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COVID-19 adding to clinician's cognitive overload

June 26, 2020
Business Affairs Health IT Risk Management

For patients with COVID-19, hospitals have connected mechanical ventilators in this way and included such vitals in their analysis to provide more meaningful decision-support information to the clinician than just an alert. Clinicians can review such holistic insights from a centralized workstation at a safe distance from patients. This tool has been able to limit unnecessary visits to the patient’s room to protect clinicians, but also reduce the usage of PPE.

Lessons from OIRD
Safely monitoring patients while reducing the alarm burden on clinicians is a challenge that is not unique to patients with COVID-19, but rather extends to many other types of complex patients. The dilemma faced during the pandemic is akin to research where our team worked with clinicians at a partner hospital to study a cohort of patients with sleep apnea, recovering from surgery and administered opioids for pain management. These patients are known to be at increased risk for opioid-induced respiratory depression (OIRD).
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At the start of our research, the medical devices (capnographs and pulse oximeters) that measured patients’ pulse (HR), oxygen saturation (SpO2), respiratory rate (RR), and end-tidal carbon dioxide (ETCO2) were set at the standard, or default, alert-time thresholds. The clinical team faced as many as 427 bedside respiratory depression alarms per hour for just one patient, although the average for patients studied was 182 per hour, or 22,812 for the entire study.

Applying basic alarm filtering delay techniques was able to reduce the number by 42%, still resulting in more than 13,000 alerts. The real impact was seen with a real-time, continuous clinical surveillance strategy that leveraged advanced analytics and was able to decrease alerts to just 209—a 99% reduction. The clinical surveillance technology supporting the strategy was also able to forward those alerts to the nurse’s mobile phone instead of sounding at the bedside only. This was possible by configuring multiple alert-threshold times through a multivariate rules engine that monitored the values of HR, RR, SpO2 and ETCO2. Moreover, our research team independently verified that no actual clinical events were overlooked and several patients received Naloxone to counteract OIRD. We also learned that in every observed case of OIRD, the in-room audible alarm annunciation did not awaken the patient.

The combination of high-fidelity data with multivariate, EHR information provided a holistic and complete source of objective information on patients that was used to eliminate non-clinically actionable alerts, but also to support prediction and clinical decision making prospectively.

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