The Electronic Medical Records and Genomics (eMERGE) Network is a consortium funded by the National Human Genome Research Institute (NHGRI) that has developed tools and practices for the use of electronic medical records (EMR) and genomic information for patient health. As a collaborative effort between 9 different centers, eMERGE aims to use phenotypic information to discover the causal factors of genetic disorders, pharmacogenomic studies, predisposition of individuals to certain conditions such as childhood obesity, autism and the integration of the results of genetic studies into EMRs. [1].Any study of this nature requires that the quality of the data found in both the EMR and the genetic repository meet a certain level of uniformity and quality. This can be a challenge for most EMR systems. There is inherent variation in EMRs due to different implementation styles of EMR systems, differences in data recording styles of different physicians, and variations due to disease demands on patients. In addition to this, there is a large amount of medical information captured in the form of free notes. Processing this information requires natural language processing which is still in the field of research. The field is not mature enough to ensure uniform and good quality information to facilitate clinical decision support systems [2]. To provide good phenotypic information for genetic studies, the integrated EHR must have information about mutations present in an individual as well as family history, although the family member may not have the clinical syndrome [2] . Such details, however, may not be available in most EHR systems today. The size of genetic data is... middle of article...... aucett, R. Li, TA Manolio, et al., "The Electronic Medical Records and Genomics (eMERGE) Network: Past, present, and future”, Genet Med, vol. 15, pp. 761-71, October 2013.[2] K. Marsolo and SA Spooner, “Clinical genomics in the world of electronic health records”, Genet Med, vol. 15, pp. 786-91, October 2013.[3] AG Ury, “Storage and interpretation of genomic information in widely deployed electronic health records systems,” Genet Med, vol. 10//print 2013.[4] JL Kannry and MS Williams, “Integrating genomics into the electronic health record: mapping the terra incognita,” Genet Med, vol. printed 2013.[5] JF Peterson, E. Bowton, JR Field, M. Beller, J. Mitchell, J. Schildcrout, et al., “Design and implementation of electronic health records for pharmacogenomics: a local perspective », Genet Med, vol. 15, pp. 833-41, October 2013.