A study showed that an automated system that uses an algorithm to detect ventilator-associated events, or VAEs, in hospitalized patients is more accurate and efficient than traditional manual surveillance performed by infection control staff, researchers said.

“Ventilator-associated pneumonia is a very serious problem that is estimated to develop in up to half the patients receiving mechanical ventilator support,” Brandon Westover, MD, PhD, a physician in the department of neurology at Massachusetts General Hospital (MGH) and director of the hospital’s Clinical Data Animation Center (CDAC), said in a news release.

Westover and colleagues developed an algorithm to retrospectively review ventilated ICU patients at Massachusetts General Hospital to identify VAEs and compared the results with surveillance conducted by infection control staff. According to results published in Infection Control & Hospital Epidemiology, the automated system was 100% accurate at identifying at-risk patients when supplied with necessary data.