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Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems.

机译:全面的临床决策支持分类法的开发和评估:商业和内部开发的电子健康记录系统中前端工具的比较。

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BACKGROUND: Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. OBJECTIVE: To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. STUDY DESIGN AND METHODS: We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). RESULTS: Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. CONCLUSION: We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content.
机译:背景:临床决策支持(CDS)是提高医疗质量和降低成本的宝贵工具。但是,尚无关于CDS类型的全面分类法,并且在当前电子健康记录(EHR)系统中各种CDS工具的可用性方面的研究有限。目的:开发和验证前端CDS工具的分类法,并评估主要商业和内部开发的EHR中对这些工具的支持。研究设计和方法:我们使用了由11位决策支持专家组成的小组的改进的Delphi方法,以开发53种前端CDS工具的分类法。基于此分类法,将CDS工具的调查问卷发送给有目的的商业EHR供应商(n = 9)和具有内部开发的最新EHR的领先医疗机构(n = 4)。结果:收到了所有医疗机构和9家EHR供应商中7家的答复(答复率:85%)。在至少一个调查的电子病历系统中找到了分类法中确定的所有53种CDS工具,但是在所有电子病历中仅存在8个功能。药物剂量支持和命令协助者是最常用的决策支持类别,而专家系统(例如,诊断决策支持,呼吸机管理建议)则是最不常见的类别。结论:我们开发并验证了前端CDS工具的综合分类法。随后对商业EHR供应商和领先的医疗机构的调查显示,一套通用的CDS工具核心很小,但在其余的临床决策支持内容中却发现了很大的差异。

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