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This study proposes the construction of indicators as a tool to evaluate how the services of an Emergency Care Unit (UPA) can be classified about the efficiency and quality of the services provided to its users. Based on metrics such as Length of Stay (LOS), Triage Cycle Time, Reception Service Time, among others, an unsupervised machine learning technique known as Exploratory Factor Analysis was used to obtain indicators. The results were obtained using the free software R. From the proposed indicators, it can be concluded that the higher the value found, generally, the worse the quality of the service provided. This indicates that the users remain in the Emergency Care Unit (UPA) for a long time.