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Proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária

OBJECTIVE. To present a methodology for the empirical evaluation of primary health care (PHC) through the construction of digital representations of potential PHC coverage areas. METHODS. In this methodological study, potential areas were constructed by combinatorial analysis between census tracts a...

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Autores principales: Rocha, Thiago Augusto Hernandes, de Almeida, Dante Grapiuna, do Amaral, Pedro Vasconcelos Maia, da Silva, Núbia Cristina, Thomaz, Erika Bárbara Abreu Fonseca, Queiroz, Rejane Christine de Sousa, Barbosa, Allan Claudius Queiroz, Vissoci, João Ricardo Nickenig
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Organización Panamericana de la Salud 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526782/
https://www.ncbi.nlm.nih.gov/pubmed/31139211
http://dx.doi.org/10.26633/RPSP.2019.47
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author Rocha, Thiago Augusto Hernandes
de Almeida, Dante Grapiuna
do Amaral, Pedro Vasconcelos Maia
da Silva, Núbia Cristina
Thomaz, Erika Bárbara Abreu Fonseca
Queiroz, Rejane Christine de Sousa
Barbosa, Allan Claudius Queiroz
Vissoci, João Ricardo Nickenig
author_facet Rocha, Thiago Augusto Hernandes
de Almeida, Dante Grapiuna
do Amaral, Pedro Vasconcelos Maia
da Silva, Núbia Cristina
Thomaz, Erika Bárbara Abreu Fonseca
Queiroz, Rejane Christine de Sousa
Barbosa, Allan Claudius Queiroz
Vissoci, João Ricardo Nickenig
author_sort Rocha, Thiago Augusto Hernandes
collection PubMed
description OBJECTIVE. To present a methodology for the empirical evaluation of primary health care (PHC) through the construction of digital representations of potential PHC coverage areas. METHODS. In this methodological study, potential areas were constructed by combinatorial analysis between census tracts and the location of basic health units with working PHC teams in Brazil. Six rules were used to parameterize the algorithm for the construction of potential areas. Thus, six restrictions were applied to enable the model: the selection of census tracts near the basic health unit; contiguous sectors; mutually exclusive sectors; sectors located in the same municipality of basic health units; sum of 4 500 users per health team in each unit; and volume of population ascribed proportional to the number of PHC teams allocated to the unit. Based on 316 594 census tracts and 39 758 basic health units, a neighborhood matrix was developed. To that matrix, a graph algorithm was applied to test combinations of sectors that simultaneously met the stipulated rules. RESULTS. A total of 1 901 114 arcs were defined, connecting 30 351 census tracts, allowing the construction of 26 907 potential areas. Based on these results, intra-municipal analyses can be performed to monitor PHC indicators. Customizable algorithm parameters can be adjusted to accommodate different sets of rules which may be adapted to different countries. CONCLUSIONS. The use of geoprocessing approaches creates conditions for the assessment of PHC impact, based on secondary databases at various levels, such as intra-municipal, basic health unit, and even at the team level.
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spelling pubmed-65267822019-05-28 Proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária Rocha, Thiago Augusto Hernandes de Almeida, Dante Grapiuna do Amaral, Pedro Vasconcelos Maia da Silva, Núbia Cristina Thomaz, Erika Bárbara Abreu Fonseca Queiroz, Rejane Christine de Sousa Barbosa, Allan Claudius Queiroz Vissoci, João Ricardo Nickenig Rev Panam Salud Publica Artigo Original OBJECTIVE. To present a methodology for the empirical evaluation of primary health care (PHC) through the construction of digital representations of potential PHC coverage areas. METHODS. In this methodological study, potential areas were constructed by combinatorial analysis between census tracts and the location of basic health units with working PHC teams in Brazil. Six rules were used to parameterize the algorithm for the construction of potential areas. Thus, six restrictions were applied to enable the model: the selection of census tracts near the basic health unit; contiguous sectors; mutually exclusive sectors; sectors located in the same municipality of basic health units; sum of 4 500 users per health team in each unit; and volume of population ascribed proportional to the number of PHC teams allocated to the unit. Based on 316 594 census tracts and 39 758 basic health units, a neighborhood matrix was developed. To that matrix, a graph algorithm was applied to test combinations of sectors that simultaneously met the stipulated rules. RESULTS. A total of 1 901 114 arcs were defined, connecting 30 351 census tracts, allowing the construction of 26 907 potential areas. Based on these results, intra-municipal analyses can be performed to monitor PHC indicators. Customizable algorithm parameters can be adjusted to accommodate different sets of rules which may be adapted to different countries. CONCLUSIONS. The use of geoprocessing approaches creates conditions for the assessment of PHC impact, based on secondary databases at various levels, such as intra-municipal, basic health unit, and even at the team level. Organización Panamericana de la Salud 2019-05-24 /pmc/articles/PMC6526782/ /pubmed/31139211 http://dx.doi.org/10.26633/RPSP.2019.47 Text en https://creativecommons.org/licenses/by/4.0/ Este é um artigo de acesso aberto distribuído sob os termos da Licença Creative Commons Attribution-NonCommercial-NoDerivs 3.0 IGO, que permite o uso, distribuição e reprodução em qualquer meio, desde que o trabalho original seja devidamente citado. Não são permitidas modificações ou uso comercial dos artigos. Em qualquer reprodução do artigo, não deve haver nenhuma sugestão de que a OPAS ou o artigo avaliem qualquer organização ou produtos específicos. Não é permitido o uso do logotipo da OPAS. Este aviso deve ser preservado juntamente com o URL original do artigo.
spellingShingle Artigo Original
Rocha, Thiago Augusto Hernandes
de Almeida, Dante Grapiuna
do Amaral, Pedro Vasconcelos Maia
da Silva, Núbia Cristina
Thomaz, Erika Bárbara Abreu Fonseca
Queiroz, Rejane Christine de Sousa
Barbosa, Allan Claudius Queiroz
Vissoci, João Ricardo Nickenig
Proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária
title Proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária
title_full Proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária
title_fullStr Proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária
title_full_unstemmed Proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária
title_short Proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária
title_sort proposta de metodologia para estimar a área de cobertura potencial por equipes de atenção primária
topic Artigo Original
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526782/
https://www.ncbi.nlm.nih.gov/pubmed/31139211
http://dx.doi.org/10.26633/RPSP.2019.47
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