Trentzsch H, Osterhoff G, Heller R, Nienaber U, Lazarovici M
Institut für Notfallmedizin und Medizinmanagement (INM), Klinikum der Universität München, LMU München, Schillerstr. 53, 80336, München, Deutschland.
Klinik und Poliklinik für Orthopädie, Unfallchirurgie und Plastische Chirurgie, Universitätsklinikum Leipzig, Leipzig, Deutschland.
Unfallchirurg. 2020 Nov;123(11):843-848. doi: 10.1007/s00113-020-00859-7.
The increasing digitalization of social life opens up new possibilities for modern health care. This article describes innovative application possibilities that could help to sustainably improve the treatment of severe injuries in the future with the help of methods such as big data, artificial intelligence, intelligence augmentation, and machine learning. For the successful application of these methods, suitable data sources must be available. The TraumaRegister DGU® (TR-DGU) currently represents the largest database in Germany in the field of care for severely injured patients that could potentially be used for digital innovations. In this context, it is a good example of the problem areas such as data transfer, interoperability, standardization of data sets, parameter definitions, and ensuring data protection, which still represent major challenges for the digitization of trauma care. In addition to the further development of new analysis methods, solutions must also continue to be sought to the question of how best to intelligently link the relevant data from the various data sources.
社会生活日益数字化为现代医疗保健带来了新的可能性。本文介绍了一些创新的应用可能性,借助大数据、人工智能、智能增强和机器学习等方法,有望在未来持续改善重伤治疗。要成功应用这些方法,必须有合适的数据源。创伤登记数据库DGU®(TR-DGU)目前是德国重伤患者护理领域最大的数据库,有可能用于数字创新。在此背景下,它是数据传输、互操作性、数据集标准化、参数定义以及确保数据保护等问题领域的一个典型例子,这些问题仍然是创伤护理数字化的重大挑战。除了进一步开发新的分析方法外,还必须继续寻求解决方案,以解决如何最好地智能链接来自各种数据源的相关数据这一问题。