By Ashley Perry, MPH, Chief Strategy & Solutions Officer
Last week, CMS released the 2023 Star Ratings for Medicare Advantage (Medicare Part C) and Medicare Part D prescription drug plans in advance of Open Enrollment, which kicked off on October 15. Since then, much has been made of the material decline in ratings, summed up by the stat that 20% of plans nationwide experienced a reduction in their overall rating. The subsequent impact on many plans’ near-term growth opportunities, revenue potential, and market valuation has been significant.
Most of the discussion around the factors contributing to the ratings decline has focused on CMS' return to pre-pandemic methodologies and the increased weighting on CAHPS scores. In our view, there are two additional key drivers worth considering as plans revamp their Stars strategies for 2023.
Voluntary member churn reached an all-time high, averaging 17.5% nationally. This metric, a helpful indicator of overall plan performance, suggests that plans have a material opportunity to improve member engagement, satisfaction, and retention. Beyond the immediate impact on Stars ratings, member churn is a significant financial driver for plans, as it takes an average of four years to recoup the acquisition costs of each member lost. Understanding your members’ social risk factors and support needs can empower your team to engage members earlier in the plan year and more holistically, reducing churn and boosting Stars ratings.
Social risk increased materially. Fueled by corrections in the financial markets, the highest rates of inflation we’ve seen in decades, and persistent economic uncertainty, social risk also increased significantly across the last performance period. In our experience analyzing social risk and Stars attainment data, we consistently see that elevated social risk impacts Star attainment. For example, our analysis of social risk exposure and Stars attainment data for a mid-Atlantic Blues plan indicated that members facing elevated social risk were materially more likely to experience attainment gaps than otherwise similar members. Importantly though, social risk did not impact attainment gaps equally across the measure set.
- Members most likely to experience attainment gaps for Annual Wellness Visits most commonly faced elevated risk of food insecurity, largely due to the affordability of food – versus the accessibility of food or their personal food literacy, the other two core drivers included within our Food Insecurity risk model.
- Members most likely to experience attainment gaps for one of the Medication Adherence measures (cholesterol, diabetes, and hypertension) most commonly faced elevated risk of Health Literacy Challenges and Housing Instability.
- Members most likely to experience attainment gaps across the Statin Use measures (cardiovascular disease, diabetes) most commonly faced elevated risk of Financial Strain and Housing Instability.
Similarly pervasive patterns have emerged through our analyses for other markets, member populations, and measures. This suggests a clear correlation between social risk exposure and Stars attainment, but in a nuanced manner that varies by market, member population, and measure. Thus, a data-driven, analytics-first approach is essential for plans seeking to improve their Stars ratings across the coming performance year.
Through our industry-leading SocialScapeⓇ platform, data packages, and expertise, Socially Determined can empower your team with a complete view of social risk exposure for your full member population, without requiring direct contact or engagement with members. This will enable your team to proactively identify members at elevated risk, understand the specific domains and drivers of their risk, and thereby enable your team to engage and support these members earlier and more effectively, driving both gap closure and member retention.
Reach out today to see our social risk analytics and solutions in action and learn how we can help your team manage risk, improve outcomes and advance equity for your MA members – at scale.