AirStrip and IBM today announced that AirStrip will work to develop a mobile monitoring solution to help clinicians predict declining health in acute and critically ill patients. IBM will provide the streaming analytics technology which allows AirStrip’s solution to use data from numerous data sources in real time.
The new solution, being co-developed by AirStrip with the University of Michigan (U-M) Center for Integrative Research in Critical Care, will bring together data from electronic medical records, body sensors and other sources with predictive analytics to create an AirStrip mobile Acute Care Early Warning System (mACEWS), that ultimately could be used to provide critical health insights to doctors’ mobile devices. The system will be designed by AirStrip and the U-M Center for Integrative Research in Critical Care (MCIRCC) to help hospitals better manage acutely ill patients.
MCIRCC will pioneer the application of this technology with AirStrip by developing the advanced analytics and testing its ability to identify and predict a serious and unexpected complication called hemodynamic decompensation, one of the most common causes of death for critically ill or injured patients. MCIRCC researchers anticipate that the resulting solution may provide the clinical decision support tool that enables clinicians to identify patient risk factors for early intervention. Early intervention can enhance critical care delivery, improve patient outcomes, and reduce ICU admissions (according to source). If successful, this clinical decision support tool created by AirStrip and MCIRCC could transition beyond critical care into comprehensive hospital-to-home care models.
“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,” said Kevin Ward, M.D., MCIRCC’s executive director and professor of Emergency Medicine, U-M Medical School. “Ultimately, we believe that clinical decision support solutions coupled with our analytic methodologies could help us improve patient outcomes while reducing overall costs in the healthcare system.”
How it Works
The AirStrip mACEWS system will collect and translate structured and unstructured data via the AirStrip ONE® platform, and deliver real-time analytics on that data using IBM® InfoSphere® Streams, an advanced analytic platform that can be used in most any industry and with multiple types of data, that allows customer-developed applications to quickly ingest, analyze and correlate millions of data points per second as they arrive from thousands of real-time sources. The AirStrip mACEWS system’s resulting predictive care insights would then be ready for consumption by clinicians who use AirStrip’s mobile applications on Apple, Android and Windows devices.
“Predictive analytics have the potential to provide clinicians the ability to see and take action on much more of the potentially available data on their patients, and course-correct sooner when a complication presents,” said Sean Hogan, vice president and general manager of IBM Healthcare.
A tool such as the one being developed by AirStrip could also be applied to patients being monitored both inside and outside the hospital to detect clinical deterioration from chronic obstructive pulmonary disease (COPD), diabetes, congestive heart failure, or other chronic diseases.
“With its ability to assimilate vast amounts of data and provide real time analytics, IBM effectively complements AirStrip’s established leadership position in mobile interoperability,” said Alan Portela, CEO of AirStrip. “Our products hold the promise of measurably improving the clinical, operational and financial bottom lines in healthcare, delivering innovation that can measurably strengthen patient care while addressing real-world challenges faced by providers.”