The data on respiratory depression in the hospital is alarming – increased use of patient-controlled analgesia (PCA) and increasing numbers of patients presenting with obesity and diagnosed or undiagnosed sleep apnea have significantly increased the risk of adverse or fatal events1:
The ECRI Institute named undetected opioid-induced respiratory depression as one of the top 10 Health Technology Hazards for 20172. In addition, both The Joint Commission3 and AAMI Foundation4 recommend continuous respiratory monitoring of patients receiving sedatives to prevent adverse events.
Until now, most efforts to mitigate the risk of respiratory depression have had limited success, due to a number of inherent challenges:
Building on our leadership in vendor-neutral medical device connectivity and streaming patient safety applications, Capsule’s Respiratory Depression Safety Surveillance (RDSS) application is a revolutionary solution. In a published, peer-reviewed clinical study5 of patients diagnosed or suspected to have Obstructive or Central Sleep Apnea, the use of Capsule’s (formerly Bernoulli Health’s) RDSS analytics with multi-variable thresholds reduced 22,812 alarms generated by bedside capnographs and pulse oximeters to just 209 respiratory depression alerts delivered to clinicians’ mobile phones, a reduction of over 90%. More importantly, the RDSS analytics alerted for every patient that experienced an actual respiratory depression episode – all patients at risk were identified early enough by the analytic to be aroused and avoid the need for any rapid response team deployment, intubation or escalation in care.
Many alarm management systems from other vendors utilize criteria that requires alarms from devices to be sustained for a certain period of time before sending an alert to a mobile clinician. In this same study, use of a 30-second sustained alarm criteria still resulted in over 13,000 alarms, potentially putting both patients and clinicians at risk due to alarm fatigue.
Another study has shown that early detection and clinical intervention for patients at risk of respiratory depression can result in savings of over $1 million dollars a year, through the avoidance of transfers to ICU, reduced length of stay and improved patient flow.6
Read the award-winning study: “Continuous Surveillance of Sleep Apnea Patients in a Medical-Surgical Unit”, published in the peer-reviewed Journal of Biomedical Instrumentation & Technology (BI&T).
Click here to access the article.
This video is sponsored by the AAMI Foundation.
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Device connectivity with the EHR and other downstream systems is only getting started. Devoting hospital resources to broaden the scope of medical device integration is well worth the investment.
An ongoing study shows that combination smart alerts derived from medical device data can help to identify clinically actionable events.