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首页> 外文期刊>JMIR Medical Informatics >Health Data for Research Through a Nationwide Privacy-Proof System in Belgium: Design and Implementation
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Health Data for Research Through a Nationwide Privacy-Proof System in Belgium: Design and Implementation

机译：通过比利时全国性隐私保护系统进行研究的健康数据：设计和实施

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Background Health data collected during routine care have important potential for reuse for other purposes, especially as part of a learning health system to advance the quality of care. Many sources of bias have been identified through the lifecycle of health data that could compromise the scientific integrity of these data. New data protection legislation requires research facilities to improve safety measures and, thus, ensure privacy. Objective This study aims to address the question on how health data can be transferred from various sources and using multiple systems to a centralized platform, called Healthdata.be, while ensuring the accuracy, validity, safety, and privacy. In addition, the study demonstrates how these processes can be used in various research designs relevant for learning health systems. Methods The Healthdata.be platform urges uniformity of the data registration at the primary source through the use of detailed clinical models. Data retrieval and transfer are organized through end-to-end encrypted electronic health channels, and data are encoded using token keys. In addition, patient identifiers are pseudonymized so that health data from the same patient collected across various sources can still be linked without compromising the deidentification. Results The Healthdata.be platform currently collects data for 150 clinical registries in Belgium. We demonstrated how the data collection for the Belgian primary care morbidity register INTEGO is organized and how the Healthdata.be platform can be used for a cluster randomized trial. Conclusions Collecting health data in various sources and linking these data to a single patient is a promising feature that can potentially address important concerns on the validity and quality of health data. Safe methods of data transfer without compromising privacy are capable of transporting these data from the primary data provider or clinician to a research facility. More research is required to demonstrate that these methods improve the quality of data collection, allowing researchers to rely on electronic health records as a valid source for scientific data.
机译：背景常规护理期间收集的健康数据具有重要的潜力，可用于其他目的，尤其是作为学习卫生系统的一部分，以提高护理质量。在健康数据的整个生命周期中已经发现了许多偏见的来源，这些偏见可能会损害这些数据的科学完整性。新的数据保护法规要求研究机构改善安全措施，从而确保隐私。目的这项研究旨在解决有关如何将健康数据从各种来源转移到多个系统并转移到称为Healthdata.be的集中式平台的问题，同时确保准确性，有效性，安全性和隐私性。此外，研究证明了如何将这些过程用于与学习卫生系统相关的各种研究设计中。方法Healthdata.be平台要求通过使用详细的临床模型来统一主要来源的数据注册。数据检索和传输通过端到端加密的电子健康通道进行组织，并且使用令牌密钥对数据进行编码。另外，对患者标识符进行了假名化，因此仍可以链接来自不同患者的同一患者的健康数据，而不会影响身份识别。结果Healthdata.be平台目前正在比利时收集150多个临床注册机构的数据。我们展示了如何组织比利时初级保健发病率寄存器INTEGO的数据收集，以及如何将Healthdata.be平台用于集群随机试验。结论收集各种来源的健康数据并将这些数据链接到单个患者是一项很有前途的功能，可以潜在地解决有关健康数据有效性和质量的重要问题。在不损害隐私的前提下，安全的数据传输方法能够将这些数据从主要数据提供者或临床医生传输到研究机构。需要更多的研究来证明这些方法可以提高数据收集的质量，从而使研究人员可以依靠电子健康记录作为科学数据的有效来源。

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