For a long time, healthcare insurance companies used to overlook people who were likely to be high-cost. As the landscape changed with new regulations, insurance providers have started offering new policies in the individual market without identifying any pre-existing conditions while enquiring about their health status. Even so, there have been many loopholes, and every administration has and continues to aim at minimizing these gaps. The One good answer thus far: risk adjustment.
What is risk adjustment?
Risk adjustment over the years has become a key mechanism used in healthcare to predict the costs incurred and ensure appropriate payments for Medicare Advantage plans, Part D plans, and health plans. Historically, it was only used in Medicaid and Medicare but lately has been an actuarial tool to ensure that health insurance plans have adequate funding and no financial hindrance in providing care to high-risk, high-need patients. Insurance companies and their plans are compared on the basis of quality and services they offer, providing a strong foundation to value-based purchasing.
Why is risk adjustment so important?
Risk adjustment advocates fair payments to health insurance plans by judging them on their efficiency and encouraging the provision of high-quality care. Beyond that, here’s why risk adjustment is important:
How is risk adjustment used in healthcare?
Healthcare risk adjustment methodologies can be used to account for changes in severity and case mixes for patients over time. Risk adjustment has been critical in reducing “cherry picking” among health plans. Dimensions of risk in care can broadly be categorized into three categories:
It’s important to ensure that by providing incentives to enroll high-cost individuals, there are necessary resources available to provide efficient and effective treatment to the relatively healthy population without overcompensation. The methodology used to risk-adjust premiums varies on the following:
On the macro level, unless the state combines its individual and small group markets, separate risk adjustment systems operate in each market. The Department of Health and Human Services (HHS), developed a risk adjustment methodology, where individual risk scores are assigned to each enrollee. The diagnoses are grouped into a Hierarchical Condition Category (HCC) and are assigned a numerical value which is averaged to calculate the plan’s average risk score. Payments and charges are calculated by comparing each plan’s average risk score to a baseline premium.
How ignoring risk adjustment can cost you?
In the current payment models, payments are risk adjusted, which makes it extremely important for every risk to be tracked and accounted for during reporting processes. Generally 1 risk point equates to $10,000 in Medicare contracts, therefore downcoding any patient’s data erroneously could mean thousands of dollar loss for the healthcare organization. It has been observed that around 15-25% of the risks are downcoded.
So for instance, if an organization has downcoded 15% of the risks erroneously equating to 1500 points, that would be roughly equal to savings opportunity worth $15Mn!
Data fuelling risk adjustment
Access to key data on enrollees’ health conditions is paramount for risk adjustment to work. Clinical data contains the most important details about patient health and risk that simply can’t be obtained from claims data alone. However, there are several obstacles:
With healthcare IT going leaps and bounds, there’s little doubt that healthcare organizations will leverage these insights and apply them to clinical data management in the future. Advanced analytics capabilities have the potential to not only impact the bottom line of a health plan, but to also improve population health management and help make organization informed decisions about premium pricing, membership expansion, bid rate calculation, etc.
The road ahead
Risk adjustment models and their correct implementation is central to achieving high-quality care. With the growing importance of value in care, the challenges in implementing a broad risk-adjustment framework should be countered to protect physicians from inadequate compensation and provide high-need patients with adequate care. Regardless of changes in administration and patient population, there is one common belief that stays true: complete, accurate, and value-based care. Only time will tell how successful any one risk adjustment model will be, but the fact that risk adjustment is fundamental to value-based care delivery is indispensable.
Visit Innovaccer at Booth #1F at Becker’s 8th Annual Meet to learn more about it and begin your journey to a data-driven healthcare.