Gastroenterology and Artificial Intelligence: 4th Annual Global Artificial Intelligence Summit (On-Demand | August 2022-Advances in AI to Improve Endoscopic Efficiency

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In this document, Dr. Shyam Thakkar discusses the importance of efficiency in endoscopic units and explores the use of AI to optimize performance. The healthcare industry in the United States is seeing rising costs, and there is a need to improve efficiency in order to enhance patient experiences and increase access to endoscopic procedures.<br /><br />Efficiency can be measured through various key metrics, including patient preparation, procedure time, anesthesia time, and recovery. By capturing unbiased workflow data automatically and integrating it with the endoscope system and electronic health records (EHRs), AI can optimize the use of resources and improve workflow management in endoscopic units.<br /><br />One solution is the development of a digital twin of the endoscopy suite, which uses deep learning and realistic computer reasoning for decision making. This digital twin can help identify bottlenecks in the workflow and suggest improvements to enhance efficiency.<br /><br />AI can also be used to automate certain processes in endoscopy, such as detecting adenomas during colonoscopies and assessing bowel preparation. Natural language processing (NLP) models can analyze medical records and extract key terms to identify important information for report generation. AI models have shown comparable or better performance than manual entry in measuring colonoscopy quality metrics.<br /><br />The document emphasizes the potential benefits of using AI in endoscopic units, including time and cost savings, standardized procedures, and improved documentation. However, there are still limitations and challenges to overcome, such as the need for further research and data on the impact of AI on workflow improvement.<br /><br />Overall, the use of AI in endoscopic units holds promise for optimizing efficiency and improving patient care in the healthcare industry.

Asset Subtitle

Shyam Thakkar, MD

Keywords

efficiency

endoscopic units

AI

performance optimization

healthcare industry

workflow data

resource optimization

automation

NLP models

workflow improvement