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Objective Sepsis Surveillance Using Electronic Clinical Data.
Infect Control Hosp Epidemiol. 2016 Feb; 37(2):163-71.IC

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.

Authors+Show Affiliations

1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.3Department of Critical Care Medicine,National Institutes of Health Clinical Center,Bethesda,Maryland.4Division of Infectious Diseases,University of California,Irvine,School of Medicine,Irvine,California.1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.1Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute,Boston,Massachusetts.

Pub Type(s)

Comparative Study
Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, P.H.S.

Language

eng

PubMed ID

26526737

Citation

Rhee, Chanu, et al. "Objective Sepsis Surveillance Using Electronic Clinical Data." Infection Control and Hospital Epidemiology, vol. 37, no. 2, 2016, pp. 163-71.
Rhee C, Kadri S, Huang SS, et al. Objective Sepsis Surveillance Using Electronic Clinical Data. Infect Control Hosp Epidemiol. 2016;37(2):163-71.
Rhee, C., Kadri, S., Huang, S. S., Murphy, M. V., Li, L., Platt, R., & Klompas, M. (2016). Objective Sepsis Surveillance Using Electronic Clinical Data. Infection Control and Hospital Epidemiology, 37(2), 163-71. https://doi.org/10.1017/ice.2015.264
Rhee C, et al. Objective Sepsis Surveillance Using Electronic Clinical Data. Infect Control Hosp Epidemiol. 2016;37(2):163-71. PubMed PMID: 26526737.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Objective Sepsis Surveillance Using Electronic Clinical Data. AU - Rhee,Chanu, AU - Kadri,Sameer, AU - Huang,Susan S, AU - Murphy,Michael V, AU - Li,Lingling, AU - Platt,Richard, AU - Klompas,Michael, Y1 - 2015/11/03/ PY - 2015/11/4/entrez PY - 2015/11/4/pubmed PY - 2016/12/15/medline SP - 163 EP - 71 JF - Infection control and hospital epidemiology JO - Infect Control Hosp Epidemiol VL - 37 IS - 2 N2 - 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. SN - 1559-6834 UR - https://www.unboundmedicine.com/medline/citation/26526737/Objective_Sepsis_Surveillance_Using_Electronic_Clinical_Data_ L2 - https://www.cambridge.org/core/product/identifier/S0899823X15002640/type/journal_article DB - PRIME DP - Unbound Medicine ER -