Information Systems Sus: A Historical Perspective and Policies of Computing and Information

Abstract

RESUMO: O Sistema Único de Saúde (SUS) é apoiado por um conjunto de sistemas de informação em seus processos administrativos, ambulatoriais, hospitalares, epidemiológicos e nas diversas ações do Ministério da Saúde. Esse artigo apresenta uma revisão de bibliografia contextualizando a criação do Datasus como um dos eventos de estruturação do SUS, enumera as principais políticas implementadas em informática, descreve o portfólio de aplicações e discute três características dessas aplicações que demandam projetos de melhoria: a integração entre as aplicações e seus bancos de dados, a cobertura de eventos de saúde e o apoio à gestão.Palavras-Chave: Gestão em saúde. Sistema Único de Saúde. Sistemas de informação. SUMMARY:A set of information systems supporting the Unified Health System (SUS) in its administrative processes, ambulatory, hospital, epidemiological and in several actions of the Ministry of Health This article presents a review of the literature, contextualizing the creation of Datasus as a structuring the events of the SUS, lists the major policies implemented in information technology, describes the portfolio of applications and discusses three characteristics of those applications that require improvement projects: the integration between applications and their databases, covering events and health management support.

Tendência da incompletude das estatísticas vitais no período neonatal, estado do Rio de Janeiro, 1999-2014*

“…This finding reflects a national trend, 20,21 resulting from investment in changes to the systems in keeping with the valuing of epidemiological information in health policies. 24 Decentralization of these information systems has enabled them to get closer to their respective data collection sources, thus facilitating monitoring and increasing data quality. 20,21,24 0 (-14.5;12.3) -66.3 c (83.3;32.1) 1.1 (-6.6;9.5) In the time series analysis of the joinpoint, when the trend pattern changes, the periods are separated ans the final year of a period coincides with the beginning year of the next period.…”

“…24 Decentralization of these information systems has enabled them to get closer to their respective data collection sources, thus facilitating monitoring and increasing data quality. 20,21,24 0 (-14.5;12.3) -66.3 c (83.3;32.1) 1.1 (-6.6;9.5) In the time series analysis of the joinpoint, when the trend pattern changes, the periods are separated ans the final year of a period coincides with the beginning year of the next period. Note: Romero & Cunha's classification for incomplete filling in of an information system data field: excellent, under 5% incompleteness; good, 5% <10%; regular, 10% <20%; poor, 20%-50%; and very poor, 50% or over.…”