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American Journal of Epidemiology Advance Access originally published online on March 30, 2007
American Journal of Epidemiology 2007 165(11):1321-1327; doi:10.1093/aje/kwm041
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American Journal of Epidemiology Copyright © 2007 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

PRACTICE OF EPIDEMIOLOGY

Nurse Staffing Level and Nosocomial Infections: Empirical Evaluation of the Case-Crossover and Case-Time-Control Designs

Stéphane Hugonnet1, Andrés Villaveces2,3 and Didier Pittet1

1 Infection Control Program, Department of Internal Medicine, University of Geneva Hospitals, Geneva, Switzerland
2 Quality of Care Unit, Medical Directorate, University of Geneva Hospitals, Geneva, Switzerland
3 Current affiliation: Department of Epidemiology, University of North Carolina, Chapel Hill, NC

Correspondence to Dr. S. Hugonnet, Infection Control Program, University of Geneva Hospitals, Rue Micheli-du-Crest 24, 1211 Geneva 14, Switzerland (e-mail: stephane.hugonnet{at}hcuge.ch).

Received for publication June 20, 2006. Accepted for publication December 20, 2006.

The authors compared a case-crossover design, a case-time-control design, and a cohort design to evaluate the effect of nurse staffing level on the risk of nosocomial infections. They evaluated two strategies, conditional logistic regression and generalized estimating equation, to analyze the case-crossover study. The study was performed among critically ill patients in the medical intensive care unit of the University of Geneva Hospitals, Geneva, Switzerland. Of 366 patients who stayed more than 7 days in the intensive care unit between 1999 and 2002, 144 developed an infection. The main reasons for admission were infectious (35.3%), cardiovascular (32.5%), and pulmonary (19.7%) conditions. A comparison of the three study designs showed that lower nurse staffing was associated with an approximately 50% increased risk of nosocomial infections. All analyses yielded similar estimates, except that the point estimate obtained by the conditional logistic regression used in the case-crossover design was biased away from unity; the generalized estimating equation yielded unbiased results and is the most appropriate technique for case-crossover designs. The case-crossover methodology in hospital epidemiology is a promising alternative to traditional approaches, but selection of the referent periods is challenging.

cross infection; epidemiologic methods; personnel staffing and scheduling


Abbreviations: ICU, intensive care unit


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