The Development and Validation of a Clinical Prediction Rule to Predict Transmission of Methicillin-Resistant Staphylococcus aureus in Nursing Homes

Abstract

The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) colonization among nursing home residents is high. Healthcare workers (HCWs) often serve as a vector in the transmission of MRSA. The ability to identify residents who are likely to transmit MRSA to HCWs' hands and clothing during clinical care is important so that infection control measures, such as Contact Precautions, can be employed. We developed a clinical prediction rule with demographics and clinical characteristics as predictors of MRSA transmission to HCWs' gowns collected from residents of community nursing homes in Maryland and Michigan between 2012-2014. We externally validated this model in a cohort of Veterans Affairs nursing home residents from 7 states between 2012-2016. The prediction model, which included sex, race, resident dependency on HCWs for care, the presence of any device, diabetes, and chronic skin breakdown, showed good performance (c-statistic=0.70, sensitivity=76%, specificity=49%) in the development set. The decision curve analysis indicates this model has greater clinical utility than using a nares surveillance culture for MRSA colonization, which is current clinical practice for placing hospital inpatients on Contact Precautions. The prediction rule demonstrated less utility in the validation cohort, suggesting a separate rule should be developed for residents of Veterans Affairs nursing homes.