Um estudo da atenção primária à saúde mediante o indicador: Internações por condições sensíveis à atenção ambulatorial (CSAA)

Abstract

The Primary Health Care - PHC is recognized as the primary and gateway to the health care system, and the proper place where it can be answered and solved most health problems. It is considered by WHO as the main tender treatment model. This importance of APS leads to the need for evaluative research of their results to adapt and improve policies and action plans outlined in relation to it. International and national surveys are conducted, in which indicators related to hospital activities are being employed with the aim of measuring effectiveness and access to PHC. One of these indicators, developed by John Billings of the University of New York in the 90s, consists of the conditions for which hospitalizations for Ambulatory Care Sensitive Conditions (ACSC) should be avoided if the PHC services were effective and accessible. Using the Brazilian list of ACSC, published in 2008, and SIH-AIH/2008 the purpose of this paper is to study the primary health care based on the hospitalization for ACSC, in the urban area Juiz de Fora-MG city. We tried to answer about the effects that occur in these admissions from the characteristics of individual patients, the characteristics of the Primary Health Care Unit-PHCU (infrastructure, production and care models) and the social conditions of the areas covered (with PHCU) and discoveries (not PHCU), with the use of multilevel logistic models with random intercept. We tried to know, too, the spatial distribution of standardized rates by age in these areas and their associations with contextual variables, using the tools of spatial analysis. The results of this study showed that the percentage of admissions for ACSC was 4.1%. Family Heath Strategy and Traditional models, the base of organization of primary care in Brazil, had no significant impact on the hospitalizations, only when analysed in form to uncovered areas with reference to the areas covered. Nor were significant variables for infrastructure and production of PHCU. The individual effects (age and sex) in ACSC were significant, with significance probabilities less than 1%, as did the Social Development Index-SDI, which includes the social, economic and environmental conditions in these areas examined. The spatial distribution of standardized rates by age showed random pattern and tests of Lagrange multipliers were not significant indicating the classical regression model (OLS) to explain these rates. For the joint analysis of covered and uncovered areas were risk factors: the economic variable (% of households with incomes up to 2 MW), the uncovered areas with reference to the areas covered and the Northeast. For areas covered variables economic, production from PHCU and Northeast were risk factors for admission rates for ACSC.