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Barreto ML, Ichihara MY, Almeida BA, Barreto ME, Cabral L, Fiaccone RL, Carreiro RP, Teles CAS, Pitta R, Penna GO, Barral-Netto M, Ali MS, Barbosa G, Denaxas S, Rodrigues LC, Smeeth L. The Centre for Data and Knowledge Integration for Health (CIDACS): Linking Health and Social Data in Brazil. Int J Popul Data Sci 2019; 4:1140. [PMID: 34095542 PMCID: PMC8142622 DOI: 10.23889/ijpds.v4i2.1140] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
The Centre for Data and Knowledge Integration for Health (CIDACS) was created in 2016 in Salvador, Bahia-Brazil with the objective of integrating data and knowledge aiming to answer scientific questions related to the health of the Brazilian population. This article details our experiences in the establishment and operations of CIDACS, as well as efforts made to obtain high-quality linked data while adhering to security, ethical use and privacy issues. Every effort has been made to conduct operations while implementing appropriate structures, procedures, processes and controls over the original and integrated databases in order to provide adequate datasets to answer relevant research questions. Looking forward, CIDACS is expected to be an important resource for researchers and policymakers interested in enhancing the evidence base pertaining to different aspects of health, in particular when investigating, from a nation-wide perspective, the role of social determinants of health and the effects of social and environmental policies on different health outcomes.
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Affiliation(s)
- ML Barreto
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
- Institute of Collective Health, Federal University of Bahia (UFBA), Salvador, Brazil.
| | - MY Ichihara
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
- Institute of Collective Health, Federal University of Bahia (UFBA), Salvador, Brazil.
| | - BA Almeida
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
| | - ME Barreto
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
- Computer Science Department, Federal University of Bahia (UFBA), Salvador, Brazil.
| | - L Cabral
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
| | - RL Fiaccone
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
- Statistics Department, Federal University of Bahia (UFBA), Brazil.
| | - RP Carreiro
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
| | - CAS Teles
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
| | - R Pitta
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
| | - GO Penna
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
- Tropical Medicine Centre, University of Brasília (UnB), Brazil.
- Escola Fiocruz de Governo, FIOCRUZ Brasília, Brazil.
| | - M Barral-Netto
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
| | - MS Ali
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
- Center for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, United Kingdom.
| | - G Barbosa
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
| | - S Denaxas
- Institute of Health Informatics, University College London, United Kingdom.
| | - LC Rodrigues
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, United Kingdom.
| | - L Smeeth
- Centre for Data and Knowledge Integration for Health (CIDACS), Gonçalo Moniz Institute, Oswaldo Cruz Foundation (FIOCRUZ), Salvador, Brazil.
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, United Kingdom.
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Brustulin R, Marson PG. Inclusão de etapa de pós-processamento determinístico para o aumento de performance do relacionamento (linkage) probabilístico. CAD SAUDE PUBLICA 2018; 34:e00088117. [DOI: 10.1590/0102-311x00088117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 03/12/2018] [Indexed: 11/22/2022] Open
Abstract
O objetivo do presente estudo foi demonstrar a aplicação de uma etapa de pós-processamento determinístico, baseada em medidas de similaridade, para aumentar a performance do relacionamento probabilístico com e sem a etapa de revisão manual. As bases de dados utilizadas no estudo foram o Sistema de Informação de Agravos de Notificação e o Sistema de Informações sobre Mortalidade, no período de 2007 a 2015, do Município de Palmas, Tocantins, Brasil. O software probabilístico utilizado foi o OpenRecLink; foi desenvolvida e aplicada uma etapa de pós-processamento determinístico aos dados obtidos por três diferentes estratégias de pareamento probabilístico. As três estratégias foram comparadas entre si e acrescidas da etapa de pós-processamento determinístico. A sensibilidade das estratégias probabilísticas sem revisão manual variou entre 69,1% e 77,8%, já as mesmas estratégias, acrescidas da etapa de pós-processamento determinístico, apresentaram uma variação entre 92,9% e 96,3%. A sensibilidade de duas estratégias probabilísticas com revisão manual foi semelhante à obtida pela etapa de pós-processamento determinístico, no entanto, o número de pares destinados à revisão manual pelas duas estratégias probabilísticas variou entre 1.177 e 1.132 registros, contra 149 e 145 após a etapa de pós-processamento determinístico. Nossos resultados sugerem que a etapa de pós-processamento determinístico é uma opção promissora, tanto para aumentar a sensibilidade quanto para reduzir o número de pares que precisam ser revisados manualmente, ou mesmo para eliminar sua necessidade.
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