Social Determinants Of Health: Aggregated Precision Investment

The current pandemic will likely have significant negative long-term consequences on health, with the economic downturn, job losses, social and emotional effects of social distancing and sheltering, and disruption to routine health care and education. These pressures exacerbate the existing shortfall of investment in social determinants of health (SDOH). Looking ahead, finding mechanisms to unleash and efficiently mobilize SDOH investment to address the country’s outsize social needs will be even more pressing.

The challenge of garnering sustainable investment in SDOH is long-standing. Len Nichols and Lauren Taylor outlined the reasons for that challenge in their Health Affairs article “Social Determinants as Public Goods: A New Approach to Financing Key Investments in Healthy Communities.” (See also a follow-up Health Affairs Blog post.) Because the benefits of such investments are diffuse, it is difficult for a single stakeholder, such as a health plan, to secure a return on investment (ROI) on SDOH outlays. Nichols and Taylor outlined an approach to overcome this difficulty by convening health care stakeholders in a given locality to make collaborative investments. 

This post attempts to outline yet another approach to catalyze sustainable investment in SDOH. This approach harnesses the use of individual-level SDOH data and technology to identify precision SDOH investment opportunities and mitigate the need to formally convene stakeholders in a market. We refer to this concept as aggregated precision investment, or API. 

Our object in introducing this concept is to spur additional dialogue to address a problem that will benefit from a multiplicity of approaches. While cohesive multistakeholder groups with a trusted convener will succeed using the Nichols and Taylor model, API can facilitate stakeholder investment in areas where such a group does not exist. Rebecca Nielsen, an author of this blog post, facilitated dialogue about collaborative SDOH investment among local stakeholders in a mid-size city hard hit by SDOH challenges. They had not had successful dialogue to that point, in part because some of the key parties were also competitors. API is a construct that can serve communities where such tensions—or other barriers—inhibit multistakeholder action.

Addressing Social Determinants Of Health

Health care stakeholders are often wary of making significant SDOH investments because they are unable to secure a reliable and timely return on investment. As Nichols and Taylor explain, when someone invests in a SDOH intervention, the benefit, or return, accrues to several stakeholders. That can include the individual receiving the intervention, her family, her health plan, her future health plan, the government, and possibly her provider. Although the aggregate benefit may justify the intervention, the benefit to any single stakeholder may not exceed the cost (see exhibit 1).

Exhibit 1: Aggregate stakeholder benefit compared to total cost of a SDOH intervention

Source: Authors’ illustration.

The sobering outcome of this reality is that SDOH remains underfunded, and the significant benefits of SDOH investment are not unleashed. However, emerging SDOH data assets and technology capabilities may make an alternative approach to addressing this issue feasible. SDOH data companies now aggregate and manufacture data that paint a detailed picture of SDOH status at the individual level, including elements such as a person’s level of financial security, social connectedness, and proximity to a grocery store or a gym.      

Aggregated Precision Investment

To illustrate this approach, we outline an example below. For an individual-level SDOH intervention, there are a significant number of potential beneficiaries (those who receive financial and non-financial benefit). As referenced above, these include the individual, her family, and various private and public for-profit and not-for-profit stakeholders. 

In this example, an “aggregator” determines to propose an intervention to provide housing and case management for homeless adults with chronic medical illness. This intervention is selected because of the robust literature indicating potential for a return on investment. (We discuss the role of the aggregator in more detail later and the multiplicity of functions they could perform. At its core, the aggregator is a pricing and contracting entity that harnesses individual-level data. Organizations that could become aggregators include data vendors or financial services entities with acumen in one or more of these core functions.)

The aggregator identifies a promising geographical market and approaches potential investors, targeting stakeholders who will derive a direct financial benefit from this intervention. This can include the providers that deliver charity care, Medicaid managed care organizations (MCOs) (for those homeless adults who have coverage), and, as Nichols and Taylor point out, the criminal justice system. The aggregator also targets stakeholders that may derive a non-financial benefit, including foundations and philanthropists with a mission of serving the homeless.

