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Converge where Healthcare meets Innovation
2015-09-02 - 2015-09-03    
All Day
MedCity CONVERGE provides the most accurate picture of the future of medical innovation by gathering decision-makers from every sector to debate the challenges and opportunities [...]
11th Global Summit and Expo on Food & Beverages
2015-09-22 - 2015-09-24    
All Day
Event Date: September 22-24, 2016 Event Venue: Embassy Suites, Las Vegas, Nevada, USA Theme: Accentuate Innovations and Emerging Novel Research in Food and Beverage Sector [...]
2015 AHIMA Convention and Exhibit
2015-09-26 - 2015-09-30    
All Day
The Affordable Care Act, Meaningful Use, HIPAA, and of course, ICD-10 are changing healthcare. Central to healthcare today is health information. It is used throughout [...]
Transforming Medicine: Evidence-Driven mHealth
2015-09-30 - 2015-10-02    
8:00 am - 5:00 pm
September 30-October 2, 2015Digital Medicine 2015 Save the Date (PDF, 1.23 MB) Download the Scripps CME app to your smart phone and/or tablet for the conference [...]
Health 2.0 9th Annual Fall Conference
2015-10-04 - 2015-10-07    
All Day
October 4th - 7th, 2015 Join us for our 9th Annual Fall Conference, October 4-7th. Set over 3 1/2 days, the 9th Annual Fall Conference will [...]
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Articles News

A study shows that AI can detect suicide risk early.

EMR Industry

As artificial intelligence helps doctors discover diseases like cancer at an early stage, it is also demonstrating its potential in tackling mental health crises. According to one study, artificial intelligence can detect patients who are at danger of suicide, providing a tool for prevention in everyday medical settings.

The study, published in the JAMA Network Open Journal, examined two approaches of notifying doctors about suicide risk: an active “pop-up” alarm demanding immediate attention and a passive system (less urgent) that displays risk information in a patient’s electronic chart.

The study discovered that active warnings beat the passive strategy, encouraging doctors to assess suicide risk in 42% of cases, against only 4% with the passive system. Furthermore, it emphasized the importance of using certain techniques to initiate a discourse about suicide risks.

This breakthrough, which combines automated risk identification with deliberately tailored alarms, provides hope for identifying and supporting more people in need of suicide prevention services.

Colin Walsh, an Associate Professor of Biomedical Informatics, Medicine, and Psychiatry at Vanderbilt University Medical Center, emphasized the importance of this breakthrough. “Most people who die by suicide have seen a healthcare provider in the year before their death, often for reasons unrelated to mental health,” according to Walsh.

Previous research indicates that 77% of people who commit suicide had contact with primary care doctors in the year before their death. These findings highlight the essential role AI can play in bridging the gap between conventional medical treatment and mental health interventions.

The Suicide Attempt and Ideation Likelihood model (VSAIL), an AI-driven system developed at Vanderbilt, was tested in three neurology clinics. The method uses normal data from electronic health records to calculate a patient’s 30-day probability of attempting suicide. When high-risk patients were identified, practitioners were encouraged to start focused conversations about mental health.

Walsh clarified: “Universal screening isn’t practical everywhere, but VSAIL helps us focus on high-risk patients and spark meaningful screening conversations.”

While the findings were promising, the researchers emphasized the importance of striking a balance between the benefits of active alerts and their possible drawbacks, such as workflow disruption. The authors proposed that comparable methods may be implemented for other medical specialties in order to broaden their reach and impact.

Cambridge University published a research earlier in 2022 that used PRISMA criteria to assess individuals who were at risk of attempting suicide.