{"id":7250,"date":"2017-11-22T01:14:35","date_gmt":"2017-11-22T01:14:35","guid":{"rendered":"http:\/\/bernoullihealth.com\/?p=7250"},"modified":"2017-11-22T01:14:35","modified_gmt":"2017-11-22T01:14:35","slug":"white-paper-preventing-respiratory-depression","status":"publish","type":"post","link":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/white-paper-preventing-respiratory-depression\/","title":{"rendered":"Bernoulli White Paper | Preventing Respiratory Depression"},"content":{"rendered":"<div class=\"flex_column av_one_full  no_margin flex_column_div av-zero-column-padding first  avia-builder-el-0  el_before_av_one_third  avia-builder-el-first  \" style='margin-top:0px; margin-bottom:0px; border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock  '   itemprop=\"text\" ><h1 style=\"text-align: center;\">Bernoulli White Paper | Preventing Respiratory Depression<\/h1>\n<\/div><\/section><br \/>\n<div  class='avia-image-container  av-styling-    avia-builder-el-2  el_after_av_textblock  avia-builder-el-last  avia-align-center '  itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\"  ><div class='avia-image-container-inner'><div class='avia-image-overlay-wrap'><img class='wp-image-0 avia-img-lazy-loading-not-0 avia_image' src=\"http:\/\/bernoullihealth.com\/wp-content\/uploads\/2017\/11\/iStock-526656069-bw-1030x687.jpg\" alt='' title=''   itemprop=\"thumbnailUrl\"  \/><\/div><\/div><\/div><\/p><\/div>\n<div class=\"flex_column av_one_third  flex_column_div first  avia-builder-el-3  el_after_av_one_full  el_before_av_two_third  column-top-margin\" style='padding:10px; background-color:#eaeaea; border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock  '   itemprop=\"text\" ><h4 class=\"p1\"><span class=\"s1\">Executive Summary <\/span><\/h4>\n<p class=\"p2\"><span class=\"s2\">Opioids are integral to most post-surgical pain management strategies. However, post-operative patients at risk for obstructive or central sleep apnea are particularly vulnerable to undetected respiratory depression.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">Analysis of site claims reviews suggest that improved surveillance techniques could prevent most opioid-induced respiratory depression (OIRD) events. Continuous clinical surveillance is a powerful tool for prediction, mitigates alarm fatigue and facilitates the distribution of real-time data to centralized dashboards or mobile devices.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">As such, continuous clinical surveillance has been recommended as a best practice by prominent healthcare advocates and governing agencies.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">The purpose of this white paper is to:<\/span><\/p>\n<ul>\n<li class=\"p3\"><span class=\"s2\">Define the inherent risks associated with undetected OIRD in patients with obstructive or central sleep apnea<\/span><\/li>\n<li class=\"p3\"><span class=\"s2\">Identify the short-comings of current surveillance tactics<\/span><\/li>\n<li class=\"p3\"><span class=\"s2\">Describe the key elements of continuous clinical surveillance<\/span><\/li>\n<li class=\"p3\"><span class=\"s2\">Demonstrate the efficacy of continuous clinical surveillance.<\/span><\/li>\n<\/ul>\n<\/div><\/section><br \/>\n<div  style=' margin-top:30px; margin-bottom:30px;'  class='hr hr-custom hr-center hr-icon-no   avia-builder-el-5  el_after_av_textblock  el_before_av_textblock '><span class='hr-inner  inner-border-av-border-fat' style=' width:50px; border-color:#7bb0e7;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock  '  style='font-size:16px; '  itemprop=\"text\" ><h3 style=\"text-align: center;\"><a href=\"http:\/\/go.bernoullihealth.com\/white-paper-preventing-respiratory-depression\"><img loading=\"lazy\" class=\"aligncenter wp-image-7256 size-full\" src=\"http:\/\/bernoullihealth.com\/wp-content\/uploads\/2017\/11\/continuous-clinical-surveillance.jpg\" alt=\"continuous clinical surveillance\" width=\"232\" height=\"300\" \/><\/a><\/h3>\n<p style=\"text-align: center;\"><span style=\"color: #3366ff;\"><a href=\"http:\/\/go.bernoullihealth.com\/white-paper-preventing-respiratory-depression\"><u>Click here<\/u><\/a><\/span><\/p>\n<p style=\"text-align: center;\"><a href=\"http:\/\/go.bernoullihealth.com\/white-paper-preventing-respiratory-depression\"><span style=\"color: #333333;\">To download a pdf version of:<br \/>\n<span style=\"line-height: inherit; font-size: 16px;\">Bernoulli White Paper:<br \/>\nPreventing Respiratory Depression<\/span><\/span><\/a><\/p>\n<\/div><\/section><\/p><\/div>\n<div class=\"flex_column av_two_third  flex_column_div av-zero-column-padding   avia-builder-el-7  el_after_av_one_third  el_before_av_one_third  column-top-margin\" style='border-radius:0px 0px 0px 0px ; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock  '   itemprop=\"text\" ><h4 class=\"p1\"><\/h4>\n<h2 class=\"p1\"><span class=\"s1\">Respiratory Depression is Preventable<\/span><\/h2>\n<p class=\"p4\"><span class=\"s2\">Injuries or death due to OIRD has become an increasingly urgent<sup>1<\/sup>\u2014and public<sup>2<\/sup>\u2014concern for hospitals and health systems.