Mandana Rezaeiahari

Mandana Rezaeiahari, Ph.D., is an Associate Professor at the Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences. She directs the Certificate and MS in Healthcare Data Analytics programs and focuses on improving health outcomes through predictive analytics and addressing health disparities using large secondary datasets. Her expertise includes operations research, Bayesian network analysis, and Lean Six Sigma methodologies.

Education:

• Ph.D. – Industrial & Systems Engineering, SUNY Binghamton
• M.S. – Industrial Engineering, University of Science and Culture
• B.S. – Industrial Engineering, University of Science and Culture (cum laude)

Research Interests: Dr. Rezaeiahari’s work emphasizes healthcare operations optimization, particularly in analyzing racial/ethnic disparities via administrative claims data. She develops predictive models for asthma exacerbations, maternal morbidity, and diabetes outcomes. Her methods include data mining, Bayesian networks, and simulation-optimization frameworks.

Publications: Her recent work spans telemedicine implementation disparities, pediatric asthma quality metrics, and maternal mortality trends. She consistently applies interdisciplinary approaches to bridge healthcare analytics and policy.

Awards: Recognized for mentorship in quality improvement programs and honored by Alpha Pi Mu Industrial Engineering Society.

Teaching: Focuses on equipping healthcare professionals with decision tree analysis and predictive analytics tools.

Labs/Teams: Engaged in collaborative projects with UAMS’ interdisciplinary teams, leveraging Lean Six Sigma and data-driven strategies to improve healthcare delivery systems.