To investigate potential risk factors associated with Helicobacter pylori (Hp) infection, we performed a case-control study in 167 consecutively selected hospitalized children in Salvador, Brazil. Hp infection was identified by the presence of IgG against Hp in serum samples. Data were gathered using a structured questionnaire, 38.3% children were found to be seropositive and classified as cases, and 61.7% were seronegative controls. After multivariate analysis, independent variables associated with Hp infection included: the educational attainment of the child's provider > or = 11 years (OR 0.1, 95% CI 0.01-0.9), poor garbage disposal service (OR 2.2, 95% CI 1.0-4.9), thumb sucking (OR 4.6, 95% CI 1.1-19.8), brushing teeth more than once a day (OR 5.6, 95% CI 1.8-17.7), having a pet dog (OR 2.5, 95% CI 1.0-6.1), and a history of chronic urticaria (OR 4.0, 95% CI 1.5-10.8). The risk factors identified are consistent with some, but not all, previous studies supporting either oral-oral or faecal-oral transmission of Hp. Our data suggested that a higher educational attainment might play an important role in preventing Hp infection.
IntroducationIn Brazil, the National Health System (SUS) provides healthcare to the public. The system has multiple administrative databases; the major databases record hospital (SIH) and outpatient (SIA) procedures. Epidemiological information is collected for all populations in subsystems, such as mortality (SIM), live births (SINASC) and diseases of compulsory declaration (SINAN). Each subsystem has its own information system, which is able to provide information about consultations, clinical information and medicines dispensed. However, these systems are not linked, thereby preventing individual-centred analysis.
ObjectiveTo describe the methods and results of parameter setting that are needed to execute the probabilistic deduplication of large administrative and epidemiological databases in Brazil and to create a National Health Database Centred on the individual.
MethodsThis paper shows the results of a record linkage model to integrate data from SIH, SIA, SIM, and SINAN, which have different formats and attributes between them and over time. These data consist of 1.3 billion records from 2000-2015. Probabilistic and deterministic record linkages were used to deduplicate these data. The Kappa statistic and clerical review were used to ensure the quality of the linkage. The graph algorithm and depth-first search were used to generate the identifiers.
ResultsThe deterministic deduplication process resulted in a database with 403,113,527 possible unique individuals. After the probabilistic deduplication process of the former database was performed, 159,703,805 unique individuals were identified. This result had an estimated a false positive error rate of 3.3%, and the false negative error was estimated at 12.3%.
ConclusionsThe National Health Database centred on the individual was generated and will allow researchers to use real-world evidence to conduct clinical, epidemiological, economic and other studies. This database represents a significant cohort, spanning 15 years of historical data and preserving patient privacy. The success of the process described will allow repeating and appending the data for future years and enable important studies to promote SUS efficiency and provide better treatments for patients.
RESUMO Este artigo analisa a série histórica de um conjunto de indicadores, de 2002 a 2014, relacionados ao Sistema Único de Saúde do Brasil, embasado na metodologia da Proposta de Avaliação de Desempenho do Sistema de Saúde. Os resultados mostram que houve uma sensível melhoria nos indicadores de dimensão socioeconômica e nos da dimensão condições de saúde. A melhoria dos indicadores de condições de saúde pode estar relacionada ao incremento de suporte financeiro; ao incremento de recursos humanos; ao aumento do acesso às consultas médicas e aos serviços de alta complexidade; e a uma maior disponibilização de horas de profissionais de saúde para a população residente.
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