Artificial Intelligence (AI) can dramatically enhance hospitals’ infection prevention efforts, according to experts. Insights presented at two pre-conference events of the European Congress of Clinical Microbiology and Infectious Diseases highlighted the pivotal role of AI in healthcare – from detecting strokes to speeding up administrative tasks, even identifying patients at high risk for HIV and other sexually transmitted infections.
Introducing refined AI systems to efficiently track employee interactions and improve data gathering can enable real-time response to outbreaks. Pioneering work in the integration of robotics for specific tasks shows that AI can be utilized to detect, and potentially prevent, hospital outbreaks.
Richmond Drew, a distinguished microbiologist at Rotunda Hospital, Ireland, notes that repetitive tasks should be delegated to AI systems. These could include environmental cleaning or auditing mask compliance. Leveraging AI can also unlock opportunities in big data analytics for specific patient groups, he adds.
However, Drew warns against potential wastage of resources. The effectiveness of AI depends on recognizing its application in the specific context of individual institutions, whether it’s in ensuring staff adherence to mask protocols, maintaining facility cleanliness, or optimizing treatment regimens.
Drew cited a review of over 30 studies using AI facial recognition technology to assess medical staff adherence to mask-wearing protocols, which proved successful. He further described that robotic AI systems could automate environmental monitoring and cleaning, thus eliminating the need for manual sanitation. Importantly, AI can enhance antimicrobial stewardship by assisting clinicians in making timely decisions on patient medication changes.
Jonas Marschall, a professor of medicine specialized in infectious diseases at the Washington University School of Medicine, illustrated the potential of AI in managing outbreaks. Relating an example of a vancomycin-resistant Enterococcus faecium (VRE) outbreak at Bern University Hospital, Switzerland, Marschall demonstrated how AI could predict risk factors for patient colonization.
Marschall emphasized how, through comprehensive coverage of all interactions involving employees, patients, and visitors, AI systems could effectively track colonizations, infections, and potential risk factors. He concluded: “The beauty of AI in outbreak management — and where its greatest power lies — is to make real-time or near real-time operational decisions easier, quicker and more precise.”