ArticleJournal of clinical and translational science2026
A method to enable clinical and translational research teams with custom real-world data from electronic health record systems.
Article in Journal of clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Custom transformations of real-world data (RWD) from electronic health record (EHR) systems are necessary to define study variables describing health and disease statuses differently among physicians in multiple specialties and basic scientists from a variety of disciplines . To increase RWD use, we hypothesized that a solution supporting three workflows - discovery, collection, and analysis - using existing rather than novel tools and requiring financial commitment from investigators would scale to meet the needs of clinical and translational research teams and ensure regulatory compliance at an academic medical center. Materials and methods: Weill Cornell Medicine (WCM) implemented custom research data repositories (RDRs) consisting of i2b2 for discovery, REDCap for collection, and Microsoft SQL Server for analysis. WCM subsidized the central information technology (IT) department to manage RDRs and required investigators to commit $50,000 for RDR startup and $7500 for annual maintenance. Results: From 2013 through 2025, WCM launched more than 17 custom RDRs for pediatrics, myeloproliferative neoplasms, obstetrics and gynecology, pulmonary and critical care, chronic kidney disease, and ophthalmology among other areas. Custom RDRs enabled academic output (e.g., publications, grants) as well as local quality improvement activities. Discussion: Custom RDRs facilitated delivery of fit-for-purpose data sets derived from EHR systems and other RWD sources. Over time, RDRs have evolved from an infrastructure product delivered by central IT to a data partnership between investigators and IT. Conclusion: Custom RDRs and data partnerships may help increase the use of RWD from EHR and other sources by clinical and translational research teams.
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