Grabenhenrich Mph Linus, Schranz Madlen, Boender Sonia, Kocher Theresa, Esins Janina, Fischer Martina
Abteilung für Methodenentwicklung und Forschungsinfrastruktur (MF), Fachgebiet Informations- und Forschungsdatenmanagement (MF 4), Robert Koch-Institut, Nordufer 20, 13353, Berlin, Deutschland.
Klinik für Dermatologie, Venerologie und Allergologie, Charité - Universitätsmedizin Berlin, Berlin, Deutschland.
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2021 Apr;64(4):412-417. doi: 10.1007/s00103-021-03300-5. Epub 2021 Mar 24.
Real-time data from medical care settings play an increasing role in guiding public health action. The COVID-19 pandemic is a good example; public health decisions depend on current data from the various clinical care settings. The automated processing and communication of health-related data is essential to ensure continuity of reporting and safe resources. So far, various technical, formal, and organizational challenges help back the development of digitally automated real-time systems with scientific quality standards. The COVID-19 pandemic pushed sustainable system developments since it began in early 2020.This article describes how a real-time data system should be structured so that automated data processing is possible. Important aspects in the consolidation of the data and their preparation and communication are presented. The processes implemented for handling routine data from emergency departments in real time and making it available to public health actors is described. As an example, we present the cooperation between the emergency admission registry of the Aktionsbündnis für Informations- und Kommunikationstechnologie in Intensiv- und Notfallmedizin (AKTIN), the Universität Magdeburg, and the RWTH Aachen as well as the Surveillance Monitor (SUMO) hosted at the Robert Koch Institute.The development of modern systems for processing research data in real-time from medical care settings can only succeed through the cooperation of a wide variety of actors. An important basis for long-term success is the development of a legal framework.
医疗机构的实时数据在指导公共卫生行动中发挥着越来越重要的作用。新冠疫情就是一个很好的例子;公共卫生决策依赖于来自各种临床医疗机构的当前数据。健康相关数据的自动化处理和通信对于确保报告的连续性和资源安全至关重要。到目前为止,各种技术、形式和组织方面的挑战阻碍了具有科学质量标准的数字自动化实时系统的发展。自2020年初新冠疫情爆发以来,它推动了可持续系统的发展。本文描述了实时数据系统应如何构建,以便实现数据的自动化处理。文中介绍了数据整合及其准备和通信方面的重要内容。描述了为实时处理急诊科的常规数据并将其提供给公共卫生行动者而实施的流程。作为一个例子,我们展示了重症与急诊医学信息与通信技术行动联盟(AKTIN)的急诊入院登记处、马格德堡大学和亚琛工业大学之间的合作,以及罗伯特·科赫研究所托管的监测监测器(SUMO)。要开发用于实时处理医疗机构研究数据的现代系统,只有通过众多参与者的合作才能成功。长期成功的一个重要基础是法律框架的制定。