Institute of Data Science, Faculty of Science and Engineering, Maastricht University, Maastricht, The Netherlands.
Brightlands Institute of Smart Society, Faculty of Science and Engineering, Maastricht University, Heerlen, The Netherlands.
J Biomed Inform. 2022 Oct;134:104194. doi: 10.1016/j.jbi.2022.104194. Epub 2022 Sep 5.
The mining of personal data collected by multiple organizations remains challenging in the presence of technical barriers, privacy concerns, and legal and/or organizational restrictions. While a number of privacy-preserving and data mining frameworks have recently emerged, much remains to show their practical utility. In this study, we implement and utilize a secure infrastructure using data from Statistics Netherlands and the Maastricht Study to learn the association between Type 2 Diabetes Mellitus (T2DM) and healthcare expenses considering the impact of lifestyle, physical activities, and complications of T2DM. Through experiments using real-world distributed personal data, we present the feasibility and effectiveness of the secure infrastructure for practical use cases of linking and analyzing vertically partitioned data across multiple organizations. We discovered that individuals diagnosed with T2DM had significantly higher expenses than those with prediabetes, while participants with prediabetes spent more than those without T2DM in all the included healthcare categories to different degrees. We further discuss a joint effort from technical, ethical-legal, and domain-specific experts that is highly valued for applying such a secure infrastructure to real-life use cases to protect data privacy.
在存在技术障碍、隐私问题以及法律和/或组织限制的情况下，挖掘多个组织收集的个人数据仍然具有挑战性。虽然最近出现了许多隐私保护和数据挖掘框架，但仍需要展示它们的实际效用。在这项研究中，我们使用来自荷兰统计局和马斯特里赫特研究的数据实施和利用安全基础设施，以了解 2 型糖尿病（T2DM）与医疗保健费用之间的关联，同时考虑生活方式、体育活动以及 T2DM 并发症的影响。通过使用真实分布式个人数据的实验，我们展示了安全基础设施对于跨多个组织链接和分析垂直分割数据的实际用例的可行性和有效性。我们发现，被诊断患有 T2DM 的个体的支出明显高于前驱糖尿病患者，而前驱糖尿病患者在所有包含的医疗保健类别中的支出均高于没有 T2DM 的患者，但程度不同。我们进一步讨论了技术、伦理法律和特定领域专家的共同努力，这对于将这种安全基础设施应用于现实生活中的用例以保护数据隐私具有重要价值。
