Varghese Julian, Schuster Alexander, Poschkamp Broder, Yildirim Kemal, Oehm Johannes, Berens Philipp, Müller Sarah, Gervelmeyer Julius, Koch Lisa, Hoffmann Katja, Sedlmayr Martin, Kakkassery Vinodh, Kohlbacher Oliver, Merle David, Bartz-Schmidt Karl Ulrich, Ueffing Marius, Stahl Dana, Leddig Torsten, Bialke Martin, Hampf Christopher, Hoffmann Wolfgang, Berthe Sebastian, Waltemath Dagmar, Walter Peter, Lipprandt Myriam, Röhrig Rainer, Storp Jens Julian, Zimmermann Julian Alexander, Holtrup Lea, Brix Tobias, Stahl Andreas, Eter Nicole
Institute of Medical Informatics, University of Münster, Institut für Medizinische Informatik Münster, Albert-Schweitzer-Campus 1, Münster, 48149, Germany.
Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany.
JMIR Med Inform. 2024 Dec 5;12:e60851. doi: 10.2196/60851.
The EyeMatics project, embedded as a clinical use case in Germany's Medical Informatics Initiative, is a large digital health initiative in ophthalmology. The objective is to improve the understanding of the treatment effects of intravitreal injections, the most frequent procedure to treat eye diseases. To achieve this, valuable patient data will be meaningfully integrated and visualized from different IT systems and hospital sites. EyeMatics emphasizes a governance framework that actively involves patient representatives, strictly implements interoperability standards, and employs artificial intelligence methods to extract biomarkers from tabular and clinical data as well as raw retinal scans. In this perspective paper, we delineate the strategies for user-centered implementation and health care-based evaluation in a multisite observational technology study.
EyeMatics项目作为德国医学信息学倡议中的一个临床用例，是眼科领域一项大型数字健康计划。其目标是增进对玻璃体内注射治疗效果的理解，玻璃体内注射是治疗眼部疾病最常用的方法。为实现这一目标，将对来自不同IT系统和医院的宝贵患者数据进行有意义的整合和可视化处理。EyeMatics强调一个治理框架，该框架积极吸纳患者代表参与，严格执行互操作性标准，并采用人工智能方法从表格数据、临床数据以及原始视网膜扫描中提取生物标志物。在这篇观点论文中，我们阐述了在多中心观察性技术研究中以用户为中心的实施策略和基于医疗保健的评估方法。
