Descrição dos acidentes de trânsito em Cuiabá a partir dos sistemas de informação SIH/SUS, SIM e do relacionamento de bases de dados

• Autor(a) principal: Duarte, Flávia Guimarães Dias
• Data de Publicação: 2014
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Biblioteca Digital de Monografias da UFMT
• Texto Completo: http://bdm.ufmt.br/handle/1/573
• topic: CNPQ::CIENCIAS DA SAUDE::SAUDE COLETIVA; Sistemas de informação; Acidentes de trânsito; Relacionamento probabilístico de base de dados; Probabilistic linkage database; Information systems; Traffic accidents

Among the external causes, traffic accidents highlight the number of fatal and non-fatal casualties, and the magnitude of the problem for the health sector and social welfare. Data on mortality and morbidity of these injuries are available in information systems in Brazil, though still inconsistent. One of the strategies used to qualify the data of traffic accidents is the probabilistic databases - Linkage. Objective: The objective was to verify, by means of probabilistic relationships between databases SIM and SIH / SUS, the gain in quality of information on deaths and hospitalizations resulting from traffic accidents, which occurred in 2012 in Cuiaba Methodology.: descriptive exploratory study based on probabilistic linkage of deaths recorded in the Mortality Information System (SIM) and hospitalizations recorded in Hospital Admissions Information System (SIH / SUS) of victims of traffic accidents occurring in Cuiaba/MT in 2012. Exploratory analysis of the records of deaths and hospitalizations and all the true pairs formed by the relationship as a secondary diagnosis of SIH/SUS and the underlying cause of death.Results: 39,078 hospitalizations were reported, including 1,606 traffic accidents and 73.7% of these motorcyclists, 80.6% male and 57.2% aged 20 to 39 years. The mortality rate was recorded 4,982 occurred in Cuiaba, with 232 traffic accidents, with the same characteristics of hospitalization. The relationship was conducted in five blocking steps resulting in 110,839 possible pairs, 3,494 pairs (3.2%) and of these 2,581 (73.9%) true pairs. In the first situation analysis Lied 59 real traffic accidents in the two systems peers. Was frequent divergences identified as causes of hospitalization and deaths recorded for the same victim Conclusion: The probabilistic linkage database was presented as an important tool in data classification and scaling victims of traffic accidents in Cuiaba.