As healthcare organizations fight the COVID-19 pandemic, their ability to understand patient data is more important now than ever before. Accurate risk assessments can save millions of dollars via reimbursements, but the problem is – staying compliant with CMS can be difficult.
The Center for Medicare and Medicaid Services (CMS) uses a Hierarchical Condition Category (HCC) risk adjustment model to assign risk scores to individual beneficiaries based on health conditions, demographic factors, and inpatient status. This model is used as a way to adjust capitated payments for Medicare Advantage Plan beneficiaries – a large and growing segment of the US population (34% of all Medicare beneficiaries or 22 million people in 2019*). Payment rates to providers vary based on a patient’s predicted level of risk (called a risk adjustment factor or RAF).
CMS requires providers to identify all conditions that may fall within an HCC category within 1 year to accurately predict risk scores and by association cost of care. These RAF calculations and risk assessments are critical and require accurate and actionable data analytics to ensure compliance and quality patient outcomes while minimizing the cost of care.
Join Tableau and our partner CitiusTech for a discussion on how analytics and visualizations can help providers:
- Accurately measure and monitor end-end CMS HCC compliance
- Identify patient population segments requiring immediate attention and care
- Leverage analytics to identify areas for increased reimbursement revenue / minimize financial penalties
Source: - Kaiser Family Foundation