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Impact of AI on Trainee ADR

Primary Purpose

Adenoma, Adenoma Colon, Colorectal Cancer

Status
Recruiting
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
AI use in Endoscopy Room
Non-AI use Standard of Care endoscopy room
Sponsored by
University of Southern California
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Adenoma

Eligibility Criteria

undefined - undefined (Child, Adult, Older Adult)All SexesAccepts Healthy Volunteers

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.

Sites / Locations

  • LAC+USC Medical CenterRecruiting

Arms of the Study

Arm 1

Arm 2

Arm Type

Active Comparator

Active Comparator

Arm Label

Artificial Intelligence Endoscopy Room

Non-Artificial Intelligence Endoscopy Room

Arm Description

The fellows will be randomized on a daily basis to perform colonoscopies in a room with AI (intervention)

The fellows will be randomized on a daily basis to perform colonoscopies in a non-AI endoscopy room (standard of care).

Outcomes

Primary Outcome Measures

Average adenoma detection rate
Adenoma detection rate with and without AI

Secondary Outcome Measures

Average of polyps detection rate
Polyp detection rate with and without AI

Full Information

First Posted
April 26, 2022
Last Updated
March 2, 2023
Sponsor
University of Southern California
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1. Study Identification

Unique Protocol Identification Number
NCT05423964
Brief Title
Impact of AI on Trainee ADR
Official Title
Impact of Artificial Intelligence on Trainee Adenoma Detection Rate
Study Type
Interventional

2. Study Status

Record Verification Date
March 2023
Overall Recruitment Status
Recruiting
Study Start Date
January 1, 2023 (Actual)
Primary Completion Date
June 2025 (Anticipated)
Study Completion Date
September 2025 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
University of Southern California

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. 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.
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

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Adenoma, Adenoma Colon, Colorectal Cancer

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
None (Open Label)
Allocation
Randomized
Enrollment
25 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title
Artificial Intelligence Endoscopy Room
Arm Type
Active Comparator
Arm Description
The fellows will be randomized on a daily basis to perform colonoscopies in a room with AI (intervention)
Arm Title
Non-Artificial Intelligence Endoscopy Room
Arm Type
Active Comparator
Arm Description
The fellows will be randomized on a daily basis to perform colonoscopies in a non-AI endoscopy room (standard of care).
Intervention Type
Diagnostic Test
Intervention Name(s)
AI use in Endoscopy Room
Intervention Description
The use of AI versus no AI in comparing the detection of adenomas during Endoscopy procedures.
Intervention Type
Other
Intervention Name(s)
Non-AI use Standard of Care endoscopy room
Intervention Description
Non-AI use in comparing the detection of adenomas during Endoscopy procedures.
Primary Outcome Measure Information:
Title
Average adenoma detection rate
Description
Adenoma detection rate with and without AI
Time Frame
Throughout study, an average of 2 years
Secondary Outcome Measure Information:
Title
Average of polyps detection rate
Description
Polyp detection rate with and without AI
Time Frame
Through out study, an average of 2 years

10. Eligibility

Sex
All
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
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.
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Jessica Serna, BS
Phone
323-409-6939
Email
Jessica.Serna@med.usce.edu
First Name & Middle Initial & Last Name or Official Title & Degree
Alex Rodriguez, BS
Phone
323-409-6939
Email
Alex.Rodriguez@med.usc.edu
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
James L Buxbaum, MD
Organizational Affiliation
University of Southern California
Official's Role
Principal Investigator
Facility Information:
Facility Name
LAC+USC Medical Center
City
Los Angeles
State/Province
California
ZIP/Postal Code
90033
Country
United States
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
James Buxbaum, MD

12. IPD Sharing Statement

Plan to Share IPD
No
Citations:
PubMed Identifier
28248415
Citation
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Results Reference
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Citation
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PubMed Identifier
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Citation
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PubMed Identifier
28555630
Citation
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PubMed Identifier
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Citation
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Citation
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Impact of AI on Trainee ADR

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