Rebalancing Risk and Value of Social Determinants 

Risk is unavoidable for every business. In healthcare, the emergence of value-based care (VBC) as the standard for incentivizing providers for improving both healthcare quality and efficiency leads us to reexamine analyzing risk and defining value. 

Two-sided VBC models mean on the upside healthcare providers and health centers share in savings if costs of care are below a determined benchmark, however, on the downside, providers must reimburse payers should payment exceed the benchmark. Risk-adjusted models are increasingly factoring in Social Determinants of Health (SDoH) into population health equations. Aggregate measures of income, education, employment, and housing status, for example, are considered variables that either directly or indirectly influence costs and risk. The limits of VBC models that merely gather and leverage SDoH data to predict risk, or even to effectively manage care, are quickly realized. 

 

The SDoH relationship to risk is often that of a stratifying variable determining tiers of risk (e.g., high, medium, and low), with each successive level representing an aggregate picture of the association between socioeconomic factors and claims or healthcare spending. In many two-sided contracts, SDoH variables are constructed as binary measures of risk tolerance or aversion.  In this case, the provider is forced to weigh the opportunity costs between paying for SDOH investments such as transportation, housing, or community health worker within a specific time frame, or reserving enough capital to cover operational expenses for foreseen, and unforeseen, downtowns. The mission versus margin choice is predicated on the idea of a return on investment. 

Both approaches have merit relative to particular populations, providers, and payors in the market.  Yet, as SDoH accounts for more than sixty percent (60%) of overall healthcare costs, glaring gaps exist in both models where there’s a failure to measure correlated variables associated with upstream public investment through paired social programs, and in measured reinvestment of cost savings.  

    

Here, the proportion of spending in government programs such as Medicare and Medicaid, for example, are budgeted in parallel and pooled with other agencies, including environment (e.g., green space, walkability), transportation, education, workforce, housing, and public safety. Whereas the parameters of risk from social investment (i.e., upside and downside) are proportionately associated with changes in SDoH gradient by geography, utilization, capacity, and surplus. The impact from upfront investment in SDoH gradient from these programs can be measured down to the individual and block group level, and on a macro-level in overall quality of life and life expectancy. 

Cyclical and routine measures would then model for improvements in population health, thus developing standard equations for reducing long-term spending on health care. 

This model rewards providers for the efficacy of execution of the mission and its attribution to lowered costs and better healthcare. As a result, the margin is shared and reinvested in replication and sustainability. In most instances, this model could draw private capital (e.g., social impact bonds (SIB) or pooled income fund) with returns on delivery of pre-defined social and health outcomes. Empirical benchmarks and calculations from a mix of actuarial models of healthcare, program effect equations of the public sector, and ROI of capital markets set the framework. 

 

Value agreement becomes reimagined through a lens where SDoH is no longer a myopic antecedent of financial terms relegated to healthcare. 

 

Under the sole healthcare perspective,  clinical benefits, costs, and the variance of risk spread across patient populations define value propositions. The intensity of resource utilization by both the provider and the patient is the primary factor of interest. Heterogeneously, patient experiences, and outcomes are measured where treatment efficacy, side effects (e.g., pain, time/effort of behavior change or exacerbated co-morbidity), and clinical differences define “customer” value. 

 

A more balanced SDoH model enhances the value definition by asking poignant questions of sustainability as to whether treatments changed individual behavior and environmental exposure for a given provider and context. For example, a reduction in emergency department visits, in-patient admissions, or 30-day readmissions may be far less valuable than increased crisis counseling utilization, 60-day housing coverage, or environmental zoning restrictions for building materials, local food sources, or greenspace elimination. Yet, in some contexts, clinically driven approaches such as utilizing walk-in clinics and urgent care sites, more prescribing of generic medications, or increased use of personalized treatment plans may outweigh social service coordination or public infrastructure investments. In either case, it's critical to understand how value is defined, measured, and used in decision making modeled against risks, rates, and returns. 

 

The relationship between socioeconomic factors and environment and their collective influence on health care dollars, provider incentives, and quality of care has become increasingly understood. Remaining to be incorporated in models of adjusted risk and measured value are parameters for governmental and private investment. Also, to be accounted for are the extraneous effects of individual choices and behaviors. 

 

It’s time to invest in cross-sector models that address the long-term impacts that the social gradient of health has on quality of life. Seizing such opportunities can yield many positive outcomes.

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