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National Automated Surveillance of Hospital-Acquired Bacteremia in Denmark Using a Computer Algorithm

Published online by Cambridge University Press:  09 March 2017

Sophie Gubbels*
Affiliation:
Department of Infectious Disease Epidemiology, Statens Serum Institut, Copenhagen, Denmark
Jens Nielsen
Affiliation:
Department of Infectious Disease Epidemiology, Statens Serum Institut, Copenhagen, Denmark
Marianne Voldstedlund
Affiliation:
Department of Infectious Disease Epidemiology, Statens Serum Institut, Copenhagen, Denmark
Brian Kristensen
Affiliation:
Department of Microbiology and Infection Control, Statens Serum Institut, Copenhagen, Denmark
Henrik C. Schønheyder
Affiliation:
Department of Clinical Microbiology, Aalborg University Hospital, Aalborg, Denmark Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
Svend Ellermann-Eriksen
Affiliation:
Department of Clinical Microbiology, Aarhus University Hospital, Aarhus, Denmark
Jørgen H. Engberg
Affiliation:
Department of Clinical Microbiology, Slagelse Hospital, Slagelse, Denmark
Jens K. Møller
Affiliation:
Department of Clinical Microbiology, Vejle Hospital, Vejle, Denmark
Christian Østergaard
Affiliation:
Department of Clinical Microbiology, Hvidovre Hospital, Hvidovre, Denmark
Kåre Mølbak
Affiliation:
Department of Infectious Disease Epidemiology, Statens Serum Institut, Copenhagen, Denmark
*
Address correspondence to Sophie Gubbels, Department of Infectious Disease Epidemiology Statens Serum Institut, Artillerivej 5, 2300 Copenhagen S, Denmark (gub@ssi.dk).

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

Type
Original Articles
Copyright
© 2017 by The Society for Healthcare Epidemiology of America. All rights reserved 

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Footnotes

PREVIOUS PRESENTATION: A description of the algorithm, but not the comparison study, was presented at the European Scientific Conference on Applied Infectious Disease Epidemiology in Stockholm, Sweden, on November 11, 2015.

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