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采用来自加泰罗尼亚初级保健研究开发信息系统(SIDIAP)的数据进行母子数据链接的方法。

A mother-child data linkage approach using data from the information system for the development of research in primary care (SIDIAP) in Catalonia.

机构信息

Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Gran Via de les Corts Catalanes, 587, Barcelona 08007, Catalonia, Spain.

Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Gran Via de les Corts Catalanes, 587, Barcelona 08007, Catalonia, Spain.

出版信息

J Biomed Inform. 2024 Nov;159:104747. doi: 10.1016/j.jbi.2024.104747. Epub 2024 Nov 6.

Abstract

BACKGROUND

Large-scale clinical databases containing routinely collected electronic health records (EHRs) data are a valuable source of information for research studies. For example, they can be used in pharmacoepidemiology studies to evaluate the effects of maternal medication exposure on neonatal and pediatric outcomes. Yet, this type of studies is infeasible without proper mother-child linkage.

METHODS

We leveraged all eligible active records (N = 8,553,321) of the Information System for Research in Primary Care (SIDIAP) database. Mothers and infants were linked using a deterministic approach and linkage accuracy was evaluated in terms of the number of records from candidate mothers that failed to link. We validated the mother-child links identified by comparison of linked and unlinked records for both candidate mothers and descendants. Differences across these two groups were evaluated by means of effect size calculations instead of p-values. Overall, we described our data linkage process following the GUidance for Information about Linking Data sets (GUILD) principles.

RESULTS

We were able to identify 744,763 unique mother-child relationships, linking 83.8 % candidate mothers with delivery dates within a period of 15 years. Of note, we provide a record-level category label used to derive a global confidence metric for the presented linkage process. Our validation analysis showed that the two groups were similar in terms of a number of aggregated attributes.

CONCLUSIONS

Complementing the SIDIAP database with mother-child links will allow clinical researchers to expand their epidemiologic studies with the ultimate goal of improving outcomes for pregnant women and their children. Importantly, the reported information at each step of the data linkage process will contribute to the validity of analyses and interpretation of results in future studies using this resource.

摘要

背景

包含常规电子健康记录 (EHR) 数据的大规模临床数据库是研究的宝贵信息来源。例如,它们可用于药物流行病学研究,以评估母体药物暴露对新生儿和儿科结局的影响。然而,如果没有适当的母子链接,这种类型的研究是不可行的。

方法

我们利用信息系统进行初级保健 (SIDIAP) 数据库中的所有合格活动记录 (N=8,553,321)。使用确定性方法对母亲和婴儿进行链接,并根据未能链接的候选母亲记录数量评估链接准确性。我们通过比较链接和未链接记录来验证所识别的母子链接,以评估候选母亲和后代的链接准确性。这两个组之间的差异通过效果大小计算而不是 p 值进行评估。总体而言,我们按照链接数据集信息指南 (GUILD) 原则描述了我们的数据链接过程。

结果

我们能够识别 744,763 个独特的母子关系,链接了 83.8%有分娩日期的候选母亲,时间跨度为 15 年。值得注意的是,我们提供了一个记录级别的类别标签,用于为所提出的链接过程得出全局置信度度量。我们的验证分析表明,这两个组在聚合属性方面相似。

结论

通过母子链接补充 SIDIAP 数据库将使临床研究人员能够扩展他们的流行病学研究,最终目标是改善孕妇及其子女的结局。重要的是,报告的数据链接过程中的每一步的信息将有助于提高使用该资源进行未来研究的分析和结果解释的有效性。

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