Electronic Health Records

About 80% of hospital admission electronic records were missing a drug prescribed to an older adult, Vanderbilt researchers found, highlighting the need for a multipronged approach to address medication discrepancies and support safe prescribing practices. Read More

The billing codes in electronic health records are useful for counting skin cancers over time — an important metric for cancer risk assessment and prevention. Read More

Professor and entrepreneur finds startup success with Vanderbilt’s spirit of collaboration and innovation. Read More

Vanderbilt researchers used genetics tools and biobanks with linked electronic health records to explore the associations between statins and noncardiovascular diseases. Read More

A mysterious inflammatory syndrome linked to COVID-19 infection and first identified in children also occurs in adults, Vanderbilt researchers report. Read More

Patients who, perhaps unbeknownst to their health care providers, are in need of genetic testing for rare undiagnosed diseases can be identified en masse based on routine information in electronic health records (EHRs), a research team reported June 3. Read More

A team of Vanderbilt-led researchers sought to better understand the goals, constraints and frustrations of medical providers when they access Electronic Health Records. The results will be shared with technology vendors to enhance EHR usability. Read More

Vanderbilt researchers have developed a response score using genetic and clinical information to aid prescribing of the widely used pain medication codeine. Read More

Team members serving COVID-19 inpatients were more densely connected, interacting far more than their medical ICU counterparts. Read More

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 to continue development of high-throughput software for quickly identifying traits of interest, or phenotypes, in electronic health records (EHRs). Read More

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. Read More

Eric Gamazon, PhD, assistant professor of Medicine, has been awarded a $1.5 million grant from the National Human Genome Research Institute, part of the National Institutes of Health (NIH), to develop novel computational tools that integrate functional genomic data and electronic health records. Read More

Electronic health records and biobanks can be effectively combined to detect and study Mendelian diseases such as cystic fibrosis. Read More

In machine learning, generative adversarial networks (GANs) involve two artificial neural networks squaring off, one, the generator, trying to delude the other, the discriminator, into accepting synthetic data as real. Beyond their science and engineering applications, GANs can generate utterly convincing “photographs” of people who do not exist. Unrestricted use on a wide scale of... Read More