Professor of Medicine, Epidemiology, and Computer Science
University of Alabama at Birmingham
Dr. Jeffrey Curtis is a Professor of Medicine in the Division of Clinical Immunology and Rheumatology at the University of Alabama at Birmingham (UAB). He completed his MD and MPH at OHSU and rheumatology fellowship at UAB. He completed a graduate program in Clinical Informatics at Stanford University and received his Master of Science (MS) degree in epidemiology at the Harvard School of Public Health.
Dr. Curtis holds the Harbert-Ball Endowed Professorship in Rheumatology and Immunology at UAB. His major research emphasis is on evaluating the safety and comparative effectiveness of medications for rheumatic diseases. He also conducts both investigator-initiated and industry-sponsored clinical trials in rheumatoid arthritis (RA) and spondyloarthritis (SpA), including large pragmatic trials. He is the PI of the UAB P30 Informatics Core funded by NIH (NIAMS), focused on digital health and ‘big data’ in musculoskeletal diseases. He is the lead of the UAB Data and Analytic Center (DAC), one of two Coordinating Centers for the ACR’s Rheumatology Informatics System for Effectiveness (RISE), the largest EHR-based rheumatology registry in the world. RISE aggregates and normalizes EHR data from more than 3 million rheumatology patients, with data contributed by more than 1,000 rheumatology providers. He is Director of the UAB Pharmacoepidemiology and Pharmacoeconomics Research (PEER) Unit. PEER uses multiple large and linked data sources to study comparative effectiveness questions across multiple chronic diseases. He is the Co-PI of the mobile health-based, PCORI-funded Patient Powered Research Network PatientSpot (formerly ArthritisPower) research registry, focused on RA, psoriasis, psoriatic arthritis, spondyloarthritis and other chronic conditions that has enrolled more than 35,000 patients. In 2022, he co-created the nation’s largest community rheumatology practice-based research network, the Excellence Network in RheumatoloGY (ENRGY), that is optimized for prospective observational and interventional research studies including traditional, platform, and decentralized clinical trials.