Implementation and Execution of Big Data-based Studies in Ophthalmology within the Framework of the GDPR.

IF 0.8 4区 医学 Q4 OPHTHALMOLOGY
Klinische Monatsblatter fur Augenheilkunde Pub Date : 2024-06-01 Epub Date: 2023-09-04 DOI:10.1055/a-2165-9815
Benedikt Siebelmann, Guido Grass, Mario Matthaei, Claus Cursiefen, Till Gerhardt, Juliane Koeberlein-Neu, Sebastian Siebelmann
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引用次数: 0

Abstract

The processing of the retrospective data pool for ophthalmology holds huge potential, especially for the research sector. "Big Data" enables medical science to draw conclusions for the future from historical data. Based on the evaluation of such data, algorithms could be trained, for instance, that are capable of making decisions with the help of artificial intelligence. As a result, the medical decision-making process on certain issues could be accelerated, enriched in qualitative and quantitative terms, or even completely be taken over. Ophthalmology is a rapidly evolving field. Due to the multitude of partly automated medical imaging technologies and the predestined accessibility of the eye for such technologies, ophthalmology, similarly to radiology or dermatology, is well suited for artificial intelligence-assisted image data analysis and the frequently associated initiation of diagnosis and therapy. Meanwhile, numerous studies exist based on AI-assisted image data analysis of ophthalmological image data. To the extent that the algorithms filter out results from the data pools by means of calculation rules and are even capable of making independent decisions on the basis of decision trees, the enormous benefit and, simultaneously, the profit for scientific research is quite obvious. Accordingly, it would be desirable to have unrestricted and comprehensive possibility of corresponding data processing of these health data for ophthalmological research. In spite of the potential for ophthalmology, for which there is only fragmentary evidence, the question of practical feasibility arises. In particular, the legal requirements and limits of European and national data protection law must be taken into account, prior to any unreflected processing of personal (health) data. Only by doing so can we circumvent existing obstacles and pitfalls, which can lead to severe fines. Most important are to date the requirements of two legal texts: The General Data Protection Regulation (GDPR) and the Federal Data Protection Act (BDSG). This article provides an overview of the relevant legal requirements applicable in the field of ophthalmology and highlights the major pitfalls and implementation requirements.

在 GDPR 框架内实施和执行眼科大数据研究。
眼科回顾性数据池的处理具有巨大潜力,尤其是对研究部门而言。"大数据 "使医学科学能够从历史数据中得出未来的结论。例如,根据对这些数据的评估,可以训练出能够借助人工智能做出决策的算法。因此,某些问题的医疗决策过程可以加快,在定性和定量方面得到丰富,甚至完全被取代。眼科是一个快速发展的领域。由于拥有大量部分自动化的医学成像技术,而且眼部注定可以使用这些技术,因此眼科与放射科或皮肤科一样,非常适合人工智能辅助的图像数据分析,以及经常与之相关的诊断和治疗的启动。与此同时,基于人工智能辅助图像数据分析眼科图像数据的研究层出不穷。这些算法通过计算规则从数据池中筛选出结果,甚至能够在决策树的基础上做出独立的决定,其巨大的好处以及同时为科学研究带来的收益是显而易见的。因此,最好能不受限制地全面处理这些健康数据,用于眼科研究。尽管眼科研究的潜力巨大,但目前仅有零星证据,实际可行性问题也随之而来。特别是,在对个人(健康)数据进行任何未经反思的处理之前,必须考虑到欧洲和国家数据保护法的法律要求和限制。只有这样,我们才能避开现有的障碍和陷阱,因为这些障碍和陷阱可能导致严重的罚款。迄今为止,最重要的是两个法律文本的要求:通用数据保护条例》(GDPR)和《联邦数据保护法》(BDSG)。本文概述了适用于眼科领域的相关法律要求,并强调了主要陷阱和实施要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.30
自引率
0.00%
发文量
235
审稿时长
4-8 weeks
期刊介绍: -Konzentriertes Fachwissen aus Klinik und Praxis: Die entscheidenden Ergebnisse der internationalen Forschung - für Sie auf den Punkt gebracht und kritisch kommentiert, Übersichtsarbeiten zu den maßgeblichen Themen der täglichen Praxis, Top informiert - breite klinische Berichterstattung. -CME-Punkte sammeln mit dem Refresher: Effiziente, CME-zertifizierte Fortbildung, mit dem Refresher, 3 CME-Punkte pro Ausgabe - bis zu 36 CME-Punkte im Jahr!. -Aktuelle Rubriken mit echtem Nutzwert: Kurzreferate zu den wichtigsten Artikeln internationaler Zeitschriften, Schwerpunktthema in jedem Heft: Ausführliche Übersichtsarbeiten zu den wichtigsten Themen der Ophthalmologie – so behalten Sie das gesamte Fach im Blick!, Originalien mit den neuesten Entwicklungen, Übersichten zu den relevanten Themen.
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