The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research.
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机译：华盛顿大学转化健康科学研究所正在开展一个名为LC Data QUEST的项目，该项目旨在为华盛顿，怀俄明州，阿拉斯加，蒙大拿州，爱达荷州地区的农村和部落居民提供初级保健实践中的数据共享能力，以建立研究基础设施。我们报告了开发技术架构的迭代过程，该技术架构在我们的试验站点和工具之间的基层医疗环境中对电子医疗数据进行了语义匹配，这将促进研究与实践社区之间的联系。我们的体系结构强调解决数据提取，对齐，质量和元数据管理的可持续技术解决方案。该体系结构通过临床决策支持工具和数据查询功能为参与的合作伙伴提供了立即受益，以支持本地质量改进工作。 FInDiT工具对整个LC Data QUEST数据共享体系结构中可用的数据的类型，数量和质量进行分类。这些工具有助于翻译研究的双向过程。
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