Revenue cycle leaders face increasing pressure to manage costs, optimize revenue, and improve revenue cycle functions. This has included more responsibility in understanding the intersection between risk adjustment coding and social determinants of health (SDOH). This intersection is critical to ensuring accurate reimbursement and optimizing revenue cycle outcomes, especially for Medicare Advantage and Medicaid populations, where SDOH significantly influences health outcomes and healthcare utilization.
The Centers for Medicare & Medicaid Services (CMS) uses risk adjustment coding to modify payments to Medicare Advantage plans based on the health status of enrollees [1]. This process supports funding to care for sicker and more complex patients. But traditional risk adjustment models have historically focused on clinical diagnoses and demographic factors while overlooking the impact of social determinants of health – including food insecurity, housing instability, and lack of transportation. As the healthcare revenue cycle begins to reflect a more holistic approach to patient outcomes, integrating SDOH into risk adjustment processes is becoming essential for accurate reimbursement and improved patient care.
Social Determinants of Health and Medicare Advantage
Medicare Advantage (MA) plans cover older adults, many of whom have complex health needs. CMS uses a prospective risk adjustment model to calculate payment for MA plans, relying on Hierarchical Condition Categories (HCCs) to predict healthcare costs based on diagnoses from the previous year. While this model accounts for clinical conditions and demographic factors, it hasn’t traditionally factored in SDOH, which account for an estimated 80% of health outcomes [2].
To address this gap, CMS and MA plans are incorporating SDOH more frequently into their risk adjustment strategies. By addressing SDOH, plans can improve health outcomes, reduce costs, and ensure more accurate risk adjustment coding. CMS is integrating SDOH into Medicare Advantage in multiple ways [3]:
- Value-Based Care Incentives: Value-based payment models encourage payers and providers to identify and address SDOH. They can improve patient outcomes and reduce unnecessary healthcare utilization, which directly impacts risk adjustment scores and reimbursement.
- Flexible Benefit Design: The agency has reinterpreted regulations to allow MA plans to offer supplemental benefits tailored to enrollee needs. These benefits, such as meal delivery, transportation, and home safety modifications, directly address SDOH and can improve health outcomes.
- Care Management Programs: MA plans are uniquely positioned to coordinate care across multiple sectors, including community-based organizations. For example, SilverSneakers, a fitness program for older adults, helps improve mobility and reduce fall risks, while programs like Commonwealth Care Alliance’s “Senior Care Options” provide meal deliveries to address food insecurity.
- Transportation and Social Support: MA plans like ChenMed and CareMore Health are addressing transportation barriers and social isolation through innovative programs. ChenMed offers “door-to-doctor” transportation services, while CareMore’s “Togetherness Program” provides wellness calls and social support to combat loneliness.
By integrating SDOH into risk adjustment strategies, MA plans have begun to more accurately capture the true cost of care for enrollees. Revenue cycle leaders, can benefit from working closely with risk adjustment coding companies to ensure accuracy in their SDOH-related billing and coding.
How States Use Social Determinants of Health in Medicaid
Medicaid populations are disproportionately affected by SDOH, including low-income individuals, children, pregnant women, and people with disabilities. Since Medicaid is administered by states, they have more flexibility in how they address SDOH within their programs. Many states are leveraging this flexibility to integrate SDOH into their risk adjustment and care management strategies. This happens in a few ways [4].
- State Innovation Models: Several states have implemented Medicaid waivers and demonstration projects to address SDOH. For example, North Carolina’s Medicaid transformation initiative includes tailored care management programs that address housing instability, food insecurity, and transportation barriers.
- Health-Related Social Needs (HRSN) Services: States like California and New York are using Medicaid funds to provide HRSN services. This includes housing support, meals, and transportation. These services can improve health outcomes and reduce healthcare costs, which in turn impact risk adjustment scores.
- Data Integration: States are increasingly using data analytics to identify Medicaid beneficiaries with unmet social needs. By integrating SDOH data into risk adjustment models, states can better predict healthcare costs and allocate resources.
- Partnerships with Community Organizations: Many states are partnering with community-based organizations to address SDOH. For example, Oregon’s Medicaid program collaborates with local food banks and housing agencies to provide wraparound services for high-risk beneficiaries.
For revenue cycle leaders, these state-level initiatives increase the importance of accurate risk adjustment coding services. Proper documentation and coding of SDOH-related interventions are essential for maximizing reimbursement and ensuring compliance with state and federal regulations.
The Future of Risk Adjustment and SDOH
As value-based care becomes more prevalent, revenue cycle leaders will need to prioritize the integration of SDOH into risk adjustment strategies. For many healthcare decision makers, this means staying ahead of the curve by working with outsourced risk adjustment coding companies.
By taking a proactive approach to SDOH, healthcare providers can improve patient outcomes, reduce costs, and ensure accurate risk adjustment coding. To learn how to leverage outsourced risk adjustment coding services at your organization, contact 3Gen Consulting today.
References
[1] Better Medicare Alliance, “Social Determinants of Health & Medicare Advantage,” June 2019. Available: https://www.bettermedicarealliance.org/wp-content/uploads/2020/03/FACT-SHEET-Social-Determinanats-of-Health-2019.pdf.
[2] M. L. Greer, M. Y. Garza, S. Sample and S. Bhattacharyya, “Social Determinants of Health Data Quality at Different Levels of Geographic Detail,” Stud Health Technol Inform, vol. 302, p. 217–221, 18 May 2023.
[3] Better Medicare Alliance, “Understanding Risk Adjustment in Medicare Advantage,” June 2017. Available: https://www.bettermedicarealliance.org/wp-content/uploads/2020/03/Understanding-Risk-Adjustment_WhitePaper_June2017.pdf.
[4] J. Jones and S. Muller, “Social determinants of health and Medicaid payments,” Deloitte, 2018. Available: https://www2.deloitte.com/content/dam/insights/us/articles/4819_Social-determinants/DI_Social-determinants.pdf.
