An Alert Notification Subsystem for AI Based Clinical Decision Support: A Protoype in NICU

The potential for recommendation systems integrated within clinical workflows for effective dissemination of vital information needed in decision making at the bedside is explored in this paper. Our premise is that by utilizing big data analytics platforms for processing high frequency physiological data from multiple patients, fused with clinical context, we can generate recommendations on patients detected as potential for onset of conditions, and that if such information is communicated on time to the appropriate health care providers could have an impact when making decisions on care of critically ill patients. To support this, we have designed and developed an alert notification subsystem that combines vast analytics to detect abnormal patient's physiology, determine who is on service at the bedside and then generate appropriate notification to that care provider during their schedule time in a hospital critical care unit.