Medicare provides healthcare coverage for millions of Americans ages 65 and over, as well as younger people with disabilities. This federal program is administered by the Centers for Medicare & Medicaid Services (CMS). A critical but less known component that ensures Medicare’s success is risk adjustment. Risk adjustment is the process of modifying payments to account for the health status and demographics of each health plan’s enrolled population. This crucial statistical technique enables fair competition among plans, encourages enrollment of sicker individuals, and allows payments to align more closely with expected costs. This article explores the role and evolution of risk adjustment in Medicare.
What is Risk Adjustment?
Risk adjustment is a statistical process that helps account for the health status and demographics of a patient population. The goal is to reduce incentives for health plans to avoid sicker patients and enroll only healthier individuals. With risk adjustment, payments to plans are increased for members expected to have higher costs and decreased for healthier members expected to have lower costs. This levels the playing field.
CMS calculates risk scores for each Medicare member using data on diagnoses, medications, and more. These risk scores are relative – an average beneficiary has a risk score of 1.0. Higher scores indicate poorer health and higher expected costs. CMS then adjusts capitation payments to plans according to the overall risk score of a plan’s membership.
Why is Risk Adjustment Necessary?
Without risk adjustment, Medicare plans get flat capitation payments per member that don’t account for health status. This means plans with sicker populations are underpaid, while plans with healthier people are overpaid. Risk adjustment fixes this imbalance.
Plans have incentives to avoid less healthy applicants and “cherry pick” only healthy people. Risk adjustment removes this motivation and allows fairer competition among plans based on efficiency and quality. It aims to pay plans accurately for the true risk level of populations they serve.
The Evolution of Medicare Risk Adjustment
In the early 2000s, CMS implemented the Hierarchical Condition Category (HCC) risk adjustment model. This uses diagnosis codes from claims to classify people into disease groups and score their expected costs.
The HCC model has improved over time but still has limitations. It relies on providers fully documenting and coding all diagnoses – which doesn’t always happen. And some factors like frailty and functional status aren’t reflected well.
This is why CMS has been exploring use of supplemental data sources for risk adjustment. These include prescriptions, lab results, and socioeconomic factors. More accurate risk scores require a multifaceted risk adjustment tool like an MRA calculator.
Implementing Enhanced Risk Adjustment
Moving to an enhanced risk adjustment methodology is complex. CMS must balance improved accuracy with minimizing administrative burdens on providers and health plans.
Some critical steps in the process include:
- Assessing data sources that improve risk score accuracy without overburdening stakeholders
- Updating regulations on what data can be used for risk adjustment
- Issuing guidance to health plans well in advance of any changes
- Phasing in any new risk adjustment model over multiple years
- Extensive testing and evaluation of model performance
The additional time and effort to implement enhanced risk adjustment pays off through more equitable Medicare payments. With improved risk adjustment, plans and providers succeed based on the value and quality of care delivered – not by avoiding sicker patients. And Medicare beneficiaries benefit from a more stable and higher quality healthcare system.
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