| Literature DB >> 30046637 |
Emily S Patterson1, Courtney M Dewart2, Kurt Stevenson2, Awa Mbodj2, Mark Lustberg2, Erinn M Hade2, Courtney Hebert2.
Abstract
Our objective is to operationalize a novel antibiotic advisor, called the personalized weighted incidence syndromic combination antibiogram (pWISCA), intended to help physicians with initial antibiotic choice in hospitals. Clinical decision support tools are a promising technology for providing evidence-based guidance that incorporates data about patients from electronic health records. Nevertheless, congruence with policies and procedures and local experts' opinions, as well as taking into account local resistance data for the medical center's patient population, is needed when selecting and ordering the antibiotic medication options provided by pWISCA. This paper presents findings from applying a mixed methods approach to identify and prioritize antibiotic medications and associated contextual data to display in a CDS tailored to the local hospital. We discuss implications of these findings.Entities:
Year: 2018 PMID: 30046637 PMCID: PMC6056269 DOI: 10.1177/2327857918071053
Source DB: PubMed Journal: Proc Int Symp Hum Factors Ergon Healthc ISSN: 2327-8579