As evidence about the impact of social and economic factors on health grows, health care organizations are increasingly experimenting with strategies to better integrate social and medical services in order to improve health outcomes. A key element of these whole person care approaches involves identifying patients? social risk factors and enabling referrals to relevant internal or external social services, for example to food banks, housing support services, benefits assistance, or medical-legal partnerships. To facilitate multi-sector social care coordination in San Diego, California, 2-1-1 San Diego has developed the Community Information Exchange (CIE), a multi-organization data-sharing system designed to improve care coordination and outcomes for San Diego?s most vulnerable residents. In primary care encounters, providers can access the CIE to view data about patients? social risk factors and service use. The CIE enables providers to adjust treatment at the point of care to minimize the impacts of social risks on treatment success. The CIE also provides a platform through which providers can refer patients to non-medical services relevant to identified social risks. The CIE has attracted national attention as a model for multi-sector care coordination. However, to date, no formal evaluation has examined how the CIE?s combined health and social data analytics affect clinical care, population health management, or community health interventions. As part of a CDC grant, in July 2019 2-1-1 San Diego will begin integrating the CIE platform into the electronic health systems of three Federally Qualified Health Centers (FQHCs) to facilitate seamless integration of health and social needs data and bi-directional referrals for chronic disease prevention and management. We propose to leverage this new federally-funded initiative to enhance the CIE for relevant primary care, population health management, and community agency stakeholders and to evaluate the impact of the enhanced data on chronic disease primary care and community interventions. First, we will use a human-centered design process to understand and prioritize barriers and facilitators to using social risk data for chronic disease-related patient care, population health management, and community health planning. We will use that information to refine the integrated social and medical risk data dashboards presented to relevant stakeholders. Following deployment of these dashboards, we will use a mixed-methods design to evaluate their multi-level impacts on chronic disease-related patient care, population health management, and community health improvement interventions. We will also identify patient, provider, and organizational factors that influence the use and impact of the dashboards in these different contexts. This project will be the first to evaluate the impact of this state-of-the-art social and medical data integration tool on chronic disease management and prevention activities both within clinical and community settings, helping to inform similar efforts across the U.S.
As evidence about the impact of social and economic factors on health grows, health care organizations are increasingly experimenting with strategies to better integrate social and medical services in order to improve health outcomes. To help inform these efforts, this study will enable key stakeholders to strengthen the quality and utility of integrated social and medical data in an existing multi-sector care coordination platform. We will then evaluate the impacts of the data integration platform on chronic disease management and prevention for primary care, population health management, and community health improvement activities in low income, racially diverse populations.