<\/span><\/p>\n<p class=\"p5\">According to the Association for the Advancement of Medical Instrumentation (AAMI), more than 20,000 opioid-induced respiratory depression interventions occur annually. This estimated cost for these interventions to the U.S. healthcare system are about $2 billion per year.<sup>3<\/sup> According to the Joint Commission\u2019s Sentinel Event database, 29 percent of adverse events are related to improper patient monitoring.<sup>4<\/sup><\/p>\n<p class=\"p5\"><span class=\"s2\">However, the overwhelming majority of respiratory depression cases\u201497 percent<sup>5<\/sup>\u2014could have been prevented with the appropriate surveillance practices.<\/span><\/p>\n<p class=\"p5\"><span class=\"s1\">In an analysis of the Anesthesia Closed Claims Project database of patients at risk for respiratory depression over a 20-year<\/span> period, Lee, et al., noted<\/p>\n<p class=\"p6\"><span class=\"s2\">\u2026a growing consensus that opioid-related adverse events are multifactorial and potentially preventable with improvements in assessment of sedation level, monitoring of oxygenation and ventilation, and early response and intervention, particularly within the first 24 [hours] postoperatively.<sup>6<\/sup><\/span><\/p>\n<p class=\"p5\"><span class=\"s2\">The Joint Commission, Anesthesia Patient Safety Foundation, AAMI and others recommend the adoption of continuous respiratory depression surveillance as a best practice. However, this practice remains the exception to the rule<sup>7<\/sup>, particularly outside critical care settings.<\/span><\/p>\n<h2 class=\"p1\"><span class=\"s1\">Current State of Patient Surveillance<\/span><\/h2>\n<p class=\"p2\"><span class=\"s2\">Current practices for monitoring patients receiving opioids are neither adequate nor comprehensive for early intervention. The most common practices include visual spot checks by clinical staff and responding to alarms by physiologic devices.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">However, beneath these strategies lie potentially lethal assumptions. Clinicians won\u2019t always be present when respiratory depression occurs. Pulse oximeters and capnographs are often set to pre-determined thresholds, which can cause false alarms.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">In truth, spots checks can leave patients unmonitored 96 percent<sup>8<\/sup> of the time, leaving them vulnerable to advanced deterioration. In addition, neither method consistently identifies gradual deterioration; only that respiratory depression is already in progress.<sup>9<\/sup><\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">Jungquist, et al., note that in 42 percent of confirmed OIRD events, \u201cthe interval between the last nursing assessment and the detection of respiratory depression was less than two hours, and in 16 [percent] of the cases, it was within 15 minutes.\u201d<sup>10<\/sup><\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">The inability to identify respiratory depression early is not just a patient safety problem. Rescuing these patients is also costly in terms of resource utilization, morbidity and mortality.<sup>11<\/sup><\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">In contrast, continuous clinical surveillance utilizes real-time data to help clinicians quickly recognize and respond to signs of respiratory distress. A rules-based analytics engine and multi-parameter physiological monitoring devices can identify, capture and distribute clinically actionable data to remote clinicians in real time while also eliminating nuisance alarms.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">There also is growing evidence that continuous clinical surveillance facilitates interventions long before OIRD degrades to a life-threatening event.<\/span><\/p>\n<h2 class=\"p1\"><span class=\"s1\">Key Elements of Continuous Clinical Surveillance<\/span><\/h2>\n<p class=\"p2\"><span class=\"s2\">Continuous clinical surveillance allows clinicians to surveil multiple patients from a centralized location or via mobile alarm notifications. Continuous clinical surveillance uses multi-variate rules to correlate data and create new early warning alarms. This helps clinicians to quickly recognize and respond to signs of respiratory distress before the patient\u2019s health is compromised.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">The solution is broken into three main buckets\u2014medical device integration (MDI), smart alarms and data distribution and communication capabilities.<\/span><\/p>\n<p class=\"p2\"><span class=\"s3\">Medical Device Integration. <\/span><span class=\"s2\">Smart alarms can be implemented using device-agnostic middleware for interfacing with bedside devices. Most medical device integration solutions gather and filter data to support documentation in an EHR. To achieve real-time surveillance, a more clinically significant capability, MDI should be able to collect data at variable speeds to meet the requirements of various clinical operational settings. The ability to retrieve data at variable rates (including at the sub-second level) requires advanced technical capabilities.