Sistema especialista de tomada de decisão Fuzzy para gerenciamento de risco à saúde de indivíduos com Diabetes mellitus em serviços de atenção primária à saúde

Abstract

Objective: This work aimed to build a specialist artificial intelligence system based on Fuzzy logic as a tool to aid in clinical decision-making for health risk management of adult individuals with an average age of 52 years with a confirmed diagnosis of Diabetes mellitus (DM) in public primary health care services in a Brazilian city. Methodology: A fuzzy logic expert clinical decision-making system was built from an electronic public database with health information from 280 individuals with DM treated in primary public health care, corresponding to five basic health units in the municipality, in the period from 2020 to 2021. Fuzzy logic is a hierarchical data structure that classifies the individual at a certain level, depending on the score that the individual receives in attributes related to risk factors for the emergence of certain clinical conditions related to the severity of DM. In this study, electronic health records of individuals with DM containing sociodemographic, clinical and laboratory information were used to enter the Fuzzy system. The risk of developing clinical conditions related to the severity of DM was represented by ophthalmological, cardiological, endocrinological, nutritional and mental health problems. of individuals diagnosed with DM. Results: This study showed that 41.42% of the total individuals in the sample had a very high risk of being referred to the ophthalmology sector. For the cardiology sector, 34.28% had a high risk for specialized care. For the endocrinology sector, 78.92% of the individuals were classified as high risk. For the nutrition sector, 67.14% had a very high risk for referral to a specialist. In the mental health sector, most individuals had a low risk of being referred to the center of specialties. Conclusion: There is evidence of the effectiveness of the Fuzzy system in the risk management service and ranking of individuals held in queues for assistance with specialists, when considering not only the age or order of arrival, but the severity of the chronic condition imposed by the disease.