A new report by Avalere identifies opportunities to improve how health plans in the Affordable Care Act (ACA) exchanges are paid. The report comes at a time when the federal government is about to hold a meeting to discuss how the ACA marketplace plans have been paid since 2014, as well as ways the payment model could be improved. In the report, Avalere describes the importance of risk adjustment in the ACA, compares the risk adjustment model used in these markets to the models used in Medicare and Medicaid, and suggests potential modifications that could improve the model.

The ACA created a risk-adjustment program for the individual and small group commercial markets to ensure health plans are accurately paid for the services they cover for their enrollees. Through risk adjustment, plans receive a higher payment for sicker enrollees with costlier care, and a lower payment for healthier enrollees, whose care costs less.

“If the risk-adjustment model is inaccurate, then plans that enroll a disproportionate share of sicker enrollees may experience financial losses and exit the market, even if they have priced premiums accurately” said Tom Kornfield, vice president at Avalere. “By appropriately compensating plans, an accurate model encourages plans to compete based on cost, quality, and health management.”

The Avalere report identifies three main limitations of the existing risk-adjustment model for the individual and small group market:

1. The exchange and individual market population is different than the large employer group population used to estimate the model

Because the risk adjustment model was developed before the ACA coverage expansions took effect, the model was constructed based on health information for people in the large group employer market. Actual individual market enrollees tend to be older, lower-income, and have higher health needs. These enrollees also tend to move in and out of coverage throughout the year. Avalere’s analysis of MORE² claims data shows 30% of people in the individual market were enrolled for less than one year and these short-term enrollees have costs per risk score that are 18% higher than full year enrollees. Such demographic differences may meaningfully impact the accuracy of the model for its target population and create undesirable market incentives.

Potential solution: Exploring ways to estimate the model based on the individual and small group commercial population could improve the accuracy of predictions.

2. The diseases used to predict costs in the model are not reflective of the health needs of the population

The model identifies 127 health conditions that are used to predict the risk of the enrollees. However, only 19.2 percent of individuals in the market ended up having one of those conditions. As a result, the model may not be accounting for important differences in health costs for enrollees who do not have one of these conditions and may not be compensating plans based on the actual risk of the individuals enrolled.

Potential solution: Reevaluating the coverage criteria for diseases included in the model.

3. By excluding prescription drug information to identify an enrollee’s HCC, the model does not take a holistic view of healthcare costs.

The premium charged by plans in the exchanges is designed to cover all expenditures, and the model itself predicts total healthcare costs (medical and prescription drug costs). However, the model does not include prescription drug information to identify health conditions or adjust for disease progression. Under the current model, plans may be systematically undercompensated for enrollees who use high-cost medications, because they are not used to inform disease identification and severity.

Potential solution: A risk adjustment model that uses prescription drug information to identify conditions beyond those captured by diagnoses and adjusts for disease severity based on medication use could be more accurate than the current model.

“Our initial analysis suggests that the unique characteristics of the Exchange and individual market populations are not being adequately accounted for in the existing risk adjustment model,” says April Todd, senior vice president at Avalere. “If factors like churn and income that are more likely to impact the Exchange population are not adequately addressed, health plans may have an incentive to participate in the individual market but not the Exchange market.”

The full report is available here.

Methodology

Avalere analysis of partial-year individual market enrollees is based on Inovalon’s Medical Outcomes Research for Effectiveness and Economics Registry® (MORE²) from 2014 and 2015.