ProMedica to Utilize New Maternal-Fetal Warning System

By: Danielle Porteus
Monroe News Staff Reporter
Posted: October 9, 2018 at 6:00pm

Vigilance is designed to help clinicians identify troubling trends earlier and more consistently than manual assessments.

ProMedica recently announced plans to deploy “Vigilance,” an artificial intelligence-based maternal-fetal early warning system in all of its labor and delivery hospitals.

Vigilance is designed to help clinicians identify troubling trends earlier and more consistently than manual assessments and creates a common language for nurses and physicians to assess cases, a news release said.

The artificial intelligence-driven technology, developed by perinatal decision support firm PeriGen, is the latest chapter in ProMedica’s commitment to lead improvement in Ohio and Michigan’s infant and maternal mortality and morbidity rates, which currently rank near the bottom of the nation.

The software is designed to be implemented in a matter of weeks and brings an unprecedented level of monitoring to the labor and delivery floor. It does not require replacing any current systems already in place.

“While we invest significantly in training our nurses, we feel this technology will enhance our ability to provide the safest care possible,” said Kent Bishop, MD, chief medical officer for ProMedica Physicians and Acute Care. “Using AI to help nurses assess and consistently identify irregularities is so logical, we considered trying to build our own solution; during our research we found a proven system that we can partner with.”

ProMedica is committed to patient safety, Matthew Sappern, CEO of PeriGen said.

“ProMedica has taken a very visible leadership role in combating infant and maternal morbidity and mortality and aspires to continuous improvement in this service line,” Sappern said.

Contact us to learn more about PeriGen’s solutions
By |2018-11-08T14:24:36+00:00October 10th, 2018|Media Coverage, News|Comments Off on ProMedica to Utilize New Maternal-Fetal Warning System