Georgia covers 1,733,146 people through it’s Medicaid and CHIP programs.
Georgia instituted a Disease Management program for it’s 100,000 aged, blind and disabled population. The program actually saved the state money according to one study. Something innovative that other states are looking at to save money for this population.
The Georgia Department of Community Health contracts with 2 private-sector DM vendors to coordinate and deliver population health outcomes management services (previously known as DM).6 These programs serve the aged, blind, and disabled populations of Medicaid (approximately 100,000 people) in different regions of the state. This study focuses on the program covering Atlanta and North Georgia. Although 7 diseases are nominally targeted for management (ie, asthma, chronic obstructive pulmonary disease, congestive heart failure, coronary artery disease, diabetes, hemophilia, and schizophrenia), the program outcomes and financial incentives are tied to overall cost and quality outcomes for all eligible enrollees, regardless of disease or comorbidity.
The state paid the North Georgia vendor a $13.94 PMPM capitation payment. Medicaid members enrolled in the program received a broad array of care coordination services, a 24/7 nurse advice line, educational services, and member/provider analysis using utilization and claims data. The core of the intervention team is the registered nurse (RN) “health coach,” but the team also includes social workers, pharmacists, mental health professionals, and provider engagement staff.
This PHM program targeting the non-Medicare disabled segment of the Georgia Medicaid population demonstrated actual expenditures substantially lower than any projections based on relevant medical inflation rates. We found a parallel decrease in hospital admissions and hospital bed-days weighted for member months, with a slight absolute reduction in length of stay, consistent with an effect related to care coordination and chronic disease care management (CDCM). Unit costs per inpatient day, per admission, and per prescription increased 5%–6%, suggesting that reductions in provider payment rates do not explain the reduction in expenditure growth. Our mixed-effects growth models also demonstrated that the rate of increase in Medicaid expenditures declined as time increased, even though the population’s risk profile measured by CDPS scores actually increased.