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Device-Associated Infection Rates for Non–Intensive Care Unit Patients

Published online by Cambridge University Press:  21 June 2016

Ralf-Peter Vonberg*
Affiliation:
German National Reference Center for Surveillance of Nosocomial Infections Division of Hospital Epidemiology and Infection Control, Institute for Medical Microbiology and Hospital Epidemiology, Medical School Hannover, Hannover, Germany
M. Behnke
Affiliation:
German National Reference Center for Surveillance of Nosocomial Infections Institute for Hygiene and Environmental Medicine, Charite-University Medicine, Free University and Humboldt University Berlin, Berlin
C. Geffers
Affiliation:
German National Reference Center for Surveillance of Nosocomial Infections Institute for Hygiene and Environmental Medicine, Charite-University Medicine, Free University and Humboldt University Berlin, Berlin
D. Sohr
Affiliation:
German National Reference Center for Surveillance of Nosocomial Infections Institute for Hygiene and Environmental Medicine, Charite-University Medicine, Free University and Humboldt University Berlin, Berlin
H. Rüden
Affiliation:
German National Reference Center for Surveillance of Nosocomial Infections Institute for Hygiene and Environmental Medicine, Charite-University Medicine, Free University and Humboldt University Berlin, Berlin
M. Dettenkofer
Affiliation:
German National Reference Center for Surveillance of Nosocomial Infections Institute of Environmental Medicine and Hospital Epidemiology, University Medical Center, University Hospital of Freiburg, Freiburg, Germany
P. Gastmeier
Affiliation:
German National Reference Center for Surveillance of Nosocomial Infections Division of Hospital Epidemiology and Infection Control, Institute for Medical Microbiology and Hospital Epidemiology, Medical School Hannover, Hannover, Germany
*
Institute for Medical Microbiology and Hospital Epidemiology, Medical School Hannover, Carl-Neuberg-Strasse 1, D-30625 Hannover, Germany (Vonberg.Ralf@MH-Hannover.DE)

Abstract

Background.

Reference data from intensive care units (ICUs) are not applicable to non-ICU patients because of the differences in device use rates, length of stay, and severity of underlying diseases among the patient populations. In contrast to the huge amount of data available for ICU patients, appropriate surveillance data for non-ICU patients have been missing in Germany.

Objective.

To establish a new module (“DEVICE-KISS”) of the German Nosocomial Infection Surveillance System for generating stratified reference data for non-ICU wards.

Setting.

Non-ICU patients from 42 German hospitals.

Methods.

Monthly patient-days, device-days and nosocomial infections (NIs) (using Centers for Disease Control and Prevention definitions) were counted. Device use rates were calculated, and NI rates were stratified by different medical specialities.

Results.

From July 2002 through June 2004, among the 77 wards, there were a total of 536,955 patient-days and 74,188 device-days (for CVC-associated primary bloodstream infections, there were 181,401 patient-days and 8,317 central vascular catheter [CVC]-days in 29 wards; for urinary catheter–associated urinary tract infections, there were 445,536 patient-days and 65,871 urinary catheter–days in 65 wards) and 483 NIs (36 bloodstream infections and 447 urinary tract infections). The mean device use rates were 4.6 device-days per 100 patient-days for CVCs (29 wards) and 14.8 device-days per 100 patient-days for urinary catheters (65 wards), respectively. Mean device-associated NI rates were 4.3 infections per 1,000 CVC-days for CVC-associated bloodstream infections and 6.8 infections per 1,000 urinary catheter–days for catheter-associated urinary tract infections.

Conclusions

DEVICE-KISS allows non-ICUs to recognize an outlier position with regard to NIs by providing well-founded reference data for non-ICU patients.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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