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 using electronic medical records (EMR ) ) and genomic information for patient healthcare. As a collaborative effort between 9 different centers, eMERGE is aimed at using phenotypic information to discover causal factors of genetic disorders, pharmacogenomics studies, predisposition of individuals to certain conditions such as childhood obesity, autism, and the integration of results of genetic studies in EMRs [1].Any study of this nature requires that the quality of data present in both the EMR and the genetic archive meets 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, the difference in data recording styles of different physicians, and variations due to disease requirements for patients. Apart from these, there is a large amount of medical information captured as free notes. Processing such information requires natural language processing which is still in the realm of research. The area is not mature enough to ensure uniform, good quality information to facilitate clinical decision support systems [2]. To provide good phenotypic information for genetic studies and integrated electronic health records it is necessary to have information regarding the mutations present in an individual and also the family history, although the family member may not have the clinical syndrome [2]. However, these details may not be available in most EHR systems today. The size of the genetic data is... half of the paper... Aucett, R. Li, TA Manolio, et al., "The Electronic Medical Records and Genomics (eMERGE) Network: past, present", and the future," Genet Med, vol. 15, pp. 761-71, October 2013. [2] K. Marsolo and S. A. Spooner, "Clinical genomics in the world of electronic health records", Genet Med, vol , October 2013.[3] AG Ury, "Storage and interpretation of genomic information in widely used electronic health record systems", Genet Med, vol Kannry and MS Williams, “Integrating genomics into the electronic health record: mapping the terra incognita,” Genet Med, vol. 757-760, 10//print 2013.[5] 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 2013.