This pilot project proposes to implement and evaluate a scalable digital patient engagement strategy intended to recruit participants to the All of Us program (AoU) and harness the vast amount of electronic health record (EHR) information available at Washington University and BJC Healthcare (WU-BJC) for precision-medicine research. To accelerate complex genetic discovery and translation, we believe it is critical to harness existing data quickly and efficiently and to engage research participants via digital mechanisms. Our project provides a prototype digital precision medicine research paradigm to increase public interest in ?citizen science? and participation in AoU. By integrating digital recruitment mechanisms and EHR-based phenotyping, we can rapidly engage, recruit, and phenotype new AoU participants in a cost-effective and timely manner. Our approach is generalizable, adaptable, and ultimately allows for the linkage of genomic data with EHR- derived phenotypes to accelerate biomedical research. We will test this approach in the WU-BJC system, Missouri's largest patient care provider (> 2 million individuals annually). We will recruit active patients for AoU, support and enable their consent, and extract and submit their EHR-derived phenotyping data to AoU. WU-BJC uses a common, cloud-hosted EHR (Epic), with ensuing clinical data available for research purposes via extraction and harmonization processes that populate an OMOP CDM 5.2 data repository (Research Data Core). By recruiting patients via our shared EHR (specifically, via the integrated patient portal, MyChart), we will quickly and efficiently create a cohort with associated and well populated clinical data sets, all with minimal costs and participant burden. This forward-thinking ?direct-to-participant? model can also be implemented to add new online assessments and rapid data updates compared to ?traditional? in-person or pre-scheduled approaches. Based on our preliminary studies, we anticipate a majority of eligible individuals will agree to participate in our study, to future use of their data, and to future contact. This approach will enable researchers to effectively target emerging health trends and research needs quickly and efficiently. We will: (1) establish a digital, community-focused patient engagement, recruitment, and consent strategy, targeting a combination of under-represented minority, rural, and medically underserved populations in the areas served by WU-BJC; (2) implement a phenotyping pipeline to extract, harmonize, and submit clinical data to AoU; and (3) evaluate and optimize strategies to recruit a representative sample of participants. We will implement a digital, direct-to-participant engagement, recruitment, and consent strategy for AoU participation. We will demonstrate the feasibility of rapidly and inexpensively creating computable participant phenotypes, extracted from our EHR platforms. We will evaluate and demonstrate the value of this approach to identify opportunities for optimization and further implementation in analogous settings. Our protocols and tools will be made available, adhering to FAIR (Findability, Accessibility, Interoperability, & Reusability) principles.
We will implement a digital, direct-to-participant engagement, recruitment, and consent strategy, which will serve to engage such participants in the All of Us initiative. We will demonstrate the feasibility of rapidly and inexpensively creating computable phenotypes for AoU participants, extracted from our EHR platforms and ?downstream? research data warehousing system, and evaluate and demonstrate the value of this approach in order to identify opportunities for optimization and further implementation. Our protocols, tools, and lessons learned will be made available for dissemination to the All of Us community as well as the broader NIH clinical and translational research community, adhering to FAIR (Findability, Accessibility, Interoperability, and Reusability) principles.
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