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Patient stakeholders are getting increasingly involved in research health data networks, particularly as research partners. However, tools do not exist to help effectively orient, educate, and engage patient stakeholders as they take on these roles. Using a human centered design approach, we conducted a patient stakeholder needs assessment qualitative study to identify key user needs to drive design recommendations for development of an online education and engagement tool for research health data networks. We found three key needs related to multiple role identities, motivations and expectations for participation on research teams, and patient journeys. Design recommendations derived from the needs assessment are discussed that can support future tool design and testing.

Bi-directional translational pathways between scientific discoveries and primary care are crucial for improving individual patient care and population health. The Data QUEST pilot project is a program supporting data sharing amongst community based primary care practices and is built on a technical infrastructure to share electronic health record data. We developed a set of governance requirements from interviewing and collaborating with partner organizations. Recommendations from our partner organizations included: 1) partner organizations can physically terminate the link to the data sharing network and only approved data exits the local site; 2) partner organizations must approve or reject each query; 3) partner organizations and researchers must respect local processes, resource restrictions, and infrastructures; and 4) partner organizations can be seamlessly added and removed from any individual data sharing query or the entire network.

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.