EMR (electronic Medical Record) adoption, big data and other trends are helping a lot in the generation of data in the healthcare industry. But data is not what drives the healthcare industry- managing this data does. In healthcare, data analytics is done in use cases. Multiple use cases are created according to the need like one while patient got admitted in some department, a use case gets created. To provide best services to patients timely, immediate access to patient’s data without the barrier of time or location. Read the full article here: http://www.computerworld.com/article/3038315/data-analytics/accelerate-time-to-value-with-healthcare-discovery-analytics.html

Why we people do not get proper consumer service is the biggest question now. Apart from fast food joints the worst consumer treatment is acquired from the people who work for doctors, when ironically we should have got the best treatment there. In cases of emergencies where e require immediate attention we are told to fill forms moreover calls irritate you on confirming whether you would be able to clear the bills even if the insurance doesn’t. Apart from banks, medical customer service frustrates people with long calls and often hang them up. The only difference is that you speak with a live person instead. Then there are these unfriendly tools on the websites which assures you about the non occurrence of the problem again but if we had spend time searching every inch of the website this wouldn’t have happened in the first place. read more at:http://managementhelp.org/blogs/training-and-development/2012/03/07/poorest-customer-service-in-the-land-where-it-really-counts/ 

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/