Using Social Determinants of Health Data to Drive Multi-Sector Collaboration for Health and Health Disparities

Wednesday, June 7, 2017: 10:30 AM
420A, Boise Centre
Crystal L. Robertson , Louisiana Department of Health and Hospitals, Baton Rouge, LA

BACKGROUND: According to America’s Health Rankings 2016 Annual Report, Louisiana ranks 49 out of 50 states, due to high prevalence of health risk behaviors and their resulting consequences, low birthweight babies, and high infant mortality. Residents face numerous health, social, and economic disparities. To improve health, eliminate disparities, and better address social determinants of health, collaboration is crucial. Inter-professional, multi-sectoral partnerships enrich health assessments, and highlight strengths and needs of the people they serve, including their economic, racial, ethnic, gender, and cultural characteristics.

METHODS: Louisiana Department of Health’s Office of Public Health (OPH) and the Louisiana Public Health Institute aligned strategies to scale health initiatives down to the parish level. The interdisciplinary, mixed-methods approach harnesses data from multiple sectors using an assemblage of stakeholders, operating both across and between boundaries. The triangulated system supports both top-down and bottom-up guidance, from the state to regions to parishes. A Health Improvement Framework based on this system and principles from Public Health 3.0 was developed. The goal was to guide and integrate work from many disciplines and allow them to share data and resources while building a culture of health.

RESULTS: A state-level advisory board, comprised of leaders from education, transportation, health care, public health, and economic development, convened to facilitate and advise implementation of the state health improvement plan (SHIP). Similar regional-level boards assist individual parishes with program planning, evaluation, and coalition building. Parishes-level coalitions are then able to make community-driven decisions using the shared data to target health inequities. A library of roadmaps based on SHIP priorities provide tools and other evidence-based resources needed for successful program development and implementation. While ensuring some degree of structure and consistency is maintained, the roadmaps lend adaptability based on targeted community needs.

CONCLUSIONS: Changes in the population health landscape encourage many agencies to become more engaged and open to widespread collection and use of social determinants of health data. However, there are still challenges to collaboration, and data sharing is an investment that must deliver returns, with value added, by filling a gap in otherwise disparate data bound by silos. The health improvement framework is a potential solution to the drive for more alliance and shared resources to meet each communities’ unique needs to improve health outcomes.