Four Ways to Overcome Partnership Hurdles and Address Social Determinants of Health

Juliette Price is the Chief Solutions Officer for Helgerson Solutions Group, a global consulting firm dedicated to the move to value in health and social care. Previously, Juliette led large-scale change efforts to increase economic mobility for children and families, and was awarded the Champion of Change award by President Barack Obama for her work in this field.

Health care costs can be reduced and health outcomes improved by investing in non-clinical interventions that address the social determinants of health (SDOH) surrounding a person’s life. This is not a new concept. What has changed over the last few years is that increasingly flexible payment methodologies allow health care payers (health plans) and providers (hospitals, clinics, physician groups) to invest in these approaches by partnering with social care providers, often nonprofit community-based organizations, that offer services to address issues such as food, housing insecurity, transportation, etc. These payment methodologies include a wide variety of models, mostly under the umbrella of value-based contracting, including bundled payments, capitated arrangements, and value-based contracts. Federal and state governments, under both Republican and Democratic control, are broadly continuing this move to value, albeit at different rates.

There is much to learn from these early efforts to implement contracts that directly address SDOH. Over the past several years, we have worked closely with a cohort of community-based organizations providing critical social services as they partner with healthcare payers and providers. We’ve seen the triumphs and frustrations of these early projects as change agents push the boundaries of systems that have not been pushed in this way before. Yet despite confidence in the value of addressing SDOH, implementation of interventions has moved at a pace slower than expected. In New York State, one of the earliest adopters of innovative payment structures for SDOH investments, just over 100 contracts have been approved by the State Department of Health for the Medicaid program’s 7 million members.

So what is causing this disconnect between dreams and reality? A few core challenges have emerged across the work we have done to help SDOH providers enter into contractual arrangements, including cultural, data-related, and funding challenges. Here are four opportunities for organizations invested in SDOH partnerships to speed success.

As the health care sector is increasingly asked to partner with adjacent sectors (social services, housing, employment), we see a familiar pattern of human behavior—leaders reach out to the organizations where they have the closest relationships. Perhaps a local non-profit was the beneficiary of a philanthropic grant from the hospital or health plan, or maybe a health care employee volunteers their time with the organization. When individuals engage with “friends” instead of going out to the broader marketplace to request proposals or understand the local ecosystem, it can often lead to a mismatch of services to need. For example, we worked with a health insurance plan who contracted quickly with a highly visible homelessness advocacy and coordinating agency in order to rapidly house the plan’s non-sheltered members. The agency was a mismatch because its core mission was really advocacy and coordinating multiple housing providers, not direct provision of housing. The plan was left with an ineffective partnership, providers in the community were confused, and the coordinating agency wasn’t able to perform in the contract.

This reflex also disadvantages certain providers of social care, particularly newer, less-well-connected, less financially powerful, and those led by non-white executives who may not have access to institutional hallways of power and influence.

The health care sector has a reputation from outsiders as being heavily data-driven—and in many ways, it is structurally more advanced than other sectors. Take, for example, the standard, universal measurement sets in health care, such as HEDIS measures—metrics that measure how health care is being delivered and its effectiveness. This kind of data infrastructure does not exist in other sectors like education, where outcome data is universally collected, but not standardized. The definition of third-grade reading proficiency looks a lot different in Alaska than it does in Arkansas, but the viral load suppression rate for persons living with HIV is exactly the same no matter where you are.

However, these structural advantages that health care has acquired do not always translate into robust data-driven cultures inside health payer and provider organizations. In our work, we have often encountered organizations where the data and analytic departments are siloed from other decision makers, which does not enable policy and practice leaders to make data-driven decisions. We have observed plans asking CBOs to design interventions to solve for a particular problem their population is experiencing (for example, to engage patients in accessing routine chronic condition management), only to find that when the CBO asks for data around this patient population, the payer hasn’t done adequate analysis that can be shared.

Equally, we have observed CBOs that, lacking the resources to adequately invest in their data systems, are limited in their ability to analyze the information they do receive, or are unable to generate information on their own interventions reliably and accessibly for the health partner.

What we know about data-driven organizations is that prior to any intervention design, deep and thorough data analysis should be done to clearly define the problem they seek to solve, and this analysis should be shared with all parties. Instead of seeing data analysis and sharing as a later-stage partnership activity, it should be seen as a foundational first-step activity.

