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02 Apr
2014-04-02    
All Day
Conference Link: http://www.nhlc-cnls.ca/default1.asp Conference Contact: Cindy MacBride at 1-800-363-9056 ext. 213, or cmacbride@cchl-ccls.ca Register: http://www.confmanager.com/main.cfm?cid=2725 Hotel: Location: Fairmont Banff Springs Hotel 405 Spray Ave Banff, [...]
HIMSS 15 Annual Conference & Exhibition
2014-04-12    
All Day
HIMSS15 may be months away, but the excitement is here...right now. It's not too early to start making plans for next April. Whether you're new [...]
2015 HIMSS Annual Conference & Exhibition
2014-04-12 - 2014-04-16    
All Day
The 2015 HIMSS Annual Conference & Exhibition, April 12-16 in Chicago, brings together 38,000+ healthcare IT professionals, clinicians, executives and vendors from around the world. [...]
IVC Miami Conference
The International Vein Congress is the premier professional meeting for vein specialists. IVC, based in Miami, FL, offers renowned, comprehensive education for both veterans and [...]
C.D. Howe Institute Roundtable Luncheon
2014-04-28    
12:00 pm - 1:30 pm
Navigating the Healthcare System: The Patient’s Perspective Please join us for this Roundtable Luncheon at the C.D. Howe Institute with Richard Alvarez, Chief Executive Officer, [...]
Events on 2014-04-02
Events on 2014-04-12
Events on 2014-04-24
IVC Miami Conference
24 Apr 14
FL
Events on 2014-04-28
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.