Slonim Noam, Carmeli Boaz, Goldsteen Abigail, Keller Oliver, Kent Carmel, Rinott Ruty
Haifa University, Mount Carmel, Haifa, Israel.
Stud Health Technol Inform. 2012;180:703-7.
Clinical Decision Support (CDS) systems hold tremendous potential for improving patient care. Most existing systems are knowledge-based tools that rely on relatively simple rules. More recent approaches rely on analytics techniques to automatically mine EHR data to reveal meaningful insights. Here, we propose the Knowledge-Analytics Synergy paradigm for CDS, in which we synergistically combine existing relevant knowledge with analytics applied to EHR data. We propose a framework for implementing such a paradigm and demonstrate its principles over real-world clinical and genomic data of hypertensive patients.
临床决策支持（CDS）系统在改善患者护理方面具有巨大潜力。大多数现有系统是基于知识的工具，依赖相对简单的规则。最近的方法则依赖分析技术来自动挖掘电子健康记录（EHR）数据以揭示有意义的见解。在此，我们提出了用于CDS的知识 - 分析协同范式，其中我们将现有的相关知识与应用于EHR数据的分析进行协同结合。我们提出了一个实施这种范式的框架，并通过高血压患者的真实临床和基因组数据展示了其原理。
