Optimization model for the installation of SAMU bases: application in Natal-RN
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRN |
Texto Completo: | https://repositorio.ufrn.br/handle/123456789/33259 |
Resumo: | A Medical Emergency Service is responsible for providing pre-hospital acute care and has the key role of providing good services to people, especially in urban areas. In Brazil, the Emergency Medical Assistance Service (SAMU) operates in several cities and aims to reach the victim early after an injury to his health has occurred, by sending vehicles manned by trained personnel. The objective of this study was the application of a mathematical model aiming to designate neighborhoods for the installation of new SAMU bases that minimize the distance traveled by the ambulances in the city of Natal / RN. After data collection, it was found that the average service response time of the SAMU was over 40 minutes for calls classified as red code. The average number of calls in 2015 was 1,930 per month, in this city with a population of 800,000. The application of the model allowed for the simulation of scenarios with the installation of 3 to 8 fixed bases. There was a significant reduction in the distance traveled by the ambulances which reached 48%, after the installation of eight bases. In other words, there was a reduction of 6,560 kilometers traveled per month by ambulances. The new SAMU bases are being installed in containers to minimize installation costs and easy relocation in the near future |
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Cabral, Eric Lucas dos SantosCastro, Wilkson Ricardo SilvaFrancisco, Claudia Aparecida CavalheiroSouza, Ricardo Pires de2021-08-30T21:06:14Z2021-08-30T21:06:14Z2019CABRAL, E. L. S.; CASTRO, W. R. S.; FRANCISCO, C. A. C.; SOUZA, R.P.. Optimization model for the installation of SAMU bases: application in Natal-RN. GEPROS. Gestão da Produção, Operações e Sistemas, v. 14, p. 161-173, 2019. Disponível em: https://revista.feb.unesp.br/index.php/gepros/article/view/2459. Acesso em: 18 mai. 2021. https://doi.org/10.15675/gepros.v14i5.2459.1984-2430https://repositorio.ufrn.br/handle/123456789/3325910.15675/gepros.v14i5.2459Universidade Estadual Paulista (UNESP)Attribution-NonCommercial 3.0 Brazilhttp://creativecommons.org/licenses/by-nc/3.0/br/info:eu-repo/semantics/openAccessEmergency medical serviceHealth careModel simulationOptimization model for the installation of SAMU bases: application in Natal-RNinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleA Medical Emergency Service is responsible for providing pre-hospital acute care and has the key role of providing good services to people, especially in urban areas. In Brazil, the Emergency Medical Assistance Service (SAMU) operates in several cities and aims to reach the victim early after an injury to his health has occurred, by sending vehicles manned by trained personnel. The objective of this study was the application of a mathematical model aiming to designate neighborhoods for the installation of new SAMU bases that minimize the distance traveled by the ambulances in the city of Natal / RN. After data collection, it was found that the average service response time of the SAMU was over 40 minutes for calls classified as red code. The average number of calls in 2015 was 1,930 per month, in this city with a population of 800,000. The application of the model allowed for the simulation of scenarios with the installation of 3 to 8 fixed bases. There was a significant reduction in the distance traveled by the ambulances which reached 48%, after the installation of eight bases. In other words, there was a reduction of 6,560 kilometers traveled per month by ambulances. The new SAMU bases are being installed in containers to minimize installation costs and easy relocation in the near futureengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNORIGINALOptimizationModelInstallation_Souza_2019.pdfOptimizationModelInstallation_Souza_2019.pdfapplication/pdf910872https://repositorio.ufrn.br/bitstream/123456789/33259/1/OptimizationModelInstallation_Souza_2019.pdfd22309163f6700be141215bd773db96aMD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8920https://repositorio.ufrn.br/bitstream/123456789/33259/2/license_rdf728dfda2fa81b274c619d08d1dfc1a03MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81484https://repositorio.ufrn.br/bitstream/123456789/33259/3/license.txte9597aa2854d128fd968be5edc8a28d9MD53123456789/332592021-08-30 18:06:14.567oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2021-08-30T21:06:14Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false |
