Bernoulli’s John Zaleski and Jeanne Venella co-author respiratory depression study in Biomedical Instrumentation & Technology
John Zaleski, PhD, CAP, CPHIMS, Chief Analytics Officer, and Jeanne Venella, DNP, MS, RN, CEN, CPEN, Chief Nursing Officer of Bernoulli, the real-time leader in patient safety, co-authored a study demonstrating the use of patented analytics, medical device connectivity and combinatorial alarms to provide remote centralized continuous monitoring of post-surgical patients at risk for opioid-induced respiratory depression (OIRD).
The peer-reviewed study—Continuous Surveillance of Sleep Apnea Patients in a Medical-Surgical Unit—published in the May/June 2017 issue of Biomedical Instrumentation & Technology, consists of two separate studies on the use of continuous capnography monitoring at a medical-surgical unit at Virtua Health System in New Jersey.
The study’s results suggest that combinatorial alarm signals based on multi-parameter assessment reduced overall load better than individual-parameter sustained alarm signals and appeared to be more effective at identifying at-risk patients.
Using only sustained alarms as the filter for notifications reduced alerts from 22,812 to 13,000. However, passing multiple series of data through a multi-variable rules engine that monitored the values of pulse (HR), oxygen saturation (SpO2), respiratory rate (RR), and end-tidal carbon dioxide (ETCO2) in order to determine which alarms to send to the nurse-call phone system further reduced alerts to just 209—a 99% reduction.
The solution leveraged in the study, Bernoulli’s Respiratory Depression Safety Surveillance, includes patented analytics with multi-variable thresholds—adjustable by the care facility—to identify clinically actionable events while significantly reducing the overall number of alarms communicated to remote and mobile clinicians, mitigating the risk of alarm fatigue.
The study’s other co-authors include Dana Supe, MD, MBA, DABSM; Leah Baron, MD; Tom Decker; and Kyle Parker of Virtua, and Kari Beaton, RN, and Sarah Williams, RT, of Bernoulli.