Modeling disease severity in multiple sclerosis using electronic health records by Xia Zongqi, Secor Elizabeth, Chibnik Lori B, Bove Riley M, Cheng Suchun, Chitnis Tanuja, Cagan Andrew, Gainer Vivian S, Chen Pei J, Liao Katherine P, Shaw Stanley Y, Ananthakrishnan Ashwin N, Szolovits Peter, Weiner Howard L, Karlson Elizabeth W, Murphy Shawn N, Savova Guergana K, Cai Tianxi, Churchill Susanne E, Plenge Robert M, Kohane Isaac S, De Jager Philip L in PloS one (2013).

[PMID: 24244385] PubMed


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 available in research settings.

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