The Virginia health system has completed the pilot project in collaboration with IBM and Epic. 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.
Carilion Clinic has utilized 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.
Content analytics and predictive modeling has been applied in the pilot project for identifying at-risk patients with an 85% accuracy rate. This model identified an additional 3,500 patients that would have been missed with traditional methods.
According to IBM, its natural language processing technology can understand information posed in natural language and uncover insights from vast amounts of data.
Coupled with advanced predictive modeling, the pilot project 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.
IBM global healthcare vice president Sean Hogan noted many predictive factors are included in structured data within today’s EMR systems, but a lot of it is hidden in doctors’ notes, discharge papers, and other sources of unstructured data.
"By tapping into the unstructured data, our clients have more complete and accurate information that allows them to make targeted interventions when appropriate that can help prevent more severe and costly medical complications," Hogan added.
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 analyzed by IBM’s Advanced Care Insights included 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, and lifestyle and environmental factors, such as occupation and marital status.
IBM has also announced that its content analysis software now allows doctors using Epic’s EMR software to accurately incorporate their notes into patient records to extract insights in real-time.
