The MIT Health Equity Research Group conducts systems-oriented research to understand how structural, social, and technological factors contribute to variation in healthcare access, quality, and outcomes. Our work focuses on identifying the mechanisms through which gaps are produced and sustained—and on generating evidence to inform interventions, policies, and innovations that improve equity and effectiveness in health systems.
Our research addresses healthcare challenges across multiple levels—ranging from neighborhood-level conditions and care delivery models to institutional policies and emerging technologies. We apply interdisciplinary methods from public health, systems engineering, policy analysis, and data science to examine where health systems succeed or fall short. Projects are organized around key stages in the healthcare landscape, with a focus on identifying strategic opportunities to design and implement responsive, high-impact solutions.
Our project portfolio is structured around four core domains:
- Structural Conditions & Barriers — investigating how foundational system features—such as geography, insurance coverage, and infrastructure—affect access and healthcare delivery;
- Clinical Access & Care Experience — analyzing care models, provider dynamics, and patient pathways, particularly in maternal and reproductive health;
- Policy & Legal Environment — examining how coverage structures, legal mandates, and policy shifts influence system responsiveness across populations;
- Technology & Innovation Equity — evaluating whether and how emerging tools—such as AI models and diagnostics—are designed, validated, and deployed to serve diverse populations.
Our approach emphasizes methodological rigor, cross-disciplinary collaboration, and real-world relevance. We engage a broad range of stakeholders—including patients, providers, community organizations, and policy leaders—and integrate both qualitative and quantitative methods. Across all projects, we aim to generate insights that support more adaptive, efficient, and context-aware health solutions.
1. Structural Conditions & Barriers
Exploring how social, geographic, legal, and economic structures shape whether individuals can access healthcare in the first place—and how those structural barriers contribute to long-standing disparities in health outcomes.
Social Determinants of Health (SDOH) Neighborhood-By-Neighborhood Impact (Current) (Freddy Nguyen)
This project integrates multiple lines of inquiry to understand how neighborhood-level structural conditions influence health equity, and how place-based solutions emerge and scale in response. We explore how local factors—including housing, education, infrastructure, and access to care—shape community health outcomes and interact with the design and implementation of equity-focused interventions. The research draws from case studies of high-impact solutions to examine how successful ideas are created, operationalized, and, in some cases, adapted across similar regions.
Insurance Status on Maternal Healthcare (Past) (Katia Powell-Laurent)
This project examines how Medicaid coverage influences access to postpartum services among BIPOC birthing individuals. By comparing benefit structures in expansion and non-expansion states, we assess disparities in services such as case management, lactation support, and doula care. The research underscores how gaps in public insurance policy contribute to maternal health inequities and identifies reforms that could improve continuity of care.
Geographic Impact on BIPOC Maternal Health (Past) (Katia Powell-Laurent)
We analyze how rurality compounds maternal health disparities for BIPOC communities by assessing access to care through spatial data and infrastructure mapping. The project evaluates proximity to birthing-friendly hospitals, federally qualified health centers, and maternal care deserts, alongside measures such as the Maternal Vulnerability Index. Findings reveal how geographic isolation intersects with race to produce significant gaps in maternal care access.
Immigrant Barriers to Healthcare (Past) (Freddy Nguyen)
This project explores how immigration status, policy restrictions, and fear of enforcement limit access to prenatal and reproductive care. We assess structural exclusions affecting undocumented and mixed-status families, including insurance eligibility and provider trust. The research identifies systemic gaps and highlights legal and policy levers to support more inclusive healthcare access for immigrant communities.
Language Barriers to Healthcare (Past) (Freddy Nguyen)
We examine how limited English proficiency impacts care quality, focusing on the availability and effectiveness of interpreter services, translated materials, and culturally appropriate communication. The project documents how language inaccessibility hinders patient understanding, care navigation, and clinical outcomes, particularly for immigrant and multilingual populations.
Mental Health Access in Homeless Populations (Past) (Freddy Nguyen)
This project investigates the structural and systemic factors limiting access to mental health services among unhoused individuals. We evaluate how barriers such as stigma, fragmented service delivery, and lack of shelter-based care contribute to unmet behavioral health needs. The findings highlight policy and infrastructure changes needed to expand equitable access to mental healthcare.
2. Clinical Access & Care Experience
Examines healthcare delivery, focusing on patient experiences, provider practices, and how power distribution and systemic biases in health systems affect equity, particularly in maternal health and reproductive justice.
Maternal Healthcare Workforce (Current) (Katia Powell-Laurent)
This project analyzes how the structure, distribution, and regulation of maternal healthcare providers—particularly doulas, midwives, and OB/GYNs—affect access and outcomes across diverse communities. We assess the impact of policy environments, workforce availability, and scope-of-practice laws on maternal care delivery. The research highlights opportunities to strengthen and integrate culturally responsive, community-based models that improve outcomes for historically underserved populations.
