According to a study published in JAMA Network Open, a combination of in-person screenings and machine learning worked better than either method alone when it came to predicting suicide attempts and suicidal ideation in adults.
Machine learning algorithm predicts risk for suicide attempt
A machine learning algorithm that predicts suicide attempt recently underwent a prospective trial at the institution where it was developed, Vanderbilt University Medical Center.
Over the 11 consecutive months concluding in April 2020, predictions ran silently in the background as adult patients were seen at VUMC. The algorithm, dubbed the Vanderbilt Suicide Attempt and Ideation Likelihood (VSAIL) model, uses routine information from electronic health records (EHRs) to calculate 30-day risk of return visits for suicide attempt, and, by extension, suicidal ideation.
Suicide has been on the rise in the U.S. for a generation and is estimated to claim the lives of 14 in 100,000 Americans each year, making it the nation s tenth leading cause of death. Nationally, some 8.5% of suicide attempts end in death.
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IMAGE: Colin Walsh, MD, MA, assistant professor of Biomedical Informatics, Medicine and Psychiatry, Vanderbilt University Medical Center. view more
Credit: Vanderbilt University Medical Center
A machine learning algorithm that predicts suicide attempt recently underwent a prospective trial at the institution where it was developed, Vanderbilt University Medical Center.
Over the 11 consecutive months concluding in April 2020, predictions ran silently in the background as adult patients were seen at VUMC. The algorithm, dubbed the Vanderbilt Suicide Attempt and Ideation Likelihood (VSAIL) model, uses routine information from electronic health records (EHRs) to calculate 30-day risk of return visits for suicide attempt, and, by extension, suicidal ideation.