Vital statistics linked birth infant death and hospital discharge record linkage for epidemiological studies
Vital statistics linked birth infant death and hospital discharge record linkage for epidemiological studies
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DOI：
10.1006/cbmr.1997.1448
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发表时间：
1997-08-01
期刊：
影响因子：
--
通讯作者：
Nesbitt, TS
中科院分区：
文献类型：
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作者：
Herrchen, B;Gould, JB;Nesbitt, TS
介绍了一种将生命统计数据与出生/死亡数据和出院数据联系起来的方法。由此产生的数据集结合了关于新生儿的社会人口特征、产前护理和死亡率方面的信息，并将其与详细的健康结果和资源利用数据联系起来，从而为流行病学研究建立了一个广泛的数据库。在缺乏两个数据库共有的通用标识符的情况下，我们的链接策略依赖于使用基于两个数据集共有的变量的虚拟标识符。在同一虚拟标识符的多次发生的情况下，我们使用次要健康状况信息来优化将一个数据库中的低出生体重或早产儿与另一个数据库中的类似健康状况的婴儿联系起来的可能性，同时随机化不存在次要信息的病例。将我们的方法应用于1992年加州出生队列，我们可以在571，189名合格出生中链接563，114名（98.59%）。在这些链接中，91.2%是基于唯一虚拟标识符建立的。在比较生命统计关联出生/死亡档案中所有单次活产的变量分布和生命统计关联出生/死亡和出院档案中的关联出生时，这种关联是内部一致的，没有明显偏倚。多重插补技术表明，随机化引起的预测误差可以忽略不计。即使计算密集，我们的方法链接的生命统计链接出生/死亡文件和出院文件似乎是有效的。然而，必须认识到由此产生的数据集的局限性，特别是它不能用于跟踪个案。该方法提供了一个适合于各种围产期流行病学分析的数据库，如新生儿疾病分布的描述性研究，疾病的地理分布的研究，以及风险和结果之间的关系的研究。(C)北京：科学出版社.
A methodology for linking vital statistics linked birth/death data and hospital discharge data is described. The resulting data set combines information on a neonate's sociodemographic characteristics, prenatal care, and mortality aspects and connects it to detailed health outcome and resource utilization data, thus establishing an extensive database for epidemiological studies. In the absence of a universal identifier common to both databases, our linkage strategy relied on using a virtual identifier based on variables common to both data sets. In the case of multiple incidences of the same virtual identifier we used secondary health status information to optimize the likelihood of linking low birth weight or premature infants in one database to infants of similar health status in the other while randomizing cases in which no secondary information was present. Applying our method to the 1992 California birth cohort, we could link 563,114 out of 571,189 eligible births (98.59%). Of these links, 91.2% were established on the basis of unique virtual identifiers. The link was internally consistent and no bias was evident when comparing variable distributions for all single live births in the vital statistics linked birth/death file and linked births in the linked vital statistics linked birth/death and hospital discharge file. Multiple imputation techniques showed that the prediction error incurred by randomization was negligible. Even though computationally intensive, our method for linking the vital statistics linked birth/death file and the hospital discharge file appeared to be effective. However, it is important to be aware of the limitations of the resulting data set, in particular the fact that it cannot be used for tracking individual cases. The method provides a database suitable for a variety of perinatal epidemiological analyses, such as descriptive studies of disease distribution in neonates, studies of the geographic distribution of disease, and studies of the relationship between risk and outcome. (C) 1997 Academic Press.