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Using Generative Artificial Intelligence for Healthcare-Associated Infection Surveillance.

Daniel J Morgan1,2, Katherine E Goodman1,3, Westyn Branch-Elliman4,5

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Clinical Infectious Diseases : an Official Publication of the Infectious Diseases Society of America
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Summary
This summary is machine-generated.

Generative artificial intelligence (GenAI) shows promise for healthcare-associated infection (HAI) surveillance by accurately analyzing clinical notes. Further prospective studies are needed to ensure safety and effectiveness for widespread adoption in clinical practice.

Keywords:
artificial intelligenceinfectionsurveillance

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Infectious Disease Surveillance

Background:

  • Generative artificial intelligence (GenAI) is rapidly advancing but has seen limited integration into medical applications.
  • Healthcare-associated infection (HAI) surveillance relies heavily on analyzing extensive clinical documentation.
  • GenAI's capability to process large volumes of text makes it a potential tool for improving HAI surveillance.

Purpose of the Study:

  • To review the current evidence on applying GenAI for HAI surveillance.
  • To identify necessary steps for integrating GenAI into clinical practice for HAI detection.
  • To highlight the potential benefits and challenges of using GenAI in this domain.

Main Methods:

  • Review of existing literature on GenAI applications in HAI surveillance.
  • Analysis of small-scale studies involving simulated patients and retrospective patient records.
  • Evaluation of GenAI's accuracy in identifying HAI criteria and making determinations compared to human experts.

Main Results:

  • Preliminary studies indicate GenAI can accurately identify HAI criteria and make determinations, comparable to human experts.
  • GenAI tools are under development to enhance HAI detection capabilities.
  • Evidence suggests GenAI can reduce inter-facility variability and improve the efficiency of HAI reviews.

Conclusions:

  • GenAI demonstrates potential to enhance HAI surveillance efficiency and accuracy.
  • Widespread adoption requires further validation through prospective clinical studies to ensure safety and efficacy.
  • Successful implementation could free up clinical resources for direct infection prevention efforts.