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Linkage of multiple electronic health record datasets using a ‘spine linkage’ approach compared with all ‘pairwise linkages’
International Journal of Epidemiology ( IF 7.7 ) Pub Date : 2022-06-24 , DOI: 10.1093/ije/dyac130
Helen A Blake 1, 2 , Linda D Sharples 3 , Katie Harron 4 , Jan H van der Meulen 1, 2 , Kate Walker 1, 2
Affiliation  

Background Methods for linking records between two datasets are well established. However, guidance is needed for linking more than two datasets. Using all ‘pairwise linkages’—linking each dataset to every other dataset—is the most inclusive, but resource-intensive, approach. The ‘spine’ approach links each dataset to a designated ‘spine dataset’, reducing the number of linkages, but potentially reducing linkage quality. Methods We compared the pairwise and spine linkage approaches using real-world data on patients undergoing emergency bowel cancer surgery between 31 October 2013 and 30 April 2018. We linked an administrative hospital dataset (Hospital Episode Statistics; HES) capturing patients admitted to hospitals in England, and two clinical datasets comprising patients diagnosed with bowel cancer and patients undergoing emergency bowel surgery. Results The spine linkage approach, with HES as the spine dataset, created an analysis cohort of 15 826 patients, equating to 98.3% of the 16 100 patients identified using the pairwise linkage approach. There were no systematic differences in patient characteristics between these analysis cohorts. Associations of patient and tumour characteristics with mortality, complications and length of stay were not sensitive to the linkage approach. When eligibility criteria were applied before linkage, spine linkage included 14 509 patients (90.0% compared with pairwise linkage). Conclusion Spine linkage can be used as an efficient alternative to pairwise linkage if case ascertainment in the spine dataset and data quality of linkage variables are high. These aspects should be systematically evaluated in the nominated spine dataset before spine linkage is used to create the analysis cohort.

中文翻译:

与所有“成对链接”相比,使用“脊柱链接”方法链接多个电子健康记录数据集

背景 在两个数据集之间链接记录的方法已经很成熟。但是,链接两个以上的数据集需要指导。使用所有“成对链接”——将每个数据集链接到每个其他数据集——是最具包容性但资源密集型的方法。“脊柱”方法将每个数据集链接到指定的“脊柱数据集”,减少了链接的数量,但可能会降低链接质量。方法 我们使用 2013 年 10 月 31 日至 2018 年 4 月 30 日期间接受急诊肠癌手术的患者的真实世界数据比较了成对和脊柱连接方法。我们链接了一个行政医院数据集(医院事件统计;HES),该数据集捕获了英国医院收治的患者, 以及两个临床数据集,包括被诊断患有肠癌的患者和接受急诊肠道手术的患者。结果 以 HES 作为脊柱数据集的脊柱关联方法创建了一个包含 15 826 名患者的分析队列,相当于使用成对关联方法确定的 16 100 名患者中的 98.3%。这些分析队列之间的患者特征没有系统差异。患者和肿瘤特征与死亡率、并发症和住院时间的关联对关联方法不敏感。当在关联之前应用资格标准时,脊柱关联包括 14 509 名患者(与成对关联相比为 90.0%)。结论 如果 spine 数据集中的案例确定和链接变量的数据质量很高,则 Spine linkage 可以用作 pairwise linkage 的有效替代方法。在使用脊柱链接创建分析队列之前,应在指定的脊柱数据集中系统地评估这些方面。
更新日期:2022-06-24
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