Our risk adjustment engine, driven by the algorithms in the Johns Hopkins ACG® (Adjusted Clinical Group) model and other industry standard or customer-specific risk models, helps predict an individual’s healthcare utilization and cost over time using information such as medical claims, electronic health records and other key patient demographics. We deliver a quantitative picture of potential health risks and cost drivers within a patient population, and can combine risk criteria with other domains, such as demographics, specific conditions or past visit history to narrow down the population of interest even further.
Risk data can be used to alert you to various patient populations, such as those considered to be at risk for high utilization, or a high probability of a specific critical event. By identifying and stratifying patients within selected risk profiles, providers can focus their care management resources on the highest-risk patients to help increase quality and reduce cost of care.
