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Am J Med Qual. 2015 Nov-Dec;30(6):559-65. doi: 10.1177/1062860614541291. Epub 2014 Jun 26.

Identifying severe sepsis via electronic surveillance.

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University of Kansas School of Medicine, Kansas City, KS.
The University of Kansas Hospital, Kansas City, KS.
University of Kansas School of Medicine, Kansas City, KS


An electronic sepsis surveillance system (ESSV) was developed to identify severe sepsis and determine its time of onset. ESSV sensitivity and specificity were evaluated during an 11-day prospective pilot and a 30-day retrospective trial. ESSV diagnostic alerts were compared with care team diagnoses and with administrative records, using expert adjudication as the standard for comparison. ESSV was 100% sensitive for detecting severe sepsis but only 62.0% specific. During the pilot, the software identified 477 patients, compared with 18 by adjudication. In the 30-day trial, adjudication identified 164 severe sepsis patients, whereas ESSV detected 996. ESSV was more sensitive but less specific than care team or administrative data. ESSV-identified time of severe sepsis onset was a median of 0.00 hours later than adjudication (interquartile range = 0.05). The system can be a useful tool when implemented appropriately but lacks specificity, largely because of its reliance on discreet data fields.


electronic medical record; electronic surveillance; quality improvement; sepsis

[Indexed for MEDLINE]

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