On many occasions, health care payers and providers have made it clear to CBOs that they are only willing to take chances on "sure bets”—meaning they look for and prioritize interventions that have the deepest evidence base, thereby encouraging the race to randomized control trials of social interventions, a bar set so high that payers/providers themselves might not be able to clear it.

This approach can crowd out innovation—today, we know certain types of medically-tailored meals can deliver a short-term return on investment, but if there’s no infrastructure to encourage experimentation, how will we ever know if providing culturally-competent cooking classes and raw produce delivery results in even better outcomes over the longer term? While we understand that health care payers and providers cannot simply issue blank checks for every idea to be tested, we also think that the lack of sandboxes built to experiment in is also detrimental to the field. Philanthropic support of healthcare investments that test innovation are an important part of moving the field forward.

Further, data collection can often reflect the underlying assumption and priorities of those who are doing the research and their biases towards the issue area, the affected population, and the intervention. For example, housing providers are now re-thinking their use of a widely adopted tool to evaluate an individual’s vulnerability as the current tool often results in a disproportionate share of white clients getting housing. Engaging community members whom the intervention is intended to serve to re-evaluate the data collection process, and to confirm that the outcomes that are being measured are actually outcomes that are locally important, will likely result in a better intervention, and will allow the evidence base to catch up with what is known at the community level.

Additionally, even the most high-quality evaluation of a specific intervention measures impact at a specific point in time, under specific conditions. Often times, we look to “proven” interventions and seek to recreate them without these same conditions and are surprised when the same impact isn’t found. Implementation science can help guide us through these choppy waters of scaling and replicating impact, but first we must shed our over-simplistic frame of just replicating “what works” and hoping for the best.

As this greenfield grows, states must keep applying pressure on the marketplace to ensure that contracts that address SDOH and reflect the health aspirations of the community continue to be moved forward. There are several ways in which the Medicaid programs in each state—often the largest purchaser of health care—can do so.

For example, states should follow New York’s lead and propose to the federal government that all SDOH intervention costs incurred by Medicaid managed care plans, and not just services like screening or referrals, be considered a medical expense, rather than as an expense that the plans are paying for out of their administrative budgets. In health plan jargon, this means that the expense could be included as part of the medical loss ratio. For the rest of us, this means that health plans do not treat this expense any differently than they do a doctor’s visit. This change creates parity between clinical and SDOH interventions, allowing plans and states to shift funds from one bucket to the other. CMS approved this change in New York’s Value Based Payment Roadmap in 2020, and now partnerships are slowly beginning the process of figuring out what it means for their work.

Even more, states need to be more explicit about their commitment to funding upstream services by establishing minimum thresholds for social service investments, for example by requiring that 2 percent of total Medicaid managed care capitation payments be invested in SDOH interventions. Plans should report on how those funds are used, and states in turn should publish annual reports that describe what plans are doing to address the SDOH needs of their members. A minimal funding threshold would ensure that more money is spent, contracts are signed, and a funding floor is created that can be raised over time. This change could be implemented within existing state budget constraints, a key consideration for states who face tough budgets to balance. We recognize that most traditional medical providers would not be keen on this change, as this does not imply that the pie gets larger, rather that the pie is re-distributed. However, we are long past due a substantial reckoning with how healthcare is funded and how community health is achieved.

At the very least, every state should have a clearly laid out SDOH strategic plan, publicly available and updated over time, detailing specific issue areas to be addressed as local data demands, the impact of investments made and the plans to reinvest savings generated in upstream community health to strengthen the cycle. Imitating the “health in all policies” efforts that have been launched across the country, a “SDOH in all policies” approach would allow states to harness their collective purchasing and regulatory power to drive system-level change. One example would be for states with Certificate of Needs programs to require that any hospital seeking to expand its physical plant adopt and implement a comprehensive SDOH strategy for the surrounding neighborhoods.

These are only a few of many options at the disposal of state officials. These policies should be developed with significant community input and states should set ambitious, measurable targets and report on progress each year.

The work to address SDOH through partnerships is daunting, complex, and often lonely. We hope that in sharing a few opportunities to speed progress we will bolster those working to improve community health and well-being.

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