As a health services and outcomes researcher, Dr. Feng (Johnson) Qian uses different types of data (e.g., clinical registry, claims, survey, EHR data, etc) and applies various statistical methods to evaluate the real-world effectiveness and economic value of healthcare innovations (e.g., device, intervention, program, etc), the diffusion and practice variation of medical technologies, as well as the access, safety and quality, and health outcomes in racial/ethnic minority groups and under-resourced communities. His funded research includes examining racial/ethnic disparities and practice variations in treating heart attack, stroke, heart failure, and surgical patients, assessing value of adding laboratory data to statewide cardiac registries in profiling hospital and provider quality performance, investigating comparative effectiveness of different generations and types of coronary stents in treating coronary artery disease, and conducting economic analysis for innovative public health programs. In addition, he studies how EHR data can be used to improve population level chronic disease detection, surveillance and management and how artificial intelligence-enabled innovations can enhance practical value in healthcare delivery. He has published over 50 peer-reviewed papers in leading healthcare journals such as the Annals of Surgery, JACC: Heart Failure, Critical Care, Health Affairs, Circulation: Cardiovascular Quality and Outcomes, International Journal of Cardiology, Medical Care, American Journal of Cardiology, Catheterization and Cardiovascular Interventions, and Health Services Research. Dr. Qian received his medical education and residency training in cardiac surgery from Shanghai Medical University, his Ph.D. in Health Services and Policy Research from University of Rochester, and his MBA from Columbia University. He teaches courses on public health leadership, economic evaluation in healthcare, clinical research methods, and health economics.