Big Data Analytics Improves Chronic Disease Risk Stratification

Population health management – and specifically chronic disease management – depend on the ability of providers to identify patients at high risk of developing costly and harmful conditions such as diabetes, heart failure, and chronic kidney disease (CKD). While basic risk stratification tasks can be performed though non-electronic means, such as patient questionnaires, manual chart reviews, and in-person assessments, the advent of big data analytics has drastically changed the way providers can develop risk scores, monitor patients, and even divide cohorts into extremely narrow subgroups to ensure precision care. RELATED ARTICLES A new study published in the American Journal of Managed Care details how researchers at Carnegie Mellon University used machine learning algorithms to accurately predict future clinical pathways and best-practice treatment decisions for patients with chronic kidney disease.  Using multidimensional…


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