IBM, Geisinger Health System and Sutter Health have partnered to build analytics tools for detecting heart failure.
The health systems hope to arrive at a deeper understanding of how to use the data contained within EHRs and advanced analytics to help detect heart failure earlier.
Another goal is to look for ways to help other hospitals and health systems integrate big data strategies into primary care, helping doctors and caregivers use evidence-based insights to better partner with patients and identify more tailored treatment options and holistic approaches to disease management that are personalized for each individual.
With EHR data offering an expansive view of a patient's health history – including demographics, medical history, medication and allergies, laboratory test results, and more – it's hoped that more sophisticated analysis of this data could help doctors identify patient's risk of heart failure and reveal signals and patterns that are indicative of such an outcome
Once patients are identified as high-risk for heart failure, physicians can better monitor their status, help motivate a patient to make potentially life-saving lifestyle changes and test clinical interventions to potentially slow or possibly reverse heart failure progression.