Factors that Improve Colon Adenoma Detection at the Community Hospital: A Group Study
Bibliographic record
Abstract
Purpose: In 2008, our group decided to add colonoscopy withdraw time (CWT) as part of our standard report. However, we had not systematically measured the impact and result of this change in practice; thus, the group's adenoma detection rate remained unknown. Last year, we reported a single practitioner colonoscopy quality improvement project after implementing the CWT (1). Since then, we have systematically analyzed the quality data for all practitioners within our group. Methods: We reviewed the charts of 722 colonoscopies performed by a four gastroenterologists from July to December 2010. Data were collected by the GI lab staff and grouped into 3rd quarter and 4th quarter of 2010. The information from the endoscopy and the pathology reports were entered manually into a Microsoft Excel spreadsheet. Age, size of largest adenoma, number of adenomas, total number of all polyps, polyp pathology, scope insertion time, and total withdraw time were collected. The data were analyzed using Microsoft Excel. The total withdraw time was the total time from cecum to anal verge, which also included the polypectomy time. Results: See Table above.Table: Table. Colonoscopy quality data per physicianConclusion: By documenting the CWT, increasing the procedure slot time to 45 minutes, recording the adenoma detection rate and the total adenomas found, the quality of the colonoscopy has improved within our group. Our adenoma detection rate has been maintained at a high level of 49-52%. The physician who has a higher adenoma detection rate also found more adenomas per patient after implementation of the CWT policy. Polypectomy increased withdraw time by 3 to 5 minutes. After knowing the 3rd quarter result, the physicians in our practice have become more aware of the withdraw time and adenoma detection. As a result, the adenoma detection rate has improved from the 3rd quarter to the 4th quarter. The policy implemented in 2008 was effective in maintaining and improving the quality of care. Moreover, the CWT and adenoma detection rate will now be used as an ongoing quality assessment for all providers in our group. A “report card” of the group and individual physician's performance will be assessed on a semi-annual basis.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".