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Advanced patient matching: Recognizable patient view for decision support in healthcare using big data analytics

机译:高级患者匹配:可识别的患者视图,可使用大数据分析为医疗保健提供决策支持

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摘要

Like Air, The whole world is bounded by the data in the current day. The volume of open information and data explosion, Healthcare industries in on a critical moment. Here Big Data plays an important role for these new changes in health care. Nowadays Healthcare industries are suffering from many problems because of data growth is speedily growing day by day. Healthcare decision support systems necessity a recognizable view of the patients for making the efficient decision against the patients and offer a better diagnosis and treatment. Patient pattern matching and identification is one of the biggest challenges in integrate to electronic healthcare record (EHR). The health care systems have the diverse document and result from unrelated systems like pharmacy, clinical, laboratory, insurance etc. we need to be matched with the fair patient record. This paper emphasizes on the challenge of patient matching records from diverse systems and offers a solution using Big Data analytic and pattern matching algorithm like Fuzzy Algorithm.
机译:像Air一样,整个世界都受到当前数据的限制。开放信息和数据爆炸的数量,医疗行业处于关键时刻。在这里,大数据在医疗保健方面的这些新变化中起着重要作用。如今,由于数据的增长与日俱增,医疗保健行业正面临许多问题。医疗保健决策支持系统需要对患者具有可识别的视图,以便针对患者做出有效的决策并提供更好的诊断和治疗。患者模式匹配和识别是集成到电子医疗记录(EHR)中的最大挑战之一。卫生保健系统具有多样化的文档,并且是由不相关的系统(例如药房,临床,实验室,保险等)产生的。我们需要与公平的患者记录相匹配。本文着重介绍了来自不同系统的患者匹配记录所面临的挑战,并提出了使用大数据分析和模式匹配算法(例如模糊算法)的解决方案。

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