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Analytics identifying Patients at Risk!

A pilot project using predictive analytics and applied natural language processing identified 8,500 patients of Carilion Clinic who are at risk of congestive heart failure. Discrete data points, such as weight and medications, can be found in structured EMR (electronic medical record) fields. Unstructured data includes physicians' notes that are typed or read into a patient's EMR or discharge papers.  The natural language processing technology searched for key words or phrases within the unstructured data as well as in structured data. In all, 20 million documents were analyzed. Because approximately half of all patients who develop heart failure die within five years, according to the “Centre for Disease Control and Prevention”, early identification is essential. About 3,500 of the 8,500 patients Carilion identified as at-risk would not have been found if the project had analyzed only the structured data, according to Steve Morgan, MD and chief medical information officer at Carilion Clinic.

To know more, please visit famous author & reporter Maggie O'Neill’s article by clicking on the following link:

http://www.baselinemag.com/analytics-big-data/analytics-ids-patients-at-risk-for-heart-failure.html/

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