从数字到洞察力:开发可行性要求的视觉队列探索器
Ahmad Albenny1, Dennis Hübner1, Franziska Bathelt1
1Medizinische Universität Lausitz - Carl Thiem.
Studies in health technology and informatics
|September 3, 2025
概括
这项研究开发了当地FDPG可行性门户数据的视觉工具,在保持患者匿名的同时增强队列理解. 在数据提取和可视化方面,SQL方法比FHIR更快.
科学领域:
- 医疗信息学
- 健康数据可视化
- 临床研究基础设施
背景情况:
- 德国医学研究数据门户 (FDPG) 的可行性门户有助于国家患者队列的识别.
- 在FDPG可行性门户网站的本地安装处进行特定地点的查询.
- 当地队列数据的可视化提高了解释性和可理解性,同时保持了匿名性.
研究的目的:
- 开发当地FDPG可行性门户群的视觉表现.
- 解决在确保数据匿名的同时提供队列洞察力的挑战.
- 提高当地可行性数据的准确性和可理解性.
主要方法:
- 使用医疗信息倡议 (MII) 工具和本地可行性门户.
- 开发了一个使用fhircrackr,echarts4r和plotly的交互式R闪亮仪表板.
- 可视化患者数据,包括性别,诊断 (ICD-10-GM),实验室 (LOINC),程序 (OPS) 和药物 (ATC).
主要成果:
- 开发了两个数据提取变体 (FHIR和SQL),并成功地可视化了队列数据.
- 交互式的Shiny应用提供了由临床专家验证的可视化图像.
- 这两种方法都能够有效地可视化本地患者队列特征.
结论:
- 与FHIR相比,SQL方法的处理时间更长.
- 对于跨站点部署,FHIR提供了更大的灵活性.
- 开发的可视化工具适用于本地部署,但国家实施需要进一步开发和基础设施改进.
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