Quality Improvement Intervention in Colonoscopy Using Artificial Intelligence

Not Applicable

Completed

• Conditions: Artificial Intelligence; Colonoscopy; Quality Control
• Interventions: Other: quality improvement intervention using artificial intelligence

• Registration Number: NCT03622281
• Lead Sponsor: Shandong University

Brief Summary

Quality measures in colonoscopy are important guides for improving the quality of patient care. But quality improvement intervention is not taking place, primarily because of the inconvenience and expense. To address the difficulties above, we used artificial intelligence for quality control of colonoscopy.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2018-07-16
• Study First Submitted QC: 2018-08-04
• Study First Posted: 2018-08-09
• Study Start: 2018-10-20
• Primary Completion: 2019-05-31
• Study Completion: 2019-05-31
• Status Verified: 2020-02
• Last Update Submitted: 2020-02-10
• Last Update Posted: 2020-02-12

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 676

Inclusion Criteria

• aged between 18 and 80;
• agree to give written informed consent.

Exclusion Criteria

• patients with the contraindications to colonoscopy examination;
• patients with a history of inflammatory bowel disease (IBD), CRC, colorectal surgery;
• patients with prior failed colonoscopy and high suspicion of polyposis syndromes, IBD and typical advanced CRC;
• patients refused to participate in the trial;
• the colonoscopyprocedure cannot be completed due to stenosis, obstruction, huge occupying lesions, or solid stool;
• the colonoscopy procedure have to be terminated due to complications of anaesthesia.

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Colonoscopists who received quality intervention	quality improvement intervention using artificial intelligence	-

Primary Outcome Measures

Name	Time	Method
Adenoma detection rate	8 months	Adenoma detection rate was defined as the number of exams with findings of adenoma divided by the total number of exams.

Trial Locations

Locations (1)

Department of Gastroenterology, Qilu Hospital, Shandong University; 🇨🇳 Jinan, Shandong, China