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Artificial Intelligence in Infection Control—Healthcare Institutions Need Intelligent Information and Communication Technologies for Surveillance and Benchmarking

  • Walter Koller
  • Andrea Rappelsberger
  • Birgit Willinger
  • Gabriel Kleinoscheg
  • Klaus-Peter AdlassnigEmail author
Chapter
  • 7 Downloads
Part of the Studies in Computational Intelligence book series (SCI, volume 899)

Abstract

Modern healthcare and medicine depend on the implementation of best practice, which includes surveillance of, and benchmarking with, predefined quality indicators. Given the automated analysis of microbiological findings and automated surveillance of healthcare-associated infections (HAIs), we put forward arguments in favor of the increasing use of intelligent information and communication technologies for the assessment and surveillance of infection. With MOMO, a modern microbiology analytics software, as well as with MONI, a fully automated detection and monitoring system for HAIs, we registered a much greater precision of analytics and surveillance. The time taken by these systems was much less than that needed for conventional surveillance. We registered the need for timely amendments and adaptations concerning new input categories or new reporting outputs as desired by clinicians, administrators, and health authorities. Intelligent information and communication technologies are thus becoming indispensable in the construction of affordable “safety nets” for quality assurance and benchmarking, based on fully automated and intelligent data and knowledge management. These, in turn, constitute the backbone of high-level healthcare, patient safety, and error prevention.

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Walter Koller
    • 1
  • Andrea Rappelsberger
    • 2
  • Birgit Willinger
    • 3
  • Gabriel Kleinoscheg
    • 4
  • Klaus-Peter Adlassnig
    • 2
    • 4
    Email author
  1. 1.Clinical Institute of Hospital HygieneMedical University of Vienna and Vienna General HospitalViennaAustria
  2. 2.Section for Artificial Intelligence and Decision Support, Center for Medical Statistics, Informatics, and Intelligent SystemsMedical University of ViennaViennaAustria
  3. 3.Division of Clinical Microbiology, Department of Laboratory MedicineMedical University of Vienna and Vienna General HospitalViennaAustria
  4. 4.Medexter Healthcare GmbHViennaAustria

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