{"id":7652,"date":"2017-05-24T13:20:48","date_gmt":"2017-05-24T13:20:48","guid":{"rendered":"http:\/\/bernoullihealth.com\/?p=5861"},"modified":"2017-05-24T13:20:48","modified_gmt":"2017-05-24T13:20:48","slug":"study-real-time-analytics-continuous-monitoring-mitigates-threat-of-respiratory-depression-2","status":"publish","type":"post","link":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/study-real-time-analytics-continuous-monitoring-mitigates-threat-of-respiratory-depression-2\/","title":{"rendered":"Study: Real-Time Analytics, Continuous Monitoring Mitigates Threat of Respiratory Depression"},"content":{"rendered":"<h3><span style=\"color: #3366ff;\">Peer-reviewed results of patented surveillance application reveals promise of real-time patient safety initiatives in hospitals and health systems<\/span><\/h3>\n<p><strong>Milford, CT\u2014May 24, 2017<\/strong>\u2014Bernoulli, the leader in real-time solutions for patient safety, announced the publication of a peer-reviewed study demonstrating the use of patented real-time 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).<\/p>\n<p>Continuous Surveillance of Sleep Apnea Patients in a Medical-Surgical Unit<sup>1<\/sup> in the May\/June 2017 issue of the Journal of Biomedical Instrumentation &amp; 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.<\/p>\n<p>The study\u2019s 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.<\/p>\n<p>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\u2014a 99% reduction.<\/p>\n<p>\u201cMore importantly, clinical staff was alerted for every patient that experienced an actual respiratory depression episode,\u201d said the study\u2019s co-author, John Zaleski, PhD, CAP, CPHIMS, Chief Analytics Officer of Bernoulli. \u201cThe 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\u2019s access to real-time data.\u201d<\/p>\n<p><strong>A Growing Patient Safety Threat<\/strong><br \/>\nThe use of opioids, such as hydromorphone and morphine sulfate, are known to increase risk of respiratory depression in patients who have been diagnosed with or are at risk for obstructive sleep apnea (OSA).<\/p>\n<p>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.<\/p>\n<p>\u201cData from multiple sources may be required to achieve improvements in patient safety, including the EHR and real-time data from medical devices,\u201d said Zaleski. \u201cMoment-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.\u201d<\/p>\n<p><strong>Respiratory Depression Safety Surveillance<\/strong><br \/>\nThe solution leveraged in the study, Bernoulli\u2019s Respiratory Depression Safety Surveillance (RDSS), includes patented analytics with multi-variable thresholds\u2014adjustable by the care facility\u2014to identify clinically actionable events while significantly reducing the overall number of alarms communicated to remote and mobile clinicians, mitigating the risk of alarm fatigue.<\/p>\n<p>RDSS is flexible, adaptable and scalable from individual departments to enterprise-wide deployments. Its vendor-neutral architecture leverages the hospital\u2019s 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.<\/p>\n<p><strong>Implications for Real-Time Healthcare<\/strong><br \/>\n\u201cCombining analysis with real-time data at the point of collection creates a powerful tool for prediction and clinical decision support,\u201d said Zaleski. \u201cThe ability to track patients throughout the hospital, continuously add new devices, and distribute real-time patient monitoring to centralized dashboards and mobile devices should be a major consideration for CIOs tasked with achieving real-time healthcare capabilities.\u201d<\/p>\n<p>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.<\/p>\n<p>\u201cThis study demonstrates the promise of using real-time data for myriad patient safety initiatives,\u201d said Janet Dillione, CEO of Bernoulli. \u201cIn addition, Bernoulli\u2019s 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.\u201d<\/p>\n<p style=\"padding-left: 30px;\"><strong><em>Reference<\/em><\/strong><br \/>\n1. Supe D, Baron L, Decker T, Parker K, Venella J, Williams S, Beaton K, Zaleski J. A pilot study in middleware-filtered capnography alarms of continuously monitored obstructive sleep apnea patient in a medical-surgical unit. BI&amp;T. May\/June 2017.<\/p>\n<h4><img loading=\"lazy\" class=\"alignleft wp-image-5071\" src=\"http:\/\/bernoullihealth.com\/wp-content\/uploads\/2016\/04\/bernoulli-logo-1400pxhigh-300x150.jpg\" alt=\"Bernoulli One\u2122 is the market\u2019s only real-time, connected healthcare platform that combines comprehensive and vendor-neutral medical device integration with powerful middleware, clinical surveillance, telemedicine\/virtual ICU, advanced alarm management, real-time analytics and robust distribution capabilities into ONE solution that empowers clinicians with tools to drive better patient safety, clinical outcomes, patient experience, and provider workflow. \" width=\"200\" height=\"100\" \/><\/h4>\n<h4>About Bernoulli<\/h4>\n<p>Bernoulli is the leader in real-time solutions for patient safety, with more than 1,200 installed, operational systems. Bernoulli One\u2122 is the market\u2019s only real-time, connected healthcare platform that combines comprehensive and vendor-neutral medical device integration with powerful middleware, clinical surveillance, telemedicine\/virtual ICU, advanced alarm management, real-time\u00a0analytics and robust distribution capabilities into ONE solution that empowers clinicians with tools to drive better patient safety, clinical outcomes, patient experience, and provider workflow. For more information about Bernoulli One, visit <a href=\"http:\/\/www.bernoullihealth.com\">www.bernoullihealth.com<\/a>. Follow us on\u00a0<a href=\"https:\/\/www.linkedin.com\/company\/553268?trk=tyah&amp;trkInfo=clickedVertical%3Acompany%2CclickedEntityId%3A553268%2Cidx%3A2-1-3%2CtarId%3A1487251448672%2Ctas%3Abernoulli\">LinkedIn<\/a> and <a href=\"https:\/\/twitter.com\/BernoulliHealth\">Twitter<\/a> . Visit our Resource Center to download <a href=\"http:\/\/bernoullihealth.com\/case-studies\/\">case studies<\/a>, <a href=\"http:\/\/bernoullihealth.com\/education-and-reference-materials\/\">white papers<\/a> and <a href=\"http:\/\/bernoullihealth.com\/articles-and-media\/\">articles<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Bernoulli 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.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[80],"tags":[206,228,143,211,103],"_links":{"self":[{"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/posts\/7652"}],"collection":[{"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/comments?post=7652"}],"version-history":[{"count":0,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/posts\/7652\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/media?parent=7652"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/categories?post=7652"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/tags?post=7652"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}