A poisson-based prediction model and warning system for MRSA daily burden

This study was designed to demonstrate that the number of methicillin-resistant Staphylococcus aureus (MRSA) isolates collected daily in a community hospital is Poisson distributed and that using a one-sided Poisson control table is a fast and easy way to recognize unusually high numbers of MRSA isolates collected daily that may signal possible outbreaks.A retrospective analysis of MRSA isolates collected daily over a three year period (2005-2007, N = 934) was performed. Observed MRSA isolate frequencies are compared to Poisson frequencies using chi-square goodness-of-fit tests. A regression equation on the mean number of MRSA isolates collected daily for the years 2005, 2006, and 2007 is used to predict the mean number of MRSA isolates for 2008. A warning system for MRSA isolates collected daily is presented and a one-tailed, mean + 2 sigma control table is provided.One-hundred-fifty bed community hospital in central Massachusetts.Goodness-of-fit tests showed close agreement between actual MRSA isolates collected daily and Poisson frequencies for 2005 (chi4(2) = 4.045, p = 0.39), 2006 (chi4(2) = 2.807, p = 0.59), and 2007 (chi4(2) = 1.494, p = 0.83).Theoretical and empirical support is provided for the Poisson probability model. The model can be used to identify unusually high occurrences ofMRSA isolates collected daily. This study was limited to a single community healthcare system but the results may be generalized to other types of healthcare settings.