Thomas Kannampallil

Thomas Kannampallil is an Associate Professor of Anesthesiology at Washington University School of Medicine in St. Louis, holding affiliate appointments in the Institute for Informatics Data Science and Biostatistics (I2DB) and the Department of Computer Science at the McKelvey School of Engineering. He serves as Assistant Dean for Data Science and Chief Data Scientist for WashU Medicine, while also acting as Associate Editor for the Journal of Biomedical Informatics.

His educational background includes a Bachelor's degree in Mechanical Engineering and a PhD in Communication, both earned at the University of Illinois. These foundational qualifications bridge engineering principles with human communication systems, informing his interdisciplinary approach to medical informatics.

Dr. Kannampallil's research centers on developing clinical decision support tools using machine learning to enhance clinical cognition and patient safety. His work specifically targets the reduction of diagnostic errors through data-driven interventions in acute care settings, with emphasis on integrating these systems into existing clinical workflows without disrupting physician decision-making processes. This research directly addresses critical gaps in perioperative medicine and patient monitoring.

He currently leads multiple R01-funded projects from the National Library of Medicine, National Institute on Aging, and Agency for Healthcare Research and Quality, focusing on innovative applications of clinical informatics to improve healthcare outcomes. These grants support the development and validation of novel decision support frameworks within electronic health record systems.

• Fellow of the American Medical Informatics Association (FAMIA)

Dr. Kannampallil maintains extensive operational expertise in Epic EHR platforms, including Clarity and Chronicles data models, Cognitive Compute for machine learning implementation, and SMART/FHIR applications. His technical proficiency enables direct translation of research findings into clinical tools through close collaboration with WashU Medicine's IT infrastructure teams and clinical departments.