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一种无需人工审核的概率性记录链接技术分析。

Analysis of a probabilistic record linkage technique without human review.

作者信息

Grannis Shaun J, Overhage J Marc, Hui Siu, McDonald Clement J

机构信息

Regenstrief Institute and Indiana University School of Medicine, Indianapolis, IN, USA.

出版信息

AMIA Annu Symp Proc. 2003;2003:259-63.

Abstract

We previously developed a deterministic record linkage algorithm demonstrating sensitivities approaching 90% while maintaining 100% specificity. Substantially better performance has been reported using probabilistic linkage techniques; however, such methods often incorporate human review into the process. To avoid human review, we employed an estimator function using the Expectation Maximization (EM) algorithm to establish a single true-link threshold. We compared the unsupervised probabilistic results against the manually reviewed gold-standard for two hospital registries, as well against our previous deterministic results. At an estimated specificity of 99.95%, actual specificities were 99.43% and 99.42% for registries A and B, respectively. At an estimated sensitivity of 99.95%, actual sensitivities were 99.19% and 98.99% for registries A and B, respectively. The EM algorithm estimated linkage parameters with acceptable accuracy, and was an improvement over the deterministic algorithm. Such a methodology may be used where record linkage is required, but human intervention is not possible or practical.

摘要

我们之前开发了一种确定性记录链接算法,该算法在保持100%特异性的同时,灵敏度接近90%。据报道,使用概率链接技术的性能要显著更好;然而,此类方法通常在过程中纳入人工审核。为避免人工审核,我们采用了一种使用期望最大化(EM)算法的估计函数来建立单个真实链接阈值。我们将无监督概率结果与两个医院登记处经人工审核的金标准进行了比较,同时也与我们之前的确定性结果进行了比较。在估计特异性为99.95%时,登记处A和B的实际特异性分别为99.43%和99.42%。在估计灵敏度为99.95%时,登记处A和B的实际灵敏度分别为99.19%和98.99%。EM算法以可接受的精度估计链接参数,并且是对确定性算法的一种改进。这种方法可用于需要记录链接但无法或不实际进行人工干预的情况。

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