Data in Motion Phenotyping: From the Intensive Care Unit to the Home
Data in motion phenotyping: from the intensive care unit to the home
On February 5, Kevin Ward, MD spoke about some of the biggest challenges that healthcare providers face when caring for critically ill and injured patients, including the volume (up to 100,000 data points per second), heterogeneity, velocity and dynamics of structured and unstructured data that is produced during 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.
Dr. Ward described current challenges and approaches in developing 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.