Health plans operating in the Medicare Advantage space will need to optimize their risk adjustment and quality prospective and retrospective strategies to optimally align and make provider engagement and data governance the foundation to an effective social determination of health and population health strategy.

In the recently released  CY 2323 Medicare Advantage (MA) and Part D Proposed Rule (CMS-4192-P), the Centers for Medicare & Medicaid Services (CMS) for the first time provides very specific guidance related to social determinants of health (SDoH).

As a refresher, SDoH are the non-medical factors that influence health outcomes, and are the conditions in which people are born, live, learn, work, play, worship, and age. They fall into five basic categories:

  • Economic stability
  • Education access and quality
  • Health care access and quality
  • Neighborhood and built environment
  • Social and community context

What's most important to understand about SDoH is that these factors by and large are not addressed as part of a standard biomedical health assessment and are very much qualitative as opposed to quantitative. Traditional medical care addresses only 10 percent of the controllable contributors that make a population healthy, so it behooves health plans and the providers that are contracted with them to incorporate SDoH screening in addressing the other 90 percent of the contributors to a healthy population. Therefore, it comes as no surprise that CMS has finally provided specific guidance related to SDoH, especially as an increasing number of Medicare beneficiaries receive services through Medicare Advantage (MA) and Part D with over 27 million beneficiaries enrolled in MA plans.

Some of these MA enrollees are concurrently enrolled in Medicaid, with an increasing number of these dually eligible beneficiaries enrolled in Medicare managed care, Medicaid managed care, or both. Dually eligible beneficiaries represent only 15 percent of Medicaid beneficiaries, but account for 34 percent of program spending. About 3.7 million dually eligible beneficiaries currently receive their Medicare services through dual eligible special needs plans (D-SNPs). Certain social risk factors can lead to unmet social needs that directly influence an individual's physical, psychosocial, and functional status, and many dually eligible individuals contend with multiple social risk factors such as housing insecurity and homelessness, food insecurity, lack of access to transportation, and low levels of health literacy. All SNPs must complete enrollee health risk assessments (HRAs) upon enrollment and annually.

Building on experiences from the CMS Innovation Center's Accountable Health Communities (AHC) model and recent standardization of various post-acute care assessments, CMS is proposing that all HRAs include specific standardized questions on the SDoH of housing stability, food security, and access to transportation. The key word here is "standardized," and CMS acknowledges the great challenge inherent in building effective screening tools when health plans that are doing this work already collect differing data elements during the HRA. Standardization also facilitates data exchange among SNPs, which can be helpful when members change plans to proactively and seamlessly address SDoH needs.

The CMS proposal would help better identify the SDoH risk factors that may inhibit enrollees from accessing care and achieving optimal health outcomes and independence. In order to do this, CMS will need to provide guidance related to standardized screening tools for SDoH so that SDoH can be identified and incorporated into care planning and provider engagement. As mentioned earlier, for several years now CMS' Innovation Center has been testing the Accountable Health Communities (AHC) Model. Under section 1115A of the Impact Act of 2014, CMS is testing whether systematically screening for health-related social needs and referrals to community-based organizations to resolve unmet needs will improve utilization and reduce costs over a five-year period. The CMS Innovation Center developed the AHC Health-Related Social Needs (HRSN) Screening Tool to identify needs in five core domains: housing instability, food insecurity, transportation problems, utility help needs, and interpersonal safety. The first AHC model evaluation report, which assessed 2017 to 2020, demonstrated high prevalence of these social risk factors. It is important to note that CMS is not explicitly proposing that SNPs be accountable for resolving all risks identified in these assessment questions but requires that the results from the initial and annual HRAs be addressed in the individualized care plan.

For example, a SNP may make a referral to an appropriate community partner, consistent with the individual's goals and preferences, to assist in meeting these needs. The SNP may also adapt communication methods to fit the individual's circumstances and take steps to maximize access to covered services that may meet the individual's needs and preferences, especially for supplemental benefits that may help with housing instability, food insecurity, or transportation. However, the traditional reactive approach to addressing SDoH by simply offering an array of supplemental benefits and referrals to community resources is insufficient. Health plans must now become proactive by accessing and using data from a variety of sources, including risk adjustment and quality data, to identify the unique SDoH of the population they serve before the need for services and supports arises. They must also effectively engage providers to do their part with regards to screening and integrating SDoH into patient care without adding to administrative burden and burnout. According to a recent report 68 percent of members have an SDoH (primarily financial insecurity and isolation), and 60 percent say they have never discussed this with a provider. Those who do discuss an SDoH with a provider are 2.5 times more likely to accept help from a provider rather than an insurance company.

Let us turn our attention now to a specific SDoH as an exemplar—food insecurity, which is in the domain of social and community context. Food insecurity is defined as the disruption of food intake or eating patterns because of lack of money and other resources. In 2014, 17.4 million U.S. households were food insecure at some time during the year, so this affects a lot more people than we might realize and is probably worse due to the ongoing stress and isolation of COVID-19. Our health plan counterparts have realized this, and Humana found that food insecure older beneficiaries are 50 percent more likely to develop diabetes, 14 percent more likely to develop hypertension, and 60 percent more likely to experience a heart attack. Thirty million people in the U.S. are afflicted with diabetes; another 84.1 million adults have prediabetes. This is staggering considering that there are about 330 million people in the US. The costs to the health care system are even more staggering, reaching $327 billion in 2017, not to mention costs associated with loss of productivity and quality of life. As a result, the ROI of addressing these chronic conditions such as diabetes and hypertension in these food insecure members is tremendous; not just on closing the intersecting risk and quality gaps but also in positively affecting the achievement of optimal health outcomes and independence that are critical to population health.

Through the example of food insecurity, we conclude that health plans operating in the MA space will need to optimize their risk adjustment and quality prospective and retrospective strategies to optimally align and will make provider engagement and data governance the foundation to an effective SDoH and population health strategy. We know that large amounts of big structured and unstructured data are necessary to harness the critical insights that clients need to understand population health and to effectively engage providers and members, and these days the issue is never the lack of data; it is the inability to access and use it effectively. Examples of the big data resources for SDoH are data from the census, from the USDA, and from the CDC such as what can be found at the CDC Sources for Data on Social Determinants of Health.

About the author

Dawn Carter is a director of product strategy at Centauri Health Solutions. Her career in health care spans 25 years, which most recently includes extensive experience in developing revenue integrity and quality software solutions, with a focus on encounter management and risk adjustment solutions for Medicare Advantage, Medicaid and Commercial health plans.

She also provides strategic advisory solutions and consulting services for revenue cycle operations. Prior to that, her experience spans all domains of health care including health plan claims and provider systems administration, and healthcare applications development. Her experience also includes multiple teaching engagements in medical administration, billing and coding. 

Dawn holds a Bachelor’s degree in Business Administration. She is a passionate and prolific industry speaker, author, blogger and subject matter expert in claims, EDI management, and risk adjustment.