Quality ControlNCT03622281
Quality Improvement Intervention in Colonoscopy Using Artificial Intelligence
A study testing quality improvement intervention using artificial intelligence in people with Quality Control and Artificial Intelligence, run by Shandong University at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Quality Control, Artificial Intelligence, Colonoscopy
- What is being tested?
- quality improvement intervention using artificial intelligence
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 676 participants
- Where
- 1 siteChina
- Study dates
- 20 Oct 2018to 31 May 2019
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- aged between 18 and 80;
- agree to give written informed consent.
Who cannot join
- 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 locations and contacts
1 site in 1 country.
China1 site
Department of Gastroenterology, Qilu Hospital, Shandong University
Jinan, Shandong, 250012
About this study
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.
- Conditions
- Quality Control, Artificial Intelligence, Colonoscopy
- Being tested
- quality improvement intervention using artificial intelligence
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
quality improvement intervention using artificial intelligenceOther
Colonoscopists received performance measure monitoring and feedback
| Study group | Role | What they receive |
|---|---|---|
| Colonoscopists who received quality intervention | Experimental | Not described Receives: Other: quality improvement intervention using artificial intelligence |
| Colonoscopists who did not received quality intervention | No intervention | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Adenoma detection rate
Adenoma detection rate was defined as the number of exams with findings of adenoma divided by the total number of exams.
Measured: 8 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Aug 2018
- Study start20 Oct 2018
- Primary completion31 May 2019
- Study completion31 May 2019
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Quality ControlStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 676 participants (actual)
Sponsor and investigators
- Lead sponsor
- Shandong University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yanqing Li, Shandong University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03622281
- Sponsor's protocol ID
- 2018SDU-QILU-716
- Status last verified
- Feb 2020
- First submitted
- 16 Jul 2018
- Last updated
- 12 Feb 2020
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
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
Study at a glance
From the registry record, last updated by the sponsor on 12 Feb 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Quality Improvement Intervention in Colonoscopy Using Artificial Intelligence
- ClinicalTrials.gov ID
- NCT03622281
- Acronym / sponsor ID
- 2018SDU-QILU-716
- Conditions
- Quality Control, Artificial Intelligence, Colonoscopy
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 676 participants (actual)
- Lead sponsor
- Shandong UniversityUniversity, hospital or other
- Study start
- 20 Oct 2018 (actual)
- Primary completion
- 31 May 2019 (actual)
- Study completion
- 31 May 2019 (actual)
- First posted
- 9 Aug 2018 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Colonoscopists who received quality intervention | Experimental | Other: quality improvement intervention using artificial intelligence |
| Colonoscopists who did not received quality intervention | No intervention | – |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- aged between 18 and 80;
- agree to give written informed consent.
Key exclusion criteria (6 listed)
- 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;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| quality improvement intervention using artificial intelligenceColonoscopists received performance measure monitoring and feedback | Other | Colonoscopists who received quality intervention |
Primary outcome
Adenoma detection rate
Time frame: 8 months
Adenoma detection rate was defined as the number of exams with findings of adenoma divided by the total number of exams.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Feb 2020.
- Derived from this study: PubMed 31454493Su 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.
Related trials for Quality Control
Not yet recruiting
A Hybrid Effectiveness-Implementation and Cost-Utility Evaluation of a Support Programme for Informal Carers of People With Dementia in Primary Care (EsCuidar2)
Quality of Life
Recruiting
The Effects of Synchronous and Asynchronous Pilates Training Based on Telerehabilitation on Core Stabilization, Balance, Cognitive Functions, and Quality of Life in Individuals With Multiple Sclerosis: A Single-Blind Randomized Controlled Trial
Multiple Sclerosis
Not yet recruiting
Testing a Multi-Level Approach to Reduce Stigma for Women Living With HIV
HIV (Human Immunodeficiency Virus)
Recruiting
MediPD: An Online Mediterranean Diet Program for People Living With Parkinson's Disease
Parkinson Disease, Idiopathic
RecruitingObservational study
Ablation Versus Non-ablation Strategies for Non-puerperal Mastitis: A Prospective Real-world Registry Study
Non-Puerperal Mastitis
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing quality improvement intervention using artificial intelligence in people with Quality Control and Artificial Intelligence, run by Shandong University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 12 Feb 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Adenoma detection rate (time frame: 8 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03622281, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Feb 2020.