Methodology for Record Linkage: A Medical Domain Case Study

M. Vargas-Vera
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Abstract

This paper presents a methodology for linking records from several sources each source might contain, missing information. This assumption of missing values has been made, without loss of generality, as the authors has observed that missing information is part of the nature of data in the health domain and also in other domains such as social sciences. The author's methodology is an attempt to deal with the linkage of records of the same patient in several databases. The first phase in her methodology is called homogenization. The homogenization of the databases/datasets is performed by applying a method which fills-in the missing values with the predicted values. The second phase of her methodology is called linking of records. It assesses the similarity between records and implements the linkage of the pairs of records with high level of similarity. Finally, the author presents an evaluation of our methodology. The evaluation of the homogenization phase was carried out using multinomial regression while, the evaluation of the aggregated similarities were performed using Jaccard, Jaro-Winkler and Monge-Elkan similarity metrics.
记录链接的方法:一个医学领域的案例研究
本文提出了一种链接来自多个来源的记录的方法,每个来源可能包含缺失信息。正如作者所观察到的那样,缺失的信息是健康领域以及其他领域(如社会科学)数据性质的一部分,这一缺失值的假设是在不丧失一般性的情况下做出的。作者的方法是试图处理在几个数据库中同一病人的记录的联系。她的方法论的第一阶段被称为均质化。数据库/数据集的均质化是通过应用一种用预测值填充缺失值的方法来实现的。她的方法的第二阶段被称为记录链接。它评估记录之间的相似度,并实现高相似度记录对的链接。最后,作者对我们的研究方法进行了评价。均质阶段采用多项回归评价,聚合相似度采用Jaccard、Jaro-Winkler和Monge-Elkan相似度指标评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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