods Sub-aim #1: A survey of endoscopy units at five other Toronto hospitals was completed. Questions were designed to gain a better understanding of routine practices and any initiatives undertaken to improve room turnover efficiency. Sub-aim #2: Median room turnover time from April 2018 to March 2019, defined as ‘patient out’ to ‘patient in’, was reported in an anonymized fashion for the following categories: 1) by endoscopist, 2) by nurse, and 3) by unique endoscopist-nurse pair. Only data from routine outpatient endoscopic procedures (e.g. colonoscopy, gastroscopy, flexible sigmoidoscopy) were included. In order to evaluate turnover times by endoscopist-nurse pair, consecutive cases not performed by the same pair were excluded. Procedures affected by patient- and transportation-related delays were also excluded. Results Of the five centers surveyed, three allocated 5 minutes for turnover and two allocated 10 minutes. All centers reported tracking turnover time and four centers reported undertaking initiatives to decrease turnover time such as involving a flow team, hiring team attendants, and sharing performance data. Over the 12-month period, 2504 routine outpatient GI endoscopic procedures were performed at SHSC, with 803 cases meeting inclusion criteria. Median turnover time for the unit was 6 minutes, ranging from 5 to 9 minutes across endoscopists, 5 to 7 minutes across nurses, and 3 to 10 minutes across unique endoscopist-nurse pairs (Figure 1). Efficiency of endoscopist-nurse pairs did not correlate with the number of cases performed as a pair over the 12-month period. Conclusions Endoscopy room turnover times at SHSC are similar to those reported by other local centers, with important variation across endoscopists and nurses. The next phase of this study will involve directly observing each of the most and least efficient individuals and pairs and recording common practices. It is anticipated that these findings will enable us to identify efficient practices that should be incorporated into standard operating procedures and training for endoscopy room personnel. Funding Agencies None
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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 | 0.009 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".