SCC-PG: Optimizing sociotechnical interventions for healthcare access using community sensing

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

Healthcare systems are increasingly recognizing the critical importance of the social determinants of health (SDOH) in impacting an individual’s ability to access health-promoting resources and living environments. One element of SDOH, transportation disadvantage (TD), refers to the absence of reliable transportation at the individual and community level, preventing an estimated 3.6 million people per year from accessing timely medical care, disproportionately impacting people of color, rural communities, disabled people, and low-income populations. The process of integrating and connecting social and health data to decision making, intervention design, and impact evaluation become critical as health systems seek interventions to lessen health inequity attributable to TD. To address these gaps, this SCC-PG project will advance data-informed time and place-responsive TD solutions and other SDOH interventions in the long term by leveraging industry partnerships, novel data collection and computational methods, and stakeholder engagement. By integrating community and individual level data to measure TD, this research will demonstrate innovative resource allocation models, ultimately reducing transportation barriers to healthcare access and improving health equity. While TD is a recognized barrier to healthcare access, its definition, impacts, and associated interventions are investigated and implemented in a fragmented manner. Understanding these relationships can support the design of customized interventions to reduce health disparities resulting from TD. Healthcare systems currently rely on coarse data that do not adequately capture spatial and temporal variations of SDOH needs within communities. Interoperability between data sources and how SDOH data will be incorporated into decision-making is also unclear. Through the planning grant, our work will 1) advance knowledge on socioecological theories of TD through extensive stakeholder engagement; 2) develop community sensing methods to address lack of granular TD/SDOH data to enable comprehensive analysis; and 3) demonstrate the integration of multilevel TD/SDOH data into optimization frameworks for decision-making for a mobile clinic pilot project in 6 North Carolina counties. Our sociotechnical approach lays the foundation for a systems-based framework to address SDOH in a smart, sustainable, and holistic manner. This work aims to improve the well-being of individuals and communities by focusing on primary prevention and upstream risk reduction strategies that can significantly improve population health and equity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.