IBM Predictive Analytics to Detect Patients at Risk for Heart Failure

More great work coming out of our analytics group, working in partnership with leading healthcare providers and IBM Business Partners.

ARMONK, N.Y. – 19 Feb 2014: IBM (NYSE: IBM) today announced that Virginia health systemCarilion Clinic has indentified 8,500 patients at risk for developing heart failure in a pilot project that could lead to early intervention and better care for these patients. 
The pilot was completed in collaboration with IBM, Epic and Carilion Clinic. The results were achieved through predictive modeling of data in Carilion Clinic’s electronic medical record (EMRs), including “unstructured” data such as clinicians’ notes and discharge documents that are not often analyzed. Using IBM’s natural language processing technology to analyze and understand these notes in the context of the EMR, the inclusion of unstructured data provides a more complete and accurate understanding of each patient. The pilot applied content analytics and predictive modeling to identify at-risk patients with an 85 percent accuracy rate. The model identified an additional 3500 patients that would have been missed with traditional methods. Each of these patients might benefit from targeted preventive care.  

IBM’s natural language processing technology – also used in the IBM Watson cognitive system – can understand information posed in natural language and uncover insights from vast amounts of data. Coupled with advanced predictive modeling, the pilot at Carilion Clinic using IBM Advanced Care Insights marks another example of IBM’s leadership in advancing predictive care and prevention.  IBM Advanced Care Insights combines predictive modeling with healthcare-specific content analysis.  

Press Release:IBM Predictive Analytics to Detect Patients at Risk for Heart Failure

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: