title: Objective Sepsis Surveillance Using Electronic Clinical Data.
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.
  
  
  METHODS
  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.
  
  
  METHODS
  Two US academic hospitals.
  
  
  METHODS
  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.
authors.affiliation: 1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.
authors.forename: Chanu
authors.initials: C
authors.lastname: Rhee
authors.affiliation: 3Department of Critical Care Medicine,National Institutes of Health Clinical Center,Bethesda,Maryland.
authors.forename: Sameer
authors.initials: S
authors.lastname: Kadri
authors.affiliation: 4Division of Infectious Diseases,University of California,Irvine,School of Medicine,Irvine,California.
authors.forename: Susan S
authors.initials: SS
authors.lastname: Huang
authors.affiliation: 1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.
authors.forename: Michael V
authors.initials: MV
authors.lastname: Murphy
authors.affiliation: 1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.
authors.forename: Lingling
authors.initials: L
authors.lastname: Li
authors.affiliation: 1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.
authors.forename: Richard
authors.initials: R
authors.lastname: Platt
authors.affiliation: 1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.
authors.forename: Michael
authors.initials: M
authors.lastname: Klompas
mesh_terms: D000046:Academic Medical Centers; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001900:Boston / Q000453:epidemiology; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D015994:Incidence; D007348:Insurance, Health; D008297:Male; D008875:Middle Aged; D012042:Registries; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D018571:Sentinel Surveillance; D018805:Sepsis / Q000175:diagnosis* / Q000453:epidemiology* / Q000401:mortality; D055815:Young Adult