This article presents our steps to integrate complex and partly unstructured medical data into a clinical research database with subsequent decision support. Our main application is an integrated faceted search tool, accompanied by the visualisation of results of automatic information extraction from textual documents. We describe the details of our technical architecture (open-source tools), to be replicated at other universities, research institutes, or hospitals. Our exemplary use cases are nephrology and mammography. The software was first developed in the nephrology domain and then adapted to the mammography use case. We report on these case studies, illustrating how the application can be used by a clinician and which questions can be answered. We show that our architecture and the employed software modules are suitable for both areas of application with a limited amount of adaptations. For example, in nephrology we try to answer questions about the temporal characteristics of event sequences to gain significant insight from the data for cohort selection. We present a versatile time-line tool that enables the user to explore relations between a multitude of diagnosis and laboratory values.

本文介绍了将复杂且部分非结构化的医学数据集成到具有后续决策支持的临床研究数据库中的步骤。我们的主要应用程序是一个集成的多面搜索工具，并带有可视化的文本文档自动信息提取结果的可视化。我们描述了我们的技术架构（开源工具）的细节，这些细节将在其他大学，研究机构或医院中复制。我们示例性的用例是肾脏科和X线摄影。该软件首先在肾脏病学领域开发，然后适应于乳腺X射线摄影用例。我们将报告这些案例研究，说明临床医生如何使用该应用程序以及可以回答哪些问题。我们证明了我们的体系结构和所采用的软件模块适用于这两个应用领域，并且进行了少量修改。例如，在肾脏病学中，我们尝试回答有关事件序列的时间特征的问题，以从用于队列选择的数据中获得重要的见识。我们提供了一种通用的时间轴工具，使用户能够探索多种诊断与实验室值之间的关系。