Data in Motion Phenotyping: From the Intensive Care Unit to the Home
MIDAS gratefully acknowledges Northrop Grumman Corporation for its generous support of the MIDAS Seminar Series.
The care of critically ill or injured patients poses enormous challenges due in large part to the volume (up to 100,000 data points per second), heterogeneity, velocity, and dynamics of structured and unstructured data produced in their care. Unlike static approaches (i.e., cell surface makers, genetic phenotypes) used to guide precision medicine in cancer, the dynamic changes that occur during critical illness and injury over multiple echelons of care demand the development of data capture, integration, and analytics capable of promoting rapid clinical decision making within minutes to hours. We will describe current challenges and approaches to develop data-in-motion phenotyping solutions that may allow continuous predictive early warning and trajectory monitoring for clinical decision making that span from the Intensive Care Unit to the home and beyond.
Kevin Ward, MD, is an Emergency Medicine specialist and Professor of Emergency Medicine in the University of Michigan Medical School. He also serves as Executive Director for two innovation programs including the Michigan Center for Integrative Research in Critical Care (MCIRCC) and the Medical School's Fast Forward Medical Innovation (FFMI) program. Dr. Ward's research encompasses developing innovative platforms and approaches that integrate and span the spectrum of complex pathophysiology of critical illness and injury ranging form the critically ill neonate to the critically injured warfighter. This includes operationalizing solutions across the challenging echelons of care that patients traverse.