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ChatGPT: Increasing accessibility for natural language processing in healthcare quality measurement
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Journal Article
ChatGPT: Increasing accessibility for natural language processing in healthcare quality measurement
2024
Overview
In this issue of Infection Control and Healthcare Epidemiology, Perret and Schmidt explore the potential for ChatGPT to support HAI surveillance activities for facilities with limited information technology (IT) resources to support automated detection.1 Although standardized definitions exist for HAIs, local data collection and recording practices vary, leading to differences in how these definitions are interpreted. Clinical notes can pose challenges, such as historical data copy forward, inconsistencies within the same note, variable spellings and abbreviations, among other real-world implementation barriers. [...]how their model performance will translate to actual clinical notes remains unknown; theoretically, however, ChatGPT should be able to learn how to read clinical documentation despite these challenges with real-world documentation. Not only could such technology reduce the human resources required to conduct HAI surveillance, but ChatGPT’s reduced need for location-specific training data also allows broader healthcare applications, potentially standardizing surveillance practices and workflows across facilities and improving interfacility comparison.
Publisher
Cambridge University Press
Subject
