Estudo dos atributos de Atenção Primária na rede de saúde de São Carlos,SP

Abstract

The strength of the orientation of the primary health care (PHC) depends on the presence and extent of each of its attributes. The APS has four essential attributes – “first contact access”, "longitudinality", “coordination” and “integrality” - and three derived attributes - family orientation, community orientation and cultural competence. The tool used to assess the PHC, called PCAtool - professional version, is capable of measuring the strength of the PHC orientation in the healthcare setting. This paper aims to evaluate the presence and extension of the PHC attributes in the São Carlos-SP’s primary healthcare network. For doing so, we had the participation of several “high educational level” professionals, such as doctors, dentists and nurses, from 12 Basic Health Unities (BHU) and 19 Family Health Unities (FHU) localized in 5 health districts (ARES). The PCAtool - professional version was applied to healthcare professionals in each healthcare unity, making a total of 64 answered forms. Each attribute was evaluated through the arithmetic mean score of its items and then was translated to a 0 to 10 scale. Values above 6.6 are considered high. The results showed that the attributes with better performance were the Family Orientation (8.51), the coordination - Information System (8.07), the integrality - Services provided (7.65), the integrality - Available services (7, 26) longitudinality (7.20), the coordination - integration of care (7,11).The worst performances were for community orientation ( 5.92) and first contact Login ( 4.63) . The attributes "first contact access" and community orientation are the weakest attributes both UBS as the USF. The USF performed significantly better (p value < 0.05) in the attributes access, coordinationinformation system, integrality, community orientation and scale for essential and general attributes. There is need for further studies to better understand the issues involved in the difference between models.