The development of very large datasets to identify in a robust and reproducible fashion specific patient subsets is a key starting point for development of evidence to implement an approach that treats some patients differently from average.1 EHRs are one such very large dataset: the EHR includes data generated during routine clinical care and can be used in a stand-alone fashion or be coupled to other data types for discovery.1 Examples of other data types include information on the sociocultural determinants of health,2 systematically acquired patient-reported or mobile device-acquired data, and biobank-derived information including genotype or sequence data as well as other “omic” (transcriptomic, proteomic, metabolomic, etc) data. This review will focus on ways in which coupling EHRs to genomic datasets can be enabling for discovery of genotype-phenotype associations and how these associations can then be implemented in EHRs to start to individualize patient care.
