Implementation of a Computerized Decision Support System to Improve the Appropriateness of Antibiotic Therapy Using Local Microbiologic Data
Identificadores
URI: http://hdl.handle.net/10481/33434DOI: 10.1155/2014/395434
ISSN: 2314-6133
ISSN: 2314-6141
Metadata
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Rodríguez-Maresca, Manuel; Sorlózano Puerto, Antonio; Grau, Magnolia; Rodríguez-Castaño, Rocío; Ruiz-Valverde, Andrés; Gutiérrez Fernández, JoséEditorial
Hindawi Publishing Corporation
Materia
Antibiotic prescriptions Electronic device Microbiology
Date
2014Referencia bibliográfica
Rodríguez-Maresca, M.; et al. Implementation of a Computerized Decision Support System to Improve the Appropriateness of Antibiotic Therapy Using Local Microbiologic Data. BioMed Research International, 2014: 395434 (2014). [http://hdl.handle.net/10481/33434]
Sponsorship
This study was developed within the Research Project “Análisis de los niveles de antibióticos y su aplicación en las guías electrónicas de resistencias como estrategia para optimizar su uso clínico” (P108/90354) funded by the Carlos III Health Institute of the Spanish Ministry of Health through the Fondo de Investigación Sanitaria.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.