Quality Improvement Intervention in Colonoscopy Using Artificial Intelligence

Shandong University

Status: Completed

Conditions: Quality Control; Artificial Intelligence; Colonoscopy

Treatments: Other: quality improvement intervention using artificial intelligence

Study type: Interventional

Funder types: Other

Identifiers

NCT03622281

2018SDU-QILU-716

Details and patient eligibility

About

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.

Enrollment: 676 patients

Sex: All

Ages: 18 to 80 years old

Volunteers: Accepts Healthy Volunteers

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.

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Double Blind

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676 participants in 2 patient groups

Colonoscopists who received quality intervention

Experimental group

Treatment:

Other: quality improvement intervention using artificial intelligence

Colonoscopists who did not received quality intervention

No Intervention group