A Systematic Review on the Effectiveness of Clinician-Directed Interventions to Improve Compliance to Post-Polypectomy Surveillance Guidelines
Bibliographic record
Abstract
INTRODUCTION: Clinical practice guidelines recommend periodic colonoscopy surveillance following colorectal adenoma excision. Inappropriate use of post-polypectomy surveillance (PPS) is common and lead to improper resource utilization. The aim of this review was to identify structured interventions which can affect PPS practises and to evaluate the effectiveness of these various interventions in improving clinician adherence to PPS guidelines. METHODS: A computerized search was performed to identify relevant studies between 1997 and November 2020. Two investigators identified eligible studies and extracted data independently. The quality of the included studies was assessed by the Newcastle-Ottawa risk of assessment scoring system. RESULTS: The search identified 5,602 citations. Forty-one articles were retrieved for full-text analysis and 7 studies met the inclusion criteria. Compliance to PPS guidelines was higher following interventions which included medical education, specialist nurse coordinators facilitation, continuous quality improvement, and clinical decision support systems. CONCLUSION: This study demonstrates that medical education, specialist nurse coordinators, continuous quality improvement, and clinical decision support systems are effective in improving clinicians' compliance to PPS guidelines, and are associated with reduction in over- and underutilization of colonoscopy surveillance resources.
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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 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".