The coronavirus disease 2019 (COVID-19) is a global public health problem. Since the beginning of the pandemic, notified in March 2020, Brazil has shown high lethality from the disease in older adults. From 2012 to 2018, the country showed an increase of 20% in the older adults’ population. Despite the completeness of vaccine protocols against COVID-19 in the country, there is evidence that this age group, associated with the presence of comorbidities, can be a predictor of the occurrence of hospitalization and severe symptoms due to COVID-19. In this direction, this paper aimed to identify patterns and relationships between symptoms, comorbidities, gender, Intensive Care Unit (ICU) admission, and survival status of older adults, fully vaccinated against COVID-19, hospitalized in Brazil. For this purpose, we perform association rules mining on the OpenDataSUS database. For the group of patients with comorbidity, associations with conditions of oxygen saturation (SpO2) <95%, dyspnea and death were predominant; The female sex was associated with survival and the presence of comorbidities, while the male sex with death and admission to the ICU; for patients admitted to the ICU and who died, associations with SpO2<95%, dyspnea, presence of comorbidities and use of ventilatory support were found. The association rule mining procedure has been shown to be useful in surveying the hospitalization profile of these patients.