Using Generative Artificial Intelligence for Healthcare-Associated Infection Surveillance

Abstract

Generative artificial intelligence (GenAI) is becoming widespread in society but has had limited impact on medicine. GenAI can rapidly digest large documents, making it particularly well-suited for healthcare-associated infection (HAI) surveillance that is largely based on clinical notes. In this paper, we review evidence on the application of GenAI for HAI surveillance and highlight necessary steps for changes to practice. Small studies of simulated patients and retrospective studies of patient records have found GenAI can isolate individual criteria for HAI and make HAI determinations with similar accuracy to human experts. GenAI tools are being developed to assist in HAI detection. Use of GenAI for HAI review could reduce variability between facilities, improve efficiency of HAI review and lead to more time for direct prevention work. For widespread adoption, GenAI HAI detection must be safe and effective in prospective clinical studies.

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