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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.

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