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Search Efficient Representation of Healthcare Data based on the HL7 RIM

机译:根据HL7边缘搜索医疗数据的高效表示

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摘要

—The Reference Information Model (RIM) of Health Level Seven (HL7) standard is a conceptual information model for health care. Data of HL7 RIM Observation class are sparse, high dimensional, and require frequent schema change. Entity Attribute Value (EAV) is the widely used solution to handle these above challenges of medical data, but EAV is not search efficient for knowledge extraction. In this paper, we have proposed a search efficient data model: Optimized Entity Attribute Value (OEAV) for physical representation of medical data as alternative of widely used EAV model. We have implemented EAV or OEAV individually to model RIM Observation class and used relational model for the remaining RIM classes. We have shown that OEAV is dramatically search efficient and occupy less storage space compared to EAV.
机译:- 健康级七(HL7)标准的参考信息模型(RIM)是医疗保健的概念信息模型。 HL7 RIM观察类的数据稀疏,高维度,并且需要频繁的架构变化。实体属性值(EAV)是广泛使用的解决方案来处理上述医疗数据的挑战,但EAV不可效率地搜索知识提取。在本文中,我们提出了一种搜索有效的数据模型:优化实体属性值(OEAv),用于医疗数据的物理表示,作为广泛使用的EAV模型的替代。我们已经单独实现了EAV或OEAV,以模拟RIM观察类和剩余的RIM类的关系模型。我们已经表明,与EAV相比,OEAv大大搜索和占用较少的存储空间。

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