Decision support model applied to the recognition of non-adherent individuals to antihypertensive therapy

This study aimed at developing a decision-making support model to identify the individuals that do not adhere to the antihypertensive therapy. A decision tree is proposed to be applied on a database of treatment adherence involving 118 hypertensive patients from a Basic Unit of Health. The deciding variable was the adherence to the treatment. Among the variables related to the adherence, 15 predictor attributes were selected. The results arrived to a tree able to correctly classify 87,28% of the individuals. The decision tree model proposed helps in the recognition of non-adherent patients in a way to collaborate with health staff in approaching these individuals.