Using individual-level SDOH data, the aggregator identifies individuals in the market that meet the criteria for the intervention (that is, homeless adults with chronic medical illness). The aggregator then calculates the likely near-term (for example, 18 months) benefit at the individual level for each stakeholder, using the existing literature as a point of reference. The aggregator then picks a price point below that level of benefit (to drive an ROI for the potential investor) but high enough to cover a portion of the cost of the intervention and a portion of the markup (see exhibit 2).

Exhibit 2: API pricing compared to aggregate stakeholder benefit

Source: Authors’ illustration.

The aggregator then shops the tailored price with each potential investor. In the case of the Medicaid MCO and the health system, the aggregator will secure eligibility data to validate that the individuals targeted for intervention are on the plan or system’s roster. (An aggregator might similarly secure eligibility data from a private health plan for intervention to say, serve nutrition-appropriate meals to vulnerable people.) The aggregator contracts with the respective investors to intervene at the proposed price if it succeeds in securing enough contracts to cover the cost of the intervention with a markup. A foundation or other mission-driven entity may contribute capital to trigger the execution of the intervention.

Once the aggregator has secured sufficient contracts, it commissions a service provider to implement the intervention and secures the funding as specified in each contract. For example, the aggregator ensures that individuals meeting the criteria for the intervention receive respite housing following hospital discharge, stable housing after recovery from hospitalization, and ongoing case management. As possible, the aggregator gathers data that inform the level of actual ROI relative to the expected return on investment (such as emergency department visits and hospitalizations).

This approach eliminates the need for stakeholders in a given market to formally convene to spur SDOH investment. It also supports rates that are financially sustainable for the purchasers.

Precision And Population Investment

As this scenario implies, the initial interventions will be “precision investments.” That is, they will be targeted at specific individuals known to have a particular need. Rather than relying on a community health needs assessment or other high-level needs reports, the aggregator in our scenario will primarily target the individuals within a population with specific, known, SDOH needs (surfaced by vendor-sourced individual-level SDOH data, through stakeholder data, or other means), whom the participating funders have elected to support. This will more likely lead to a successful intervention and higher financial ROI for the investors.

This model paves the way for not only individual-level interventions (such as meal delivery) but also population-level interventions (such as establishing a grocery store in a food desert). The more stakeholders the aggregator contracts within a given market, the more likely it is that the aggregator can execute community-based, root-cause interventions. This is because many stakeholders have a vested interest in the well-being of their members or attributed patients, but also in the well-being of other community members (such as those who may churn onto their plan or those they may employ in the future). Although a health plan will not likely be willing to pay a high rate to support interventions for a non-member, they will likely be willing to pay something to support intervention. That contribution, coupled with the contributions of other market stakeholders, such as employers, government entities, or mission-driven organizations, may be enough to support interventions for a wider swath of a community. 

At scale, a single stakeholder may pay the aggregator to intervene for thousands of members and non-members, all at rates that are commensurate with the stakeholder’s likely return for each individual in the portfolio. In time, although stakeholders will continue to pay “precision rates” (that is, rates based on the expected return to the stakeholder of intervening with an individual), the investments can be communitywide if interventions are funded for a critical number of individuals in an area.

The aggregator in our scenario will marry individual-level SDOH data with a plan’s, risk-bearing provider’s, or other stakeholder’s “membership” data to estimate the likely return to an investor and appropriately price its offer. As would be expected, a plan will see a much higher return on an intervention for a member than it will see on an intervention for a non-member. Similarly, expected rates of member turnover and individual-level characteristics (such as disease burden) may impact the return on investment and can also inform the pricing.

In each contract, the intervention will only be executed if the aggregator is successful in securing enough funding for a given individual to exceed the cost of the intervention and the markup. For that reason, the aggregator will concentrate its efforts on securing multiple contracts in a service area. Although the member’s payer or the government will likely be the biggest financial beneficiary of an intervention (excepting the member herself), other entities such as anchor institutions or foundations can pay a rate higher than their expected return to catalyze the intervention. Essentially, mission-driven stakeholders may agree to rates that represent the difference between the amount of funding that is under contract and the amount of funding needed to activate the intervention for a particular individual.

