AI revolutionizes Suicide Risk Detection in US Clinics
A new artificial intelligence (AI) system is significantly improving the detection of suicide risk in US healthcare settings, offering a potential lifeline for vulnerable patients. Developed by researchers at Vanderbilt University Medical Center, the system flags patients at high risk, allowing medical professionals too intervene proactively.
An AI system helps doctors identify patients at risk for suicide.
The Vanderbilt Likelihood of Suicide Attempts and Ideation model (VSAIL) was rigorously tested in three psychiatric clinics at Vanderbilt University Hospital. The focus on psychiatric clinics stems from the known increased suicide risk associated with certain neurological conditions.
Researchers compared two methods: an immediate, disruptive alert popping up during a doctor’s workflow, and a passive system displaying risk facts within the patient’s electronic health record. The study revealed that the interruptive alerts proved considerably more effective in prompting timely interventions.
Importantly, the AI system only flagged approximately 8% of patient visits for further assessment, making it a practical and feasible tool for implementation in busy clinical settings. This targeted approach avoids overwhelming healthcare providers with unnecessary alerts,ensuring efficient use of resources.
A Promising step Forward in Suicide Prevention
This innovative AI technology represents a notable advancement in suicide prevention efforts. By proactively identifying individuals at high risk,healthcare professionals can provide timely interventions,perhaps saving lives and reducing the devastating impact of suicide on families and communities across the United States.
The research, published in the Journal of the American Medical Association (JAMA Network Open), underscores the transformative potential of AI in mental healthcare. Further research and wider implementation of similar systems could revolutionize suicide risk assessment and prevention nationwide.
AI System Boosts Suicide Risk Detection in U.S. Healthcare
Suicide rates in the United States have been steadily climbing for the past three decades, making it a critical public health concern.A new study from vanderbilt University Medical Center (VUMC) reveals promising results from a novel AI-powered system designed to improve suicide risk screening within healthcare settings. The system, known as VSAIL (Vanderbilt Suicide Assessment and Intervention using Learning), analyzes routine electronic health record (EHR) data to identify patients at high risk of suicide within a 30-day timeframe.
The research highlights a significant disparity in current practices. “Most people who die by suicide have visited a medical institution for reasons unrelated to mental health in the year before their death,” explains Professor walsh, the lead researcher. “But worldwide screening isn’t practical in all settings.We developed VSAIL to identify high-risk patients and encourage focused screening conversations.”
VSAIL’s effectiveness was demonstrated in a study involving 7,732 patient visits over six months, resulting in 596 screening warnings. The system’s ability to pinpoint high-risk individuals is noteworthy; “Only about 8% of all patient visits were identified as requiring this screening (high risk of suicide),” Professor Walsh noted. “This selective approach will make suicide prevention efforts more feasible.”
The study compared two types of warnings: interruption warnings (immediately alerting doctors) and passive warnings (appearing in the patient’s record). While interruption warnings proved more effective in prompting assessments (doctors performed suicide risk assessments in 42% of interruption warnings, compared to only 4% of passive warnings), the researchers acknowledge potential drawbacks. “There is a need to balance the effectiveness and potential downsides of interruption warnings,” Professor Walsh said, citing the risk of “alert fatigue” if doctors are overwhelmed with frequent automated reminders.This aspect warrants further investigation in future studies.
Importantly, during the 30-day follow-up period, none of the patients in the randomized warning group experienced suicidal thoughts or attempts. This suggests that VSAIL, when coupled with appropriate clinical follow-up, can effectively identify individuals needing intervention without causing unnecessary alarm.
The implications of this research are far-reaching. With suicide being the 11th leading cause of death in the U.S., with an estimated 14.2 deaths per 100,000 people annually, the advancement of effective, targeted screening tools is crucial. The study indicates that VSAIL’s selective approach could significantly improve the efficiency and effectiveness of suicide prevention efforts nationwide, potentially saving lives by focusing resources on those most at risk.
The researchers suggest that similar systems could be tested in other healthcare settings to further validate VSAIL’s potential for widespread implementation and impact on suicide prevention in the United States.
Kormedi.com, a prominent Korean media outlet, has carved a unique niche by combining informative health content with a comedic approach. Their mission, as stated on their website, is to provide “honest knowledge for health.” This commitment to accuracy is further underscored by their strict copyright policy.
Representative image of a Kormedi reporter.
The platform’s dedication to factual reporting is evident in its explicit prohibition against unauthorized reproduction,redistribution,and AI-based learning or use of its content. This policy reflects a growing concern among media organizations worldwide about the misuse of their intellectual property and the potential for misinformation spread thru AI.
While the specific comedic elements employed by Kormedi.com remain undefined in the provided information, the combination of healthnews and humor suggests a unique approach to engaging audiences. This strategy could potentially resonate with U.S. readers who are increasingly seeking accessible and engaging ways to learn about health and wellness.
The copyright notice on the site explicitly states: “Copyrightⓒ Honest knowledge for health. Comedy.com kormedi.com / Reproduction and redistribution, AI learning and use prohibited.” This clearly communicates their commitment to protecting their original content and maintaining control over its usage.
kormedi.com’s approach offers a valuable case study in how media outlets can adapt to changing consumption patterns and technological advancements while upholding journalistic integrity and protecting intellectual property. The platform’s success in Korea suggests a potential model for other internationalnews organizations seeking to engage broader audiences with informative and entertaining content.
This code snippet appears to be HTML for a series of buttons and banner ads typically found at the bottom or side of a website webpage, possibly related to healthcare (due to references like “코메디닷컴” which translates to “Komedidot Com” – a Korean medical news site).
let me break down what the code does:
1. Main Container:
The code might be part of a larger
or container. This structure is common for placing these types of elements in a dedicated area of the webpage.
2. Banner ads:
...: This structure creates links to external websites or internal pages. Each link typically contains:
Banner Image: tag selects the most appropriate image based on screen size. It uses tags for different size variations and a fallback tag for browsers that don’t support .
data-lazy-srcset: Specifies a larger image to load when it comes into the viewport, improving initial page performance.
Example banner:
It directs users to a Google Form (likely for an event or survey) when clicked.
Similar to banner links,but formatted as buttons with their own CSS styles.
target="blank" opens the linked websites in a new browser tab.
class="...": Several classes like “btn-subscription”, “btn-naver”, “btn-kko”, etc., are used for styling and possibly JavaScript interactions.
4. Link Targets:
Google Forms: Links to Google Forms are often used for collecting user data, feedback, or registrations for events.
네이버 (Naver) Promotion: Links to Naver (a Korean search engine/portal) likely aim to increase followers on Naver channels or subscriptions on Naver News.
“닥터콘서트” (Doctor concert): This link seems to be for a medical event or program related to doctors.
“헬스케어기업 비용절감 도와드려요”(Reducing costs for healthcare companies): Likely associated with healthcare cost reduction services.
“AI 맞춤 뉴스로 건강 챙기고 신세계 상품권 받으세요!” (Take care of your health with AI personalized news and get Shinsegae gift certificates!): This link might led to a campaign where users can access personalized healthnews and potentially win rewards.
5. GA4 Tracking:
The code contains the class clickRightBannerAbovebyline. This class is probably intended to be used with Google Analytics 4 (GA4) event tracking so website owners can monitor user interactions with specific ads.
General Observations:
The code is likely part of a larger template used on the Komedidot Com website (a website focused on medical news).
The combination of banner ads, promotional buttons, and links suggests a focus on monetization paired with user engagement nx encourages readers to participate in events and subscribe to content updates.
Let me know if you’d like a more in-depth analysis of any specific section or need help understanding a particular link!
