• Center on Health Equity and Access
  • Clinical
  • Health Care Cost
  • Health Care Delivery
  • Insurance
  • Policy
  • Technology
  • Value-Based Care

Implementing a Targeted Approach to Social Determinants of Health Interventions

Publication
Article
The American Journal of Managed CareDecember 2020
Volume 26
Issue 12

We must rethink our one-size-fits-all approach to social determinants of health interventions and instead target patients who truly need and would benefit from these interventions.

ABSTRACT

The scale of the coronavirus disease 2019 pandemic and its disproportionate impact on vulnerable populations has spurred unprecedented focus on and investment in social determinants of health (SDOH). Although the greater focus on social determinants is laudable and necessary, there is a tendency for health care organizations to implement SDOH programs at scale without rigorous evidence of effect, rather than targeting interventions to specific patients and assessing their impact. This broad, and sometimes blind, application of SDOH interventions can be costly and wasteful. We argue for rejecting the “more is better” mindset and specifically targeting patients who truly need and would substantially benefit from SDOH interventions. Matching interventions to the most appropriate patients involves screening for social needs, developing rigorous evidence of effect, and accompanying policy reform.

Am J Manag Care. 2020;26(12):502-504. https://doi.org/10.37765/ajmc.2020.88537

_____

Takeaway Points

  • There is a tendency for health care organizations to implement social determinants of health (SDOH) programs at scale without rigorous evidence of effect, rather than targeting interventions to specific patients and assessing their impact.
  • Efforts to screen for and address SDOH should receive the same scrutiny as clinical interventions to diagnose and treat disease.
  • Matching SDOH interventions to the most appropriate patients involves screening for social needs, developing rigorous evidence of effect, and accompanying policy reform.

_____

Long before coronavirus disease 2019 (COVID-19), there was ample evidence that social factors are primary drivers of health outcomes. However, the scale of the pandemic and its disproportionate impact on vulnerable populations have spurred unprecedented focus on and investment in social determinants of health (SDOH).1 Payers such as Tufts Health Plan and Humana have committed funding to addressing social isolation, food insecurity, and transportation access among seniors. At the federal level, HHS provided $1.3 billion to support community health centers in managing patients’ medical and social needs.2 On the surface, the bet being made is straightforward and grounded in common sense: If social factors are driving poor health and, in turn, greater health care spending, then investments to address those factors should lead to better outcomes and lower overall health care costs.

Although the greater focus on social determinants is laudable and necessary, optimism should be tempered by our relatively limited understanding of whether and which SDOH interventions actually improve the social circumstances or health of vulnerable patients.3 Interventions can be quite expensive and, if applied to individuals where there is little to no benefit, wasteful.

There is a tendency for health care organizations to implement SDOH programs at scale without rigorous evidence of effect, rather than targeting interventions to specific patients and assessing their impact. We believe that efforts to screen for and address SDOH should receive the same scrutiny as clinical interventions to diagnose and treat disease. Just as we would never prescribe an antibiotic for a patient whose infection could not be appropriately treated by that medicine, we should be careful not to prescribe social interventions without confidence that they will solve the problem at hand.

For example, one might suspect that providing rideshare services to patients in the Medicaid program would reduce no-shows. Yet, a clinical trial conducted at 2 clinics in West Philadelphia, Pennsylvania, showed that patients offered rideshare services missed the same number of appointments as controls. Upon further investigation, researchers found that other factors (eg, caregiver role for family members, stress, pressure to be at work) posed a greater obstacle to some patients than transportation.4 These findings caution against the broad, and sometimes blind, application of SDOH interventions.

Similarly, intensive care management programs for patients with high use of health care services have been tested in select populations to improve outcomes and reduce spending. The “hotspotting” program created by the Camden Coalition of Healthcare Providers is an oft-cited example that uses hospital admissions data to identify “superutilizers” and coordinate outpatient care and social services in the months following discharge. However, a recent randomized controlled trial (RCT) showed that the program did not result in the expected decreases in readmission rates.5 Patients enrolled in the program had diverse medical and social needs, and it is possible that the Camden model’s approach to care management was insufficient for some.