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">Data collection and analysis are further enhanced when including methods for disseminating, analyzing, and distributing the data and the smart alarm signals. These features facilitate better patient care management and clinical workflow by allowing patients to be monitored remotely. This enables dynamically adding and removing medical devices and distributing real-time patient monitoring to dashboards and mobile devices. <\/span><\/p>\n<p class=\"p2\"><span class=\"s3\">Smart Alarms. <\/span><span class=\"s2\">An underlying factor that produces alarm fatigue is that the simplistic threshold limits in pulse oximeters and capnographs are highly susceptible to false alarms. Optimization of the alarm limits on these devices and silencing of non-actionable alarms is not enough to eliminate the risk of alarm fatigue. The challenge of attenuating alarm data is achieving the balance between communicating essential patient information while minimizing spurious and non-emergent events.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">Continuous clinical surveillance solutions that analyze real-time patient data can generate smart alarms. Identifying clinically relevant trends, sustained conditions, reoccurrences and combinatorial indications may indicate a degraded patient condition prior to the violation of any individual parameter. In addition, clinicians can leverage settings and adjustments data from bedside devices to evaluate adherence to or deviation from evidence-based care plans and best-practice protocols.<\/span><\/p>\n<p class=\"p2\"><span class=\"s3\">Data Distribution. <\/span><span class=\"s2\">Clinicians can\u2019t be everywhere at once. Even the most aggressive rounding protocols will leave patients alone for a significant period of time. In addition, the physical layout of the care unit can impair a clinician\u2019s ability to move quickly from patient to patient.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">Continuous clinical surveillance allows clinical staff to monitor patients remotely. Networked laptop and desktop computers as well as scrolling message bars can provide clinical staff with access to data and alarms from all surveilled patients. In addition, alarms can easily be routed to central stations via dashboards or mobile devices and pagers.<\/span><\/p>\n<h2 class=\"p1\"><span class=\"s1\">Continuous Clinical Surveillance at Work<\/span><\/h2>\n<p class=\"p2\"><span class=\"s2\">Bernoulli recently collaborated with Virtua Health System to determine if selectively delayed notifications using adjustable, multi-variable thresholds could identify clinically-actionable events and reduce false alarms without risking patient safety.<sup>12<\/sup><\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">The study measured pulse (HR), oxygen saturation (SpO<sub>2<\/sub>), respiratory rate (RR), and end-tidal carbon dioxide (ETCO2) continuously. It then compared alarms received through the bedside monitoring devices with remote alerts annunciated through the Bernoulli system, designed to trigger only after a selective delay.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">Using only sustained alarms as the filter for notifications reduced alerts from 22,812 to 13,272, which was still high enough to risk alarm fatigue. Passing multiple data time series through a multi-variate rules engine that monitored the values of HR, RR, SPO2 and ETCO<sub>2<\/sub> reduced the number alerts sent to the nurse-call phone system to 209\u2014a 99 percent reduction. In addition, that it was independently verified that no actual clinical events were missed and several patients received Naloxone to counteract OIRD.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">An important observation made during this study was that remote alarm communication was an important aide to in-room monitoring alarm annunciation. A key argument that is made for in-room annunciation in the case of conscious or waking sleep apnea patients is the room audible alert. Yet, in every observed case of OIRD, the in-room audible annunciation had no effect on waking or stirring the patients. Hence, remote monitoring capability to catch such instances is necessary to ensure patients do not slip through the cracks.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">Beyond high-acuity areas, healthcare systems are creating a foundation for other real-time healthcare innovations, including clinical surveillance modules, MDI with the EHR and virtual ICUs.<\/span><\/p>\n<h2 class=\"p1\"><span class=\"s1\">Conclusion<\/span><\/h2>\n<p class=\"p2\"><span class=\"s2\">Healthcare organizations face a steep climb to significantly reduce OIRD events. The inadequacy of spot-checks and the medical community\u2019s consensus on the superiority of continuous surveillance point to an urgent need for new best practices.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">However, concerns over adding to clinician alarm fatigue and contributing to an increasingly noisy hospital environment are significant obstacles. Hospitals need to take a system-wide inventory of alarms, apply analytics to understand their value and convene project teams to embark on a technology transformation.