Sariyar Murat, Schlünder Irene
Institute of Medical Informatics, Bern University of Applied Sciences, Bienne, Switzerland.
TMF - Technologie- und Methodenplattform e.V., Berlin, Germany.
Front Big Data. 2019 Nov 12;2:40. doi: 10.3389/fdata.2019.00040. eCollection 2019.
Profiling of individuals based on inborn, acquired, and assigned characteristics is central for decision making in health care. In the era of omics and big smart data, it becomes urgent to differentiate between different data governance affordances for different profiling activities. Typically, diagnostic profiling is in the focus of researchers and physicians, and other types are regarded as undesired side-effects; for example, in the connection of health care insurance risk calculations. Profiling in a legal sense is addressed, for example, by the EU data protection law. It is defined in the General Data Protection Regulation as automated decision making. This term does not correspond fully with profiling in biomedical research and healthcare, and the impact on privacy has hardly ever been examined. But profiling is also an issue concerning the fundamental right of non-discrimination, whenever profiles are used in a way that has a discriminatory effect on individuals. Here, we will focus on genetic profiling, define related notions as legal and subject-matter definitions frequently differ, and discuss the ethical and legal challenges.
基于个体的先天、后天和赋予特征进行剖析，是医疗保健决策的核心。在组学和大数据时代，区分不同剖析活动的不同数据治理能力变得迫在眉睫。通常，诊断剖析是研究人员和医生关注的焦点，而其他类型的剖析则被视为不良副作用；例如，在医疗保险风险计算方面。法律意义上的剖析，例如由欧盟数据保护法进行规范。它在《通用数据保护条例》中被定义为自动化决策。这个术语与生物医学研究和医疗保健中的剖析并不完全对应，而且对隐私的影响几乎从未被研究过。但是，只要剖析以对个人产生歧视性影响的方式使用，剖析也是一个涉及非歧视基本权利的问题。在这里，我们将重点关注基因剖析，由于法律定义和主题定义经常不同，我们将对相关概念进行界定，并讨论伦理和法律挑战。