Although COVID-19 should motivate us to shore up investments in SDOH, it is also a pivotal opportunity to rethink our one-size-fits-all approach and curb overuse in our resource-constrained system. This requires rejecting the “more is better” mindset and specifically targeting patients who truly need and would substantially benefit from SDOH interventions. When interventions are broadly applied, the entities that most stand to benefit are the growing for-profit industry of vendors focused on this area, not the patient. Although social services can be used by nearly everyone, organizations must be thoughtful about matching interventions to the most appropriate patients. This involves (1) screening for social needs, (2) developing rigorous evidence of effect, and (3) accompanying policy reform.

Effectively Screening for Social Needs

Selectively providing social resources to those most in need requires an accurate and reliable method of identifying these individuals. Although most hospitals screen at least some patients for health-related social needs, this screening is often fragmented and ad hoc.3

Providers often believe that comprehensive social needs screening is not feasible in a clinic setting, but the success of programs such as WellRx in Albuquerque, New Mexico, proves otherwise. In this pilot, an 11-question instrument was used to screen 3048 patients over a 90-day period. Medical assistants and community health workers connected patients who screened positive for unmet social needs with appropriate services and resources. Although similar programs at other institutions have produced mixed results, the WellRx pilot demonstrates that a consistent and systematic approach to screening is indeed possible.6

There is no standard method for social needs screening, and approaches should be tailored to each community and organization. This starts with selecting the right screening tool—although the number and use of screening tools are increasing, few are validated.3 Codesigning screening tools with patients, clinicians, and community stakeholders is a useful strategy; patients can provide valuable insights into the most important questions to ask, clinicians can ensure that screening processes dovetail with their clinical work, and representatives of community-based organizations are privy to the needs and preferences of the communities they serve.

Developing Rigorous Evidence of Effect

Once individuals with social needs are identified, the next step is matching them to the appropriate interventions. However, the evidence base for SDOH interventions is scant and many questions remain unanswered. Which interventions have the greatest impact on health, and for which patients are these most effective? What are the requisite contextual factors necessary to ensure that an intervention is delivered effectively?

If we expect to make real progress, it is time to start treating SDOH interventions with the same rigor as biomedical interventions. A national survey of health care executives revealed that most do not monitor or evaluate SDOH interventions—and if they are evaluated, most evaluations are uncontrolled pre-post studies or cross-sectional studies without a follow-up period of greater than 1 year.7

As a useful model, consider the process of drug development: Compounds are designed and synthesized based on medical need, hypotheses are tested in animal studies, results are analyzed, and compounds are modified accordingly to maximize efficacy and minimize toxicity. This process is iterated before compounds are sent off to clinical trials and ultimately reach the market.

Similarly, an evidence-based approach to evaluating SDOH interventions means starting small, observing what does and does not work, and making adjustments as needed. Although the Camden trial results were disappointing, a growing number of RCTs have demonstrated the value of using implementation science to evaluate SDOH interventions. The Individualized Management for Patient-Centered Targets (IMPaCT) program is an excellent example. This community health worker intervention that helps patients with low incomes achieve their chronic disease management goals was first piloted in a primary care clinic in Philadelphia, studied via a single-center RCT, and then expanded to 3 clinics. A multicenter RCT showed that the intervention improved patient-perceived quality of care while reducing hospitalizations.8 SDOH interventions are neither homogenous nor simple, but this is an outstanding example of using rigorous science to evaluate and fine-tune an intervention for a specific population.

These RCTs are also a reminder to widen the aperture on our metrics for success. Of course, organizations need to understand whether patients are using provided services and whether these services are producing their intended effects. However, the Camden and IMPaCT trials illustrate the importance of measuring outcomes beyond health care utilization. Social needs are, by definition, personal, and a combination of quantitative and qualitative metrics is needed to capture the breadth of an intervention’s impact on people’s lives. Moreover, addressing SDOH takes time—organizations must have the patience to realize long-term improvements in health outcomes.

Policy Reform

Increasing awareness that social determinants have a profound influence on health care outcomes and costs has motivated a slew of policy changes and recommendations intended to incentivize providers to screen for and address patients’ social needs.9 Although these reforms are a step in the right direction, they can have unintended consequences, such as pressuring organizations into the broad application of SDOH programs.

We recommend that policies incentivize the targeted provision of SDOH interventions to specific communities or individuals most likely to benefit from these services. One way to do this is by holding hospitals and health systems accountable for (1) comprehensive screening to distinguish between patients with and without social needs and (2) rigorous studies examining the effects of interventions on specific subpopulations. For example, federal and state departments of health could require that organizations implement and report data on these components of proposed SDOH interventions to be eligible for funding.

