Comparison of Flexible Sigmoidoscopy Screening in Average Risk Patients Performed by Nurses Versus Gastroenterologists
Bibliographic record
Abstract
BACKGROUND: Screening sigmoidoscopy is effective in reducing mortality from colorectal cancer. In 2009, Cancer Care Ontario (CCO) launched a nurse-performed screening flexible sigmoidoscopy program at Hotel Dieu Hospital, Kingston, Ontario. Prior to this program, there was a pilot sigmoidoscopy screening program by gastroenterologists in a similar average risk cohort. AIM: To compare neoplasia detection rates and associated costs of screening sigmoidoscopy performed by nurses and gastroenterologists. METHOD: A retrospective chart review was conducted on flexible sigmoidoscopies performed as part of two average risk screening programs performed by gastroenterologists and nurse-endoscopists. Detected polyps were categorized as hyperplastic, low-risk adenomas or high-risk adenomas. Average cost per procedure was estimated based on physician fee for service charges, nurse wage and benefits, physician supervisory fees, pathology costs and administrative expenses. RESULTS: There were 538 procedures performed by nurses and 174 by physicians. Adenomas were detected in 18% of nurse-performed procedures versus 9% in physician-performed procedures (p=0.003), with the higher adenoma detection rate restricted to low risk adenomas. One cancer was found in the physician group. Seven physicians performed the 174 sigmoidoscopies, with one physician performing the majority. This physician's adenoma detection rate was 4.5%, whereas detection rate for the remaining physicians combined was 16.5%. Nurses biopsied more polyps per case (0.96 versus 0.18). Average estimated cost per case was greater for nurses ($387.54 versus $309.37). CONCLUSION: Well-trained nurse-endoscopists can provide an effective service for colorectal cancer screening, but as currently structured in Ontario, the associated cost is higher for nurse-performed procedures.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".