In this study, the investigators proposed an artificial intelligence-based preoperative automatic reminder system on colonocopy, which can improve the quality of bowel preparation and the rate of polyps and adenomas detection.
Despite advances in bowel preparation methods, bowel preparation is inadequate in up to one-third of all colonoscopies in reported series. Inadequate bowel cleansing results in negative con-sequences for the examination, including incomplete visualization of the colon, missed lesions(22-48%), procedural difficulties, prolonged procedure time and reduced time interval until follow-up, and an estimated 12-22% increase in overall colonoscopy cost. The adequacy of a bowel preparation is closely linked to patient compliance with both dietary and purge instructions. Previous work has shown that 18-23.5% of the patients with poor preparation had failed to follow preparation instructions. One study performed in Asia showed that non-compliance with bowel preparation instructions, lower education level, and a long wait for the colonoscopy appointment were independent risk factors for poor bowel preparation. A survey among doctors showed that gastroenterologists with the highest number of patients with inadequate bowel preparation believed that patients are unwilling to follow preparation instructions, struggle with the prescribed diet, and are unable to tolerate the full course of purgative. It is reasonable to hypothesis that efforts to improve education and maximize patient compliance during the preparatory period will enhance the efficacy of bowel preparation. A research has shown that telephone-based re-education about the details of bowel preparation on the day before colonoscopy significantly improved the quality of bowel preparation and polys detection rate. In recent years, artificial intelligence (AI) has been successfully applied in multiple medical fields. But there has not been an artificial-intelligence-based system which can automatically remind patients of the details of bowel preparation on the day before colonoscopy. In this study, we proposed an artificial intelligence-based preoperative automatic reminder system on colonoscopy, which can improve the quality of bowel preparation and the rate of polyps and adenomas detection.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SCREENING
Masking
DOUBLE
Enrollment
829
the patients in the experimental group will be sent a message and a phone call by AI system on the day before colonoscopy, which will emphasize the importance of bowel preparation, the directions for use and side effects of purgatives, the proper food type, and the start time. The system is an non-invasive AI system.
Renmin hospital of Wuhan University
Wuhan, Hubei, China
the rate of adequate bowel preparation
The numerator is the number of patients qualified for intestinal preparation, and the denominator is the number of all patients undergoing colonoscopy. The definition of intestinal preparation qualification is: e-bbps qualification is defined as colonoscopy with e-bbps ≥ 6; BBPS is defined as enteroscopy with scores ≥2 for ascending colon, transverse colon and descending colon. At the same time, if one or more of the following conditions are met, intestinal preparation is considered insufficient: (1) colonoscopy with e-bbps \<6 is insufficient（ 2) Cancel colonoscopy due to poor intestinal preparation or personal reasons（ 3) Incomplete colonoscopy.
Time frame: From the beginning to the end of colonoscopy
Detection rate of adenoma
The numerator is the number of patients diagnosed with adenomas, and the denominator is the total number of patients undergoing colonoscopy.
Time frame: A month
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