Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFMG |
Texto Completo: | https://doi.org/10.23889/ijpds.v3i1.446 http://hdl.handle.net/1843/50902 https://orcid.org/0000-0001-5256-0577 https://orcid.org/0000-0002-0206-2462 https://orcid.org/0000-0001-5622-567X https://orcid.org/0000-0003-1956-5100 https://orcid.org/0000-0002-5880-5261 https://orcid.org/0000-0002-2614-2723 |
Resumo: | Objective: To 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. Methods: This 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 consistof 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 ofthe linkage. The graph algorithm and depth-first search were used to generate the identifiers. Results: The 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%. Conclusions: The 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. |
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2023-03-14T21:43:02Z2023-03-14T21:43:02Z201831https://doi.org/10.23889/ijpds.v3i1.4462399-4908http://hdl.handle.net/1843/50902https://orcid.org/0000-0001-5256-0577https://orcid.org/0000-0002-0206-2462https://orcid.org/0000-0001-5622-567Xhttps://orcid.org/0000-0003-1956-5100https://orcid.org/0000-0002-5880-5261https://orcid.org/0000-0002-2614-2723Objective: To 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. Methods: This 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 consistof 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 ofthe linkage. The graph algorithm and depth-first search were used to generate the identifiers. Results: The 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%. Conclusions: The 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.Objetivo: Descrever os métodos e resultados de parametrização necessários para realizar a desduplicação probabilística de grandes bancos de dados administrativos e epidemiológicos no Brasil e criar um Banco Nacional de Dados de Saúde Centrado no indivíduo. Métodos: Este artigo apresenta os resultados de um modelo de vinculação de registros para integrar dados do SIH, SIA, SIM e SINAN, que possuem diferentes formatos e atributos entre si e ao longo do tempo. Esses dados consistem em 1,3 bilhão de registros de 2000-2015. Ligações de registros probabilísticas e determinísticas foram usadas para desduplicar esses dados. A estatística Kappa e a revisão clerical foram usadas para garantir a qualidade da ligação. O algoritmo do grafo e a busca em profundidade foram usados para gerar os identificadores. Resultados: O processo de deduplicação determinística resultou em um banco de dados com 403.113.527 possíveis indivíduos únicos. Após a realização do processo de desduplicação probabilística da base de dados anterior, foram identificados 159.703.805 indivíduos únicos. Este resultado teve uma taxa de erro falso positivo estimada de 3,3%, e o erro falso negativo foi estimado em 12,3%. Conclusões: O Banco de Dados Nacional de Saúde centrado no indivíduo foi gerado e permitirá aos pesquisadores usar evidências do mundo real para realizar estudos clínicos, epidemiológicos, econômicos e outros. Este banco de dados representa uma coorte significativa, abrangendo 15 anos de dados históricos e preservando a privacidade do paciente. O sucesso do processo descrito permitirá repetir e anexar os dados para anos futuros e viabilizar estudos importantes para promover a eficiência do SUS e proporcionar melhores tratamentos aos pacientes.engUniversidade Federal de Minas GeraisUFMGBrasilFAR - DEPARTAMENTO DE FARMÁCIA SOCIALFARMACIA - FACULDADE DE FARMACIAICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃOMED - DEPARTAMENTO DE MEDICINA PREVENTIVA SOCIALThe International Journal of Population Data Science (IJPDS)Sistema Único de SaúdeBanco de dados - SaúdeMedicina - Processamento de dadosData linkageRecord linkageBrazilian health databaseSUS deduplicationBuilding the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015Construindo o Banco Nacional de Dados de Saúde Centrada no Indivíduo: Relacionamento Administrativo e Ficha Epidemiológica - Brasil, 2000-2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://ijpds.org/article/view/446Augusto Afonso Guerra JúniorRamon Gonçalves PereiraEli Iola Gurgel AndradeMariangela Leal CherchigliaLeonardo Vinícius Dias da SilvaJuliano ÁvilaNúbia SantosAfonso ReisFrancisco de Assis AcurcioWagner Meira Juniorapplication/pdfinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/50902/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALBuilding the National Database of Health Centred on the Individual Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015.pdfBuilding the National Database of Health Centred on the Individual Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015.pdfapplication/pdf700418https://repositorio.ufmg.br/bitstream/1843/50902/2/Building%20the%20National%20Database%20of%20Health%20Centred%20on%20the%20Individual%20Adminis-trative%20and%20Epidemiological%20Record%20Linkage%20-%20Brazil%2c%202000-2015.pdfa2d0bb91fee394ecc836ddcdeac7b519MD521843/509022023-03-14 18:57:10.717oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2023-03-14T21:57:10Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.pt_BR.fl_str_mv |
Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015 |
dc.title.alternative.pt_BR.fl_str_mv |
Construindo o Banco Nacional de Dados de Saúde Centrada no Indivíduo: Relacionamento Administrativo e Ficha Epidemiológica - Brasil, 2000-2015 |
title |
Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015 |
spellingShingle |
Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015 Augusto Afonso Guerra Júnior Data linkage Record linkage Brazilian health database SUS deduplication Sistema Único de Saúde Banco de dados - Saúde Medicina - Processamento de dados |
title_short |
Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015 |
title_full |
Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015 |
title_fullStr |
Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015 |
title_full_unstemmed |
Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015 |
title_sort |
Building the National Database of Health Centred on the Individual: Adminis-trative and Epidemiological Record Linkage - Brazil, 2000-2015 |
author |
Augusto Afonso Guerra Júnior |
author_facet |
Augusto Afonso Guerra Júnior Ramon Gonçalves Pereira Eli Iola Gurgel Andrade Mariangela Leal Cherchiglia Leonardo Vinícius Dias da Silva Juliano Ávila Núbia Santos Afonso Reis Francisco de Assis Acurcio Wagner Meira Junior |
author_role |
author |
author2 |
Ramon Gonçalves Pereira Eli Iola Gurgel Andrade Mariangela Leal Cherchiglia Leonardo Vinícius Dias da Silva Juliano Ávila Núbia Santos Afonso Reis Francisco de Assis Acurcio Wagner Meira Junior |
author2_role |
author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Augusto Afonso Guerra Júnior Ramon Gonçalves Pereira Eli Iola Gurgel Andrade Mariangela Leal Cherchiglia Leonardo Vinícius Dias da Silva Juliano Ávila Núbia Santos Afonso Reis Francisco de Assis Acurcio Wagner Meira Junior |
dc.subject.por.fl_str_mv |
Data linkage Record linkage Brazilian health database SUS deduplication |
topic |
Data linkage Record linkage Brazilian health database SUS deduplication Sistema Único de Saúde Banco de dados - Saúde Medicina - Processamento de dados |
dc.subject.other.pt_BR.fl_str_mv |
Sistema Único de Saúde Banco de dados - Saúde Medicina - Processamento de dados |
description |
Objective: To 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. Methods: This 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 consistof 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 ofthe linkage. The graph algorithm and depth-first search were used to generate the identifiers. Results: The 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%. Conclusions: The 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. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018 |
dc.date.accessioned.fl_str_mv |
2023-03-14T21:43:02Z |
dc.date.available.fl_str_mv |
2023-03-14T21:43:02Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1843/50902 |
dc.identifier.doi.pt_BR.fl_str_mv |
https://doi.org/10.23889/ijpds.v3i1.446 |
dc.identifier.issn.pt_BR.fl_str_mv |
2399-4908 |
dc.identifier.orcid.pt_BR.fl_str_mv |
https://orcid.org/0000-0001-5256-0577 https://orcid.org/0000-0002-0206-2462 https://orcid.org/0000-0001-5622-567X https://orcid.org/0000-0003-1956-5100 https://orcid.org/0000-0002-5880-5261 https://orcid.org/0000-0002-2614-2723 |
url |
https://doi.org/10.23889/ijpds.v3i1.446 http://hdl.handle.net/1843/50902 https://orcid.org/0000-0001-5256-0577 https://orcid.org/0000-0002-0206-2462 https://orcid.org/0000-0001-5622-567X https://orcid.org/0000-0003-1956-5100 https://orcid.org/0000-0002-5880-5261 https://orcid.org/0000-0002-2614-2723 |
identifier_str_mv |
2399-4908 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.none.fl_str_mv |
The International Journal of Population Data Science (IJPDS) |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
dc.publisher.initials.fl_str_mv |
UFMG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
FAR - DEPARTAMENTO DE FARMÁCIA SOCIAL FARMACIA - FACULDADE DE FARMACIA ICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO MED - DEPARTAMENTO DE MEDICINA PREVENTIVA SOCIAL |
publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
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reponame:Repositório Institucional da UFMG instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
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