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Design and Implementation of Big Data-Based Documents to Optimize Medical Coding

机译:基于大数据的文档的设计与实现,优化医学编码

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Clinical information systems (CISs) in some hospitals streamline the data management from data warehouses. These warehouses contain heterogeneous information from all medical specialties that offer patient care services. It is increasingly difficult to manage large volumes of data in a specific clinical context such as quality coding of medical services. The document-based Not Only SQL (NO-SQL) model can provide an accessible, extensive and robust coding data management framework while maintaining certain flexibility. This paper focus on the design and implementation of a big data-coding warehouse, it also defines the rules to convert a conceptual model of coding into a document-oriented logical model. Using that model, we implemented, analyzed a big data-coding warehouse via the Mongodb database, and evaluated it using data research mono- and multi-criteria and then calculated the precision of our model.
机译:一些医院的临床信息系统(CISS)简化了数据仓库的数据管理。这些仓库包含来自所有提供患者护理服务的医学专业的异质信息。在特定的临床环境中管理大量数据越来越困难,例如医疗服务的质量编码。基于文档的基于SQL(NO-SQL)模型可以提供可访问的,广泛且强大的编码数据管理框架,同时保持某些灵活性。本文侧重于大数据编码仓库的设计和实现,它还定义了将编码概念模型转换为面向文档的逻辑模型的规则。我们通过MongoDB数据库实现了使用该模型,通过MongoDB数据库分析了大数据编码仓库,并使用数据研究单和多标准进行评估,然后计算模型的精度。

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