More than 40% of individuals who die by suicide visit healthcare providers within the month leading to their death. Researchers are focusing on electronic health records (EHRs) to enhance the identification of suicide risk. A study developed new suicide risk prediction models using EHR data from over 331,000 visits by more than 16,000 adults in the Indian Health Service. These models accurately identified risk with 82% accuracy, outperforming existing methods that only achieved 64% accuracy in recognizing individuals at risk within 90 days of healthcare contact.
Over 40% of people who die by suicide visit a health care provider in the month before their death, highlighting the importance of healthcare in suicide prevention.
Researchers analyzed electronic health records from over 331,000 visits to IHS providers, identifying a significant number of suicide attempts and deaths occurring shortly after healthcare contact.
The predictive models developed from EHR data outperformed traditional screening methods, identifying those at risk for suicide with 82% accuracy compared to 64% for conventional approaches.
Both new models accurately identified individuals at risk for suicide within 90 days after a healthcare visit, reinforcing the need for improved detection strategies in clinical settings.
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