A Clinical Case of Electronic Health Record Drug Alert Fatigue: Consequences for Patient Outcome
Abstract
Despite advances in electronic medication order entry systems, it has been well established that clinicians override many drug allergy alerts generated by the electronic health record. The direct clinical consequences of overalerting clinicians in a pediatric setting have not been well demonstrated in the literature. We observed a patient in the PICU who experienced complications as a result of an extended series of non–evidence-based alerts in the electronic health record. Subsequently, evidence-based allergy alerting changes were made to the hospital’s system. Incorporating clinical evidence in electronic drug allergy alerting systems remains challenging, especially in pediatric settings.
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It is widely accepted that alert fatigue explains high override rates.
“It is widely accepted that “alert fatigue” explains high override rates [7, 9–14].”
From Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system (2017) · cites this paper as [9]
The desensitization model holds that repeated exposure to alerts leads to declining responsiveness.
“A second conceptual model of alert fatigue is that repeated exposure to alerts leads to declining responsiveness [9, 19, 20], a phenomenon that can be called desensitization .”
From Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system (2017) · cites this paper as [9]
Application of AI systems in the real world may lead to many unintended outcomes, including alert fatigue, additional burdens for clinicians, disruption of interpersonal communications, and generation of specific threats requiring increased vigilance to recognize.
“Application of AI systems in the real world may lead to many unintended outcomes, including alert fatigue,131 additional burdens for clinicians, disruption of interpersonal communications, and generation of specific threats requiring increased vigilance to recognize.132”
From Artificial intelligence in diabetes management: Advancements, opportunities, and challenges (2023) · cites this paper as [131]
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- Authors
- Carspecken, C. W., Sharek, P. J., Longhurst, C., & Pageler, N. M.
- Affiliations
- Harvard University (US)
- Lucile Packard Children's Hospital (US)
- Systems Medicine, and
- Stanford Medicine (US)
- ORCID
- Pageler, Natalie M.
- Venue
- Pediatrics
- Publisher
- American Academy of Pediatrics (AAP)
- Published
- 2013-06-01
- Volume
- 131
- Issue
- 6
- Pages
- e1970-e1973
- ISSN
- 0031-4005 (ISSN-L)
- 1098-4275
- OpenAlex
- W2047955590
- Cited by
- 142
- References
- 22
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 9 · 2023: 11 · 2022: 11 · 2021: 10 · 2020: 15 · 2019: 11 · 2018: 8 · 2017: 11 · 2016: 11 · 2015: 17 · 2014: 8 · 2013: 2
- FWCI
- 21.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- PEDIATRICS (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
- Health Sciences › Medicine › Pharmacology › Drug-Induced Adverse Reactions
- Keywords
- drug allergy alerts, electronic health records, alarm fatigue, alert override, pediatric intensive care unit, drug safety, patient outcomes
- MeSH terms
- Child, Preschool, Diagnosis, Differential, Drug Hypersensitivity, Fatigue, Humans, Male, Medication Errors, Practice Patterns, Physicians', Evidence-Based Medicine, Decision Support Systems, Clinical, Medical Order Entry Systems, Electronic Health Records
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