Automated surveillance of Clostridium difficile infections using BioSense.
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.


METHODS
Retrospective, multicenter cohort study.


METHODS
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.
Division of Emergency Preparedness and Response, National Center for Public Health Informatics, Atlanta, Georgia 30333, USA. bvy8@cdc.gov
Stephen R
SR
Benoit
L Clifford
LC
McDonald
Roseanne
R
English
Jerome I
JI
Tokars
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001331:Automation; D002648:Child; D002675:Child, Preschool; D016360:Clostridioides difficile / Q000302:isolation & purification*; D015331:Cohort Studies; D004761:Enterocolitis, Pseudomembranous / Q000175:diagnosis*; D005260:Female; D006751:Hospital Information Systems; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D011159:Population Surveillance / Q000379:methods*; D012189:Retrospective Studies; D039061:Systematized Nomenclature of Medicine; D055815:Young Adult