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增强涉及低质量个人标识符的记录链接能力:最佳链接原则和死亡原因先验可能性的应用

Enhancing the power of record linkage involving low quality personal identifiers: use of the best link principle and cause of death prior likelihoods.

作者信息

MacLeod M C, Bray C A, Kendrick S W, Cobbe S M

机构信息

Information and Statistics Division, NHSiS, Scotland.

出版信息

Comput Biomed Res. 1998 Aug;31(4):257-70. doi: 10.1006/cbmr.1998.1480.

DOI:10.1006/cbmr.1998.1480
PMID:9731268
Abstract

The Heartstart Scotland study collects details of all resuscitation attempts carried out by the Scottish Ambulance Service. The linkage between records for Heartstart study subjects who died before admission to a hospital and the national file of death records maintained by the Registrar General for Scotland is described. The conditions under which the Heartstart data is collected make it inevitable that the personal identifying information on which linkage must rely tends to be relatively incomplete and of low accuracy. The linkage process was able to use the best-link principle to take maximum advantage of the fact that, because the Heartstart subjects involved had died, there was an extremely high a priori probability that they would be represented on the national deaths file. In addition, although no cause of death information was recorded on the Heartstart records, a priori expectations of the distribution of causes of death among linked death records were used. Despite these enhancements, however, clerical resolution of a proportion of the potential links generated by the automatic algorithm significantly improved the accuracy of the linkage.

摘要

“苏格兰心脏复苏启动研究”收集了苏格兰救护服务机构实施的所有复苏尝试的详细信息。本文描述了在医院入院前死亡的“心脏复苏启动研究”受试者记录与苏格兰总登记官维护的国家死亡记录档案之间的关联。收集“心脏复苏启动研究”数据的条件使得关联所必须依赖的个人识别信息不可避免地相对不完整且准确性较低。关联过程能够运用最佳关联原则,充分利用这样一个事实:由于所涉及的“心脏复苏启动研究”受试者已经死亡,他们极有可能出现在国家死亡档案中。此外,尽管“心脏复苏启动研究”记录中未记录死亡原因信息,但仍使用了关联死亡记录中死亡原因分布的先验预期。然而,尽管有这些改进措施,通过人工解决自动算法生成的一部分潜在关联,显著提高了关联的准确性。

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An empiric modification to the probabilistic record linkage algorithm using frequency-based weight scaling.基于频率的权重缩放的概率记录链接算法的经验修正。
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