Fatores associados aos gastos com a produção ambulatorial em média complexidade

Abstract

After the Unified Health System establishment, the lack of health resources and the its inefficient use have been constantly debated. These debates have exposed the SUS's incapability of funding the Health System, which could compromise its expected efficiency. In the current Unified Health System management model, there are levels of assistance, which should be set hierarchically, decentralized and regionalized to better meet the population needs. In this sense, we believe there are associated factors between the production and the outpatient spending of medium complexity. Objective: Therefore, the aim of this research was to measure the association between spending on outpatient services of medium complexity and other associated factors. Methodology: Thus, we considered the 853 counties, from Minas Gerais State, aggregated in micro-regions to the year of 2014. This research consisted in an ecological and analytical-observational study, with a bivariate and multivariate analysis, which allowed us to analyze some relevant variables, such as the spending associated with production of medium complexity, and other explanatory variables, like demographic and economic factors, Family Health Strategy coverage, number of medical specialists, number of doctors from primary care, and supply services (equipment) in medium complexity. Results: Regarding the results, we found a positive correlation between outpatient treatment of moderate complexity and the following variables: Gross Domestic Product, the households with Middle-Income, the Municipal Human Development Index, housing condition, Female Genre, medical specialists and doctors from primary care. We also found a negative correlation between outpatient services of moderate complexity and the variables: Illiteracy rate and Coverage of Family Health Strategy. All correlations were statistically significant (p < 0.05). The same result was found to the correlation between spending on outpatient services of moderate complexity and other variables. When analyzing the models with multiple linear regressions, with a range of confidence of 95%, we have noted that some variables have not contributed significantly to explain the variance. The housing condition and the number of medical specialists were the variables with the best predictive values. Conclusion: Therefore, we believe our study helps to understand and rationalize the use of available resources in moderate complexity.