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Health IT Summit in San Francisco
2015-03-03 - 2015-03-04    
All Day
iHT2 [eye-h-tee-squared]: 1. an awe-inspiring summit featuring some of the world.s best and brightest. 2. great food for thought that will leave you begging for more. 3. [...]
How to Get Paid for the New Chronic Care Management Code
2015-03-10    
1:00 am - 10:00 am
Under a new chronic care management program authorized by CMS and taking effect in 2015, you can bill for care that you are probably already [...]
The 12th Annual World Health Care  Congress & Exhibition
2015-03-22 - 2015-03-25    
All Day
The 12th Annual World Health Care Congress convenes decision makers from all sectors of health care to catalyze change. In 2015, faculty focus on critical challenges and [...]
ICD-10 Success: How to Get There From Here
2015-03-24    
1:00 pm
Tuesday, March 24, 2015 1:00 PM Eastern / 10:00 AM Pacific Make sure your practice is ready for ICD-10 coding with this complimentary overview of [...]
Customer Analytics & Engagement in Health Insurance
2015-03-25 - 2015-03-26    
All Day
Takeaway business ROI: Drive business value with customer analytics: learn what every business person needs to know about analytics to improve your customer base Debate key customer [...]
How to survive a HIPPA Audit
2015-03-25    
2:00 pm - 3:30 pm
Wednesday, March 25th from 2:00 – 3:30 EST If you were audited for HIPAA compliance tomorrow, would you be prepared? The question is not so hypothetical, [...]
Events on 2015-03-03
Health IT Summit in San Francisco
3 Mar 15
San Francisco
Events on 2015-03-10
Events on 2015-03-22
Events on 2015-03-24
Events on 2015-03-25
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.