Not all colonoscopies are the same: New AI audits them at scale
Colonoscopies are one of the most effective ways to prevent colorectal cancer, which is surging among young adults in the U.S. Yet, the quality of each procedure can vary substantially from one physician to another. As a result, medical societies recommend routinely reviewing every colonoscopist—something that's challenging and time-consuming for practices to implement.
Colorectal cancer rates are rising among younger people in the United States, making colonoscopies a vital tool in prevention. However, the quality of these procedures can vary widely between medical professionals. To address this issue, Northwestern Medicine researchers have created an artificial intelligence (AI) tool that can efficiently and accurately assess the quality of colonoscopies by analyzing procedure footage.
In a study involving nearly 19,000 colonoscopies, the AI tool demonstrated impressive accuracy when compared to assessments made by nurses and other clinicians. The tool's capability to measure key quality indicators, such as withdrawal time and polyp removal rates, could make it easier for hospitals and health care systems to monitor and improve colonoscopy quality on a large scale.
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