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OYSTER: A Tool for Entity Resolution in Health Information Exchange

机译：牡蛎：健康信息交换中实体分辨率的工具

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Entity resolution, also known as data matching or record linkage, is the task of identifying and matching records from several databases that refer to the same entities. Entity resolution is an important information quality process required before accurate analyses of entityrelated data are possible. Many health organizations are increasingly faced with the challenge of having large databases containing references to patients, physicians, drugs, and other entities that need to be matched in real-time with a stream of query records also containing entity references. Entity resolution is a core process in health information exchange (HIE) systems that have been evolving to address this problem. In this paper, we introduce a new entity resolution system OYSTER that supports both batch and transactional entity resolution in rela-tional data. OYSTER effectively combines relational entity resolution algorithms with a configurable framework that enables users to make use of an entity's relational context in making resolution decisions. We describe resolution strategies based on pairs or sets of references and show appropriate visualizations for each. Since resolution decisions often are interdependent, OYSTER facilitates understanding this com-plex process through a history mechanism that allows users to inspect chains of resolution decisions. An empirical study with 12 hospitals confirmed the benefits of the relational context visualization on the per-formance of OYSTER in relational data in terms of time as well as users' confidence and satisfaction.
机译：实体分辨率，也称为数据匹配或记录链接，是识别和匹配来自引用同一实体的多个数据库的记录的任务。实体分辨率是在精确分析EntityRellated数据之前所需的重要信息质量过程。许多卫生组织越来越多地面临着包含对患者，医生，药物和其他需要实时匹配的其他实体的大型数据库的挑战，该数据库还使用包含实体引用的查询记录的流。实体分辨率是健康信息交换（HIE）系统中的核心进程，这一直在不断发展解决此问题。在本文中，我们介绍了一个新的实体解析系统牡蛎，它支持Rela-Tional数据中的批处理和事务实体分辨率。牡蛎有效地将关系实体分辨率算法与可配置的框架结合起来，该框架使用户能够在制定分辨率决策时利用实体的关系上下文。我们描述了基于对或一组参考的分辨率策略，并为每个引用显示适当的可视化。由于解决方案决策通常是相互依存的，牡蛎通过允许用户检查解决方案决策链接的历史机制来了解这一COM-PLEX过程。与12家医院的实证研究证实了关系语境可视化对时间和满意度的关系数据中的牡蛎的每种效果，以及用户的信心和满意度。

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