Improving Quality and Safety In Your Endoscopy Unit: Live and Virtual | October 2022-Approaching Automation of Data Collection and Data Analysis

Video Transcription

Video Summary

In this video, the speaker discusses the challenges and limitations of automation in data collection and analysis for endoscopy procedures. They highlight the need for a large volume of procedures to confidently measure procedural quality and how this can be a challenge, especially for rural surgeons and gastroenterologists who may not perform enough procedures annually. The speaker also discusses the limitations of quality metrics, such as the calculation and actionable feedback provided. They explore different methods for data collection, including manual chart review, data registries like GI QIP, data warehouses, and natural language processing. The advantages and disadvantages of each method are discussed. The speaker also emphasizes the importance of watching procedures to assess skill, as demonstrated by the use of videos in determining outcomes for bariatric surgery procedures. They highlight the potential of AI in improving the assessment of quality and skill during procedures, including the use of AI algorithms to analyze endoscopy videos and provide feedback on aspects such as polyp detection and removal. The speaker concludes by discussing the need for better registries and novel measures to accurately measure quality and the potential for AI to reduce barriers in data collection and analysis.

Asset Subtitle

Raj Keswani, MD MS

Keywords

automation

data collection

endoscopy procedures

procedural quality

AI

data analysis