Association between hospitalisation for ambulatory care-sensitive conditions and primary health care physician specialisation: a cross-sectional ecological study in curitiba (brazil)

• Autor(a) principal: Marcelo Pellizzaro Dias Afonso
• Data de Publicação: 2017
• Outros Autores: Helena e Shimizu, Edgar Merchan-hamann, Walter m Ramalho, Tarcisio Afonso
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFMG
• Texto Completo: http://hdl.handle.net/1843/60730
• topic: Hospitalization; Primary Health Care; Hospitalization; Primary Health Care

Introduction Hospitalisation for ambulatory care-sensitive conditions (HACSCs) is frequently used as an indicator of the quality and effectiveness of primary healthcare (PHC) services around the world. The aim of the present study was to evaluate whether the PHC model (family health strategy (FHS) x conventional) and the availability of specialised PHC physicians is associated or not with total hospitalisation or HACSCs in the National Health System (SUS) of the municipality of Curitiba, Paraná state (PR), Brazil.Methodology:This is a cross-sectional ecological study using multiple linear regression with socioeconomic and professional data from municipal health units (MHUs) between 1 April 2014 and 31 March 2015.Results: After adjustment for age and sex and control of socioeconomic variables, the FHS model was associated with six fewer HACSCs a year per 10 000 inhabitants in relation to the conventional model and the availability of one family physician at each FHS model MHU per 10 000 inhabitants was associated with 1.1 fewer HACSCs for heart failure a year per 10 000 inhabitants. Basic specialists (clinicians, paediatricians and obstetrician/gynaecologists) and subspecialists showed no significant association with HACSC rates.Conclusion These results obtained in a major Brazilian city reinforce the role of FHS as a priority PHC model in the country and indicate the potentially significant impact of specialising in family medicine on improving the health conditions of the population.