An automated system for identifying patients at risk for complications associated with the use of mechanical ventilators provided significantly more accurate results than did traditional surveillance methods, which rely on manual recording and interpretation of individual patient data. In their paper published in Infection Control & Hospital Epidemiology, a Massachusetts General Hospital (MGH) research team report that their system—using an […]

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