John Tilford

John Tilford, Ph.D., is a Professor in the Department of Health Policy and Management at the Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences (UAMS). He also holds a secondary appointment as Professor in the Division of Pharmaceutical Evaluation and Policy at the UAMS College of Pharmacy. He directs the Health Systems and Services PhD Program and the Healthcare Data Analytics MS Program. His research focuses on economic evaluation of health services, racial/ethnic health disparities, and healthcare analytics. Dr. Tilford has advised numerous PhD students and mentored faculty in grant writing. He has received awards such as the 2021 Chancellor’s Award for Society and Health Education Excellence and the 2018 Outstanding Faculty Award from the College of Public Health Student Council.

Education: Ph.D. in Economics from Wayne State University, M.A. and B.S. in Economics from Central Michigan University.

Research Interests: Dr. Tilford examines the economic impact of health policies, particularly focusing on outcomes for children with neurodevelopmental disabilities and their caregivers. He uses large-scale datasets like the Arkansas All Payers Claims Database to study social determinants of health, including ADHD diagnosis rates and disparities in healthcare access. His work emphasizes improving health equity through evidence-based interventions.

Awards: In addition to his recent recognitions, Dr. Tilford received the 2006 Emergency Medical Services for Children Program Best Project Award and the 2000 UAMS Educator of the Year Award.

Teaching and Mentoring: He teaches courses on healthcare economics and emphasizes the importance of understanding market failures in healthcare systems. He actively mentors students and faculty in grant development, particularly in health policy and data science.

Labs/Teams: His research leverages interdisciplinary teams to address complex health systems challenges, including telehealth adoption, Medicaid expansion impacts, and predictive modeling for asthma and substance use disorders.