• Outstanding research
On 40% of people die from suicide Visit a medical care provider in the month prior to his death, underlining the critical role of medical care environments in suicide prevention. Researchers have been trying to find better ways to detect the risk of suicide quickly and precisely in these environments. A tactic that has proven promising is to analyze electronic health records (EHR) to quickly identify people who need help.
In a study funded by the National Health Institutes, Emily Haroz, Ph.D. , Roy Adams, Ph.D. , Novalene Alsenay Goklish, DBH And colleagues created new suicide risk prediction models using data in EHR of the Indian Health Service (IHS). The models were better to identify those at risk of suicide than the detection methods currently used.
What did the researchers do in the study?
The researchers analyzed EHR data of more than 331,000 visits for more than 16,000 adults to IHS suppliers between 2017 and 2021. During this period, 324 people tried to commit suicide and 37 people died for suicide. Of these, 72% of suicide attempts and 50% of suicide deaths occurred in the 90 days after contact with the health system.
The researchers created models that incorporated suicide risk factors found in EHRS. Then they tested the models to see if they predicted the risk of an attempt at suicide or death in the 90 days after an IHS visit better than the methods currently used. The methods currently used include the suicide exam and consider the history of the past of suicide attempts and recent diagnoses of suicide ideation.
What did the researchers find?
The researchers found that both models also served, correctly identifying the people who tried or died for suicide within 90 days after the visit of their last visit to medical care 82% of the time. This suggests that the test does a good job by distinguishing between those at risk of suicide and those that are not. On the contrary, the detection methods currently used correctly identified those at risk only 64% of the time, which is just a little better than chance (50%).
Why is this study important?
Suicide is the eleventh cause of death in general in the United States, and the populations of American and native Alaska have the highest suicide rate of any racial or ethnic group. The factors that drive the risk of suicide are varied and complex, which makes it important to identify the best methods to identify and prevent suicide risk in different contexts and populations.
In this study, EHR -based models surpassed existing suicide risk detection methods. These findings suggest that the use of EHR -based models can be an important way to reduce the risk of suicide in medical care environments that serve this highly affected population.
Reference
Adams, R., Haroz, USA, rebman, P., Suttle, R., Grosvenor, L., Bajaj, M., Dayal, RR, Maggio, D., Kettering, Cl, Goklish, N. (2024). Develop a suicide risk model for use in India’s health service. NPJ mental health research3 (1), 47. https://doi.org/10.1038/s44184-024-00088-5
