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Impact of AI on Trainee ADR

Impact of Artificial Intelligence on Trainee Adenoma Detection Rate

Status
UNKNOWN
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05423964
Enrollment
25
Registered
2022-06-21
Start date
2023-01-01
Completion date
2025-09-30
Last updated
2023-03-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Adenoma, Adenoma Colon, Colorectal Cancer

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.

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

Interventions

DIAGNOSTIC_TESTAI use in Endoscopy Room

The use of AI versus no AI in comparing the detection of adenomas during Endoscopy procedures.

OTHERNon-AI use Standard of Care endoscopy room

Non-AI use in comparing the detection of adenomas during Endoscopy procedures.

Sponsors

University of Southern California
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
NONE

Eligibility

Sex/Gender
ALL
Healthy volunteers
Yes

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.

Design outcomes

Primary

MeasureTime frameDescription
Average adenoma detection rateThroughout study, an average of 2 yearsAdenoma detection rate with and without AI

Secondary

MeasureTime frameDescription
Average of polyps detection rateThrough out study, an average of 2 yearsPolyp detection rate with and without AI

Countries

United States

Contacts

Primary ContactJessica Serna, BS
Jessica.Serna@med.usce.edu323-409-6939
Backup ContactAlex Rodriguez, BS
Alex.Rodriguez@med.usc.edu323-409-6939

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 8, 2026