Impact of AI on Trainee ADR
Study Details
Study Description
Brief Summary
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.
Condition or Disease | Intervention/Treatment | Phase |
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N/A |
Detailed Description
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 Design
Arms and Interventions
Arm | Intervention/Treatment |
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Active Comparator: Artificial Intelligence Endoscopy Room The fellows will be randomized on a daily basis to perform colonoscopies in a room with AI (intervention) |
Diagnostic Test: AI use in Endoscopy Room
The use of AI versus no AI in comparing the detection of adenomas during Endoscopy procedures.
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Active Comparator: Non-Artificial Intelligence Endoscopy Room The fellows will be randomized on a daily basis to perform colonoscopies in a non-AI endoscopy room (standard of care). |
Other: Non-AI use Standard of Care endoscopy room
Non-AI use in comparing the detection of adenomas during Endoscopy procedures.
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Outcome Measures
Primary Outcome Measures
- Average adenoma detection rate [Throughout study, an average of 2 years]
Adenoma detection rate with and without AI
Secondary Outcome Measures
- Average of polyps detection rate [Through out study, an average of 2 years]
Polyp detection rate with and without AI
Eligibility Criteria
Criteria
Inclusion Criteria:
- All Gastroenterology fellows at USC performing Endoscopies will be included in the study.
Exclusion Criteria:
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If fellows refuse informed consent they will be excluded.
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Procedures performed in the intensive care unit or the operating room will not be counted toward the study metrics as the AI system will only be available in the endoscopy unit.
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If procedures are performed only by faculty, in which the fellow is not the primary operator, they will not be used for study metrics.
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- University of Southern California
Investigators
- Principal Investigator: James L Buxbaum, MD, University of Southern California
Study Documents (Full-Text)
None provided.More Information
Publications
- Abadir AP, Ali MF, Karnes W, Samarasena JB. Artificial Intelligence in Gastrointestinal Endoscopy. Clin Endosc. 2020 Mar;53(2):132-141. doi: 10.5946/ce.2020.038. Epub 2020 Mar 30.
- Calderwood AH, Jacobson BC. Comprehensive validation of the Boston Bowel Preparation Scale. Gastrointest Endosc. 2010 Oct;72(4):686-92. doi: 10.1016/j.gie.2010.06.068.
- Corley DA, Jensen CD, Marks AR, Zhao WK, Lee JK, Doubeni CA, Zauber AG, de Boer J, Fireman BH, Schottinger JE, Quinn VP, Ghai NR, Levin TR, Quesenberry CP. Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med. 2014 Apr 3;370(14):1298-306. doi: 10.1056/NEJMoa1309086.
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- HS-21-00094