Systemic Bias and Patient Autonomy in Women’s Health (Current) (Katia Powell-Laurent)
This project investigates how institutional practices and provider interactions shape patient autonomy in reproductive and maternal health settings. We focus on how race, gender, and class intersect to influence communication, consent, and clinical decision-making. The research identifies structural and interpersonal factors that undermine autonomy and offers frameworks for building more equitable and trust-centered models of care.
Pain Perception and Management (Past) (Katia Powell-Laurent)
This project explores disparities in pain assessment and management during labor, with a focus on how implicit bias affects the treatment of BIPOC birthing individuals. Through analysis of clinical literature and patient narratives, we examine systemic contributors to under-treated pain and medical misjudgment. Findings emphasize the need for culturally competent provider training and equity-informed labor management protocols.
Stress Factors and Management (Past) (Katia Powell-Laurent)
This project examines how chronic stressors—including financial insecurity, housing instability, and systemic racism—affect maternal health during the perinatal and postpartum periods. We assess the relationship between stress exposure and health outcomes for BIPOC birthing persons and explore models that integrate mental health and social support into maternal care. The findings underscore the importance of comprehensive, trauma-informed approaches to maternal well-being.
Finances of C-Section vs Vaginal Birth (Past) (Katia Powell-Laurent)
This project evaluates how reimbursement models and financial incentives influence the rates of cesarean versus vaginal births. We analyze provider compensation structures, hospital billing practices, and coverage rules to determine how economic factors may shape clinical decision-making. The research calls attention to the misalignment between financial incentives and evidence-based, patient-centered birth practices.
3. Policy & Legal Environment
Studying how health policy, insurance coverage, and legal frameworks affect access, quality, and reproductive justice—especially for BIPOC, immigrant, and underserved communities navigating systemic inequities.
Impact of U.S. Policies on Fertility and Reproductive Health (Current) (Katia Powell-Laurent)
This project examines how access to reproductive and fertility care has shifted in the wake of Roe v. Wade being overturned. We analyze state-level policy changes, insurance restrictions, and provider availability to understand their combined impact on BIPOC women’s reproductive autonomy and health outcomes. The research highlights geographic and racial disparities in care access and informs policy responses that center justice and equity in reproductive health.
Insurance Status on Maternal Healthcare (Past) (Katia Powell-Laurent)
This project evaluates how Medicaid design and coverage continuity influence maternal health outcomes, particularly among BIPOC populations. By comparing states with and without Medicaid expansion, we assess disparities in access to essential postpartum services such as doula care, lactation support, and mental health care. The findings point to critical insurance policy reforms needed to improve care equity across maternal health systems.
Immigrant Barriers to Healthcare (Past) (Freddy Nguyen)
We examine how immigration status, policy restrictions, and enforcement environments affect access to prenatal and reproductive healthcare for immigrant communities. The project identifies structural exclusions rooted in documentation requirements, insurance eligibility, and medical mistrust. Our research proposes policy and systems-level solutions to expand equitable care access for undocumented and mixed-status families.
Language Barriers to Healthcare (Past) (Freddy Nguyen)
This project investigates how language inaccessibility undermines health equity, with a focus on interpreter services, translated materials, and institutional compliance with language access laws. We explore how limited English proficiency affects clinical communication, care navigation, and patient safety. The findings highlight the importance of robust language access infrastructure as a legal and operational foundation for equitable care delivery.
4. Technology & Innovation Equity
Understanding how equity is built—or overlooked—within the design, testing, and regulation of medical technologies, AI tools, and clinical research systems that shape the future of healthcare.
Medical Technologies Development (Current) (Freddy Nguyen)
We investigate how diagnostic technologies account for physiological diversity in design, testing, and real-world deployment. The project evaluates device performance across variables such as skin tone, body composition, and hydration—factors often underrepresented in clinical trials. Our findings highlight gaps in regulatory guidance and industry standards and support new frameworks for inclusive innovation in health technology.
Diversity in Cancer Clinical Trials and Screening (Current) (Freddy Nguyen)
This project explores how racial and socioeconomic disparities in clinical trial participation shape downstream decisions in cancer screening and treatment. We assess barriers to enrollment, analyze trial demographic data, and examine the policy landscape guiding inclusion. The research advocates for more accountable and representative research pipelines that reflect the diversity of the populations most affected by cancer.
AI Bias in Healthcare (Paused) (Freddy Nguyen)
This project examines how artificial intelligence models used in breast cancer risk prediction perform across patient populations. We assess disparities in algorithmic accuracy by race, age, and breast density, and analyze how data limitations contribute to performance gaps. The research critically examines current AI tools and investigates whether more inclusive datasets improve model fairness. Findings inform best practices for equitable algorithm development and regulatory oversight.