Fei Han, a policy analyst at The Hilltop Institute, is responsible for conducting research, policy, and quantitative analysis for publicly funded long-term services and supports (LTSS) programs for older adults and individuals with chronic conditions and disabilities. Among his current projects are applying statistical methods, machine learning, and data mining techniques for predictive models of hospitalization for nursing home residents as well as predictive models on other health care output measurements. Fei also leads a survey data analysis for the Maryland Department of Health, conducts clinical trial data analyses and program evaluation analyses, and leads LTSS data deliverables using Medicaid, Minimum Data Set (MDS), Medicare, and LTSSMaryland databases.
Prior to joining Hilltop, Fei was a statistician for the U.S. Department of Agriculture (USDA), where he developed and modified statistically based national sampling plans for dietary supplement analytical studies. He also developed and implemented a statistical method for quality control of analytical data, designed and administered in-house databases, and used SAS to analyze large data sets. Before that, Fei was a research assistant at Louisiana Tech University. He also has teaching experience as an assistant professor at Huaqiao University (China). Undergraduate courses he taught include probability and mathematical statistics, mathematical modeling, calculus, algebra, operations research, and discrete mathematics.
Fei earned his PhD in computational analysis and modeling, as well as his MS in mathematics and statistics from Louisiana Tech University. He earned an MS in pure mathematics from Huaqiao University (China) and a BS in mathematics and applied mathematics from China University of Geosciences (China).