Elham Mahmoudi, Ph.D.

Associate Professor
Areas of Research
Health disparities; Care for patients with disabilities; Big data and machine learning in health care predictive modeling.


NCRC, Building 14, Room G234
2800 Plymouth Rd
Ann Arbor, MI


Elham Mahmoudi, Ph.D. is an Associate Professor of Health Economics. She has more than 70 peer-reviewed publications and has extensive experience using a variety of large secondary data sources, including nationally representative survey data, public and private administrative claims data, and electronic health records, to conduct research. She is also trained in quantitative analysis and econometric methodologies. 

Dr. Mahmoudi's research has focused on evaluating healthcare policies aimed at reducing racial/ethnic disparities in access to and quality of care. She is a mixed methods researcher, examining healthcare use and cost. She also studies efficiency of care for older adults with Alzheimer’s disease and related dementia and mild cognitive impairment, as well as individuals with disabilities. Additionally, she works with programs in China and is on the editorial board of eLife and PLOS One.




Advanced Degrees
  • Ph.D., Economics, Wayne State University
  • M.B.A., University of Detroit Mercy
  • M.S., Computer Information Systems, University of Detroit Mercy
  • B.A., Accounting, University of Shahid Beheshti

2014  Exemplary Scholar Award, National Center for Institutional Diversity, University of Michigan

Additional Grants

 Working as a fully grant-funded researcher, Dr. Mahmoudi has served as the Principal Investigator for the following grants:

    • DoD: (SC200247)
    • NIA K01(AG068361)
    • Nielsen Foundation (721097)
    • Alzheimer’s Association (AARG-NTF-20-685960)

She has served as Co-Investigator/Project Director of the following grants:

    • NIDILRR-based grant (90RTHF0001-01-00)
    • NIA (U54 AG063546)
    • NIA (2-P30-AG-024824-14)
    • NIA(P30-AG)
    • NIDCD (R01 DC014703-5-S1)]
    • Two University of Michigan Internal Grants


I would use electronic medical records to identify the best practices in care coordination and continuation for vulnerable patient populations, including African Americans, Latinos, people with disability and older adults. I would also work with administrative claims data such as Medicare and Medicaid information for various projects related to the prevention of adverse health events among high-need patients.