Frequency of passive EHR alerts in the ICU: another form of alert fatigue?
Open accessAbstract
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.
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Critical care patients generate approximately 100 EHR alerts for end-users per day.
“One study showed that critical care patients generate approximately 100 EHR alerts for end-users per day.”
From Qualitative Study of Inpatient Hospital Medicine Interruptive Alerts and Clinical Decision Support (2026) · cites this paper as [13]
The Results (page not specified) report a mean of 64.1 passive EHR alerts generated per ICU patient per day, rising to 165.3 when repeated appearances during chart review are counted. The study supports substantial daily alert exposure, but neither measure is approximately 100 alerts, and its findings concern passive alerts rather than all EHR alerts. (LLM, conf=0.86)
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Fallon, A., Haralambides, K., Mazzillo, J., & Gleber, C. (2024) · Applied Clinical Informatics · doi:10.1055/a-2226-8144 · Cited by 22 · see citing works
Qualitative Study of Inpatient Hospital Medicine Interruptive Alerts and Clinical Decision Support
Khan, A., & Schnipper, J. (2026) · Applied Clinical Informatics · doi:10.1055/a-2955-9555
- Authors
- Kizzier-Carnahan, V., Artis, K. A., Mohan, V., & Gold, J. A.
- Affiliations
- Division of Pulmonary and Critical Care
- Oregon Health & Science University (US)
- Corresponding author
- Kizzier-Carnahan, Vanessa
- Artis, Kathryn A.
- Gold, Jeffrey A.
- Venue
- Journal of Patient Safety
- Published
- 2016-06-22
- Volume
- 15
- Issue
- 3
- Pages
- 246-250
- ISSN
- 1549-8417 (ISSN-L)
- 1549-8425
- PMC
- PMC5820226
- OpenAlex
- W2468571596
- Cited by
- 32
- References
- 2
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 3 · 2023: 6 · 2022: 4 · 2021: 3 · 2020: 5 · 2018: 2 · 2017: 3
- FWCI
- 1.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Patient Safety (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- Agency for Healthcare Research and Quality (R01 HS023793, R18HS021637)
- Topics
- Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
- Keywords
- alarm fatigue, electronic health records, intensive care unit, patient safety, laboratory abnormalities, EHR design, clinical decision-making
- MeSH terms
- Fatigue, Humans, Intensive Care Units, Middle Aged, Electronic Health Records
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