by L. Eleanor Herriman, MD, MBA
Medicare’s rapid move to value-based pay has pushed population health management to the top of the priority list for health systems and ACOs.
CKD, a common, costly comorbidity in diabetes and heart failure, is currently managed in a suboptimal manner, as providers lack tools to accurately predict which patients will progress to renal failure requiring dialysis or transplant, and the CKD patient population is heterogeneous. A new, automated, globally validated solution for predicting the risk of progression in CKD patients shows promise for improving patient outcomes and organization profitability.
Medicare’s rapid move to value-based pay necessitates the use of population health management (PHM) in Accountable Care Organizations (ACOs) and health systems. Among the top diseases presenting the biggest challenges in PHM are diabetes and congestive heart failure (CHF), given their high prevalence, expensive interventions, and associated complications.
While the payer mandate is clear — get costs under control and improve patient outcomes — the way forward is murkier. In the quagmires of diabetes and CHF population health management, comorbidities can complicate resource focus in order to pull free of the costly status quo.