Screening and Addressing Social Determinants of Health

Assessing, monitoring, and addressing social determinants of health (SDOH) have emerged as key tools for improving health outcomes and reducing the incidence and burden of chronic diseases.  

Because food insecurity and poor diet have a significant impact on health and chronic disease management, Food Is Medicine (FIM) programs offer an approach for addressing food security along with other SDOH. As such, incorporating actionable SDOH frameworks into FIM programs can enable policymakers and researchers to assess the effectiveness of these programs on other SDOH measures (e.g., housing insecurity).

Frameworks for addressing SDOH have historically been based on relatively simple and narrow data points that primarily focus on easily measurable individual-level factors (e.g., annual income, marital status) rather than community-level factors (e.g., availability and accessibility of green infrastructure). 

For example, SDOH measured in FIM studies, excluding demographic information (e.g., race, ethnicity, gender), include the following:

• Food insecurity 
• Medicaid eligibility (as proxy measure for income) 
• Eligibility for Free- and Reduced-Price School Meals (as proxy measure for household income and food insecurity) 
• Housing insecurity 
• Distance from FIM clinic 

Although valuable, this scope may not capture relevant individual-level SDOH that significantly impact access and adherence to healthy diets, such as grocery store access, transportation barriers, and competing costs for basic needs (e.g., housing).

Moreover, many validated screening tools for SDOH were developed for research purposes rather than for clinical applications and may fail to capture SDOH that are most relevant to patients themselves. Some newer tools and frameworks that are more expansive and enable more person-focused, action-oriented implementation are noted below.

Centers for Medicare and Medicaid (CMS) now use the HRSN framework when evaluating new proposals for FIM coverage through Medicaid Section 1115 demonstrations, 1915(c) waivers, and managed care in lieu of service care and settings. 

Accountable Health Communities Model HRSN Screening Tool

As part of its Accountable Health Communities (AHC) Model, CMS tested its AHC HRSN Screening Tool for use across health systems and health care providers programs funded through Medicaid. This tool screens for the following information:

• Five core domains: housing insecurity, food access/security, transportation access, utilities, and safety 
• Eight supplemental domains: financial strain, employment, family and community support, education, physical activity, substance use, mental health, and disabilities 

The tool incorporates the Hunger Vital Sign to screen for food insecurity, which is a validated 2-question screening tool based on the U.S. Household Food Security Survey Module to identify households at risk of food insecurity. It has been validated for use among youth, adolescents, and adults.  

For more information, CMS created a guide to using the Accountable Health Communities Health-Related Social Needs Screening Tool.

In addition to the Accountable Health Communities Health-Related Social Needs Screening Tool, several screening tools are used to identify HRSNs in patients across various health care settings. 

Some of the most commonly used tools are below.

PRAPARE Tool

The Protocol for Responding to and Assessing Patients’ Risks and Experiences (PRAPARE) Tool is designed for use across health care settings to screen patients for HRSNs.

See more of the Protocol for Responding to and Assessing Patients’ Risks and Experiences (PRAPARE) tool. 

Well Rx

The tool is meant for use at every patient visit and covers the domains of food insecurity, housing, utilities, income, employment, transportation, education, substance abuse, childcare, safety, and abuse.

See the report on Addressing Social Determinants of Health in a Clinic Setting: The WellRx Pilot in Albuquerque, New Mexico.

AAFP Social Needs Screening Tool

Developed by the American Academy of Family Physicians (AAFP), this tool is geared toward primary care settings and aims to help primary care physicians address the social determinants of health within their community.

Download the PDF of the Social Needs Screening Tool.

Health Leads

This screening tool is part of a larger toolkit. Similar to the AHC HRSN Screening Tool, this tool is split into recommended and optional domains. The recommended domains are food insecurity, housing instability, utility needs, financial resource strain, transportation, exposure to violence, and socio-demographic information. The optional domains include childcare, education, employment, health behaviors, social isolation and supports, and behavioral health.

See more information on Social Needs Screening Tool table.

Health Begins Upstream Risk Screening Tool 

This tool includes recommendations on the frequency of screening and a method to calculate an overall upstream risk score. It includes questions on education, employment, social support, immigration, financial strain, housing insecurity and quality, food insecurity, transportation, violence exposure, stress, and civic engagement.

See more information on Social Needs Screening Tool table.

Your Current Life Situation Survey

This tool, developed by Kaiser Permanente, screens for various HRSNs, including living situations, housing, food, utilities, childcare, debts, medical needs, transportation, stress, and social isolation.

See more information on Social Needs Screening Tool table.

Tufts Nutrition Security Screener

The Tufts Food is Medicine Institute is has created and is currently validating a nutrition security screening tool.

See more about the Development and Validation of a Nutrition Security Screener.

Developing optimal SDOH screening approaches also requires mitigating potential risks and challenges. Multiple authors have highlighted potential ethical challenges associated with screening for SDOH without effective approaches for addressing material needs (e.g., lack of stable housing) identified during this screening. 

Many social services programs (e.g., nutrition and housing assistance programs) have been chronically underfunded and many have long waitlists so referrals alone may not address significant patient needs.

Data Sharing Considerations for Social Determinants of Health Screening

Data sharing between FIM programs and other stakeholder resources (e.g., EHRs, payer claims databases) may provide opportunities for improving the collection of relevant program evaluation and SDOH data. 

For example, integrating medical and pharmacy claims data into FIM studies can provide granular data on the efficacy of FIM interventions in reducing healthcare and pharmacy costs. Similarly, EHR data for participants in produce prescription and MTM programs can provide detailed information on changes in health outcomes (e.g., HbA1c levels, health care utilization).

Despite these benefits, multiple legal and logistical barriers can hinder or prevent this data exchange. The Health Insurance Portability and Accountability Act (HIPAA) and other patient privacy laws may restrict sharing of patient data, particularly between HIPAA-covered entities (e.g., hospitals, EHR systems) and entities not covered by HIPAA (e.g., community-based organizations [CBOs]). 

Data sharing may also require participating parties to create and execute data use agreements, which can require significant time and effort depending on the types of data sought. 

In addition, the lack of CDEs between many datasets may hinder data aggregation, harmonization, and analysis needed to identify changes in health outcomes.

Potential approaches for resolving these challenges include the following:

• Collection of data directly (e.g., survey data) from participants in clinical trials and FIM pilot studies. This approach should consider participant burden when developing survey instruments to prevent participant burnout and attrition
• Collaboration with third-party administrators to obtain de-identified patient data for tracking health outcomes
• Usage of de-identified data from Medicaid and other medical claims databases
• Collection of relevant data on health outcomes from large representative surveys (e.g., NHANES, American Community Survey)
• Usage of vendor tracking systems (e.g., retailer rewards programs, produce inventory systems) to estimate community consumption of healthy foods.