Department of Biomedical Informatics

Grant supports speedy sorting of health records by phenotype

Wei-Qi Wei, MD, PhD, assistant professor of Biomedical Informatics and scientific director of the Precision Phenotyping Core at the Center for Precision Medicine, has been awarded a four-year, $1.7 million grant from the National Institutes of Health (grant GM139891) to continue

Ancker named vice chair for Educational Affairs in the Department of Biomedical Informatics

Health informatics expert and educator Jessica Ancker, PhD, MPH, has joined the Department of Biomedical Informatics as vice chair for Educational Affairs. Ancker comes from Weill Cornell Medical College and Weill Cornell Graduate School of Medical Sciences, where she was an associate professor.

Building a cohort, the easy way

An automated system using keyword searches can help identify candidates for clinical trials on adverse drug reactions.

COVID-associated delays for elective services studied

This spring in the U.S., there were widespread delays in elective health care procedures and screenings. Hospitals, in observance of federal guidelines, were, for a time, conserving beds and protective equipment in preparation for a surge in COVID-19 admissions. And, perhaps on a more prolonged basis, patients in many areas of the country stayed away due to anxiety over catching COVID-19 from other patients or their health care team.

Model students: improving clinical decision-making

Vanderbilt investigators have devised a system to alert health IT teams to deteriorating performance in clinical prediction models.

Team tracks sources of false positives in urine drug screens

False positives on urine drug screens are common and are frequently due to cross-reactivity of these tests to medications. Last year, Vanderbilt University Medical Center researchers Jacob Hughey, PhD, assistant professor of Biomedical Informatics, and Jennifer Colby, PhD, at that time assistant professor of Pathology, Microbiology and Immunology, devised, tested and published a method to systematically identify medications that interfere with screenings for drugs of abuse.

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