Medical centers location and specialists’ allocation: a healthcare planning case study
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Production |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132019000100805 |
Resumo: | Abstract Paper aims To set the locations of new medical centers to meet the population’s secondary care needs, the additional number of specialists, equipment, and an installation sequence at municipalities. Originality We developed descriptive cost functions models and adopted aggregate data from official sources to set parameters of an integrated MILP model. Research method A case study at the Brazilian state of Minas Gerais. Main findings For every scenario, the recommended locations set centers dispersed over the state area, in cities with the minimum required infrastructure. We also propose a scenario of secondary care network re-design and demonstrate the reduced cost of such a strategy. Implications for theory and practice To automate the decision process, we developed a web-based system, providing flexibility and scientific-based results. Finally, we propose a sequence for installing 43 new medical centers and improving the capacity of 27 existing infrastructure based on equality principles. |
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Medical centers location and specialists’ allocation: a healthcare planning case studyPublic healthcare planningFacility locationMixed integer linear programmingAbstract Paper aims To set the locations of new medical centers to meet the population’s secondary care needs, the additional number of specialists, equipment, and an installation sequence at municipalities. Originality We developed descriptive cost functions models and adopted aggregate data from official sources to set parameters of an integrated MILP model. Research method A case study at the Brazilian state of Minas Gerais. Main findings For every scenario, the recommended locations set centers dispersed over the state area, in cities with the minimum required infrastructure. We also propose a scenario of secondary care network re-design and demonstrate the reduced cost of such a strategy. Implications for theory and practice To automate the decision process, we developed a web-based system, providing flexibility and scientific-based results. Finally, we propose a sequence for installing 43 new medical centers and improving the capacity of 27 existing infrastructure based on equality principles.Associação Brasileira de Engenharia de Produção2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132019000100805Production v.29 2019reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/0103-6513.20190006info:eu-repo/semantics/openAccessAlmeida,João Flávio de FreitasPinto,Luiz RicardoConceição,Samuel VieiraCampos,Francisco Carlos Cardoso deeng2019-11-27T00:00:00Zoai:scielo:S0103-65132019000100805Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2019-11-27T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
Medical centers location and specialists’ allocation: a healthcare planning case study |
title |
Medical centers location and specialists’ allocation: a healthcare planning case study |
spellingShingle |
Medical centers location and specialists’ allocation: a healthcare planning case study Almeida,João Flávio de Freitas Public healthcare planning Facility location Mixed integer linear programming |
title_short |
Medical centers location and specialists’ allocation: a healthcare planning case study |
title_full |
Medical centers location and specialists’ allocation: a healthcare planning case study |
title_fullStr |
Medical centers location and specialists’ allocation: a healthcare planning case study |
title_full_unstemmed |
Medical centers location and specialists’ allocation: a healthcare planning case study |
title_sort |
Medical centers location and specialists’ allocation: a healthcare planning case study |
author |
Almeida,João Flávio de Freitas |
author_facet |
Almeida,João Flávio de Freitas Pinto,Luiz Ricardo Conceição,Samuel Vieira Campos,Francisco Carlos Cardoso de |
author_role |
author |
author2 |
Pinto,Luiz Ricardo Conceição,Samuel Vieira Campos,Francisco Carlos Cardoso de |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Almeida,João Flávio de Freitas Pinto,Luiz Ricardo Conceição,Samuel Vieira Campos,Francisco Carlos Cardoso de |
dc.subject.por.fl_str_mv |
Public healthcare planning Facility location Mixed integer linear programming |
topic |
Public healthcare planning Facility location Mixed integer linear programming |
description |
Abstract Paper aims To set the locations of new medical centers to meet the population’s secondary care needs, the additional number of specialists, equipment, and an installation sequence at municipalities. Originality We developed descriptive cost functions models and adopted aggregate data from official sources to set parameters of an integrated MILP model. Research method A case study at the Brazilian state of Minas Gerais. Main findings For every scenario, the recommended locations set centers dispersed over the state area, in cities with the minimum required infrastructure. We also propose a scenario of secondary care network re-design and demonstrate the reduced cost of such a strategy. Implications for theory and practice To automate the decision process, we developed a web-based system, providing flexibility and scientific-based results. Finally, we propose a sequence for installing 43 new medical centers and improving the capacity of 27 existing infrastructure based on equality principles. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132019000100805 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132019000100805 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0103-6513.20190006 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
dc.source.none.fl_str_mv |
Production v.29 2019 reponame:Production instname:Associação Brasileira de Engenharia de Produção (ABEPRO) instacron:ABEPRO |
instname_str |
Associação Brasileira de Engenharia de Produção (ABEPRO) |
instacron_str |
ABEPRO |
institution |
ABEPRO |
reponame_str |
Production |
collection |
Production |
repository.name.fl_str_mv |
Production - Associação Brasileira de Engenharia de Produção (ABEPRO) |
repository.mail.fl_str_mv |
||production@editoracubo.com.br |
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1754213154516107264 |