Processo sistemático fundamentado em modelagem ontológica aplicado à estratificação de risco em saúde mental para análise quali-­quanti

Abstract

Mental disorders are among the leading causes of disability in the world. Anxiety is a disorder caused by trauma, stress due to an illness, or from other mental disorders. Mental health studies often use estimates and socio­demographic and psychopathology data. Assessment tools are used to chart values for signs and symptoms and track them during treatment, such as risk stratification. Structured and non­structured data are generated from these instruments, which makes quantitative and qualitative analyses difficult, should signs and symptoms be reevaluated or if the effectiveness and efficiency of treatments have served to mitigate that patient's risk. Thus, this article presents a systematic process based on ontological modeling for the quantitative and qualitative analysis of risk stratification data in anxiety, together with data extracted from psychotherapeutic treatments. The process addresses the use of ontologies and the Semantic Data Dictionary (SDD) technique for data understanding and preparation. Knowledge graphs are generated and hold the semantically annotated data. These graphs can be useful for finding relationships between diseases, symptoms and treatments as well as serving as a tool for forming diagnoses and helping to define levels of patient care.