Intravenous literature: Magill, S.S., Hellinger, W., Cohen, J., Kay, R., Bailey, C., Boland, B., Carey, D., de Guzman, J., Dominguez, K., Edwards, J., Goraczewski, L., Horan, T., Miller, M., Phelps, M., Saltford, R., Seibert, J., Smith, B., Starling, P., Viergutz, B., Walsh, K., Rathore, M., Guzman, N. and Fridkin, S. (2012) Prevalence of Healthcare-Associated Infections in Acute Care Hospitals in Jacksonville, Florida. Infection Control and Hospital Epidemiology. 33(3), p.283-291.
Objective – To determine healthcare-associated infection (HAI) prevalence in 9 hospitals in Jacksonville, Florida; to evaluate the performance of proxy indicators for HAIs; and to refine methodology in preparation for a multistate survey.
Design – Point prevalence survey.
Patients – Acute care inpatients of any age.
Methods – HAIs were defined using National Healthcare Safety Network criteria. In each facility a trained primary team (PT) of infection prevention (IP) staff performed the survey on 1 day, reviewing records and collecting data on a random sample of inpatients. PTs assessed patients with one or more proxy indicators (abnormal white blood cell count, abnormal temperature, or antimicrobial therapy) for the presence of HAIs. An external IP expert team collected data from a subset of patient records reviewed by PTs to assess proxy indicator performance and PT data collection.
Results – Of 851 patients surveyed by PTs, 51 had one or more HAIs (6.0%; 95% confidence interval, 4.5%â€“7.7%). Surgical site infections (), urinary tract infections (), pneumonia (), and bloodstream infections () accounted for 75.8% of 58 HAIs detected by PTs. Staphylococcus aureus was the most common pathogen, causing 9 HAIs (15.5%). Antimicrobial therapy was the most sensitive proxy indicator, identifying 95.5% of patients with HAIs.
Conclusions – HAI prevalence in this pilot was similar to that reported in the 1970s by the Centers for Disease Control and Preventions Study on the Efficacy of Nosocomial Infection Control. Antimicrobial therapy was a sensitive screening variable with which to identify those patients at higher risk for infection and reduce data collection burden. Additional work is needed on validation and feasibility to extend this methodology to a national scale.