Impact of an Artificial Intelligence-Based Computer Aided Detection System (CADe) on Colonoscopies Performed in...

Area of Science:

• Gastroenterology
• Medical Technology
• Artificial Intelligence

Background:

• Rising demand for colonoscopies due to aging population, post-COVID-19 backlog, and increased colorectal cancer (CRC) in younger individuals.
• Quality indicators like adenoma detection rate (ADR) are crucial for high-quality colonoscopies and reducing missed lesions.
• Computer-aided detection (CADe) systems, including AI, aim to enhance endoscopist polyp identification and improve ADR.

Purpose of the Study:

• To evaluate the impact of the GI Genius CADe system on ADR in Hawaii, the first location in the state to implement this technology.
• To conduct a cost-effectiveness analysis of the GI Genius system compared to standard colonoscopy.

Main Methods:

• Data collection on aggregate ADR for male and female patients before and after GI Genius implementation in Hawaiian ambulatory surgery centers.
• Statistical analysis to determine the significance of changes in ADR.
• Cost-estimate analysis comparing GI Genius with standard colonoscopy.

Main Results:

• The GI Genius system led to a statistically significant increase in ADR for both male and female patients.
• The implementation of GI Genius was found to be cost-effective.
• Anticipated reduction in CRC-related healthcare costs associated with the improved ADR.

Conclusions:

• GI Genius CADe is a promising tool for improving colonoscopy quality and increasing ADR.
• The AI system demonstrates cost-effectiveness, potentially lowering future healthcare expenditures related to colorectal cancer.
• Further research is necessary to ascertain the long-term effects of CADe on CRC incidence and mortality.