The Public Interest Technology Initiative at UMass Amherst (PIT@UMass) has selected Assistant Professor Muge Capan of the Mechanical and Industrial Engineering (MIE) Department and her two research colleagues for the 2023 class of PIT Fellows. Team leader Capan will be collaborating with MIE Associate Professor Chaitra Gopalappa and Assistant Professor Jessica Boakye of the Civil and Environmental Engineering Department on an “Exploratory Study for the Development of a Social Vulnerability Scoring System to Inform Equitable Maternal and Child Healthcare Resource Allocation in Massachusetts.”

Capan’s multidisciplinary research team will also be coordinating with the Massachusetts Department of Public Health Special Analytics Projects Unit.

The PIT initiative seeks to develop critical thinking, tech and social literacy, and pragmatic strategies needed to promote personal and professional social responsibility through the development of curricular, research, experiential, and outreach offerings across UMass Amherst’s diverse schools and colleges. Each PIT Fellowship provides the research team with from $5,000 to $8,000 in seed funding to support the groundwork or strengthen ongoing work that will ultimately be submitted for external funding. 

As Capan explains about the background of her project, “Healthcare disparities are related to economic and societal disparities. Specifically, in maternal and child health, the disproportionate distribution of healthcare resources combined with social conditions impact health outcomes of mother and baby.”

Capan says that research studies show how certain populations experience a disproportionate impact of illness and disease during the perinatal period. “The goals of this project,” she says, “are to quantify and risk-stratify social vulnerability and healthcare disparities in maternal and childcare through the responsible use of health systems engineering and information technologies.”

According to Capan, her research team will focus on understanding the emerging public health needs in maternal and child healthcare in Massachusetts through a literature review and search of databases. The team will also develop a “novel, multi-dimensional, quantitative model (Social Vulnerability Scoring System)” that takes into consideration the individual social factors and their correlations.

As Capan says, “Our approach of integrating operations research, health systems engineering, civil engineering, machine learning, and spatial analysis has the potential to quantify and rank the social vulnerability in predefined geographical regions by using an analytical model that goes beyond linear combination of individual social factors.”

Capan and her colleagues will also link this model to disparities in people’s access to care, diagnostics, and health outcomes.

Capan concludes that the results of this multidisciplinary approach can reduce disparities in maternal and child healthcare by providing public health officials with data-driven metrics to support their decision-making for providing an equitable allocation of healthcare resources across the socioeconomic spectrum.

Capan’s research laboratory specializes in data science, statistical analysis, and decision modeling in healthcare to develop smart and connected clinical decision support systems. Gopalappa’s lab does research in systems simulation modeling and machine learning for economic analysis of public health decisions. Boakye’s lab works on quantifying, predicting, and mitigating the consequences of infrastructure failure, disruption, or inaccessibility.

Some of the prerequisites for PIT projects are that they address a complex problem with public interest impacts, involve the responsible use of information technologies, and reduce cultural, economic, and other societal disparities. (April 2023)

Article posted in Research