Frequency of Passive EHR Alerts in the ICU: Another Form of Alert Fatigue?. Issue 3 (September 2019)

• Record Type: Journal Article
• Authors: Kizzier-Carnahan, Vanessa; Artis, Kathryn A.; Mohan, Vishnu; Gold, Jeffrey A.
• Is Part Of: Journal of patient safety. Volume 15:Issue 3(2019)
• Publication Date: 2019-09
• Subjects: alert -- electronic health record -- ICU -- simulation; Patients -- Safety measures -- Periodicals; Medicine -- Practice -- Safety measures -- Periodicals; Medical errors -- Prevention -- Periodicals; 610.289
• DOI: 10.1097/PTS.0000000000000270
• Languages: English
• ISSNs: 1549-8417

Abstract

Abstract : Objectives: The intensive care unit (ICU) is a complex environment in terms of data density and alerts, with alert fatigue, a recognized barrier to patient safety. The Electronic Health Record (EHR) is a major source of these alerts. Although studies have looked at the incidence and impact of active EHR alerts, little research has studied the impact of passive data alerts on patient safety. Method: We reviewed the EHR database of 100 consecutive ICU patient records; within, we assessed the number of values flagged as either as abnormal or "panic" across all data domains. We used data from our previous studies to determine the 10 most commonly visited screens while preparing for rounds to determine the total number of times, an abnormal value would be expected to be viewed. Results: There were 64.1 passive alerts/patient per day, of which only 4.5% were panic values. When accounting for the commonly used EHR screens by providers, this was increased to 165.3 patient/d. Laboratory values comprised 71% of alerts, with the remaining occurring in vitals (25%) and medications (6%). Despite the high prevalence of alerts, certain domains including ventilator settings (0.04 flags/d) were rarely flagged. Conclusions: The average ICU patient generates a large number of passive alerts daily, many of which may be clinically irrelevant. Issues with EHR design and use likely further magnify this problem. Our results establish the need for additional studies to understand how a high burden of passive alerts impact clinical decision making and how to design passive alerts to optimize their clinical utility.