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Automated Surveillance of Clostridium difficile Infections Using BioSense

Published online by Cambridge University Press:  02 January 2015

Stephen R. Benoit ,
L. Clifford McDonald ,
Roseanne English  and
Jerome I. Tokars
Stephen R. Benoit*
Affiliation:
Division of Emergency Preparedness and Response, National Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, Georgia
L. Clifford McDonald
Affiliation:
Division of Healthcare Quality Promotion, National Center for Preparedness, Detection, and Control of Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
Roseanne English
Affiliation:
Division of Emergency Preparedness and Response, National Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, Georgia
Jerome I. Tokars
Affiliation:
Division of Emergency Preparedness and Response, National Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, Georgia
*
Centers for Disease Control and Prevention, 1600 Clifton Road NE, MS E-90, Atlanta, GA 30333 ([email protected])
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Abstract

Objective.

To determine the feasibility of using electronic laboratory and admission-discharge-transfer data from BioSense, a national automated surveillance system, to apply new modified Clostridium difficile infection (CDI) surveillance definitions and calculate overall and facility-specific rates of disease.

Design.

Retrospective, multicenter cohort study.

Setting.

Thirty-four hospitals sending inpatient, emergency department, and /or outpatient data to BioSense.

Methods.

Laboratory codes and text-parsing methods were used to extract C. difficile-positive toxin assay results from laboratory data sent to BioSense during the period from January 1, 2007, through June 30, 2008; these were merged with administrative records to determine whether cases were community associated or healthcare onset, as well as patient-day data for rate calculations. A patient was classified as having hospital-onset CDI if he or she had a C. difficile toxin-positive result on a stool sample collected 3 or more days after admission and community-onset CDI if the specimen was collected less than 3 days after admission or the patient was not hospitalized.

Results.

A total of 4,585 patients from 34 hospitals in 12 states had C. difficile-positive assay results. More than half (53.0%) of the cases were community-onset, and 30.8% of these occurred in patients who were recently hospitalized. The overall rate of healthcare-onset CDI was 7.8 cases per 10,000 patient-days, with a range among facilities of 1.5-27.8 cases per 10,000 patient-days.

Conclusions.

Electronic laboratory data sent to the BioSense surveillance system were successfully used to produce disease rates of CDI comparable to those of other studies, which shows the feasibility of using electronic laboratory data to track a disease of public health importance.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 32 , Issue 1 , January 2011 , pp. 26 - 33
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2011

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