Santiago Romero-Brufau combines a background in engineering, an M.D. and a Ph.D. in Clinical Informatics to develop and implement machine-learning solutions in medicine. He is Adjunct Assistant Professor for the Department of Biostatistics at the Harvard T.H. Chan School of Public Health, where he teaches in the Health Data Science Program. His primary role is for the Department of Otorhinolaryngology and Head & Neck Surgery (ENT) at Mayo Clinic, where he is also an Assistant Professor in ENT, Medicine, and Healthcare Systems Engineering at Mayo Clinic. 

Dr. Romero-Brufau’s main area of interest is in the development of clinical decision support tools using machine learning, and the implementation of those tools into the clinical practice. At Harvard, he teaches aspiring health data scientists to develop their data science tool to fit into the clinical workflow, and how to best combine human and computer-based information processing. At Mayo Clinic, his current focus is in the implementation of triaging algorithms to efficiently determine appropriate specialty appointments for ambiguous clinical conditions, as well as new approaches to risk identification.

In collaboration with his mentor, Dr. Jeanne Huddleston, he has also consulted for several hospital systems to help them establish new systems and processes, like a mortality review or identification of admission risk. Further, he has been a co-investigator on an NSF-funded research grant focused on identification and optimal management of sepsis using engineering principles. Several of his inventions have also been licensed to Mayo Clinic’s industry partners.

During the pandemic, Dr. Romero-Brufau participated in the development of exposure notification systems that were put in place in several US states. He also studied the optimal allocation of vaccines by age groups and doses, influencing healthcare policy that has been estimated to have saved 10,000 lives.