Associate ProfessorEmailPubMed articlesCurriculum Vitae
Dr. Hillegass is an Associate Professor of Data Science and Medicine. As a clinical investigator during 25 years of interventional cardiovascular practice, Dr. Hillegass employed a broad range of research methods including prospective randomized trials, observational studies, and secondary data-analyses. His applied research includes antithrombotic therapies, acute coronary syndromes, peripheral vascular diseases, cardiovascular diseases in diabetics, and interventional therapies. His basic statistical methods research concerns indirect treatment comparison methods. He has focused on quantitative methods to verify the assumptions and validity of indirect treatment comparison methods such as network meta-analysis. He has developed methods to improve the robustness of indirect treatment effect estimators. His additional methodological areas of interest and research include individual patient data meta-analysis, retrospective harmonization of covariates and endpoints across studies & databases, adaptive clinical trial designs, simulated clinical trials, bioinformatics for precision medicine, and cost-effectiveness analyses.
Dr. Hillegass has mentored undergraduate, graduate, medical, and post-graduate trainees in multiple clinical research projects yielding peer-reviewed publications.
Dr. Hillegass studied molecular genetics and econometrics as an undergraduate at Yale. Medicine and clinical research design & application at Harvard Medical School, Harvard School Public Health, and Brigham and Women's Hospital. He trained in cardiovascular diseases and cardiovascular research at Duke University Medical Center and the Duke Clinical Research Institute. His PhD training in biostatistics was at the University of Alabama at Birmingham.