Quality Improvement Intervention in Colonoscopy Using Artificial Intelligence

NCT ID: NCT03622281

Last Updated: 2020-02-12

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

676 participants

Study Classification

INTERVENTIONAL

Study Start Date

2018-10-20

Study Completion Date

2019-05-31

Brief Summary

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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

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Conditions

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Quality Control Artificial Intelligence Colonoscopy

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

HEALTH_SERVICES_RESEARCH

Blinding Strategy

DOUBLE

Participants Outcome Assessors

Study Groups

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Colonoscopists who received quality intervention

Group Type EXPERIMENTAL

quality improvement intervention using artificial intelligence

Intervention Type OTHER

Colonoscopists received performance measure monitoring and feedback

Colonoscopists who did not received quality intervention

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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quality improvement intervention using artificial intelligence

Colonoscopists received performance measure monitoring and feedback

Intervention Type OTHER

Eligibility Criteria

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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.
Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Shandong University

OTHER

Sponsor Role lead

Responsible Party

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Yanqing Li

Vice president of QiLu Hospital

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Department of Gastroenterology, Qilu Hospital, Shandong University

Jinan, Shandong, China

Site Status

Countries

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China

References

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Su JR, Li Z, Shao XJ, Ji CR, Ji R, Zhou RC, Li GC, Liu GQ, He YS, Zuo XL, Li YQ. Impact of a real-time automatic quality control system on colorectal polyp and adenoma detection: a prospective randomized controlled study (with videos). Gastrointest Endosc. 2020 Feb;91(2):415-424.e4. doi: 10.1016/j.gie.2019.08.026. Epub 2019 Aug 24.

Reference Type DERIVED
PMID: 31454493 (View on PubMed)

Other Identifiers

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2018SDU-QILU-716

Identifier Type: -

Identifier Source: org_study_id

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