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In response to an alarming increase in superbug infections, the Hong Kong Hospital Authority is turning to artificial intelligence (AI) as a key tool in tracking antibiotic resistance and developing new treatment strategies. This initiative comes as multidrug-resistant organisms (MDROs) like vancomycin-resistant enterococci and Candida auris pose a growing public health threat. Addressing the challenge of MDROs Recent reports by the South China Morning Post have highlighted a significant surge in cases of MDROs in Hong Kong. Dr. Raymond Lai, the chief infection control officer of the Hospital Authority, reported a marked increase in such infections during the first three quarters of 2023 compared to previous years. The rise is attributed to factors including the overuse of antibiotics and the reallocation of healthcare resources during the COVID-19 pandemic. The statistics are particularly concerning for Candida auris, a fungal infection with an escalated number of cases from nearly 200 in 2020 to over 300 in 2023. Vancomycin-resistant enterococci have also significantly increased, rising from 40 patients in 2021 to 140 by the third quarter of 2023. These figures underscore the urgent need for effective strategies to manage and mitigate the spread of these superbugs. AI pilot program for infection control To address this growing challenge, the Hospital Authority is implementing an AI pilot program, initially involving the Princess Margaret Hospital in Kwai Chung and the Prince of Wales Hospital in Sha Tin. This program aims to identify infection trends and patterns of antibiotic resistance, which is crucial for developing effective treatment plans. The AI system will assist medical personnel in making informed decisions about prescribing antibiotics, thereby helping to prevent the emergence of new resistant strains of bacteria. The program is slated for expansion to 17 other hospitals in a phased process throughout 2024. This initiative represents a significant step forward…

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Filed under: News - @ December 3, 2023 5:02 pm