Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records

@inproceedings{Xia2013ModelingDS,
  title={Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records},
  author={Zongqi Xia and Elizabeth Secor and Lori Beth Chibnik and Riley M Bove and Suchun Cheng and Tanuja Chitnis and Andrew Cagan and Vivian S. Gainer and Pei J. Chen and Katherine P. Liao and Stanley Y. Shaw and Ashwin N. Ananthakrishnan and Peter Szolovits and Howard L. Weiner and Elizabeth W. Karlson and Shawn N. Murphy and Guergana K. Savova and Tianxi Cai and Susanne E. Churchill and Robert M. Plenge and Isaac S. Kohane and Philip L De Jager},
  booktitle={PloS one},
  year={2013}
}
OBJECTIVE To optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only… CONTINUE READING

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