Thursday, April 26, 2012
Abay Poster Exhibition and Hall (Millennium Hall)
High rates of hospitalization for conditions sensitive to primary care in a population may be associated with deficiencies in service coverage and / or low outcomes of primary care for certain health problems. This hospitalizations excess represents a warning signal, which can trigger mechanisms for analysis and search for explanations for its occurrence. The aim of this study is to analyze the spatial distribution of admissions, with an emphasis on those for Primary Care Sensitive Conditions (ACSC), in Bauru State Hospital (HEB), in Bauru, São Paulo, from July 2010 to in June 2011. In the period studied, 157 patients admitted HEB, municipalities of São Paulo from virtually all regions of the state, and the hospitalization rate of 3.25 per 10,000 inhabitants. Hospitalizations for conditions sensitive to primary care in 2097 were among the 13,429 SUS hospitalizations, accounting for 18.5%. The average age of patients hospitalized for ACSC was higher (50.6 years versus 44.9 years) and length of hospital stay (8.1 versus 5.5), statistically significant (p <0.001). Regarding gender, there was a statistically significant difference for the greater proportion of men (54.9%) among admissions for conditions not susceptible to primary care. 91.4% of patients hospitalized for ACSC were under 8 years of study. For spatial analysis, were also used concepts of Bayesian inference, because the crude rates show great instability in regions with small population at risk, who are more susceptible to fluctuations due to the occurrence of a few events by chance, the that populous regions. The use of data from hospitalization for conditions sensitive to primary care may serve as indicators of the quality of the health system, thereby contributing to the evaluation of the deployment and implementation of health policies.
Learning Objectives: To evaluate how well diseasesensitive to primary care actions may influential of the profile of a university hospital. To recognize how this information can help local managers to assess the quality of primary health care