Abstract
BACKGROUND: The Supplemental Nutrition Assistance Program (SNAP) is one of the most successful national programs to reduce poverty and improve health outcomes, but millions of Americans who qualify still do not have access to SNAP, and limited data are available to determine how referrals to the program can be completed successfully. OBJECTIVES: We aimed to design and develop a standards-based digital care coordination platform to support closed-loop social services referrals between patients and social and health care providers and demonstrate the feasibility to screen, diagnose, plan, and complete interventions with selected patients in real settings. METHODS: We partnered with community members to design the platform through Community Engagement Studios and with a Federally Qualified Health Center, Local Mental Health Authority, and Food Bank to determine the features and workflow requirements of the platform design. We customized currently available systems to use Fast Healthcare Interoperability Resources (FHIR) Application Programming Interfaces (APIs) that could exchange information in real time across providers and participants. RESULTS: The platform was successfully demonstrated through a pilot where patients were recruited in clinical settings and referred to a Food Bank that provided SNAP application assistance to study participants. We translated the requirements of the platform to national standards and required workflows of providers and patients. Study participants were notified electronically of the specific steps to follow to complete their SNAP applications while receiving support from specialists from the Food Bank. CONCLUSION: The pilot demonstrated the feasibility of collecting granular social service referral information that can be used to better address gaps in social care. The pilot also highlighted the importance of further coordination on the usage and harmonization of needs assessment nationally and that current digital systems are still not ready to fully utilize national Social Determinants of Health data standards.