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Representativeness of the Surveillance Data in the Intensive Care Unit Component of the German Nosocomial Infections Surveillance System

Published online by Cambridge University Press:  02 January 2015

Irina Zuschneid*
Affiliation:
Institute of Hygiene and Environmental Medicine, Charité-University Medicine Berlin, and the National Reference Center for Surveillance of Nosocomial Infections, Berlin Friedrichshain-Kreuzberg Community Health Center, Berlin
Gerta Rücker
Affiliation:
Institute of Medical Biometry and Medical Informatics, University Medical Center, and the Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany
Rotraut Schoop
Affiliation:
Institute of Medical Biometry and Medical Informatics, University Medical Center, and the Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany
Jan Beyersmann
Affiliation:
Institute of Medical Biometry and Medical Informatics, University Medical Center, and the Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany
Martin Schumacher
Affiliation:
Institute of Medical Biometry and Medical Informatics, University Medical Center, and the Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany
Christine Geffers
Affiliation:
Institute of Hygiene and Environmental Medicine, Charité-University Medicine Berlin, and the National Reference Center for Surveillance of Nosocomial Infections, Berlin
Henning Rüden
Affiliation:
Institute of Hygiene and Environmental Medicine, Charité-University Medicine Berlin, and the National Reference Center for Surveillance of Nosocomial Infections, Berlin
Petra Gastmeier
Affiliation:
Institute of Hygiene and Environmental Medicine, Charité-University Medicine Berlin, and the National Reference Center for Surveillance of Nosocomial Infections, Berlin
*
Friedrichshain-Kreuzberg Community Health Center, Urbanstrasse 24, 10967 Berlin, Germany (Irina.Zuschneid@ba-fk.verwalt-berlin.de)

Abstract

Objective.

To assess the representativeness of the data in the Krankenhaus Infektions Surveillance System (KISS), which is a nosocomial infections surveillance system for intensive care units (ICUs) in Germany.

Design.

Prospective and retrospective surveillance study.

Setting.

Medical-surgical ICUs in Germany.

Methods.

A sample of medical-surgical ICUs from all over Germany, stratified according to hospital size, was randomly selected. Surveillance personnel from the hospitals were trained in surveillance of nosocomial infections, and they subsequently conducted a 2-month surveillance in their ICUs. Data were compared with KISS data for medical-surgical ICUs.

Results.

During the period from 2004 through 2005, a total of 50 medical-surgical ICUs agreed to participate in our study: 21,832 patient-days were surveyed, and 262 cases of nosocomial infection were registered, 176 of which were cases of device-associated nosocomial infection (100 cases of lower respiratory tract infection, 47 cases of urinary tract infection, and 29 cases of bloodstream infection). The overall incidence density of all types of nosocomial infections was estimated to be 10.65 cases per 1,000 patient-days. Device utilization rates in the study ICUs and in the KISS medical-surgical ICUs were similar. The pooled mean device-associated infection rates were higher in the study ICUs than in the KISS medical-surgical ICUs (10.2 vs 5.1 cases of pneumonia; 2.0 vs 1.2 cases of bloodstream infection; and 2.7 vs 1.2 cases of urinary tract infection), but the pooled mean device-associated infection rates in the study ICUs were comparable to those of the KISS ICUs during their first year of participation in KISS. The incidence density for nosocomial infections in the study ICUs varied according hospital size, with ICUs in larger hospitals having a higher incidence density than those in smaller hospitals.

Conclusions.

KISS ICUs started with nosocomial infection rates comparable to those found in our study ICUs. Over the years of participation, however, a decrease in nosocomial infections is seen. Thus, rates of nosocomial infection from KISS should be used as benchmarks, but estimations for Germany that are based on KISS data may underestimate the real burden of nosocomial infections.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2010

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References

1. Gastmeier, R Geifers, C, Sohr, D, Dettenkofer, M, Daschner, F, Rüden, H. Five years working with the German Nosocomial Infection Surveillance System KISS. Am J Infect Control 2003;31:316321.CrossRefGoogle Scholar
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3. Emori, TG, Culver, DH, Horan, TC, et al. National nosocomial infection surveillance system (NNIS): description of surveillance Methods. Am J Infect Control 1991;19(1):1935.CrossRefGoogle ScholarPubMed
4. Deutsches Krankenhausadressbuch (CD-ROM). Freiburg, Germany: Rom-bach;2003.Google ScholarPubMed
5. Rücker, G, Schoop, R, Beyersmann, J, Schumacher, M, Zuschneid, I. Are KISS data representative of German intensive care units? Statistical issues. Methods Inf Med 2006;45:424429.Google ScholarPubMed
6. Zuschneid, I, Geffers, C, Sohr, D, et al. Validation of the surveillance in the intensive care unit component of the German nosocomial infections surveillance system. Infect Control Hosp Epidemiol 2007;28(4):496499.CrossRefGoogle ScholarPubMed
7. Geffers, C, Schwab, F, Gastmeier R Accuracy of diagnostic nosocomial infections tested by case reports and their association to nosocomial infection rates within a surveillance system. Paper presented at:19th Annual Scientific Meeting of the Society for Healthcare Epidemiology of America; March 19-22, 2009; San Diego, California.Google Scholar
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