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Implementation of a computerized decision support system to improve the appropriateness of antibiotic therapy using local microbiologic data. | LitMetric

Implementation of a computerized decision support system to improve the appropriateness of antibiotic therapy using local microbiologic data.

Biomed Res Int

Department of Microbiology, School of Medicine, University of Granada, Avenida de Madrid 11, 18012 Granada, Spain ; Service of Microbiology, Virgen de las Nieves University Hospital, Avenida de las Fuerzas Armadas 2, 18014 Granada, Spain.

Published: June 2015

AI Article Synopsis

Article Abstract

A prospective quasi-experimental study was undertaken in 218 patients with suspicion of nosocomial infection hospitalized in a polyvalent ICU where a new electronic device (GERB) has been designed for antibiotic prescriptions. Two GERB-based applications were developed to provide local resistance maps (LRMs) and preliminary microbiological reports with therapeutic recommendation (PMRTRs). Both applications used the data in the Laboratory Information System of the Microbiology Department to report on the optimal empiric therapeutic option, based on the most likely susceptibility profile of the microorganisms potentially responsible for infection in patients and taking into account the local epidemiology of the hospital department/unit. LRMs were used for antibiotic prescription in 20.2% of the patients and PMRTRs in 78.2%, and active antibiotics against the finally identified bacteria were prescribed in 80.0% of the former group and 82.4% of the latter. When neither LMRs nor PMRTRs were considered for empiric treatment prescription, only around 40% of the antibiotics prescribed were active. Hence, the percentage appropriateness of the empiric antibiotic treatments was significantly higher when LRM or PMRTR guidelines were followed rather than other criteria. LRMs and PMRTRs applications are dynamic, highly accessible, and readily interpreted instruments that contribute to the appropriateness of empiric antibiotic treatments.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4150543PMC
http://dx.doi.org/10.1155/2014/395434DOI Listing

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