New groundbreaking AI helps identify patients at risk for suicide
Suicide remains a major public health crisis, claiming the lives of approximately 14.2 per 100,000 Americans annually. Despite its prevalence, many individuals who die by suicide have interacted with healthcare providers in the year leading up to their death, often for reasons unrelated to mental health. This underscores a critical gap in routine risk identification and the need for innovative solutions to enhance suicide prevention efforts. A recent study conducted by researchers at Vanderbilt University Medical Center offers promising insights into how artificial intelligence (AI) can bridge this gap. Published in the journal, JAMA Network Open, the research focused on the Vanderbilt Suicide Attempt and Ideation Likelihood model (VSAIL), an AI system designed to analyze routine data from electronic health records (EHRs) to calculate a patient’s 30-day risk of suicide. By leveraging AI-driven clinical decision support (CDS) systems, the study aimed to improve suicide risk assessments during regular healthcare visits, particularly in neurology clinics. The study was a randomized controlled trial (RCT) involving 7,732 patient visits over six months across three neurology clinics at Vanderbilt. …