Opportunities and challenges for biomarker discovery using electronic health record data.

Electronic health records (EHRs) have become increasingly relied upon as a source for biomedical research. Many different data types are available in EHR, including diagnoses, laboratory measurements, imaging and digital diagnostic data for identifying digital biomarkers, and clinical notes. There are challenges to consider when using EHR data, including potential bias in the availability of EHR data and the implications of missing data in EHR. Different modalities of longitudinal patient data can be used to investigate dynamic changes in health and inform biomarker discovery. There is a bright and opportunistic future of the EHR, including data capture, quality control, interoperability, governance, and utility. Electronic health records (EHRs) have become increasingly relied upon as a source for biomedical research. One important research application of EHRs is the identification of biomarkers associated with specific patient states, especially within complex conditions. However, using EHRs for biomarker identification can be challenging because the EHR was not designed with research as the primary focus. Despite this challenge, the EHR offers huge potential for biomarker discovery research to transform our understanding of disease etiology and treatment and generate biological insights informing precision medicine initiatives. This review paper provides an in-depth analysis of how EHR data is currently used for phenotyping and identifying molecular biomarkers, current challenges and limitations, and strategies we can take to mitigate challenges going forward. [ABSTRACT FROM AUTHOR]