<\/span><\/p>\n<p class=\"p2\"><span class=\"s2\">This transformation should include the perspectives of frontline clinicians and should respect the significance of disrupting workflows. Hospitals should employ smart technologies to ensure only actionable alarm signals are sent to clinical staff. The deployment of continuous clinical surveillance requires a careful investment of time and money in addition to workflow considerations to ensure the highest level of patient safety.<\/span><\/p>\n<\/div><\/section><\/div>\n<div class=\"flex_column av_one_third  flex_column_div av-zero-column-padding first  avia-builder-el-9  el_after_av_two_third  el_before_av_two_third  column-top-margin\" style='border-radius:0px; '><\/div>\n<div class=\"flex_column av_two_third  flex_column_div av-zero-column-padding   avia-builder-el-10  el_after_av_one_third  avia-builder-el-last  column-top-margin\" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock  '  style='font-size:11px; '  itemprop=\"text\" ><p class=\"p1\"><span class=\"s1\"><b>References<\/b><\/span><\/p>\n<ol>\n<li class=\"p2\"><span class=\"s1\">ECRI Institute. Top 10 Health Technology Hazards for 2017. November 2017. Available at: www.ecri.org\/Resources\/Whitepapers_and_reports\/Haz17.pdf.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Regan R. \u2018Dead in bed\u2019 cases result in rising malpractice lawsuits nationwide. News 5 Cleveland. December 21, 2016. Available at:<br \/>\nwww.news5cleveland.com\/news\/local-news\/investigations\/dead-in-bed-cases-result-in-rising-malpractice-lawsuits-nationwide.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">AAMI Foundation. Opioid Safety &amp; Patient Monitoring Conference Compendium. November 14, 2014. Available at: http:\/\/s3.amazonaws.com\/rdcms-aami\/files\/production\/public\/Libraries\/Opioids\/Opioid_Compendium_2015.pdf.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">The Joint Commission. Sentinel Event Alert. Issue 49. August 8, 2012. Available at: www.jointcommission.org\/assets\/1\/18\/SEA_49_opioids_8_2_12_final.pdf.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Lee LA, Caplan RA, Stephens LS, Posner KL, Terman GW, Voepel-Lewis T, Domino KB. Postoperative opioid-induced respiratory depression: a closed claims analysis. Pain Medicine. March 2015. Available at: http:\/\/anesthesiology.pubs.asahq.org\/article.aspx?articleid=2087871.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Ibid.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Curry JP and Jungquist CR. A critical assessment of monitoring practices, patient deterioration, and alarm fatigue on inpatient wards: a review. Patient Saf Surg. 2014;8:29. Available at: www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC4109792.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Weinger MB and Lee La. No patient shall be harmed by opioid-induced respiratory depression. APSF Newsletter. Fall. 2011. Available at: www.apsf.org\/newsletters\/html\/2011\/fall\/01_opioid.htm.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Curry JP and Jungquist CR. A critical assessment of monitoring practices, patient deterioration, and alarm fatigue on inpatient wards: a review. Patient Saf Surg. 2014;8:29.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Jungquist CR, Smith K, Nicely KL, Polomano RC. Monitoring hospitalized adult patients for opioid-induced sedation and respiratory depression. AJN. March 2017; 117(3):S27\u2013S35. Available at: http:\/\/journals.lww.com\/ajnonline\/Fulltext\/2017\/03001\/Monitoring_Hospitalized_Adult_Patients_for.4.aspx.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Calzavacca P, Licari E, Tee A, Egi M, Haase M, Haase-Fielitz A, Bellomo R. A prospective study of factors influencing the outcome of patients after a Medical Emergency Team review. Intensive Care Med. November 2008;34(11):2112-6. Available at: www.ncbi.nlm.nih.gov\/pubmed\/18651130.<\/span><\/li>\n<li class=\"p2\"><span class=\"s1\">Supe D, Baron L, Decker T, Parker K, Venella J, Williams S, Beaton L, Zaleski J. Research: Continuous surveillance of sleep apnea patients in a medical-surgical unit. Biomedical Instrumentation &amp; Technology. May\/June 2017; 51(3): 236-251. Available at: http:\/\/aami-bit.org\/doi\/full\/10.2345\/0899-8205-51.3.236?code=aami-site.<\/span><\/li>\n<\/ol>\n<\/div><\/section><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":7258,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[184,331],"tags":[158,330,83,182],"_links":{"self":[{"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/posts\/7250"}],"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=7250"}],"version-history":[{"count":0,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/posts\/7250\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/media\/7258"}],"wp:attachment":[{"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/media?parent=7250"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/categories?post=7250"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.light4soul.com\/testingsite\/cardiop\/wp-json\/wp\/v2\/tags?post=7250"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}