The arrival last March of the COVID-19 pandemic in Tennessee presented challenges for the clinical research enterprise at Vanderbilt University Medical Center. Prompt recruitment of patients newly diagnosed with COVID-19 into clinical trials was, and remains, a public health imperative with top-level backing from the federal government.

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

Retrieval of clearer, more complete information from the EHR could go a long way toward improving predictive models of who will next be at risk of suicide, thereby improving care for patients with suicidal thoughts and behaviors.

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

In a large-scale study of electronic health records, Vanderbilt University Medical Center investigators have determined the prevalence of functional seizures and characterized comorbidities associated with them.

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.

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.