ACA Risk Adjustment Leaders: You’re Leaving Big Money on the Table
Get it back with a predictive model that improves HCC coding accuracy for new members from day one. by Kaitlyn Fischer
Most ACA plans fail to capture all their new members’ hierarchical condition categories (HCCs) in the first year of coverage, imposing a cost in reduced risk transfer payments equivalent to about 3% of premiums. This article explains how Curv® Risk Adjustment sorts new members into tiers corresponding to HCC likelihood enabling plans to accurately target outreach efforts like in-home assessments.
The 2024 ACA open enrollment period broke records with a 30% year-over-year increase in signups through marketplaces. That means new members are flooding plans, making it even more important to efficiently screen them for the hierarchical condition categories (HCCs) that are imperative to optimal risk adjustment. Early and accurate HCC coding will make a significant difference to your bottom-line next year when the final submission deadline rolls around.
The old saying goes, “What you don’t know won’t hurt you,” but the inability to identify which new members are most likely to have HCCs certainly hurts your risk transfer payments, and the financial pain will only increase with this enrollment spike. The simple fact is that ACA plans that don’t accurately code new members leave money—a lot of it—on the table.
So how do you move all that money from the table back to your bottom line? Close the “new-member gap.”
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