Background: Empirically driven personalized diagnostic applications and treatment stratification is widely perceived as a major hallmark in psychiatry. However, databased personalized decision making requires standardized data acquisition and data access, which are currently absent in psychiatric clinical routine. Objective: Here, we describe the informatics infrastructure implemented at the psychiatric Münster University Hospital, which allows standardized acquisition, transfer, storage, and export of clinical data for future real-time predictive modelling in psychiatric routine. Methods: We designed and implemented a technical architecture that includes an extension of the electronic health record (EHR) via scalable standardized data collection and data transfer between EHRs and research databases, thus allowing the pooling of EHRs and research data in a unified database and technical solutions for the visual presentation of collected data and analyses results in the EHR. The Single-source Metadata ARchitecture Transformation (SMA:T) was used as the software architecture. SMA:T is an extension of the EHR system and uses module-driven engineering to generate standardized applications and interfaces. The operational data model was used as the standard. Standardized data were entered on iPads via the Mobile Patient Survey (MoPat) and the web application Mopat@home, and the standardized transmission, processing, display, and export of data were realized via SMA:T. Results: The technical feasibility of the informatics infrastructure was demonstrated in the course of this study. We created 19 standardized documentation forms with 241 items. For 317 patients, 6451 instances were automatically transferred to the EHR system without errors. Moreover, 96,323 instances were automatically transferred from the EHR system to the research database for further analyses. Conclusions: In this study, we present the successful implementation of the informatics infrastructure enabling standardized data acquisition and data access for future real-time predictive modelling in clinical routine in psychiatry. The technical solution presented here might guide similar initiatives at other sites and thus help to pave the way toward future application of predictive models in psychiatric clinical routine.

中文翻译：

---

精神科临床常规中标准化数据采集、传输、存储和导出的信息学基础设施的设计和实施：可行性研究

背景：经验驱动的个性化诊断应用和治疗分层被广泛认为是精神病学的一个主要标志。然而，数据库化的个性化决策需要标准化的数据采集和数据访问，而这在目前精神病临床常规中是不存在的。目标：在这里，我们描述了在精神病学明斯特大学医院实施的信息学基础设施，它允许标准化获取、传输、存储和导出临床数据，以用于未来精神病常规的实时预测建模。方法：我们设计并实施了一种技术架构，其中包括通过可扩展的标准化数据收集和 EHR 与研究数据库之间的数据传输来扩展电子健康记录 (EHR)，从而允许将 EHR 和研究数据汇集到一个统一的数据库和技术解决方案中。 EHR 中收集的数据和分析结果的可视化呈现。单源元数据架构转换 (SMA:T) 被用作软件架构。SMA:T 是 EHR 系统的扩展，使用模块驱动的工程来生成标准化的应用程序和接口。操作数据模型被用作标准。通过移动患者调查 (MoPat) 和网络应用程序 Mopat@home 在 iPad 上输入标准化数据，标准化传输、处理、显示、结果：在本研究过程中证明了信息学基础设施的技术可行性。我们创建了 19 个标准化文档表格，包含 241 个项目。对于 317 名患者，有 6451 个实例被自动传输到 EHR 系统，没有错误。此外，96,323 个实例自动从 EHR 系统传输到研究数据库以进行进一步分析。结论：在这项研究中，我们展示了信息学基础设施的成功实施，使标准化数据采集和数据访问成为可能，以用于精神病学临床常规中未来的实时预测建模。这里介绍的技术解决方案可能会指导其他站点的类似举措，从而有助于为未来在精神病临床常规中应用预测模型铺平道路。