Impact of AI on Trainee ADR

Study Overview
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Brief Summary
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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.

Detailed Description
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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

Official Title
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Impact of Artificial Intelligence on Trainee Adenoma Detection Rate

Conditions
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Adenoma, Adenoma Colon, Colorectal Cancer

Intervention / Treatment
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* Diagnostic Test: AI use in Endoscopy Room
* Other: Non-AI use Standard of Care endoscopy room


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: All Gastroenterology fellows at USC performing Endoscopies will be included in the study. Exclusion Criteria: If fellows refuse informed consent they will be excluded. 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. If procedures are performed only by faculty, in which the fellow is not the primary operator, they will not be used for study metrics.
Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Active Comparator: Artificial Intelligence Endoscopy Room<br>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<br>* The use of AI versus no AI in comparing the detection of adenomas during Endoscopy procedures.<br>|
| Active Comparator: Non-Artificial Intelligence Endoscopy Room<br>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<br>* Non-AI use in comparing the detection of adenomas during Endoscopy procedures.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Average adenoma detection rate | Adenoma detection rate with and without AI | Throughout study, an average of 2 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Average of polyps detection rate | Polyp detection rate with and without AI | Through out study, an average of 2 years |