The Challenge Of Convening

This model may prove to be a useful alternative to Nichols and Taylor’s model of SDOH intervention due to the challenge of convening and sustaining an investor alliance. As described in Finding Allies, Building Alliances, by former Utah Governor Mike Leavitt, also one of the authors of this post, effectively bringing stakeholders together in an alliance generally requires several key elements, including a convener of stature and a common pain. A common pain is a shared problem that motivates groups to work together in ways that they otherwise will not. For most health system and health plan leaders, the challenge and opportunity of SDOH has not yet created sufficient pain to cause them to invest the needed ongoing time (think years) and resources to sustain a community alliance.

Convening and sustaining an alliance also requires a convener of stature, a respected and influential presence that can bring and keep people together. In successful collaborations, a convener with sufficient gravitas to bring people to the table is critical. This convener can also facilitate the ongoing collaboration by helping to clarify objectives, set directions, and drive toward consensus. The challenge of finding and enlisting such a convener in disparate local markets makes an alliance model difficult to scale. While it is likely that an investor alliance model will work in some markets, we believe that some potential investors will only engage and remain engaged if the barriers to participation are low.

The advantage of our model is that by making investing easy (that is, transactional) for stakeholders in a given market, the aggregator increases the likelihood that investors will put money on the table. It is the ease of investing that creates the potential to secure investment not only from entities with SDOH in their mission statement, or who have a lot to gain, but also from entities with a nominal stake in the game who are simply self-interested.

Sizing The Return On Investment

In routine experiences with making investments, the marketable value of the investment changes over time in a way that is translatable into dollars and cents. The financial benefits of individual or community-level SDOH investments will not appear as accruals in an investment account, but they may be equally tangible. The form of the financial benefit will vary by stakeholder. It may surface as medical cost savings for a health plan, reduced expenditures for the criminal justice system, or a lower ratio of charity to compensated care for a health system.

For some interventions, the expected ROI is quite well established in the literature. Over time, capturing and publishing ROI findings will advance the evidence base, and in turn attract additional investors. It will take additional effort to develop appropriate methods to determine and recognize the benefits in financial models and reporting, but an ability to identify the benefit attributable to each investor will accelerate the adoption of this approach.

The Role Of The Aggregator

The aggregator in this model wears several hats. We envision that the aggregator will receive and deploy investment dollars but may enlist other organizations to execute the identified interventions. The aggregator also fulfills several other roles referenced earlier, some of which can be outsourced if needed. The aggregator:

• Identifies high-potential geographical markets;
• Profiles the social needs of individuals in a market;
• Determines individual or community-level interventions that will generate a ROI based on precedent implementations;
• Approaches disparate market entities;
• Calculates individual-level rates or prices for disparate market entities based on expected ROI and entity-supplied data;
• Contracts with disparate market entities and aggregates the investment funds if the minimum investment threshold is met;
• Contracts with outside organizations or directly executes the interventions; and
• Supports the dissemination or publication of de-identified ROI information.

The challenge of this model is establishing an aggregator with the management, computing, and contracting prowess to price and aggregate investments.

The Impact On Service Providers, Community-Based Organizations, And Foundations

The aggregator in the API model pays service providers to execute the SDOH interventions, whether they are meal delivery, housing, transportation, care management, or other entities. Because the API construct seeks to unlock timely returns for investors, the payments will flow to service providers and community-based organizations that deliver interventions for which there is established or emerging cost-effectiveness or ROI literature. 

The aggregator will also seek mission-driven organizations to participate as investors. As stated earlier, these partners can catalyze the execution of an intervention in instances where there are not enough investors to clear the threshold amount or to expand the number of individuals for whom an intervention is fully funded.

Summing Up

Conditions are unfolding to establish sustainable models of SDOH investment, and the current pandemic only increases the imperative to find them. We believe that there is room for a model that leverages individual-level SDOH data and available computing technology to bring together stakeholders in the market without the challenge of maintaining formal cross-stakeholder investment collaboratives. Payers, employers, local government entities, anchor institutions, and others have much to gain financially and otherwise by making investments to address social needs. SDOH investment using the API model will not only appeal to an entity’s charitable instincts—but also its self-interest—by offering a timely return on investment.