Performance measures in inflammatory bowel disease surveillance colonoscopy: Implementing changes to practice improves performance
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND AIM: Dye-based chromoendoscopy (DCE) with targeted biopsies is recommended for inflammatory bowel disease (IBD) surveillance. However, DCE has not yet been widely adopted into clinical practice. We evaluated quality indicators in IBD surveillance following introduction of structured changes in service delivery. METHODS: In August 2016, we introduced a number of changes to IBD surveillance practice in our endoscopy unit. These included training using interactive videos/images in a structured module, DCE as standard by using a foot-pedal operated pump jet, allocation of 45-minute procedure timeslots, targeted biopsies (except in high-risk patients), scoring of endoscopic disease activity, and lesion detection/morphology characterization. All IBD surveillance colonoscopies were allocated to a small team of four DCE-trained endoscopists. We compared quality measures for surveillance procedures carried out pre- and post-August 2016. The two groups were compared using chi-squared statistics RESULTS: A total of 598 IBD surveillance procedures (277 pre-August 2016 and 321 post-August 2016) were done and included in the study. Use of DCE increased (54.2% vs 76.0% P < 0.0005) whereas random biopsy surveillance decreased (12.3% vs 3.1% P < 0.0005). Use of Paris classification (26.1% vs 57.0% P < 0.0005) and Kudo pit pattern increased (21.7% vs 59.0% P < 0.0005). There was also an increase in lesion detection rate (24.9% vs 33.1% P < 0.05). CONCLUSIONS: Implementation of extensive changes in practice of surveillance colonoscopy resulted in significant improvement in quality indicators within a short period of time. Training, education and audit may continue to facilitate the adoption of DCE and further improve quality of performance in IBD surveillance.
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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 | 0.001 | 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 | 0.000 |
| 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 it