Abstract
This population-based study aimed to determine the profile of early neonatal deaths in Belo Horizonte, Minas Gerais, Brazil, from 2000 to 2003. Profiles were analyzed from the perspective of avoidability, justified by persistently high early neonatal mortality rates in the city. Three profiles were generated for multiple causes of death from the perspective of fuzzy sets, using the Grade of Membership method. Birth weight and the hospital's corporate status were also related to the three profiles. Private hospitals were characterized by so-called "difficult-to-prevent deaths, with mention of congenital malformations" (profile 2). The Unified National Health System (SUS) generated two distinct profiles. Private maternity facilities contracted out by the SUS showed "preventable deaths" (profile 1), while "premature deaths" (profile 3) occurred in the public Federal and State maternity hospitals. This typology highlights the need to adopt differential policies in the SUS, focusing on evaluation and accreditation for maternity facilities contracted out by the SUS and--for the system as a whole--on the routine adoption of protocols for childbirth care and prophylactic measures that are known to reduce neonatal morbidity and mortality.
Highlights
O Brasil é signatário dos Objetivos de Desenvolvimento do Milênio (ODM), compromisso proposto às nações pela Organização Mundial da Saúde no ano 2000 1
Alfredo Balena 190, sala 10020, Belo Horizonte, MG 30130-100, Brasil. efranca@medicina.ufmg.br. This population-based study aimed to determine the profile of early neonatal deaths in Belo Horizonte, Minas Gerais, Brazil, from 2000 to 2003
Three profiles were generated for multiple causes of death from the perspective of fuzzy sets, using the Grade of Membership method
Summary
Analisaram-se inicialmente todos óbitos neonatais precoces de residentes em Belo Horizonte, ocorridos no período de 2000 a 2003, obtidos no Sistema de Informações sobre Mortalidade (SIM) da Secretaria de Saúde do município. Assume-se ainda que λkjl é a probabilidade de que a l-ésima resposta à variável j-ésima esteja associada com o k-ésimo conjunto nebuloso e que gik é o parâmetro que mensura o grau de similaridade das causas múltiplas de morte específicas de um dado indivíduo em relação às características de cada um dos K perfis extremos, com as seguintes restrições: 0 ≤ λkjl ≤ 1, Σk λkjl =1, 0 ≤ gik ≤ 1, Σk gik =1. As causas de morte fazem parte da conformação dos perfis e dos graus de pertencimento, enquanto que as estimativas de λkjl obtidas para as variáveis remanescentes foram empregadas como uma aproximação de variáveis de estratificação de cada um dos perfis extremos [15,16].
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