A Poisson-based Prediction Model and Warning System for MRSA Daily Burden

Rocco J Perla; Bradford D Allen

doi:10.29074/ascls.22.1.22

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Rocco J Perla, EdD⇑
1. is IHI/George W Merck Fellow, Institute for Healthcare Improvement, Cambridge MA; and section head, Clinical Microbiology & Diagnostic Immunology, and epidemiologist, Department of Infection Control and Prevention, HealthAlliance Hospital, Leominster MA
Bradford D Allen, EdD
1. is chair, Department of Mathematics and Science, Lasell College, Newton, MA

Address for correspondence: Rocco J Perla EdD, IHI/George W Merck Fellow, Institute for Healthcare Improvement, 20 University Road, 7^th Floor, Cambridge MA 02138. (617) 301-4800, (617) 301-4848 (fax). rperla{at}IHI.org.

Abstract

OBJECTIVE: 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.

METHODS: 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.

SETTING: One-hundred-fifty bed community hospital in central Massachusetts.

RESULTS: Goodness-of-fit tests showed close agreement between actual MRSA isolates collected daily and Poisson frequencies for 2005 (χ²₄ = 4.045, p = 0.39), 2006 (χ²₄ = 2.807, p = 0.59), and 2007 (χ²₄ = 1.494, p = 0.83).

CONCLUSION: Theoretical and empirical support is provided for the Poisson probability model. The model can be used to identify unusually high occurrences of MRSA 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.

ABBREVIATIONS: ICPs = infection control practitioners; MDROs = multi-drug resistant organisms; MRSA = methicillin-resistant Staphylococcus aureus.