Adenoma detection rate (ADR) is a validated quality metric for colonoscopy with higher ADR correlated with improved colorectal cancer outcomes. Artificial intelligence (AI) can automatically detect polyps on the video monitor which may allow endoscopists in training to improve their ADR. Objective and Purpose of the study: Measure the effect of AI in a prospective, randomized manner to determine its impact on ADR of Gastroenterology trainees.
Our objective is to determine the impact of AI on the adenoma detection rate of Gastroenterology trainees. The secondary aim of this quality improvement study is to determine the impact of AI based endoscopy on the rate of recording of quality improvement metrics versus historical performance in our program. Fellows will undergo educational session prior to the start of study, describing commonly used metrics for assessing quality of colonoscopy and how to use the artificial intelligence software. Gastroenterology fellows will be consented for the study prior to initiation. The fellows will be randomized on a daily basis to perform colonoscopies in a room. Outcomes will measure the effects of AI in fellows
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
25
The use of AI versus no AI in comparing the detection of adenomas during Endoscopy procedures.
Non-AI use in comparing the detection of adenomas during Endoscopy procedures.
LAC+USC Medical Center
Los Angeles, California, United States
RECRUITINGAverage adenoma detection rate
Adenoma detection rate with and without AI
Time frame: Throughout study, an average of 2 years
Average of polyps detection rate
Polyp detection rate with and without AI
Time frame: Through out study, an average of 2 years
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