Imagine a scenario where two individuals apply for enrollment in a health plan. One individual is a 75-year-old diabetic with chronic obstructive pulmonary disease. The other is a young, healthy individual. Actuary tables would clearly show that the second individual is substantially less likely to incur medical costs. Under a value-based care model where payments are determined by patient outcomes, guess which individual the health plan would prefer to enroll?
This scenario demonstrates what the industry refers to as adverse selection, where there is an incentive for health plans to enroll healthy members while avoiding chronically ill members. The scenario is one of the many reasons why risk adjustment reimbursement methodologies were created – to remove the perverse incentives that could potentially steer health plans away from covering patients with chronic conditions.
Although Medicare and Medicaid programs have employed some type of risk adjustment in their reimbursement models for upwards of 15 years, the introduction of these practices in the commercial payer market is relatively new.
To excel in this changing marketplace, health plans need to create risk adjustment programs that accurately identify risk factors to earn maximum reimbursement, which helps offset the costs of caring for chronically ill patients. However, health plans need to create different risk adjustment strategies depending upon the market that they participate in.
Commercial Payers and the ACA
There are some unique considerations for health plans that participate in health insurance exchanges operating under the Affordable Care Act (ACA). The risk adjustment program works by redistributing funds (known as transfer payments) from plans with lower-risk enrollees to plans with higher-risk enrollees. The goals of the program are to spread the financial risk across the market and encourage insurers to compete based on the value and efficiency of their plans, rather than by attracting healthier enrollees.
Since enrollees in exchange plans are relatively new, carriers do not have a complete picture of the health status of their members based on a history of claims data. As such, plans must implement strategies that encourage their members – many of whom are young and relatively healthy – to schedule primary care visits so that accurate risk profiles can be constructed. Further, plans must analyze patients’ clinical documentation rather than rely solely on claims, which may be incomplete. With a large influx of new patients with unknown health status, plans should utilize technology to automate processes in order to expand the scope of their risk adjustment operations.
Unlike health plans participating in health exchanges, Medicare Advantage (MA) health plans receive risk-adjusted reimbursements directly from the Centers for Medicare & Medicaid Services (CMS); there is no risk pool or transfer payments. Additionally, MA plans use a prospective approach to determine risk, meaning that the prior year’s diagnoses are used to predict current year risks.
Compared with other markets, the financial impact of risk adjustment in the MA market is significantly greater given that risk conditions are much more prevalent in elderly patients. Therefore, it is important for MA plans to cast as wide a net as possible in their clinical document collection efforts – and, over the long term, invest in programs and systems that strengthen relationships with the provider network and facilitate exchange of clinical data. Many patients are also homebound, which may necessitate a targeted home assessment campaign. This is another process that can benefit from advanced analytics to guide the efficient deployment of resources.
Further, the importance of coding accuracy cannot be understated given the considerable amount of revenue at stake. Accordingly, MA plans may be subject to greater scrutiny from regulators. The MA market, more than any other, requires solutions that can efficiently ingest large volumes of clinical data, streamline accurate coding, and mitigate compliance risks.
Few markets have experienced the dynamic population changes that have taken place within the Medicaid markets. Medicaid plans across the country have been flooded with millions of new members due to Medicaid expansion under the ACA.
One of the challenges of the Medicaid population is that a sizable percentage of members migrate between plans due to income variances. For example, a member who is covered by an employer-sponsored plan and loses her job may switch to Medicaid coverage for a time, then migrate back to health exchange coverage when her income or employment changes. For most states, payments are based upon how a plan’s risk score ranks against other Medicaid plans in the same state or sub-state region rather than the plan’s risk score itself.
Additionally, the Medicaid population is much more heterogeneous than the Medicare population, which creates more risks that need to be identified. This factor, combined with the challenges mentioned above, create the need for a more robust risk adjustment strategy that can:
- Quickly and efficiently create risk profiles for individuals during dynamic membership changes
- Take into account state-specific nuances, such as risk models used and data requirements
- Provide insights to structure programs and premiums to attract desired risk profiles
- Identify high priority segments of membership where additional documentation would improve risk-adjusted reimbursements
Expanding Risk Adjustment Strategies
Effective risk adjustment is essential to the success of any risk-based payment model. Risk adjustment helps to ensure that risk-bearing organizations are appropriately compensated for the risk of their enrollees and will encourage innovative plan offerings. The organizations that best understand the risks within their membership and the populations they serve will be able to tailor their programs and premiums to optimize profitability and the care that their members receive.