This is the second post in a four-part series about social determinants of health (SDOH). The first post provides an overview of SDOH, and subsequent posts will focus on measuring quality in the context of SDOH and evaluating programs that address SDOH.
Over the last few years, the transition to value-based care has dramatically expanded the importance of connecting patients with community service providers to address social determinants of health (SDOH). This need has been made even more apparent by the COVID-19 pandemic, which has shone a bright light on the health outcome inequities associated with disparities in SDOH factors: low income and minority communities have higher infection rates, higher death rates, and are more likely to be affected by the destabilizing financial impacts of the pandemic.
Connecting patients with community service providers is currently a cumbersome and labor-intensive process. Using health information technology (health IT) to share information with community service providers offers promise, but it also presents new, unique technical challenges. The challenges of interoperability have been exacerbated by the pandemic as the data sharing needs have grown, as have the consequences on health outcomes for lacking interoperability. However, the existing momentum to enable interoperable exchange of SDOH data has also been magnified.
Even prior to the pandemic, addressing social determinants of health has become a prominent priority in many national initiatives, including the draft 2020–2025 Federal Strategic Plan for Health IT. The plan recognizes that value-based care provides new incentives for health care providers and the role of SDOH and has a major objective to integrate health and human services information. Accomplishing this objective will require strategies to extend health IT infrastructure to community-based organizations and to capture and integrate SDOH data in EHRs. Having social and behavioral data available in health IT systems and applications will foster communication; support shared decision-making between patients and caregivers; enable population health initiatives; and ultimately, help address these underlying social, behavioral, and environmental needs. Additionally, the Office of the Chief Technology Officer (CTO) in the U.S. Department of Health and Human Services (HHS) co-hosted a recent discussion focused on using SDOH factors to predict and address COVID-19. By building the infrastructure for collecting and sharing SDOH data into the typical clinical data workflows, clinicians, government, and social support systems can be poised to leap into action at the time of crisis.
Determining Which SDOH Data Should Be Collected is Key
Before SDOH data can be seamlessly exchanged between systems, there must be agreement on which data should be collected and shared and how that data is represented. Many social needs concepts for screening, assessment/diagnosis, and intervention are already present in the nationally required clinical terminologies like LOINC and SNOMED CT. Yet, SDOH data exchange is an emerging area, so there are (addressable) gaps in the standard terminologies and lack of agreement across the field about what is “useful” to capture and exchange. For example, which screening tools should be used? What level of granularity should be recorded? Which interventions are being delivered, and for what purposes? To provide a space and process for achieving broad consensus, the Gravity Project launched in late 2018 to bring together industry stakeholder groups to identify priority social domains, agree on related data elements, and recommend ways to collect this data.
The Office of the National Coordinator for Health Information Technology (ONC) curates the Interoperability Standards Advisory (ISA), which identifies, assesses, and determines "recognized" interoperability standards and implementation specifications for industry use. Informed by the work of the Gravity Project and the certification requirements for health IT, the latest version of the ISA identifies 12 different social, psychological, and behavioral data and related clinical terminologies to be used by the industry, including financial resource strain, stress, and social connection and isolation..
In the future, we expect the United States Core Data for Interoperability (USCDI) to address these emerging data classes and be integrated in EHR certification processes as required by the ONC Cures Act Final Rule.
With these initial data standards in place, the foundation is set and new possibilities are open for patients, caregivers, community service providers and others to interact and share data. The Gravity Project is working to advance the technical aspects of interoperable exchange of SDOH data using standard clinical terminologies together with HL7® Fast Health Interoperability Resource (FHIR®) exchange mechanisms. As part of the PACIO Project, we are working with the Centers for Medicare and Medicaid Services (CMS) and other collaborators to take assessment content represented in the standard terminologies referenced in the ISA and then build FHIR® data resources for functional and cognitive status and—in the future—SDOH data as well. Once established as a FHIR® resource, the patient assessment and observation data in an EHR can be shared in a multitude of ways, from populating a chronic kidney patient’s eCare plan or an electronic long-term services and supports plan to sharing relevant information seamlessly with payers and health plans designed under the DaVinci Project. As data standards for social determinants of health are integrated into various FHIR® initiatives, health care providers, patients, community services, and agencies will have new ways to support transitions in care, care coordination, and service planning.
The health care industry has awakened to the important role social risks play in improving health and care quality. We continue to move toward value-based care models which link quality measures and patient outcomes to payment and are building innovative new ways to empower the patient, connect community providers and services, and aggregate data for population health and wellness. In future crises, accurate and thorough SDOH data will allow for infrastructure support, such as equipment, supply chain support, and food distribution, to be distributed to communities most in need.23 With foundational SDOH data standards in place, a springboard is set for a new generation of innovations and tools that connect the broader health care community. The challenge ahead is determining whether those tools will materialize, if incentives for use will be aligned for each stakeholder involved, and whether patients will embrace their new, empowered role of interacting with technology. Trials are just beginning for quality and outcome measures that adjust for social risk. These measures need to be tested and evaluated to understand the impact on value-based care models. The next post in this series will look more closely at the issue of quality and the impact of social determinants of health.