The University of Michigan Center for Integrative Research in Critical Care is co-developing technology to predict declining health status in acute and critically ill patients and to alert appropriate clinicians via smartphones.

The university is working with AirStrip, a vendor of software to transmit patient data from monitoring devices and electronic health records to a clinician’s mobile device. The product being developed, called the mobile Acute Care Early Warning System (mACEWS), initially will focus on identifying hemodynamic decompensation, an inability of the heart to adequately circulate blood. The goal is to create a decision support tool that can identify risk factors that warrant early intervention.

Over time, the technology also could be used to better detect adverse health status in patients with chronic obstructive pulmonary disease, diabetes, congestive heart failure and other chronic conditions. Further, the technology could be used in homes.

The warning system will collect structured and unstructured data and analyze it on IBM’s InfoSphere Streams data analytics platform. Warnings would be sent to clinicians using AirStrips’ mobile applications on Apple, Android and Windows devices.

“By mining multiple data streams, looking at real-time analytics and applying our adaptive learning algorithms, we believe we can come up with new computed vital signs that are even more valuable than the signals we’re monitoring today,” Kevin Ward, M.D., professor of emergency medicine at U-M Medical School, said in a statement.

Register or login for access to this item and much more

All Health Data Management content is archived after seven days.

Community members receive:
  • All recent and archived articles
  • Conference offers and updates
  • A full menu of enewsletter options
  • Web seminars, white papers, ebooks

Don't have an account? Register for Free Unlimited Access