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Use of Multistate Models to Assess Prolongation of Intensive Care Unit Stay Due to Nosocomial Infection

Published online by Cambridge University Press:  21 June 2016

J. Beyersmann ,
P. Gastmeier ,
H. Grundmann ,
S. Bärwolff ,
C. Geffers ,
M. Behnke ,
H. Rüden  and
M. Schumacher
J. Beyersmann*
Affiliation:
Institute of Medical Biometry and Medical Informatics, University Hospital Freiburg, Freiberg Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiberg
P. Gastmeier
Affiliation:
Institute of Medical Microbiology and Hospital Epidemiology, Hannover Medical School, Hannover
H. Grundmann
Affiliation:
RIVM Bilthoven, Bilthoven, Germany
S. Bärwolff
Affiliation:
Institute of Hygiene and Environmental Medicine, Charite University of Medicine, Berlin, Germany
C. Geffers
Affiliation:
Institute of Hygiene and Environmental Medicine, Charite University of Medicine, Berlin, Germany
M. Behnke
Affiliation:
Institute of Hygiene and Environmental Medicine, Charite University of Medicine, Berlin, Germany
H. Rüden
Affiliation:
Institute of Hygiene and Environmental Medicine, Charite University of Medicine, Berlin, Germany
M. Schumacher
Affiliation:
Institute of Medical Biometry and Medical Informatics, University Hospital Freiburg, Freiberg
*
Freiburg Centre for Data Analysis and Modeling, University of Freiburg, Eckerstrasse 1, Freiburg D-79104, Germany (jan@fdm.uni-freiburg.de)
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Abstract

Background.

Reliable data on the costs attributable to nosocomial infection (NI) are crucial to demonstrating the real cost-effectiveness of infection control measures. Several studies investigating this issue with regard to intensive care unit (ICU) patients have probably overestimated, as a result of inappropriate study methods, the part played by NIs in prolonging the length of stay.

Methods.

Data from a prospective study of the incidence of NI in 5 ICUs over a period of 18 months formed the basis of this analysis. For describing the temporal dynamics of the data, a multistate model was used. Thus, ICU patients were counted as case patients as soon as an NI was ascertained on any particular day. All patients were then regarded as control subjects as long as they remained free of NI (time-to-event data analysis technique).

Results.

Admitted patients (n = 1,876) were observed for the development of NI over a period of 28,498 patient-days. In total, 431 NIs were ascertained during the study period (incidence density, 15.1 NIs per 1,000 patient-days). The influence of NI as a time-dependent covariate in a proportional hazards model was highly significant (P< .0001, Wald test). NI significantly reduced the discharge hazard (hazard ratio, 0.72 [95% confidence interval, 0.63-0.82])—that is, it prolonged the ICU stay. The mean prolongation of ICU length of stay due to NI ( ± standard error) was estimated to be 5.3 ± 1.6 days.

Conclusions.

Further studies are required to enable comparison of data on prolongation of ICU length of stay with the results of various study methods.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 27 , Issue 5 , May 2006 , pp. 493 - 499
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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