基于网络的 FHIR® 问卷回复图形探索原型。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01
Johann Frei, Florian J Auer, Steffen Netzband, Yevgeniia Ignatenko, Frank Kramer
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引用次数: 0

摘要

临床问卷评估是实证研究中获取知识的重要组成部分。电子采集的回答以标准格式编码,如 HL7 FHIR®,有利于数据交换和系统互操作性。然而,如果没有适当的工具,这也会使获取信息以探索和解释结果变得更加复杂。在这项工作中,我们介绍了一种基于网络的分类问卷答复数据图形探索工具的设计,该工具可与符合 FHIR 的 HTTP 端点进行交互。该网络应用程序可使非技术用户以简化、直接的可视化方式访问高度结构化的 FHIR 问卷答复数据,并可适用于任意数据探索任务。我们介绍了抽象的功能设计和衍生的技术实现,以实现通用的、用户可配置的数据子选择机制,生成有条件的一维和二维图表。我们在合成 FHIR 数据上演示了所开发原型的适用性,源代码可在 https://github.com/frankkramer-lab/FHIR-QR-Explorer 上获取。
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Web-based Prototype for Graphical Exploration of FHIR® Questionnaire Responses.

The evaluation of clinical questionnaires is an important part of gaining knowledge in empirical research. The electronically captured responses are encoded in a standard format such as HL7 FHIR® that facilitates data exchange and systems interoperability. However, this also complicates access of the information to explore and interpret the results without appropriate tools. In this work, we present the design of a web-based graphical exploration tool for categorical questionnaire response data that can interact with FHIR-conformant HTTP endpoints. The web app enables non-technical users with simplified, direct visual access to highly structured FHIR questionnaire response data and preserves the applicability in arbitrary data exploration tasks. We describe the abstract feature design with the derived technical implementation to allow a universal, user-configurable data subselection mechanism to generate conditional one- and two-data-dimensional charts. The applicability of our developed prototype is demonstrated on synthetic FHIR data with the source code available at https://github.com/frankkramer-lab/FHIR-QR-Explorer.

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