Automating the Generation of Antimicrobial Resistance Surveillance Reports: Proof-of-Concept Study Involving Seven Hospitals in Seven Countries

• Главные авторы: Lim, Cherry (Автор), Miliya, Thyl (Автор), Chansamouth, Vilada (Автор), Aung, Myint Thazin (Автор), Karkey, Abhilasha (Автор), Teparrukkul, Prapit (Автор), Rahul, Batra (Автор), Lan, Nguyen Phu Huong (Автор), Stelling, John (Автор), Turner, Paul (Автор), Ashley, Elizabeth (Автор), van Doorn, H Rogier (Автор), Lin, Htet Naing (Автор), Ling, Clare (Автор), Hinjoy, Soawapak (Автор), Iamsirithaworn, Sopon (Автор), Dunachie, Susanna (Автор), Wangrangsimakul, Tri (Автор), Hantrakun, Viriya (Автор), Schilling, William (Автор), Yen, Lam Minh (Автор), Tan, Le Van (Автор), Hlaing, Htay Htay (Автор), Mayxay, Mayfong (Автор), Vongsouvath, Manivanh (Автор), Basnyat, Buddha (Автор), Edgeworth, Jonathan (Автор), Peacock, Sharon J (Автор), Thwaites, Guy (Автор), Day, Nicholas PJ (Автор), Cooper, Ben S (Автор), Limmathurotsakul, Direk (Автор)
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• Опубликовано: JMIR Publications, 2020-10-01T00:00:00Z.
• Предметы: article
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BackgroundReporting cumulative antimicrobial susceptibility testing data on a regular basis is crucial to inform antimicrobial resistance (AMR) action plans at local, national, and global levels. However, analyzing data and generating a report are time consuming and often require trained personnel....