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Comparative Study
. 2016 Feb;37(2):163-71.
doi: 10.1017/ice.2015.264. Epub 2015 Nov 3.

Objective Sepsis Surveillance Using Electronic Clinical Data

Chanu Rhee  1 , Sameer Kadri  2 , Susan S Huang  3 , Michael V Murphy  1 , Lingling Li  1 , Richard Platt  1 , Michael Klompas  1
Affiliations
Comparative Study

Objective Sepsis Surveillance Using Electronic Clinical Data

Chanu Rhee et al. Infect Control Hosp Epidemiol. 2016 Feb.

Abstract

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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Conflict of interest statement

Potential conflicts of interest. All authors report no conflicts of interest relevant to this article.

Figures

FIGURE 1
FIGURE 1
Severe sepsis incidence trends using surveillance definitions based on electronic health record (EHR) clinical data versus claims data, 2003–2012. Percentages next to each method refer to fitted 10-year change relative to 2003, with associated 95% confidence limits.
FIGURE 2
FIGURE 2
Severe sepsis mortality trends using surveillance definitions based on electronic health record (EHR) clinical data versus claims data, 2003–2012. Percentages next to each method refer to fitted absolute 10-year change, with associated 95% confidence limits.
See this image and copyright information in PMC

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