BACKGROUND Electronic health record (EHR) systems contain large volumes of novel heterogeneous data that can be linked to trauma registry data to enable innovative research not possible with either data source alone. OBJECTIVE This article describes an approach for linking electronically extracted EHR data to trauma registry data at the institutional level and assesses the value of probabilistic linkage. METHODS Encounter data were independently obtained from the EHR data warehouse (n = 1,632) and the pediatric trauma registry (n = 1,829) at a Level I pediatric trauma center. Deterministic linkage was attempted using nine different combinations of medical record number (MRN), encounter identity (ID) (visit ID), age, gender, and emergency department (ED) arrival date. True matches from the best performing variable combination were used to create a gold standard, which was used to evaluate the performance of each variable combination, and to train a probabilistic algorithm that was separately used to link records unmatched by deterministic linkage and the entire cohort. Additional records that matched probabilistically were investigated via chart review and compared against records that matched deterministically. RESULTS Deterministic linkage with exact matching on any three of MRN, encounter ID, age, gender, and ED arrival date gave the best yield of 1,276 true matches while an additional probabilistic linkage step following deterministic linkage yielded 110 true matches. These records contained a significantly higher number of boys compared to records that matched deterministically and etiology was attributable to mismatch between MRNs in the two data sets. Probabilistic linkage of the entire cohort yielded 1,363 true matches. CONCLUSION The combination of deterministic and an additional probabilistic method represents a robust approach for linking EHR data to trauma registry data. This approach may be generalizable to studies involving other registries and databases.

中文翻译：

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链接电子病历和创伤登记数据：评估概率链接的价值。

背景技术电子健康记录（EHR）系统包含大量新颖的异构数据，这些数据可以链接到创伤登记数据，以实现仅使用任一数据源都不可能进行的创新研究。目的本文介绍一种在机构级别将电子提取的EHR数据与创伤登记数据链接的方法，并评估概率链接的价值。方法遇到的数据是分别从EHR数据仓库（n = 1,632）和小儿创伤中心的小儿创伤登记处（n = 1,829）获得的。确定性链接尝试使用九种不同组合的病历号（MRN），遭遇身份（ID）（访问ID），年龄，性别和急诊室（ED）到达日期。来自性能最佳的变量组合的真实匹配用于创建黄金标准，该标准用于评估每个变量组合的性能，并训练概率算法，该算法分别用于链接确定性链接无法匹配的记录和整个队列。通过图表审查调查了与概率匹配的其他记录，并将其与确定性匹配的记录进行比较。结果在MRN，遇到的ID，年龄，性别和ED到达日期中的任意三个点上具有精确匹配的确定性链接给出了1,276个真实匹配的最佳产量，而在确定性链接之后进行的另一个概率链接步骤则产生了110个真实匹配。与确定性匹配的记录相比，这些记录包含的男孩数量要多得多，病因归因于两个数据集中的MRN之间不匹配。整个队列的概率关联产生了1,363个真实匹配。结论确定性方法和附加概率方法的组合代表了将EHR数据与创伤登记数据链接的可靠方法。这种方法可以推广到涉及其他注册表和数据库的研究。