dc.title.pt_BR.fl_str_mv |
Optimization model for the installation of SAMU bases: application in Natal-RN |
title |
Optimization model for the installation of SAMU bases: application in Natal-RN |
spellingShingle |
Optimization model for the installation of SAMU bases: application in Natal-RN Cabral, Eric Lucas dos Santos Emergency medical service Health care Model simulation |
title_short |
Optimization model for the installation of SAMU bases: application in Natal-RN |
title_full |
Optimization model for the installation of SAMU bases: application in Natal-RN |
title_fullStr |
Optimization model for the installation of SAMU bases: application in Natal-RN |
title_full_unstemmed |
Optimization model for the installation of SAMU bases: application in Natal-RN |
title_sort |
Optimization model for the installation of SAMU bases: application in Natal-RN |
author |
Cabral, Eric Lucas dos Santos |
author_facet |
Cabral, Eric Lucas dos Santos Castro, Wilkson Ricardo Silva Francisco, Claudia Aparecida Cavalheiro Souza, Ricardo Pires de |
author_role |
author |
author2 |
Castro, Wilkson Ricardo Silva Francisco, Claudia Aparecida Cavalheiro Souza, Ricardo Pires de |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Cabral, Eric Lucas dos Santos Castro, Wilkson Ricardo Silva Francisco, Claudia Aparecida Cavalheiro Souza, Ricardo Pires de |
dc.subject.por.fl_str_mv |
Emergency medical service Health care Model simulation |
topic |
Emergency medical service Health care Model simulation |
description |
A Medical Emergency Service is responsible for providing pre-hospital acute care and has the key role of providing good services to people, especially in urban areas. In Brazil, the Emergency Medical Assistance Service (SAMU) operates in several cities and aims to reach the victim early after an injury to his health has occurred, by sending vehicles manned by trained personnel. The objective of this study was the application of a mathematical model aiming to designate neighborhoods for the installation of new SAMU bases that minimize the distance traveled by the ambulances in the city of Natal / RN. After data collection, it was found that the average service response time of the SAMU was over 40 minutes for calls classified as red code. The average number of calls in 2015 was 1,930 per month, in this city with a population of 800,000. The application of the model allowed for the simulation of scenarios with the installation of 3 to 8 fixed bases. There was a significant reduction in the distance traveled by the ambulances which reached 48%, after the installation of eight bases. In other words, there was a reduction of 6,560 kilometers traveled per month by ambulances. The new SAMU bases are being installed in containers to minimize installation costs and easy relocation in the near future |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019 |
dc.date.accessioned.fl_str_mv |
2021-08-30T21:06:14Z |
dc.date.available.fl_str_mv |
2021-08-30T21:06:14Z |
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.citation.fl_str_mv |
CABRAL, E. L. S.; CASTRO, W. R. S.; FRANCISCO, C. A. C.; SOUZA, R.P.. Optimization model for the installation of SAMU bases: application in Natal-RN. GEPROS. Gestão da Produção, Operações e Sistemas, v. 14, p. 161-173, 2019. Disponível em: https://revista.feb.unesp.br/index.php/gepros/article/view/2459. Acesso em: 18 mai. 2021. https://doi.org/10.15675/gepros.v14i5.2459. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufrn.br/handle/123456789/33259 |
dc.identifier.issn.none.fl_str_mv |
1984-2430 |
dc.identifier.doi.none.fl_str_mv |
10.15675/gepros.v14i5.2459 |
identifier_str_mv |
CABRAL, E. L. S.; CASTRO, W. R. S.; FRANCISCO, C. A. C.; SOUZA, R.P.. Optimization model for the installation of SAMU bases: application in Natal-RN. GEPROS. Gestão da Produção, Operações e Sistemas, v. 14, p. 161-173, 2019. Disponível em: https://revista.feb.unesp.br/index.php/gepros/article/view/2459. Acesso em: 18 mai. 2021. https://doi.org/10.15675/gepros.v14i5.2459. 1984-2430 10.15675/gepros.v14i5.2459 |
url |
https://repositorio.ufrn.br/handle/123456789/33259 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial 3.0 Brazil http://creativecommons.org/licenses/by-nc/3.0/br/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial 3.0 Brazil http://creativecommons.org/licenses/by-nc/3.0/br/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
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Universidade Estadual Paulista (UNESP) |
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