Sachin Wani1, Matthew Hall2, Rajesh N Keswani3, Harry R Aslanian4, Brenna Casey5, Rebecca Burbridge6, Amitabh Chak7, Ann M Chen8, Gregory Cote9, Steven A Edmundowicz10, Ashley L Faulx7, Thomas G Hollander10, Linda S Lee5, Daniel Mullady10, Faris Murad10, V Raman Muthusamy11, Patrick R Pfau12, James M Scheiman13, Jeffrey Tokar14, Mihir S Wagh15, Rabindra Watson11, Dayna Early10. 1. Division of Gastroenterology and Hepatology, University of Colorado Anschutz Medical Center, Aurora, Colorado. Electronic address: sachinwani10@yahoo.com. 2. Division of Gastroenterology and Hepatology, University of Colorado Anschutz Medical Center, Aurora, Colorado. 3. Division of Gastroenterology and Hepatology, Northwestern University, Chicago, Illinois. 4. Division of Gastroenterology and Hepatology, Yale University, New Haven, Connecticut. 5. Division of Gastroenterology and Hepatology, Massachusetts General Hospital and Brigham and Women's Hospital, Boston, Massachusetts. 6. Division of Gastroenterology and Hepatology, Duke University, Durham, North Carolina. 7. Division of Gastroenterology and Hepatology, University Hospitals Case Medical Center, Cleveland, Ohio. 8. Division of Gastroenterology and Hepatology, Stanford University, Stanford, California. 9. Division of Gastroenterology and Hepatology, Indiana University Hospital, Indianapolis, Indiana. 10. Division of Gastroenterology and Hepatology, Washington University School of Medicine, St. Louis, Missouri. 11. Division of Gastroenterology and Hepatology, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California. 12. Division of Gastroenterology and Hepatology, University of Wisconsin School of Medicine, Madison, Wisconsin. 13. Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, Michigan. 14. Division of Gastroenterology and Hepatology, Fox Chase Cancer Center, Philadelphia, Pennsylvania. 15. Division of Gastroenterology and Hepatology, University of Florida, Gainesville, Florida.
Abstract
BACKGROUND & AIMS: Studies have reported substantial variation in the competency of advanced endoscopy trainees, indicating a need for more supervised training in endoscopic ultrasound (EUS). We used a standardized, validated, data collection tool to evaluate learning curves and measure competency in EUS among trainees at multiple centers. METHODS: In a prospective study performed at 15 centers, 17 trainees with no prior EUS experience were evaluated by experienced attending endosonographers at the 25th and then every 10th upper EUS examination, over a 12-month training period. A standardized data collection form was used (using a 5-point scoring system) to grade the EUS examination. Cumulative sum analysis was applied to produce a learning curve for each trainee; it tracked the overall performance based on median scores at different stations and also at each station. Competency was defined by a median score of 1, with acceptable and unacceptable failure rates of 10% and 20%, respectively. RESULTS: Twelve trainees were included in the final analysis. Each of the trainees performed 265 to 540 EUS examinations (total, 4257 examinations). There was a large amount of variation in their learning curves: 2 trainees crossed the threshold for acceptable performance (at cases 225 and 245), 2 trainees had a trend toward acceptable performance (after 289 and 355 cases) but required continued observation, and 8 trainees needed additional training and observation. Similar results were observed at individual stations. CONCLUSIONS: A specific case load does not ensure competency in EUS; 225 cases should be considered the minimum caseload for training because we found that no trainee achieved competency before this point. Ongoing training should be provided for trainees until competency is confirmed using objective measures.
BACKGROUND & AIMS: Studies have reported substantial variation in the competency of advanced endoscopy trainees, indicating a need for more supervised training in endoscopic ultrasound (EUS). We used a standardized, validated, data collection tool to evaluate learning curves and measure competency in EUS among trainees at multiple centers. METHODS: In a prospective study performed at 15 centers, 17 trainees with no prior EUS experience were evaluated by experienced attending endosonographers at the 25th and then every 10th upper EUS examination, over a 12-month training period. A standardized data collection form was used (using a 5-point scoring system) to grade the EUS examination. Cumulative sum analysis was applied to produce a learning curve for each trainee; it tracked the overall performance based on median scores at different stations and also at each station. Competency was defined by a median score of 1, with acceptable and unacceptable failure rates of 10% and 20%, respectively. RESULTS: Twelve trainees were included in the final analysis. Each of the trainees performed 265 to 540 EUS examinations (total, 4257 examinations). There was a large amount of variation in their learning curves: 2 trainees crossed the threshold for acceptable performance (at cases 225 and 245), 2 trainees had a trend toward acceptable performance (after 289 and 355 cases) but required continued observation, and 8 trainees needed additional training and observation. Similar results were observed at individual stations. CONCLUSIONS: A specific case load does not ensure competency in EUS; 225 cases should be considered the minimum caseload for training because we found that no trainee achieved competency before this point. Ongoing training should be provided for trainees until competency is confirmed using objective measures.
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