We use our own cookies and third parties ones to offer our services and collect statistical data. If you continue browsing the internet you accept them. More information


Why it matters

Many individuals, especially young people, go through episodes of self-harm, but a significant number of them do not receive the treatment they need. This leaves them vulnerable to more self-harm and, ultimately, the risk of suicide. Emergency departments play a crucial role in addressing this issue, as they are often the first point of contact with medical professionals after an episode of self-harm. This makes them well-placed to provide targeted referrals and initiate specialized care.  

Effective treatment for preventing self-harm and suicide do exist, including various types of psychotherapy, medication, hospitalization, or a combination of these. It is important to understand self-harm and suicide risk are influenced by a complex mix of individual factors that vary greatly from person to person. Therefore, treatment should also be highly personalized. This puts clinicians in the emergency department in the challenging position of finding the right treatment options for each patient based on their unique needs and risks.  

Past research has shown that current clinical guidelines and screening tools often fall short in achieving this, leading to unnecessary hospitalizations and patient dissatisfaction on one side and undetected suicide risks resulting in preventable deaths on the other.  

Recent studies suggest that clinical risk assessment could be significantly improved using artificial intelligence and machine learning techniques. These advanced technologies can process vast amounts of data to create algorithms capable of making highly complex predictions beyond human capacity. This opens exciting possibilities to enhance the accuracy of clinical risk assessments, considering a multitude of risk factors and calculating personalized risk scores.  

The PERMANENS research project aims to create a medical software prototype that assists clinicians in delivering personalized assessments and care to patients arriving at the emergency department with a heightened risk of self-harm or suicide. This software will harness the power of artificial intelligence to provide precise risk assessments and access evidence-based information, enabling the identification of effective treatment options tailored to each patient’s unique needs and risk profile.
The software prototype will be developed collaboratively with input from patients and clinicians to ensure its usability, practicality, and acceptance. Clinicians will receive recommendations for a personalized treatment plan, offering the best possible treatment option that aligns with each patient's risk profile. The personalized approach will increase the likelihood of patients initiating and continuing effective mental health treatment, thereby reducing the risk of further self-harm and suicide. Consequently, the PERMANENS software tool holds significant potential to effectively reduce self-harm and suicide rates in the population.  
Gobierno de España Instituto de Salud Carlos III European Union ERA Per Med

The PERMANENS project is supported by Instituto de Salud Carlos III (ISCIII) and by the European Union NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia (AC22/00006; AC22/00045), the Swedish Innovation Agency (no. 2022-00549), the Research Council of Norway (project no. 342386) and the Health Research Board Ireland (ERAPERMED2022) under the frame of ERA PerMed.