Probabilistic linkage without personal information successfully linked national clinical datasets
Probabilistic linkage without personal information successfully linked national clinical datasets
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DOI：
10.1016/j.jclinepi.2021.04.0150895-4356
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发表时间：
2021-08-01
影响因子：
7.2
通讯作者：
Walker, Kate
中科院分区：
文献类型：
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作者：
Blake, Helen A.;Sharples, Linda D.;Walker, Kate
背景：概率联系可以将来自不同临床数据库的患者联系起来，而不需要个人信息。如果能够实现准确的关联，将加速使用关联数据集来解决重要的临床和公共卫生问题。目的：我们开发了一个逐步的过程，用于在没有个人信息的情况下对国家临床和行政数据集进行概率链接，并使用患者标识符对确定性链接进行验证。研究设计和设置：我们使用了来自国家肠癌审计和医院事件统计数据库的电子健康记录，用于在英国国民健康服务中接受紧急手术的10，566名肠癌患者。结果如下：81.4%的国家肠癌审计记录与医院事件统计数据之间存在可能的联系，而使用确定性联系的比例为82.8%。没有系统的差异，患者之间的联系，并没有看到，根据患者和肿瘤特征的死亡率和住院时间的回归模型是不敏感的联系方法。结论：概率联系成功地将接受重大外科手术的患者的国家临床和管理数据集联系起来。它允许高度安全的数据环境之外的分析人员进行链接，同时最大限度地减少成本和延迟，保护数据安全并保持链接质量。(c)2021年，任作者。爱思唯尔公司出版这是一个在CC BY-NC-ND许可下的开放获取文章（http：//creativecommons.org/licenses/by-nc-nd/4.0/）。
Background: Probabilistic linkage can link patients from different clinical databases without the need for personal information. If accurate linkage can be achieved, it would accelerate the use of linked datasets to address important clinical and public health questions. Objective: We developed a step-by-step process for probabilistic linkage of national clinical and administrative datasets without personal information, and validated it against deterministic linkage using patient identifiers. Study Design and Setting: We used electronic health records from the National Bowel Cancer Audit and Hospital Episode Statistics databases for 10,566 bowel cancer patients undergoing emergency surgery in the English National Health Service. Results: Probabilistic linkage linked 81.4% of National Bowel Cancer Audit records to Hospital Episode Statistics, vs. 82.8% using deterministic linkage. No systematic differences were seen between patients that were and were not linked, and regression models for mortality and length of hospital stay according to patient and tumour characteristics were not sensitive to the linkage approach. Conclusion: Probabilistic linkage was successful in linking national clinical and administrative datasets for patients undergoing a major surgical procedure. It allows analysts outside highly secure data environments to undertake linkage while minimizing costs and delays, protecting data security, and maintaining linkage quality. (c) 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)