Electronic Health Record: Real-world Data and Real-world Challenges by Wenke Hwang, PhD, on Mar. 18, 1-2 p.m.

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Electronic health record (EHR) is an important source of real-world data for clinical and translational science investigators. EHR collected during the course of patient care can provide researchers a great deal of insight into the actual patients, as well as the processes and outcomes related to their care.  Various EHR-based common data models (CDMs) featuring data standardization and harmonization have been adopted by many medical institutions across the country and around the world. These CDMs have further accelerated multi-site research collaboration covering a wide range of patient population, geographic locations, and clinical practices. The CDM data infrastructure can help facilitate patient recruitment, assess patient outcomes, and make studying rare diseases more feasible. However, using EHRs, particularly for multi-site research, remains a challenge as there are many technical and methodological nuances. If left unattended, the research can produce inaccurate or biased results. The Penn State CTSI Informatics Core currently supports four different CDMs:  PCORnet, TriNetX, OMOP, and ACT.  This presentation aims to introduce our PCORnet data resource, to examine real-world examples, and to help navigate the complexity in the world of EHR research.