Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study

@article{Kho2012UseOD,
  title={Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study},
  author={Abel N. Kho and M. Geoffrey Hayes and Laura Rasmussen-Torvik and Jennifer A. Pacheco and William K. Thompson and Loren L. Armstrong and Joshua C. Denny and Peggy L. Peissig and Aaron W. Miller and Wei-Qi Wei and Suzette J. Bielinski and Christopher G. Chute and Cynthia L. Leibson and Gail P. Jarvik and David R. Crosslin and Christopher S. Carlson and Katherine M. Newton and Wendy A. Wolf and Rex L. Chisholm and William L. Lowe},
  journal={Journal of the American Medical Informatics Association : JAMIA},
  year={2012},
  volume={19 2},
  pages={212-8}
}
OBJECTIVE Genome-wide association studies (GWAS) require high specificity and large numbers of subjects to identify genotype-phenotype correlations accurately. The aim of this study was to identify type 2 diabetes (T2D) cases and controls for a GWAS, using data captured through routine clinical care across five institutions using different electronic medical record (EMR) systems. MATERIALS AND METHODS An algorithm was developed to identify T2D cases and controls based on a combination of… CONTINUE READING
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