Friele Minou, Bröckerhoff Peter, Fröhlich Wiebke, Spiecker Genannt Döhmann Indra, Woopen Christiane
Cologne Center for Ethics, Rights, Economics, and Social Sciences of Health (ceres), Universität zu Köln, Köln, Deutschland.
Medizinische Fakultät, Uniklinik Köln, Forschungsstelle Ethik, Universität zu Köln, 50924, Köln, Deutschland.
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2020 Jun;63(6):741-748. doi: 10.1007/s00103-020-03147-2.
Digitization offers considerable potential for strengthening prevention in the healthcare system. Data from various clinical and nonclinical sources can be collected in a structured way and systematically processed using algorithms. Prevention needs can thus be identified more quickly and precisely, and interventions can be planned, implemented, and evaluated for specific target groups. At the same time, however, it is necessary that data processing not only meets high technical but also ethical standards and legal data protection regulations in order to avoid or minimize risks.This discussion article examines the potentials and risks of digital prevention first from a "data perspective," which deals with the use of health-related data for the purpose of prevention, and second from an "algorithm perspective," which focuses on the use of algorithmic systems, including artificial intelligence, for the assessment of needs and evaluation of preventive measures, from an ethical and legal point of view. Finally, recommendations are formulated for framework conditions that should be created to strengthen the further development of prevention in the healthcare system.
数字化为加强医疗保健系统中的预防工作提供了巨大潜力。来自各种临床和非临床来源的数据可以以结构化的方式收集,并使用算法进行系统处理。这样就能更快、更精确地识别预防需求,并针对特定目标群体规划、实施和评估干预措施。然而,与此同时,数据处理不仅要符合高技术标准,还必须符合道德标准和法律数据保护规定,以避免或尽量减少风险。这篇讨论文章首先从 “数据视角” 审视数字预防的潜力和风险,该视角涉及将与健康相关的数据用于预防目的;其次从 “算法视角” 进行审视,该视角从伦理和法律角度关注使用算法系统,包括人工智能,来评估需求和评价预防措施。最后,针对为加强医疗保健系统中预防工作的进一步发展应创造的框架条件提出了建议。