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[纳入确定性后处理阶段以提高概率性记录链接的性能]

[Inclusion of a deterministic post-processing stage to increase the performance of probabilistic record linkage].

作者信息

Brustulin Rafael, Marson Poliana Guerino

机构信息

Secretaria Municipal de Saúde de Palmas, Palmas, Brasil.

Universidade Federal do Tocantins, Palmas, Brasil.

出版信息

Cad Saude Publica. 2018 Jun 21;34(6):e00088117. doi: 10.1590/0102-311X00088117.

Abstract

The aim of this study was to demonstrate the application of a deterministic post-processing stage, based on measures of similarity, to increase the performance of probabilistic record linkage with and without manual revision. The databases used in the study were the Brazilian Information System for Notificable Diseases and the Brazilian Mortality Information System, from 2007 to 2015, in Palmas, Tocantins State, Brazil. The probabilistic software was OpenRecLink, and a deterministic post-processing stage was applied to the data obtained from three different probabilistic linkage strategies. The three strategies were compared to each other, and the deterministic post-processing stage was added. The sensibility of the probabilistic strategies without manual revision varied from 69.1% and 77.8%, while the same strategies plus the deterministic post-processing stage varied from 92.9% to 96.3%. Sensitivity of the two probabilistic strategies with manual revision was similar to that obtained by the deterministic post-processing stage, but the number of matches that were referred to manual revision by the two probabilistic strategies varied between 1,177 and 1,132 records, compared to 149 and 145 after the deterministic post-processing stage. Our findings suggest that the deterministic post-processing stage is a promising option, both to increase the sensitivity and to reduce the number of matches that need to be reviewed manually, or even to eliminate the need for manual revision altogether.

摘要

本研究的目的是展示基于相似性度量的确定性后处理阶段的应用,以提高在有或没有人工修订情况下概率性记录链接的性能。该研究中使用的数据库是巴西法定传染病信息系统和巴西死亡率信息系统,数据来自2007年至2015年巴西托坎廷斯州帕尔马斯市。概率性软件是OpenRecLink,并且对从三种不同概率性链接策略获得的数据应用了确定性后处理阶段。对这三种策略进行了相互比较,并添加了确定性后处理阶段。未经人工修订的概率性策略的敏感性在69.1%至77.8%之间,而相同策略加上确定性后处理阶段的敏感性在92.9%至96.3%之间。两种经过人工修订的概率性策略的敏感性与确定性后处理阶段获得的敏感性相似,但两种概率性策略提交人工修订的匹配记录数量在1177至1132条记录之间,而确定性后处理阶段之后为149条和145条。我们的研究结果表明,确定性后处理阶段是一个有前景的选择,既能提高敏感性,又能减少需要人工审核的匹配数量,甚至完全消除人工修订的必要性。

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