交换基于背景和来源的标准化患者生成的健康数据与电子健康记录.
Abdullahi Abubakar Kawu1, Lucy Hederman2, Dympna O'Sullivan1
1Technological University Dublin, Dublin, Ireland.
AMIA ... Annual Symposium proceedings. AMIA Symposium
|February 23, 2026
概括
患者生成的健康数据 (PGHD) 可以通过捕捉收集时的上下文和来源来改善临床使用. 一个基于本体学的模型提高了PGHD在电子健康记录 (EHR) 中的可靠性和可用性.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 本体学 工程学 工程学
背景情况:
- 患者生成的健康数据 (PGHD) 赋予患者权力,但缺乏用于临床整合的上下文信息.
- 临床医生需要上下文和来源数据,以便在电子健康记录 (EHR) 中可靠地使用PGHD.
- 现有的方法往往无法捕捉到PGHD收集点的基本上下文.
研究的目的:
- 描述一种以本体学为驱动的模型,以捕捉PGHD的来源和上下文.
- 确保PGHD足以用于临床决策.
- 评估该模型的应用和与电子健康系统的数据共享.
主要方法:
- 开发了一个本体学驱动的模型来捕捉PGHD,包括来源和上下文.
- 使用两个不同的PGHD来源评估模型.
- 使用资源描述框架 (RDF) 和快速医疗互操作资源 (FHIR) 格式与EHR进行标准化数据共享.
主要成果:
- 在本体学驱动的模型成功地捕获了PGHD与必要的来源和背景.
- 证明了将这种丰富的PGHD与EHR共享的可行性.
- 标准化格式 (RDF/FHIR) 促进了互操作性.
结论:
- 一种基于本体学的方法可以有效地提高PGHD的可靠性,信任性和可用性,用于临床决策.
- 这个模型为将更丰富的PGHD集成到EHR系统中提供了基础.
- 需要进一步的临床验证,以使其与医疗保健工作流程保持一致.
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