The COVID-19 crisis represents a generational opportunity to reshape our approach to addressing SDOH. It is not enough to continue investing in SDOH because it is “the right thing to do.” At the same time, we are not advocating for depriving patients in need of adequate access to social services. Rather, the reality is that most health systems, especially those in underserved communities, have little bandwidth to meaningfully address social determinants for high-need patients. Pursuing a more targeted approach can ensure that interventions actually bear fruit for individual patients and reduce wastage of limited resources.

Author Affiliations: SCAN Group and Health Plan (SHJ), Long Beach, CA; Stanford University School of Medicine (SHJ), Stanford, CA; Harvard Medical School (PC), Boston, MA.

Source of Funding: None.

Author Disclosures: Dr Jain owns stock in Anthem, Blink Health, Curisium, Cyft, Datavant, Embedded Healthcare, Firefly Health, General Electric, Koneksa Health, Merck, Safeguard Scientifics, Thrive Earlier Detection, Valera Health, Vertex, Vital, and U.S. Healthworks. Ms Chandrashekar reports no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (PC); drafting of the manuscript (PC); critical revision of the manuscript for important intellectual content (SHJ, PC); provision of patients or study materials (SHJ); and administrative, technical, or logistic support (SHJ).

Address Correspondence to: Sachin H. Jain, MD, MBA, SCAN Group and Health Plan, 3800 Kilroy Airport Way, Long Beach, CA 90806. Email: Sjain@scanhealthplan.com.

REFERENCES

1. Essien UR, Venkataramani A. Data and policy solutions to address racial and ethnic disparities in the COVID-19 pandemic. JAMA Health Forum. April 28, 2020. Accessed June 9, 2020. https://jamanetwork.com/channels/health-forum/fullarticle/2765498

2. HHS awards $1.3 billion to health centers in historic U.S. response to COVID-19. News release. HHS; April 8, 2020. Accessed June 18, 2020. https://www.hhs.gov/about/news/2020/04/08/hhs-awards-billion-to-health-centers-in-historic-covid19-response.html

3. Abir M, Hammond S, Iovan S, Lantz PM. Why more evidence is needed on the effectiveness of screening for social needs among high-use patients in acute care settings. Health Affairs. May 23, 2019. Accessed June 18, 2020. https://www.healthaffairs.org/do/10.1377/hblog20190520.243444/full/

4. Chaiyachati KH, Hubbard RA, Yeager A, et al. Association of rideshare-based transportation services and missed primary care appointments: a clinical trial. JAMA Intern Med. 2018;178(3):383-389. doi:10.1001/jamainternmed.2017.8336

5. Finkelstein A, Zhou A, Taubman S, Doyle J. Health care hotspotting—a randomized, controlled trial. N Engl J Med. 2020;382(2):152-162. doi:10.1056/NEJMsa1906848

6. Page-Reeves J, Kaufman W, Bleecker M, et al. Addressing social determinants of health in a clinic setting: the WellRx pilot in Albuquerque, New Mexico. J Am Board Fam Med. 2016;29(3):414-418. doi:10.3122/jabfm.2016.03.150272

7. Lee J, Majerol M, Burke J. Addressing the social determinants of health for Medicare and Medicaid enrollees. Deloitte. February 27, 2019. Accessed June 27, 2020. https://www2.deloitte.com/us/en/insights/industry/health-care/applying-social-determinants-of-health-mcos.html

8. Kangovi S, Mitra N, Norton L, et al. Effect of community health worker support on clinical outcomes of low-income patients across primary care facilities: a randomized clinical trial. JAMA Intern Med. 2018;178(12):1635-1643. doi:10.1001/jamainternmed.2018.4630

9. Social Determinants Accelerator Act of 2019, HR 4004, 116th Cong (2019). Accessed June 27, 2020. https://www.congress.gov/bill/116th-congress/house-bill/4004

Related Videos
Mila Felder, MD, FACEP
Shawn Gremminger
Dr Lucy Langer
Dr Lucy Langer
Edward Arrowsmith, MD, MPH
Lalan Wilfong, MD, in an interview on blue AJMC background
Miriam Atkins, MD, president of Community Oncology Alliance, during a video interview on blue AJMC background
Dr David Fajgenbaum | Image credit: The Castleman Disease Collaborative Network
Ted Okon, MBA, of Community Oncology Alliance, during a Zoom video interview
Related Content
© 2024 MJH Life Sciences
AJMC®
All rights reserved.