Michael E. Matheny, MD, MS, MPH, FACMI, FAMIA

Professor
Department of Biomedical Informatics
Professor
Department of Medicine
Professor
Department of Biostatistics
Director
Center for Improving the Public’s Health through Informatics
Associate Director
Advanced Fellowship in Medical Informatics, TVHS Veterans Affairs
GRECC
TVHS Veterans' Administration
Nashville, TN
615-873-8017

Michael E. Matheny, MD, MS, MPH, is a practicing general internist and medical informatician at Vanderbilt University and TVHS Veteran’s Administration. He received a B.S. in Chemical Engineering and an M.D from the University of Kentucky, completed Internal Medicine residency training at St. Vincent's, Indianapolis, IN, and was an NLM Biomedical Informatics Fellow at Decision Systems Group at Brigham & Women's Hospital, Boston, MA during which time he completed a Master’s in public health at Harvard University as well as a master’s of science in biomedical informatics at MIT.

He has expertise in developing and adapting methods for post-marketing medical device surveillance, and has been involved in the development, evaluation, and validation of automated outcome surveillance statistical methods and computer applications. He is leading the OMOP extract, transform, and load team within VINCI for the national VHA data, and is a Co-Principal Investigator for the pScanner CDRN Phase 2. He also is currently independently funded for two VA HSR&D IIR's in automated surveillance and data visualization techniques for acute kidney injury following cardiac catheterization and patients with cirrhosis. His key focus areas include natural language processing, data mining and population health analytics as well as health services research in acute kidney injury, diabetes, and device safety in interventional cardiology.

Research Description

http://www.researchgate.net/profile/Michael_Matheny

https://scholar.google.com/citations?user=T6SPYrsAAAAJ&hl=en

http://orcid.org/0000-0003-3217-4147

Research Information

Predictive analytics, machine learning and data mining, medical device surveillance, and natural language processing. Involved in a variety of diabetes and acute kidney injury health services research, as well as statistical and informatics tool development related to medical product surveillance.