“It's so important to find the joy of saying hello, calling each person by his or her name.”

Over the past few decades the electronic health record (EHR) has become an object of intensive study, opening new ground in biomedical research. Natural language sections of the EHR, such as physician’s notes and health team messages, are a rich vein for research, but patient privacy considerations entail first scrubbing patient identifiers from these notes and messages. Historically, this has been accomplished through large, complex software systems that are expensive to develop and maintain.

With the aid of a four-year, $3.4 million grant from the National Institute of Mental Health, researchers at Vanderbilt University Medical Center and Massachusetts General Hospital (MGH) will apply new techniques to investigate treatment resistance of two devastating mental disorders — major depressive disorder, which befalls 15 percent of people at some point in their lives, and schizophrenia, which affects approximately 1 percent.

In 1906, English statistician Francis Galton happened to visit a livestock fair where fairgoers were invited to guess the dressed weight of an ox scheduled for imminent slaughter. Some 800 attendees took part and afterwards Galton got hold of the contest data.

Some biomedical researchers may be unsure about routine electronic health record (EHR) data and how useful it ultimately may prove for drawing meaningful, actionable associations that warrant changes to clinical practice and lead to improved clinical outcomes.

Using data from the UK Biobank and Vanderbilt’s BioVU, a new study in the journal Molecular Psychiatry finds that approximately 4 percent of suicide attempt risk is captured by genotype data.