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A MIXED METHODS APPROACH TO TAILORING EVIDENCE-BASED GUIDANCE FOR ANTIBIOTIC STEWARDSHIP TO ONE MEDICAL SYSTEM

机译:一种基于循证指导的抗生素对一个医疗系统的指导的混合方法

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摘要

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.
机译:我们的目标是要运行一种新型的抗生素顾问服务,即个性化加权发病综合征组合抗生素(pWISCA),旨在帮助医生在医院中初步选择抗生素。临床决策支持工具是一种有前途的技术,可提供基于证据的指导,并结合电子健康记录中有关患者的数据。尽管如此,在选择和订购pWISCA提供的抗生素药物选择时,仍需要与政策和程序以及当地专家的意见相一致,并考虑到医疗中心患者人群的当地耐药性数据。本文介绍了采用混合方法来识别抗生素药物和相关上下文数据并对其进行优先排序以显示在适合当地医院的CDS中的发现。我们讨论这些发现的含义。

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