Methods to identify gene-disease associations primarily rely on clinical trials or observational cohorts and, more recently, Electronic Medical Record-linked DNA Biobanks.  At Vanderbilt, we have used an EMR-linked DNA biobank called BioVU to derive case and controls populations using data within the EMR to define clinical phenotypes.  Genetic data for these EMR-linked association studies are redeposited into BioVU for future EMR-linked studies.  This has opened the possibility of "reverse GWAS" or "Phenome-wide association studies" (PheWAS). 

MEDI (MEDication Indication) is an ensemble medication indication resource for primary and secondary uses of electronic medical record (EMR) data.  MEDI was created based on multiple commonly used medication resources (RxNorm, MedlinePlus, SIDER 2, and Wikipedia ) and by leveraging both ontology and natural language processing (NLP) techniques.   

Nature Biotech featured PheWAS paper as one of the top computational biology innovations in 2010.http://www.nature.com/nbt/journal/v29/n1/full/nbt0111-46.html

The Nashville Scene recently did an article about Innovators in middle Tennessee.  They featured PheWAS as one of 11 "groundbreaking" innovations.  See section "Model Behavior" in the Nashville Scene article. 

We replicated known genetic associations for five diseases. We genotyped the first 10,000 samples accrued into BioVU (the Vanderbilt EMR-associated DNA biobank) for twenty-one loci were associated with five common diseases (reported odds ratios 1.14-2.36) in at least two previous studies. We developed automated phenotype identification algorithms that used NLP techniques (to identify key findings, medication names, and family history), billing code queries, and structured data elements (such as laboratory results) to identify cases (n=70-698) and controls (n=808-3818).

KnowledgeMap Learning Portfolio collects trainee-created documents reflecting their direct patient experiences via the Electronic Medical Records (EMR), providing a rich log of a trainee's clinical exposure without requiring additional manual effort. The interface between the EMR system and Portfolio provides historical data from which trainees can continue to build their knowledge base, tagged to core learning objectives, and supplies the mentor the opportunity to review and evaluate trainee performance.

A paper on a terminology of section headers received the 2008 Homer Warner Award: Denny JC, Miller RA, Johnson KB, Spickard A 3rd. Development and evaluation of a clinical note section header terminology. AMIA Annu Symp Proc. 2008 Nov 6:156-60.