Objective To compare three groupings of Electronic Health Record (EHR) billing codes for
their ability to represent clinically meaningful phenotypes and to replicate known genetic …

Electronic health records (EHRs) are a rich source of data for researchers, but extracting
meaningful information out of this highly complex data source is challenging. Phecodes …

Clinical data in electronic medical records (EMRs) are a potential source of longitudinal
clinical data for research. The Electronic Medical Records and Genomics Network …

Electronic health records contain patient‐level data collected during and for clinical care.
Data within the electronic health record include diagnostic billing codes, procedure codes …

Background Genetic studies require precise phenotype definitions, but electronic medical
record (EMR) phenotype data are recorded inconsistently and in a variety of formats …

Abstract The Electronic Medical Records and Genomics Network is a National Human
Genome Research Institute–funded consortium engaged in the development of methods …

Motivation: Emergence of genetic data coupled to longitudinal electronic medical records
(EMRs) offers the possibility of phenome-wide association scans (PheWAS) for disease …

Candidate gene and genome-wide association studies (GWAS) have identified genetic
variants that modulate risk for human disease; many of these associations require further …

Most phenome-wide association studies (PheWASs) to date have used a small to moderate
number of SNPs for association with phenotypic data. We performed a large-scale single …

Large-scale DNA databanks linked to electronic medical record (EMR) systems have been
proposed as an approach for rapidly generating large, diverse cohorts for discovery and …