One of the biggest challenges for payers in the Affordable Care Act (ACA) individual market is managing a population’s risk scores relative to the population’s underlying morbidity. In the individual ACA market, payers are limited in the population risk factors for which they are allowed to price. At the state level, each ACA market has a risk adjustment program, where payers that have enrolled high risk members (but have been unable to sufficiently price for such members) get financial payments funded by payers that have enrolled low risk members (relative to the premiums they charged). This risk transfer can be a material component of the payer’s financial results each year (as an example, risk transfers were projected to be as much as +/-30% premiums for individual payers in the 2024 Florida individual market rate filings) and is not fully known until nearly mid-way through the year following the performance year. This mechanism, while providing some benefit to market stability, can also create challenges for health plans, particularly smaller ones.

Understanding the dynamics of risk adjustment in ACA markets

The risk adjustment program within each state is a “zero-sum” game. That is, the risk transfers paid to health plans that enrolled “higher risk than can be priced for” members can only equal the amounts paid from health plans that enrolled “lower risk than can be priced for” members. There is an incentive on both sides of this equation to ensure that risk scores, then, are appropriate for the morbidity of the population enrolled, and that each health plan is maintaining this level of appropriateness at the same rate as the overall market.

One challenge in the individual market to understanding a population’s true morbidity burden is the level of enrollment churn. This market is particularly price sensitive, and changing carriers is common. In addition, members may be churning in/out of Medicaid due to the end of the public health emergency, or from plans that have exited or entered the market. A member’s new health plan may have no claims history on them, which poses a challenge to ensure that underlying morbidity will be appropriately captured through a concurrent risk score model.

Three ways to optimize new member morbidity

In our experience, a best practices approach to having a robust perspective on new member morbidity is represented within a three-pronged framework of data mining, provider outreach, and patient monitoring.

1. Leveraging data mining to supplement medical claims with real-time data

• Prescription drug data: Analyzing the unique combination of drugs a patient takes often provides insight into the presence of chronic conditions driving risk models.
• Lab data: More complex than traditional claims data, but contains more objective measures of patient health, such as blood markers for specific conditions, and can be highly predictive of precursors for risk-adjustable conditions.
• Electronic Medical Records (EMRs): EMRs represent the most real-time information from a patient visit, with physician notes that may provide critical insights into diagnoses and information related to clinical disease history.
• Universal Member Identifiers: Many entities have different systems for different business segments. Establishing universal members identifiers across systems and lines of business allows for the tracking of more complex clinical history (for instance, membership churn between Managed Medicaid and ACA).

2. Empowering providers with patient history insights through outreach

• Providers need to be given the resources to access all critical information related to their patients’ risk adjustable history.
• Patient portals can be deployed to request clinical history from the patient and/or their previous providers.
• Provider-facing profiles can be deployed to include “clues” such as historically coded conditions, previously prescribed medications, and tracking of annual wellness visits.

3. Enhancing primary care through patient monitoring and outreach

• Providers and health plans should coordinate the monitoring of patient panels and upcoming visits to ensure annual wellness visits are occurring each year.
• These visits have the highest likelihood of triggering accurate and appropriate coding of risk-adjustable conditions.
• Increased primary care utilization feeds data elements for future tracking, reporting, and accurate code capture.

Overall, payers and providers need to work closely with one another to set up accurate and consistent practices for managing newly enrolled members or patients new to providers. Providers managing current patients that are new to the health plan have critical information on that patient’s clinical history that the health plan does not. Additionally, health plans need to leverage as many data sources as possible to empower their provider partners with the resources to appropriately and consistently code patient conditions.

A continual feedback loop of data analytics, provider outreach, and patient visit monitoring allows health plans to prospectively think about their ACA populations and optimize the appropriate capture of risk regardless of the concurrent nature of the risk adjustment. Managing risk coding and transfer payments is a core competency in the ACA market, and particularly critical as payers look to grow sustainably.