Prospective Trial of Real-Time Electronic Surveillance to Expedite Early Care of Severe Sepsis
Abstract
Study objective An automated, real-time electronic medical record query and caregiver notification system was developed and examined for its utility in improving sepsis care. We hypothesize that the algorithm will increase the rate and timeliness of sampling of blood lactate and blood cultures, performance of chest radiography, and provision of antibiotics. Methods A before-and-after, prospective study with consecutive enrollment examined an algorithm that automatically identified adult patients accumulating 2 or more systemic inflammatory response syndrome (SIRS) criteria and 2 or more blood pressure measurements less than or equal to 90 mm Hg during their emergency department (ED) stay. In phase 1, the system collected information but did not alert caregivers. In phase 2, caregivers were notified by alphanumeric paging and a text entry into the electronic medical record of the patients' potential illness and were provided with specific recommendations. Results Patients (33,460) were screened during 6 months; 398 patients activated the system, including 184 (46%) appropriately identified as severely septic. The algorithm had a 54% positive predictive value and 99% negative predictive value in detecting severe infection with acute organ dysfunction. The median time for patients to accumulate SIRS and blood pressure criteria was 152 minutes (interquartile range [IQR] 71 to 284 minutes), underscoring the dynamic nature of diagnosing critical illness in the emergency setting and…
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Interventional studies using traditional SIRS and SOFA alarm systems have not shown significant changes in clinical outcomes.
“Interventional studies using traditional SIRS and SOFA alarm systems have not shown significant changes in clinical outcomes [48–50].”
From Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy (2020) · cites this paper as [49]
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- Authors
- Nelson, J. L., Smith, B. L., Jared, J. D., & Younger, J. G.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Younger, John G.
- Venue
- Annals of Emergency Medicine
- Publisher
- Elsevier BV
- Published
- 2011-05
- Volume
- 57
- Issue
- 5
- Pages
- 500-504
- ISSN
- 0196-0644 (ISSN-L)
- OpenAlex
- W1969760843
- Cited by
- 122
- References
- 1
- Citations by year
- 2025: 4 · 2024: 6 · 2023: 2 · 2022: 3 · 2021: 6 · 2020: 12 · 2019: 12 · 2018: 10 · 2017: 17 · 2016: 16 · 2015: 11 · 2014: 11 · 2013: 4 · 2012: 6
- FWCI
- 5.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annals of Emergency Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Center for Research Resources (UL1RR024986)
- Topics
- Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
- Keywords
- severe sepsis, electronic surveillance, automated clinical decision support, systemic inflammatory response syndrome, hypotension, blood culture, blood lactate, chest radiography, antibiotic administration, emergency department, caregiver notification
- MeSH terms
- Algorithms, Diagnosis, Computer-Assisted, Emergency Service, Hospital, Humans, Prospective Studies, Time Factors, Systemic Inflammatory Response Syndrome, Sepsis, Early Diagnosis, Electronic Health Records
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