Learning Objective #1: Understand the evidence-based implications of an antibiogram; identify and apply local interventions to prevent antimicrobial resistance in hospitals and other health care facilities

Learning Objective #2: Identify pragmatic and advanced technologic methods for clinicians, hospitals, and other organizational partners to launch a multidisciplinary effort in the prevention of antimicrobial resistance

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Today, almost all of the bacteria that cause human infections in the United States and throughout the world are becoming resistant. In the USA, 50-60% of the > 2 million annual nosocomial infections are caused by antibiotic-resistant bacteria. Also a worldwide problem, the incidence in the UK increased from 17% to 23% between the years 1991-2001.

The significant trend of increasing resistance to antibiotics over time constitutes an important warning system. The widespread use of antibiotics is promoting the spread of antibiotic resistance. Antibiotic resistance is among the CDC's highest priority concerns. The influence of organisms resistant to most antibiotics have a significant impact on health by: impeding effective treatment, treatment failures of serious infections, and deaths due to treatment failure.

Methods: Antimicrobial susceptibility data are often aggregated into “antibiograms,” which provide a summary picture of common organisms and their susceptibility to many antimicrobial agents. Local antibiograms (e.g., by unit, hospital, or facility) provide a starting point for making decisions about empiric antimicrobial treatment. In this study, four hospitals, that comprise a part of a network, were used to compare their resistance patterns to imipenem for the organism Pseudomonas aeruginosa. The dependent variable is the resistance of the organism, independent variables are the hospitals themselves, and the temporal sequence. Statistical analyses: Full Model 2-way ANOVA analysis, with a subsequent 1-way ANOVA performed as the Reduced Model.

Conclusion: One of the hospitals had a different antibiogram and resistance pattern than did the other three hospitals. Knowledge of local patterns of resistance contained within the antibiogram will allow the infection control nurse to be alerted to significant shifts in the populations of organisms within the locale and report those findings to all stakeholders. This information can be used via the internet and a PDA for real-time clinical decisions at the bedside.