A18 IMPROVING COMPLIANCE WITH COLONOSCOPY SURVEILLANCE INTERVAL GUIDELINES
Bibliographic record
Abstract
Research suggests that colonoscopy is over utilized in patients undergoing colorectal cancer (CRC) or adenoma surveillance. To improve endoscopist compliance with the 2013 Canadian Association of Gastroenterology (CAG) guidelines on CRC surveillance. In 2014, a trained nurse reviewed a sample of surveillance colonoscopies conducted by each endoscopist at one of five hospitals in Eastern Health (EH) Newfoundland. The endoscopist recommendation for the next surveillance colonoscopy was compared to that of the CAG guidelines based upon the findings and polyp histology. A three-part intervention was undertaken. First, each endoscopist was informed of their own compliance rate and that of the group. Second, a survey was conducted to ascertain how endoscopists decided upon surveillance intervals and barriers to following guidelines. Finally, the group met to discuss the survey results and identify ways to optimize compliance. In 2016, the same nurse determined the endoscopist compliance rate, which was compared to 2014. Only endoscopists who contributed patients to both time periods were included in the analysis. Approximately 25 cases were chosen for each endoscopist at each time point. Data were entered into SPSS version 20.0 for analysis. The study received approval from the local Health Research Ethics Board. In 2014, 526 surveillance colonoscopies performed by 18 endoscopists (10 Surgeons, 8 Gastroenterologists) were reviewed. Surveillance intervals were appropriate in 74.9% of cases. Endoscopist compliance rates ranged from 50.0% to 100%. Fourteen endoscopists completed the survey on guideline compliance. 85.7% indicated they used the CAG guidelines to determine surveillance intervals. The three most common reasons for deviating from guidelines were poor bowel preparation (71.4%), booking the next procedure prior to reviewing polyp histology (50%) and patient preference for a different interval (50%). These results prompted EH to emphasize to patients the importance of high quality bowel preparation and to utilize split dose preparations more frequently. In 2016, 533 surveillance colonoscopies performed by the same endoscopists were reviewed. Surveillance intervals were appropriate in 82.7% of cases (p=0.002 compared to 2014). Endoscopist compliance ranged from 56% to 100%. It was noted that Gastroenterologists had a higher level of compliance than surgeons (84.9% vs. 72.7%; p<0.001). A multi-faceted intervention was associated with an improvement in compliance with the CAG colonoscopy surveillance guidelines. Further study is required to determine which part of the intervention was most effective and if these results are sustained over time. Health Care Foundation
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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 | 0.013 | 0.046 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".