A new report from the Healthcare Intelligence Network presents a range of risk stratification practices to identify and manage super utilizers, improve health outcomes and reduce healthcare spend.
To fully thrive in a value-based system, healthcare organizations must identify high-risk, high-cost patients and members for targeted population health interventions. Recently, CMS has funded initiatives targeting “super-utilizers”—beneficiaries with complex, unaddressed health issues and a history of frequent encounters with healthcare providers.
Stratifying High-Risk, High-Cost Patients: Benchmarks, Predictive Algorithms and Data Analytics presents a range of risk stratification tools and analytics to determine candidates for health coaching, case management, home visits, remote monitoring and other initiatives designed to engage individuals with chronic illness, improve health outcomes and reduce healthcare spend.
Each program discussion is supplemented by market data on risk stratification approaches for that care coordination intervention.
The 30-page report compiles risk stratification profiles for a range of programs from such industry leaders as Humana, Adventist Health, Taconic Professional Resources, Monarch Healthcare (a Pioneer ACO), Stanford Coordinated Care, Ochsner Health System and others.
Accompanying each risk stratification profile are HIN market metrics from 2013 and 2014 on the top methods for identifying candidates for these interventions, based on responses from hundreds of healthcare organizations.
"Health risk stratification is the cornerstone of population health management and a crucial prerequisite to success in a system increasingly partial to value-based reimbursement,” Melanie Matthews, HIN executive vice president and chief operating officer. “Stratifying high-risk, high-cost patients can improve all-important quality and improvement metrics like avoidable emergency room visits and 30-day readmissions among Medicare beneficiaries."
Healthcare Intelligence Network, US
