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Quality improvement project with the aim to use a standardized assessment tool (EMR-STAT) to establish learning curves and competence thresholds for key cognitive and technical colorectal EMR core skills among advanced endoscopy trainees (AETs).
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Baseline and Post-Training Questionnaires: The EMR-STAT Baseline Questionnaire is to better understand the participant's level of comfort with the C-EMR procedure. At the end of their training, the participant will complete the EMR-STAT Post-Training Questionnaire to evaluate their training experience.
Standardized Assessment tool (EMR-STAT) and Grading Protocol (Phase 1): The EMR-STAT is a tool designed for competence assessment. The tool will be used in a continuous fashion during the AETs training in colorectal EMR. The aim of the tool is to evaluate key concepts and core skills necessary for high-quality colorectal EMR as recently outlined by the US Multi-Society Task Force on Colorectal Cancer10. We have previously demonstrated the feasibility of this tool in a prior study9. The instrument evaluates for key cognitive and technical steps, including scope positioning, lesion assessment, submucosal lifting, endoscopic resection, adjunct resection/ablative techniques, management of adverse events, and elective defect closure. A 4-point scoring system was developed to grade each endpoint: 4 (superior), achieves task without instruction; 3 (advanced), achieves with minimal verbal cues; 2 (intermediate), achieves with multiple verbal cues or hands-on assistance; 1 (novice), unable to complete and requires trainer to take over. Setting these pre-defined anchors for specific individual cognitive and technical skills during grading ensures that the data collected are reproducible from one evaluator to the next. In addition, a 10-point overall assessment score (1-3, below average; 4-6, intermediate; 7-9, advanced; 10, superior) will be provided for each case. This grading format for endoscopic performance has been previously validated6,11,12
The trainees will be evaluated during live cases as part of the training experience. There will patient data that will be collected on the EMR_STAT but no patient identifiers will be documented. This data collection is integral to the study because these factors may play a role in the complexity of the procedure and impact trainees' EMR performance (ex. a cancerous lesion is more difficult to dissect than a non-cancerous lesion). This data will be analyzed as part of the learning curve for the trainees
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