Improving healthcare access in marginalized communities through smart connected technologies
Lead PI:
Yu Nie
Co-Pi:
Abstract

This planning grant aims to deliver better healthcare to and encourage health-promotion behavioral changes among seniors from marginalized communities, by strengthening access to health care, services, and resources. The project envisions a Smart Health Access and Resource Portal (SHARP), which offers both an interface through which individuals gain access to care and resources in health systems, and an engine that designs, recommends, and operationalizes virtual and physical access. The results from this project will accumulate knowledge about the existing healthcare barriers faced by seniors from marginalized communities, reveal their health-related preferences and choice behaviors, and prescribe potential solutions to strengthening their physical and virtual access while maintaining privacy to health care, services, and resources. They will also lay the foundation for a future integrative research proposal that will implement, deploy, and evaluate SHARP. If succeeded, the seniors who participate in the SHARP pilot study will see tangible health benefits gained from better access to and engagement with healthcare systems. Improving the health of seniors contributes to the overall wellbeing of the society and helps lower healthcare costs. In the long run, SHARP can be deployed in other marginalized/underserved communities to help build a healthier and more equitable society. Research results will be broadly disseminated and adopted through publications/presentations, collaborations with industry partners, as well as engagement with various community stakeholders.


This integrative research spans across social science and technology domains. Central to the promise of the proposed solution is a holistic approach to integrating virtual and physical access. The project assembles a team of experts from Northwestern University (NU), Kaizen Health (KH), and Center for Neighborhood Technology (CNT), with expertise in transportation and mobility systems, computer engineering, behavioral science, social epidemiology, human-computer interaction and informatic, healthcare logistics, and community engagement. The team will work with a range of community partners led by CNT to identify and engage seniors living in selected low-income neighborhoods located in the southside of Chicago. The project will bring together academic, industry and community stakeholders to (i) understand needs, priorities and barriers related to healthcare and mobility via dialogue and discussions; (ii) assess the needs for an integrated digital tool that addresses the identified transportation and healthcare access challenges, and (iii) build partnerships for a meaningful future local pilot study. To fulfill these community engagement objectives, the project will conduct community-centered activities such as Steering Committee Meeting, Expert Panel, Listening Session, and Survey. The project will mine various data collected in this research and acquired from other sources. The findings from data mining will lay the foundation for new socio-behavioral theory that explores the complex relationship between mobility and health and between healthcare accessibility and broad health-related behaviors (e.g., health monitoring and management). They will also inspire new human-computer interaction methods that aim to reveal how seniors currently interact with digital tools, establish the correlations between such interactions and health-related behaviors, and assess their needs for an integrated health tool like SHARP. Taken together, the project will deepen our understanding of (i) the barrier to healthcare access among seniors from marginalized communities, and (ii) institutional and technological challenges in integrating conventional and emerging mobility services from both private and public sectors. The project will also lead to the creation of a suite of analytical and computational tools that form the core intelligence of SHARP. These include (i) a human digital twin model and a novel resource allocation model that address the choice between virtual and physical access at the individual and the system level, respectively; and (ii) mathematical models and solution algorithms supporting the design and operation of an integrated transportation and health logistics system.

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.

Yu Nie
My primary interest is to better understand and predict the behavior of transportation networks, and to formulate new design and control strategies to improve mobility, reliability and sustainability of these systems. Unlike other networks such as communication and social networks, the behavior of a transportation network depends on the interactions between human activities (travel choice and driving behavior), physical characteristics of the infrastructure and network topology. As a result, my analyses of transportation systems take an interdisciplinary approach that draws on tools from optimization, network science, traffic flow theory, economics, and statistics. My research covers various aspects of transportation systems analysis, ranging from developing specialized routing algorithms to designing Pareto-improving congestion pricing schemes. Despite their diversity, most problems that I have been working on address research questions that not only are of theoretical interest but also promise relevant real-world impacts.
Performance Period: 10/01/2021 - 09/30/2022
Institution: Northwestern University
Award Number: 2125488