Efficiency of Health Spending in Brazilian States: Analysis Based on Clusters

• Autor(a) principal: Viana, Cátia Cilene Ferreira
• Data de Publicação: 2022
• Outros Autores: Boente, Diego Rodrigues
• Tipo de documento: Artigo
• Idioma: por; eng
• Título da fonte: Contabilidade, Gestão e Governança
• Texto Completo: https://revistacgg.org/index.php/contabil/article/view/2712
• topic: eficiência do gasto; saúde pública; gestão pública; cluster; spending efficiency; public health; public spending; cluster

Objective: This study seeks to ascertain the efficiency of health spending in the Brazilian states and the Federal District. Method: This is a descriptive quantitative study which segments the states into clusters, calculating the efficiency of each cluster and compares the results with and without clusters during the period from 2015 to 2018. To calculate the efficiency scores of the country’s 27 units, we use Data Envelopment Analysis (DEA) with Constant Returns to Scale and Variable Returns to Scale models, which are oriented toward the outputs. Originality/Relevance: Cluster segregation is the differential of the research by Andrett et al. (2018), who also analyzed the efficiency of public spending in the states. There is little approach regarding the creation of criteria for grouping, in the states, regarding public health in Brazil. Results: The results show that the states of Minas Gerais, Maranhão and São Paulo obtained scores with an efficiency equal to 1, independent of whether they were grouped or not grouped in clusters, and for the other states in at least one period their segregation by clusters altered their efficiency scores, which suggests the existence of problems in the management of health spending, and therefore their quality of services needs to improve and maximum use needs to be made of public health resources. Theoretical/Methodological contributions: This study makes a practical contribution not only to the academic environment but can also inform the decision making of public managers in order to improve the quality of health services through the use of cluster techniques to evaluate this spending.