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Study: Real-Time Analytics, Continuous Monitoring Mitigates Threat of Respiratory DepressionMILFORD, Conn., May 24, 2017 /PRNewswire/ -- Bernoulli, the leader in real-time solutions for patient safety, announced the publication of a peer-reviewed 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). Continuous Surveillance of Sleep Apnea Patients in a Medical-Surgical Unit1 in the May/June 2017 issue of the Journal 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. "More importantly, clinical staff was alerted for every patient that experienced an actual respiratory depression episode," said the study's co-author, John Zaleski, PhD, CAP, CPHIMS, Chief Analytics Officer o Bernoulli. "The successful implementation of real-time patient safety initiatives have long been a goal of health system CIOs, but recognizing and responding to signs of patient deterioration requires medical devices connectivity as well as clinician's access to real-time data." A Growing Patient Safety Threat More than half of medication-related deaths and 20,000 incidences of respiratory depression-related interventions annually are attributed to the delivery of opioids in a care setting, at a cost of approximately $2 billion per year to the U.S. healthcare system. "Data from multiple sources may be required to achieve improvements in patient safety, including the EHR and real-time data from medical devices," said Zaleski. "Moment-to-moment changes in patient vitals are not usually available in the long-term clinical record, so a hybrid approach involving both real-time and aperiodic and discrete data is required to improve the overall surveillance of these patients." Respiratory Depression Safety Surveillance RDSS is flexible, adaptable and scalable from individual departments to enterprise-wide deployments. Its vendor-neutral architecture leverages the hospital's existing investments in IT, network, wireless and mobile infrastructure, while its FDA class II clearance includes indications for use to provide remote monitoring and alarm surveillance. Implications for Real-Time Healthcare Beyond high-acuity areas, healthcare systems are creating a foundation for other real-time healthcare innovations, including clinical surveillance modules, medical device integration in an EHR and virtual ICUs. "This study demonstrates the promise of using real-time data for myriad patient safety initiatives," said Janet Dillione, CEO of Bernoulli. "In addition, Bernoulli's RDSS solution sets the stage for a wide range of applications, including medical device integration, precision alarm notifications, and clinical surveillance modules in various care settings." Reference
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