title: Identifying severe sepsis via electronic surveillance.
abstract: 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.
authors: University of Kansas School of Medicine, Kansas City, KS.
authors: Bristol N
authors: BN
authors: Brandt
authors: The University of Kansas Hospital, Kansas City, KS.
authors: Amanda B
authors: AB
authors: Gartner
authors: University of Kansas School of Medicine, Kansas City, KS.
authors: Michael
authors: M
authors: Moncure
authors: University of Kansas School of Medicine, Kansas City, KS.
authors: Chad M
authors: CM
authors: Cannon
authors: The University of Kansas Hospital, Kansas City, KS.
authors: Elizabeth
authors: E
authors: Carlton
authors: The University of Kansas Hospital, Kansas City, KS.
authors: Carol
authors: C
authors: Cleek
authors: The University of Kansas Hospital, Kansas City, KS.
authors: Chris
authors: C
authors: Wittkopp
authors: University of Kansas School of Medicine, Kansas City, KS ssimpson3@kumc.edu.
authors: Steven Q
authors: SQ
authors: Simpson
mesh_terms: D000410:Alanine Transaminase / Q000097:blood; D000465:Algorithms; D001219:Aspartate Aminotransferases / Q000097:blood; D001831:Body Temperature; D002245:Carbon Dioxide / Q000097:blood; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D057286:Electronic Health Records; D006339:Heart Rate; D006801:Humans; D007362:Intensive Care Units; D007958:Leukocyte Count; D063305:Organ Dysfunction Scores; D011446:Prospective Studies; D056152:Respiratory Rate; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D018805:Sepsis / Q000175:diagnosis* / Q000503:physiopathology*; D018746:Systemic Inflammatory Response Syndrome / Q000503:physiopathology; D013997:Time Factors
chemical_list: D002245:Carbon Dioxide; D001219:Aspartate Aminotransferases; D000410:Alanine Transaminase
keywords: electronic medical record; electronic surveillance; quality improvement; sepsis