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Advantech Europe

AI-Powered Early Warning Solution Facilitates Timely Intervention

By HospiMedica International staff writers
Posted on 12 Mar 2018
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Image: The PeriWatch Vigilance is designed as a new fetal and maternal early warning platform (Photo courtesy of PeriGen).
Image: The PeriWatch Vigilance is designed as a new fetal and maternal early warning platform (Photo courtesy of PeriGen).
PeriGen (Cary, NC, USA), a provider of perinatal early warning systems, delivered a sneak peek of PeriWatch Vigilance, its new fetal and maternal early warning platform, at the 2018 HIMSS Conference & Exhibition (HIMSS18).

PeriGen offers innovative perinatal software solutions, which incorporate artificial intelligence (AI) to enhance clinical efficiency and standardization of care during childbirth. The company’s new PeriWatch Vigilance early warning platform for obstetrics automatically identifies patients whose conditions are worsening, facilitating more timely interventions. The "always on" software uses proprietary intelligent algorithms to analyze maternal vital signs, fetal heart rate, contractions and labor progress in real time, alerting clinicians of emerging abnormalities. Specific thresholds and automated checklists can be configured according to the hospital’s preferences.

The enterprise-wide platform augments currently installed fetal surveillance systems, providing a critical layer of patient safety without requiring hospitals to "rip and replace" their current systems. Simple to implement, it allows clinicians to spend more time on direct patient care and less time on manual calculations and data manipulation.

"Delayed response to clinical warning signs is by far the leading human factor found in severe birth-related morbidity," said Matthew Sappern, CEO of PeriGen. "The tireless analyses performed by PeriWatch Vigilance help clinicians see worrisome trends at a glance, and intervene before it is too late. Use of early warning systems as well as the PeriWatch modules has been associated with a reduction in morbidity."

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