Uso de dicionários semânticos na estratificação de riscos em saúde mental

Abstract

Care teams use risk stratification in mental health to determine the level of risk and the severity of the signs and symptoms presented by patients. Risk stratification allows extracting data which are structured into groups of questions. This structure does not favor the analysis of the results based on the answered questions. Health care teams need data to be organized and prepared to answer different questions, or even the severity of signs and symptoms stratified. Ontologies have been used to organize and describe knowledge about data collections. They facilitate the extraction of information, disambiguate terms, and preserve the semantics of the patient's health variables using semantic data annotation. Thus, "how to improve the analysis of data on risk stratification in mental health in order to guide the definition of levels of mental health care?" To answer this question, we propose ontological modeling of risk stratification and semantic annotation of data using the SDD (Semantic Data Dictionary) technique. SDD uses semantic data dictionaries to generate knowledge graphs from ontologies and metadata templates. As a result of the research, graphs are generated to facilitate the visualization of information and the discovery of relationships between, e.g., diseases, signs, and symptoms, serving as a tool to improve the stratification process, as well as helping to define levels of patient care.