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CompletedNCT03622281Updated Feb 12, 2020

Quality Improvement Intervention in Colonoscopy Using Artificial Intelligence

An interventional study of quality improvement intervention using artificial intelligence in Quality Control, Artificial Intelligence and Colonoscopy, sponsored by Shandong University. Completed at 1 site in China. Open to participants aged 18 Years to 80 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2020-02-12.

Sponsored by Shandong University · Not applicable, Interventional, and Health services research

Phase
Not applicable
Study type
Interventional
Enrollment
676
Allocation
Randomized
Ages
18 Years to 80 Years
Sex
All
01

Study 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.

02

Conditions studied

  • Quality Control
  • Artificial Intelligence
  • Colonoscopy
03

In context

Lead sponsor

Shandong University is the lead sponsor of 284 studies on the registry; 59 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 80 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Inclusion criteria

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

Exclusion criteria

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.
05

Study design

Phase
Not applicable
Primary purpose
Health services research
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Double (Participant, Outcomes assessor)
Enrollment
676 participants (actual)

Study arms

  • Experimental
    Colonoscopists who received quality intervention

    Other: quality improvement intervention using artificial intelligence

  • No intervention
    Colonoscopists who did not received quality intervention

Interventions

  • Otherquality improvement intervention using artificial intelligence

    Colonoscopists received performance measure monitoring and feedback

06

What researchers measure

Primary outcomes

  1. Adenoma detection rate

    Adenoma detection rate was defined as the number of exams with findings of adenoma divided by the total number of exams.

    Time frame: 8 months

07

Study locations

1 site
  • Department of Gastroenterology, Qilu Hospital, Shandong University
    Jinan, Shandong 250012, China
08

References and documents

Publications

  • 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. PubMed 31454493 ↗
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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Feb 12, 2020, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT03622281
Lead sponsor
Shandong University
Responsible party
Yanqing Li (Vice president of QiLu Hospital, Shandong University) — Principal investigator
First posted
Aug 9, 2018
Start date
Oct 20, 2018
Primary completion
May 31, 2019
Completion
May 31, 2019
Last update
Feb 12, 2020

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is completed, as verified in Feb 2020. You cannot join it, but the record below documents what was studied.

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