Risk Adjustment is a statistical process that considers the underlying health status and health spending of an enrollee in an insurance plan when looking at their healthcare costs and outcomes, as defined by HealthCare.gov.¹
In 2020, the Medicare Payment Advisory Commission (MedPAC) estimated that the risk scores for beneficiaries in Medicare Advantage (MA) were about 9.5 per cent higher than what they would have been for a similar beneficiary in traditional Medicare, resulting in about $12 billion in excess payments to plans.²
In 2022, 28 million individuals were enrolled in MA plans, and $427 billion (or 55%) of total federal Medicare spending (net of premiums), according to The Henry J. Kaiser Family Foundation.
Today, the average Medicare beneficiary has access to thirty-nine MA plans, the largest number of options available in more than a decade.³
Why is accurate risk adjustment important for Value-Based care?
The transition from fee-for-service to a Value-Based Care (VBC) delivery model is not only changing how patients are cared for but also how providers and plans are measured and compensated for performance.
With an ever-growing number of patients covered under VBC programs, it’s crucial for MA organizations to ensure accurate risk adjustment workflow so that they can position themselves for financial success in risk-sharing arrangements.
In addition, VBC programs reward healthcare providers with incentive payments for the quality of care they give to people with Medicare. These programs are part of the Centers for Medicare & Medicaid Services (CMS)’s larger quality strategy to reform how health care is delivered and paid for. 4
Risk-based payment models in healthcare refer to the practice of accounting for the differences in the underlying risk (i.e., expected costs) of patient populations. It would be unfair to compare the costs incurred by a healthy member to that of a sick member without proper adjustment based on the member’s existing health status. However, risk adjustment is not just a payment model mechanism. Successful capture of risk, Hierarchical Condition Categories (HCC) codes, enables obtaining a complete and accurate picture of your patients’ acuity, which is critical to ensuring proper reimbursements, whilst effectively and appropriately managing the costs of your high-risk members and delivering high-quality care.
However, ensuring accurate risk adjustment is not an easy task. Some of the key hurdles providers and health plans cite are the lack of access to administrative and claims data, and the required risk adjustment workflow to effectively manage HCC code documentation and risk adjustment factor score (RAF) score derivation.
The US healthcare system produces billions of pages of medical records each year, and the data contained in these records are needed by multiple stakeholders, including providers and payers, for a multitude of purposes, such as risk adjustment data comparison, disease trend analysis, population health management, and revenue cycle management.
Risk adjustment being a process used to appropriately compensate health plans and providers under Value-Based care models, the key to successful risk adjustment in Value-Based care is to accurately identify patients’ full disease burden with substantiated data and documentation.
Contact us now to adopt natural language processing (NLP) powered solutions that can help you ensure accuracy in Risk Adjustment, including chart review, chart audits, and triggering of risk adjustment factor scores for your MA enrollees.