Cited by 18Electronic Health Records SystemsHealthcare Technology and Patient MonitoringSepsis Diagnosis and Treatment

The Nature and Variability of Automated Practice Alerts Derived from Electronic Health Records in a U.S. Nationwide Critical Care Research Network

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Benthin, Cody, Pannu, Sonal, Khan, Akram, Gong, Michelle·2016·Annals of the American Thoracic Society

Abstract

Rationale: The nature, variability, and extent of early warning clinical practice alerts derived from automated query of electronic health records (e-alerts) currently used in acute care settings for clinical care or research is unknown. Objectives: To describe e-alerts in current use in acute care settings at medical centers participating in a nationwide critical care research network. Methods: We surveyed investigators at 38 institutions involved in the National Institutes of Health–funded Clinical Trials Network for the Prevention and Early Treatment of Acute Lung Injury (PETAL) for quantitative and qualitative analysis. Measurements and Main Results: Thirty sites completed the survey (79% response rate). All sites used electronic health record systems. Epic Systems was used at 56% of sites; the others used alternate commercially available vendors or homegrown systems. Respondents at 57% of sites represented in this survey used e-alerts. All but 1 of these 17 sites used an e-alert for early detection of sepsis-related syndromes, and 35% used an e-alert for pneumonia. E-alerts were triggered by abnormal laboratory values (37%), vital signs (37%), or radiology reports (15%) and were used about equally for clinical decision support and research. Only 59% of sites with e-alerts have evaluated them either for accuracy or for validity. Conclusions: A majority of the research network sites participating in this survey use e-alerts for early notification of potential threats to hospitalized patients; however, there was significant variability in the nature of e-alerts between institutions. Use of one common electronic health record vendor at more than half of the participating sites suggests that it may be possible to standardize e-alerts across multiple sites in research networks, particularly among sites using the same medical record platform.

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Authors
Benthin, C., Pannu, S., Khan, A., & Gong, M.
Affiliations
  • Oregon Health & Science University (US)
  • The Ohio State University Wexner Medical Center (US)
  • Albert Einstein College of Medicine (US)
Corresponding author
Khan, Akram
Venue
Annals of the American Thoracic Society
Published
2016-10-01
Volume
13
Issue
10
Pages
1784-1788
ISSN
  • 2325-6621 (ISSN-L)
  • 2329-6933
OpenAlex
W2461415823
Cited by
18
References
1
Citations by year
2026: 2 · 2025: 3 · 2024: 1 · 2023: 1 · 2022: 2 · 2021: 2 · 2020: 2 · 2019: 2 · 2018: 2 · 2017: 1
FWCI
2.57
Type
journal article
Language
en
Open access
Locations
  • Annals of the American Thoracic Society (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Institutes of Health (RR024140)
  • Oregon Clinical and Translational Research Institute (UL1RR024140, RR024140)
  • National Heart, Lung, and Blood Institute (HL123020, HL123018, U01HL122989, HL123023, U01HL123009, U01HL123008, U01HL123018, U01HL123027, U01HL123031, HL123004, U01HL123023, U01HL123010, HL123009, HL123027, HL122998, HL123010, HL123033, U01HL122998, U01HL123022, HL123008, U01HL123020, U01HL123004, HL122989, HL123022, HL123031, U01HL123033)
  • National Center for Research Resources (UL1RR024140)
  • National Center for Advancing Translational Sciences
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
  • Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
Keywords
electronic health record alerts, automated alerts, early warning systems, sepsis detection, pneumonia detection, clinical decision support, acute care, petals, Epic Systems
MeSH terms
Clinical Decision-Making, Critical Care, Humans, Pneumonia, Surveys and Questionnaires, Respiratory Distress Syndrome, United States, Randomized Controlled Trials as Topic, Sepsis, Decision Support Systems, Clinical, Biomedical Research, Electronic Health Records

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