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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Colonoscopists who received quality intervention | Experimental |
| |
| Colonoscopists who did not received quality intervention | No Intervention |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| quality improvement intervention using artificial intelligence | Other | Colonoscopists received performance measure monitoring and feedback |
|
| Measure | Description | Time Frame |
|---|---|---|
| Adenoma detection rate | Adenoma detection rate was defined as the number of exams with findings of adenoma divided by the total number of exams. | 8 months |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Department of Gastroenterology, Qilu Hospital, Shandong University | Jinan | Shandong | 250012 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31454493 | Derived | 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. |
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