Engaging patients, clinicians, and the community in a Clinical Data Research Network: Lessons learned from the CAPriCORN CDRN.

Engaging patients, clinicians, and community members in the development of a research network creates opportunities and challenges beyond engagement in discrete learning activities. This paper describes our experiences establishing and maintaining a stakeholder engagement infrastructure for the Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) and highlights important lessons learned over the first 4 years. During this time, the CAPriCORN Patient and Community Advisory Committee (PCAC) appointed patient, clinician, and community representatives to governance and advisory groups throughout the network, developed a process and criteria for patient- and clinician-centered review of research proposals, and evolved from a large, diverse group to a smaller yet still diverse, more actively engaged group with connections to the broader community. Key challenges faced by the PCAC have included determining the optimal size and composition of the group, understanding the complex structure of the network as a whole, coordinating with other network entities and functions, and integrating the patient and community voice into the research review process. Efforts to engage stakeholders in clinical data research networks should anticipate and develop solutions to address these challenges.

A Novel Patient Recruitment Strategy: Patient Selection Directly from the Community through Linkage to Clinical Data.

OBJECTIVE: This article presents and describes our methods in developing a novel strategy for recruitment of underrepresented, community-based participants, for pragmatic research studies leveraging routinely collected electronic health record (EHR) data. METHODS: We designed a new approach for recruiting eligible patients from the community, while also leveraging affiliated health systems to extract clinical data for community participants. The strategy involves methods for data collection, linkage, and tracking. In this workflow, potential participants are identified in the community and surveyed regarding eligibility. These data are then encrypted and deidentified via a hashing algorithm for linkage of the community participant back to a record at a clinical site. The linkage allows for eligibility verification and automated follow-up. Longitudinal data are collected by querying the EHR data and surveying the community participant directly. We discuss this strategy within the context of two national research projects, a clinical trial and an observational cohort study. CONCLUSION: The community-based recruitment strategy is a novel, low-touch, clinical trial enrollment method to engage a diverse set of participants. Direct outreach to community participants, while utilizing EHR data for clinical information and follow-up, allows for efficient recruitment and follow-up strategies. This new strategy for recruitment links data reported from community participants to clinical data in the EHR and allows for eligibility verification and automated follow-up. The workflow has the potential to improve recruitment efficiency and engage traditionally underrepresented individuals in research.