Implementing automated surveillance for tracking Clostridium difficile infection at multiple healthcare facilities.
Automated surveillance using electronically available data has been found to be accurate and save time. An automated Clostridium difficile infection (CDI) surveillance algorithm was validated at 4 Centers for Disease Control and Prevention Epicenter hospitals. Electronic surveillance was highly sensitive, specific, and showed good to excellent agreement for hospital-onset; community-onset, study facility-associated; indeterminate; and recurrent CDI.
Washington University School of Medicine, St. Louis, MO 63110, USA. edubberk@dom.wustl.edu
Erik R
ER
Dubberke
Humaa A
HA
Nyazee
Deborah S
DS
Yokoe
Jeanmarie
J
Mayer
Kurt B
KB
Stevenson
Julie E
JE
Mangino
Yosef M
YM
Khan
Victoria J
VJ
Fraser
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001331:Automation / Q000379:methods; D002487:Centers for Disease Control and Prevention, U.S.; D016360:Clostridioides difficile / Q000302:isolation & purification; D003428:Cross Infection / Q000453:epidemiology* / Q000382:microbiology; D057286:Electronic Health Records; D004761:Enterocolitis, Pseudomembranous / Q000175:diagnosis / Q000453:epidemiology*; D005243:Feces / Q000382:microbiology; D006268:Health Facilities; D006801:Humans; D016347:Medical Records Systems, Computerized; D008875:Middle Aged; D012680:Sensitivity and Specificity; D018571:Sentinel Surveillance; D014481:United States / Q000453:epidemiology; D055815:Young Adult