title: National Automated Surveillance of Hospital-Acquired Bacteremia in Denmark Using a Computer Algorithm.
abstract: BACKGROUND In 2015, Denmark launched an automated surveillance system for hospital-acquired infections, the Hospital-Acquired Infections Database (HAIBA). OBJECTIVE To describe the algorithm used in HAIBA, to determine its concordance with point prevalence surveys (PPSs), and to present trends for hospital-acquired bacteremia SETTING Private and public hospitals in Denmark METHODS A hospital-acquired bacteremia case was defined as at least 1 positive blood culture with at least 1 pathogen (bacterium or fungus) taken between 48 hours after admission and 48 hours after discharge, using the Danish Microbiology Database and the Danish National Patient Registry. PPSs performed in 2012 and 2013 were used for comparison. RESULTS National trends showed an increase in HA bacteremia cases between 2010 and 2014. Incidence was higher for men than women (9.6 vs 5.4 per 10,000 risk days) and was highest for those aged 61-80 years (9.5 per 10,000 risk days). The median daily prevalence was 3.1% (range, 2.1%-4.7%). Regional incidence varied from 6.1 to 8.1 per 10,000 risk days. The microorganisms identified were typical for HA bacteremia. Comparison of HAIBA with PPS showed a sensitivity of 36% and a specificity of 99%. HAIBA was less sensitive for patients in hematology departments and intensive care units. Excluding these departments improved the sensitivity of HAIBA to 44%. CONCLUSIONS Although the estimated sensitivity of HAIBA compared with PPS is low, a PPS is not a gold standard. Given the many advantages of automated surveillance, HAIBA allows monitoring of HA bacteremia across the healthcare system, supports prioritizing preventive measures, and holds promise for evaluating interventions. Infect Control Hosp Epidemiol 2017;38:559-566.
authors.affiliation: 1Department of Infectious Disease Epidemiology,Statens Serum Institut,Copenhagen,Denmark.
authors.forename: Sophie
authors.initials: S
authors.lastname: Gubbels
authors.affiliation: 1Department of Infectious Disease Epidemiology,Statens Serum Institut,Copenhagen,Denmark.
authors.forename: Jens
authors.initials: J
authors.lastname: Nielsen
authors.affiliation: 1Department of Infectious Disease Epidemiology,Statens Serum Institut,Copenhagen,Denmark.
authors.forename: Marianne
authors.initials: M
authors.lastname: Voldstedlund
authors.affiliation: 2Department of Microbiology and Infection Control,Statens Serum Institut,Copenhagen,Denmark.
authors.forename: Brian
authors.initials: B
authors.lastname: Kristensen
authors.affiliation: 3Department of Clinical Microbiology,Aalborg University Hospital,Aalborg,Denmark.
authors.forename: Henrik C
authors.initials: HC
authors.lastname: Schønheyder
authors.affiliation: 5Department of Clinical Microbiology,Aarhus University Hospital,Aarhus,Denmark.
authors.forename: Svend
authors.initials: S
authors.lastname: Ellermann-Eriksen
authors.affiliation: 6Department of Clinical Microbiology,Slagelse Hospital,Slagelse,Denmark.
authors.forename: Jørgen H
authors.initials: JH
authors.lastname: Engberg
authors.affiliation: 7Department of Clinical Microbiology,Vejle Hospital,Vejle,Denmark.
authors.forename: Jens K
authors.initials: JK
authors.lastname: Møller
authors.affiliation: 8Department of Clinical Microbiology,Hvidovre Hospital,Hvidovre,Denmark.
authors.forename: Christian
authors.initials: C
authors.lastname: Østergaard
authors.affiliation: 1Department of Infectious Disease Epidemiology,Statens Serum Institut,Copenhagen,Denmark.
authors.forename: Kåre
authors.initials: K
authors.lastname: Mølbak
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D016470:Bacteremia / Q000175:diagnosis* / Q000453:epidemiology*; D002648:Child; D002675:Child, Preschool; D003428:Cross Infection / Q000175:diagnosis / Q000453:epidemiology* / Q000382:microbiology*; D016208:Databases, Factual; D003718:Denmark / Q000453:epidemiology; D005260:Female; D006761:Hospitals; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D012042:Registries; D012680:Sensitivity and Specificity; D018571:Sentinel Surveillance; D017678:Sex Distribution; D055815:Young Adult