Data for PERMANENS come from well-established, population-representative electronic health care records from three countries and one region (Ireland, Norway, Sweden, and Catalonia [Spain]).
The project aims to use data analysis to identify adverse clinical events related to self-harm. Data from electronic medical records will be analyzed using machine learning to create classification models. These models will calculate risk scores based on various patient-relevant variables, enabling the creation of personalized risk profiles. User advisory groups, including patients, clinicians, and individuals with relevant experience, will guide the project's development to ensure its relevance and usefulness. The project emphasizes evidence-based approaches and user-centered design, conducting small-scale tests to assess tool usability, feasibility, and acceptability. The final product will be a user-oriented Clinical Decision Support System (CDSS) that links identified risk with expert-based interventions and provides a clear, visualized interface displaying risk scores and personalized treatment plans.
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.
