Mansmann U
Institut für Medizinische Informatik, Biometrie und Epidemiologie, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377, München, Deutschland.
Z Rheumatol. 2018 Apr;77(3):209-218. doi: 10.1007/s00393-018-0424-7.
Over the past 100 years, evidence-based medicine has undergone several fundamental changes. Through the field of physiology, medical doctors were introduced to the natural sciences. Since the late 1940s, randomized and epidemiological studies have come to provide the evidence for medical practice, which led to the emergence of clinical epidemiology as a new field in the medical sciences. Within the past few years, big data has become the driving force behind the vision for having a comprehensive set of health-related data which tracks individual healthcare histories and consequently that of large populations.
The aim of this article is to discuss the implications of data-driven medicine, and to examine how it can find a place within clinical care.
The EU-wide discussion on the development of data-driven medicine is presented.
The following features and suggested actions were identified: harmonizing data formats, data processing and analysis, data exchange, related legal frameworks and ethical challenges. For the effective development of data-driven medicine, pilot projects need to be conducted to allow for open and transparent discussion on the advantages and challenges. The Federal Ministry of Education and Research ("Bundesministerium für Bildung und Forschung," BMBF) Arthromark project is an important example. Another example is the Medical Informatics Initiative of the BMBF.
The digital revolution affects clinic practice. Data can be generated and stored in quantities that are almost unimaginable. It is possible to take advantage of this for development of a learning healthcare system if the principles of medical evidence generation are integrated into innovative IT-infrastructures and processes.
在过去的100年里，循证医学经历了几次根本性的变革。通过生理学领域，医生们开始接触自然科学。自20世纪40年代末以来，随机和流行病学研究开始为医学实践提供证据，这导致临床流行病学作为医学科学中的一个新领域出现。在过去几年中，大数据已成为获取一套全面的健康相关数据愿景背后的驱动力，这些数据可追踪个人的医疗史以及大量人群的医疗史。
本文旨在探讨数据驱动型医学的影响，并研究其如何在临床护理中找到立足之地。
介绍了欧盟范围内关于数据驱动型医学发展的讨论。
确定了以下特征和建议行动：统一数据格式、数据处理与分析、数据交换、相关法律框架和伦理挑战。为了有效发展数据驱动型医学，需要开展试点项目，以便就优势和挑战进行开放和透明的讨论。联邦教育与研究部（“Bundesministerium für Bildung und Forschung”，BMBF）的Arthromark项目就是一个重要例子。另一个例子是BMBF的医学信息学倡议。
数字革命影响临床实践。数据能够以几乎难以想象的数量生成和存储。如果将医学证据生成原则融入创新的信息技术基础设施和流程中，就有可能利用这一点来发展学习型医疗系统。
