4.4 Article

Objective Sepsis Surveillance Using Electronic Clinical Data

Journal

INFECTION CONTROL AND HOSPITAL EPIDEMIOLOGY
Volume 37, Issue 2, Pages 163-171

Publisher

CAMBRIDGE UNIV PRESS
DOI: 10.1017/ice.2015.264

Keywords

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Funding

  1. Prevention Epicenters Program of the Centers for Disease Control and Prevention [3U54 CK000172-04S1]
  2. National Institutes of Health [T32 AI007061]

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OBJECTIVE. To compare the accuracy of surveillance of severe sepsis using electronic health record clinical data vs claims and to compare incidence and mortality trends using both methods. DESIGN. We created an electronic health record-based surveillance definition for severe sepsis using clinical indicators of infection (blood culture and antibiotic orders) and concurrent organ dysfunction (vasopressors, mechanical ventilation, and/or abnormal laboratory values). We reviewed 1,000 randomly selected medical charts to characterize the definition's accuracy and stability over time compared with a claims-based definition requiring infection and organ dysfunction codes. We compared incidence and mortality trends from 2003-2012 using both methods. SETTING. Two US academic hospitals. PATIENTS. Adult inpatients. RESULTS. The electronic health record-based clinical surveillance definition had stable and high sensitivity over time (77% in 2003-2009 vs 80% in 2012, P=.58) whereas the sensitivity of claims increased (52% in 2003-2009 vs 67% in 2012, P=.02). Positive predictive values for claims and clinical surveillance definitions were comparable (55% vs 53%, P=.65) and stable over time. From 2003 to 2012, severe sepsis incidence imputed from claims rose by 72% (95% CI, 57%-88%) and absolute mortality declined by 5.4% (95% CI, 4.6%-6.7%). In contrast, incidence using the clinical surveillance definition increased by 7.7% (95% CI, -1.1% to 17%) and mortality declined by 1.7% (95% CI, 1.1%-2.3%). CONCLUSIONS. Sepsis surveillance using clinical data is more sensitive and more stable over time compared with claims and can be done electronically. This may enable more reliable estimates of sepsis burden and trends.

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