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Carilion Clinic Pilot Emphasizes Predictive Analytics

February 21, 2014
by Rajiv Leventhal
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The Roanoke, Va.-based Carilion Clinic has identified 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 and Epic. The results were achieved through predictive modeling of data in Carilion Clinic’s electronic medical record (EMR), 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, officials say.

The pilot applied content analytics and predictive modeling to identify at-risk patients with an 85 percent accuracy rate, and the model identified an additional 3500 patients that would have been missed with traditional methods.

Heart failure currently afflicts more than five million U.S. adults, half of whom will not survive five years after diagnosis, according to the Centers for Disease Control and Prevention (CDC). Heart failure is one of the most common causes of hospitalization for people age 65 and older, and costs the nation $32 billion each year.

Early detection and prevention of heart failure has proven difficult prior to the introduction of advanced analytics.  Patients identified in the pilot as being at-risk for heart failure were expected to develop the disease within one year and are candidates for care management and early interventions. Predictors included:

  • Physiological data such as maximum systolic blood pressure
  • Prescription drug use of alpha blockers, beta blockers, beta agonists, and others
  • Previous diagnoses such as chronic obstructive pulmonary disease
  • Obesity
  • Lifestyle and environmental factors, such as occupation and marital status

“We’ve learned that predictive analytics insights from both structured and unstructured data is imperative to meet our goal of improving patient care at lower costs,” Steve Morgan, M.D., CMIO, Carilion Clinic, said in a statement. “We were very impressed with the accuracy and usability of IBM’s predictive modeling, which the IBM team developed and deployed in six weeks. These results and innovations are helping us move the needle on quality and the costs of care.”  

Read the source article at IBM - United States

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