Using Data to Address Social Determinants of Health: Two Approaches

National interest in the use of social determinants of health (SDOH) data to improve patient and population health continues to grow. To complement this ongoing work, All In: Data for Community Health hosted a webinar outlining two different approaches to collecting and using SDOH data. In case you missed it, here are our reflections and key takeaways on these SDOH data-sharing strategies.

SDOH Case Study #1: The PRAPARE Project

The primary goal of PRAPARE (Protocol to Respond to and Assess Patient Assets, Risks, and Experiences) is to create a standardized screening instrument for collecting SDOH data to include in patient EHR records at community health centers. Data from the PRAPARE questionnaire can be used at the point of care to drive clinical decision-making or aggregated to reveal trends at a population level, which then allow health centers to develop strategic partnerships to better address patients’ SDOH needs.

During the pilot, the screening tool was successfully administered to nearly 3,000 patients across all sites. Preliminary analysis of this data suggests that there are some variations in the most salient SDOH indicators by demographic stratification (e.g. urban vs. rural, Hawaii vs. NYC).

A key accomplishment of PRAPARE has been building clinic staff capacity to collect SDOH data. Clinic staff have been trained to use the responses to refer patients to social services through community asset inventories. Andrew Hamilton, RN, BSN, MS, Chief Informatics Officer at Alliance of Chicago, a pilot site for PRAPARE, commented:

“The secret sauce is both the standardizing of the tool so there is similarity and harmony in collecting the data around social determinants, and then the second component was really that workflow: how do we assist and support our health centers and our care teams to be able to access the tool, provide the inventory of resources for those patients that we identified social determinants, and then to follow-up on patients that we’ve identified.”

SDOH Case Study #2: The Duke-Durham Collaborative Community Health Indicators Project

The Duke-Durham Collaborative Community Health Indicators Project is focused on creating a publicly accessible portal that combines health and SDOH data on the block group level to allow for targeted intervention and action at the community level. The combined data will be available on the Durham Neighborhood Compass platform, which currently houses a variety of transit and demographic indicators. The next step is to integrate healthcare data, starting with diabetes and then add other health indicators.

When developing indicators and metrics, community involvement is key. Michelle Lyn, MBA, MHA, Associate Director for the Duke Center for Community and Population Health, emphasized:

“It’s important to engage the surrounding community to make sure the indicators are indeed meaningful, and that does require an all-in approach with our community members.”

Another aim of the project is to “democratize the data.” This means data won’t just be used institutionally for planning and improvement, but will be available to anyone in the community through to drive collaborations and neighborhood-level actions. Lyn explained:

“If we are expecting all sectors to collaborate on improving the health of our communities, everyone has to have access to information that translates to knowledge that translates to action.”

The goal is to eventually have a standalone governing body for the Neighborhood Compass with a board of community members and representatives—a truly community-owned resource.

Key Takeaways

Though these are two very different projects, key areas of overlap can be applied to efforts engaged in multi-sector collaborations sharing SDOH data.

1) Engage the Community as Collaborators

Community engagement is a critical element to both approaches. For PRAPARE, community collaboration was essential to compiling the community asset inventories for the pilot sites and determining the best way to elicit sometimes sensitive SDOH data from patients. For the Neighborhood Compass project, involving the community ensures that the online tool provides useful information. This access to relevant data drives community action. For example, some local groups in Durham have used the data available through the Neighborhood Compass to advocate for new sidewalks and farmer’s markets in their neighborhoods.

2) Generate meaningful indicators and metrics

Comprehensible data in the form of useful indicators and metrics drives action, both at the local level and more broadly. In the PRAPARE project, it was important to allow for some flexibility in the way that questions were phrased across geographies so that patients would be comfortable responding, while at the same time making sure the collected data remained comparable across sites. Similarly, moving forward, the Durham Neighborhood Compass project will be working to determine how to layer healthcare delivery data, paying particular attention to the appropriate level of granularity for developing targeted, community interventions.

3) Drive Policy Forward

Both projects have long-term implications beyond the immediate project goals. The PRAPARE pilot highlights the need for national standards to leverage Health Information Exchanges (HIEs) to share SDOH data. As a part of the Neighborhood Compass project, Duke hopes the data collected will drive effective policies—not only within their own best practices as a health system, but on the national sphere.

Generating a more nuanced understanding of SDOH data can be a catalyst for addressing our nation’s most pressing public health challenges. As communities apply new approaches to collecting and using this data, the insights and lessons learned can work to guide the field and build capacity to improve community health outcomes.