False alarms are widely considered the No. 1 hazard caused by use of medical technologies.

Health care providers can be overwhelmed with as many as 350 alarms triggered per patient per day, of which 80-99 percent are meaningless or false. These false alarms, which can be due to several factors, may result in alarm fatigue among health care providers where the possibility of missing a true life-threatening event can be lost in a cacophony of multiple alarms.

Fatemeh Afghah, an assistant professor in the School of Informatics, Computing, and Cyber Systems at Northern Arizona University, received a $175,000 grant from the National Science Foundation to develop a computational framework to reduce the false alarm rate in intensive care units (ICUs) by integrating principles from information theory, game theory and signal processing.

In this project, Afghah aims to develop an accurate yet general method to reduce the number of false alarms while avoiding the suppression of true alarms through integrating information from a variety of devices. The proposed false alarm detection method will potentially save many patients’ lives and significantly reduce medical costs.

Alarm safety has been determined as a national patient safety goal by The Joint Commission, which accredits and certifies nearly 21,000 health care organizations and programs in the United States.