Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | São Paulo medical journal (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-31802021000200178 |
Resumo: | ABSTRACT BACKGROUND: The fragility of healthcare systems worldwide had not been exposed by any pandemic until now. The lack of integrated methods for bed capacity planning compromises the effectiveness of public and private hospitals’ services. OBJECTIVES: To estimate the impact of the COVID-19 pandemic on the provision of intensive care unit and clinical beds for Brazilian states, using an integrated model. DESIGN AND SETTING: Experimental study applying healthcare informatics to data on COVID-19 cases from the official electronic platform of the Brazilian Ministry of Health. METHODS: A predictive model based on the historical records of Brazilian states was developed to estimate the need for hospital beds during the COVID-19 pandemic. RESULTS: The proposed model projected in advance that there was a lack of 22,771 hospital beds for Brazilian states, of which 38.95% were ICU beds, and 61.05% were clinical beds. CONCLUSIONS: The proposed approach provides valuable information to help hospital managers anticipate actions for improving healthcare system capacity. |
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Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive modelPublic health administrationBed occupancyCoronavirus infectionsPandemicsHospital bed capacityPublic health planningPopulation dynamicsCOVID-19 pandemicCOVID-19 virus diseaseCompartmental modelABSTRACT BACKGROUND: The fragility of healthcare systems worldwide had not been exposed by any pandemic until now. The lack of integrated methods for bed capacity planning compromises the effectiveness of public and private hospitals’ services. OBJECTIVES: To estimate the impact of the COVID-19 pandemic on the provision of intensive care unit and clinical beds for Brazilian states, using an integrated model. DESIGN AND SETTING: Experimental study applying healthcare informatics to data on COVID-19 cases from the official electronic platform of the Brazilian Ministry of Health. METHODS: A predictive model based on the historical records of Brazilian states was developed to estimate the need for hospital beds during the COVID-19 pandemic. RESULTS: The proposed model projected in advance that there was a lack of 22,771 hospital beds for Brazilian states, of which 38.95% were ICU beds, and 61.05% were clinical beds. CONCLUSIONS: The proposed approach provides valuable information to help hospital managers anticipate actions for improving healthcare system capacity.Associação Paulista de Medicina - APM2021-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-31802021000200178Sao Paulo Medical Journal v.139 n.2 2021reponame:São Paulo medical journal (Online)instname:Associação Paulista de Medicinainstacron:APM10.1590/1516-3180.2020.0517.r1.0212020info:eu-repo/semantics/openAccessAlmeida,João Flávio de FreitasConceição,Samuel VieiraPinto,Luiz RicardoHorta,Cláudia Júlia GuimarãesMagalhães,Virgínia SilvaCampos,Francisco Carlos Cardoso deeng2021-03-31T00:00:00Zoai:scielo:S1516-31802021000200178Revistahttp://www.scielo.br/spmjhttps://old.scielo.br/oai/scielo-oai.phprevistas@apm.org.br1806-94601516-3180opendoar:2021-03-31T00:00São Paulo medical journal (Online) - Associação Paulista de Medicinafalse |
dc.title.none.fl_str_mv |
Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model |
title |
Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model |
spellingShingle |
Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model Almeida,João Flávio de Freitas Public health administration Bed occupancy Coronavirus infections Pandemics Hospital bed capacity Public health planning Population dynamics COVID-19 pandemic COVID-19 virus disease Compartmental model |
title_short |
Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model |
title_full |
Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model |
title_fullStr |
Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model |
title_full_unstemmed |
Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model |
title_sort |
Estimating Brazilian states’ demands for intensive care unit and clinical hospital beds during the COVID-19 pandemic: development of a predictive model |
author |
Almeida,João Flávio de Freitas |
author_facet |
Almeida,João Flávio de Freitas Conceição,Samuel Vieira Pinto,Luiz Ricardo Horta,Cláudia Júlia Guimarães Magalhães,Virgínia Silva Campos,Francisco Carlos Cardoso de |
author_role |
author |
author2 |
Conceição,Samuel Vieira Pinto,Luiz Ricardo Horta,Cláudia Júlia Guimarães Magalhães,Virgínia Silva Campos,Francisco Carlos Cardoso de |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Almeida,João Flávio de Freitas Conceição,Samuel Vieira Pinto,Luiz Ricardo Horta,Cláudia Júlia Guimarães Magalhães,Virgínia Silva Campos,Francisco Carlos Cardoso de |
dc.subject.por.fl_str_mv |
Public health administration Bed occupancy Coronavirus infections Pandemics Hospital bed capacity Public health planning Population dynamics COVID-19 pandemic COVID-19 virus disease Compartmental model |
topic |
Public health administration Bed occupancy Coronavirus infections Pandemics Hospital bed capacity Public health planning Population dynamics COVID-19 pandemic COVID-19 virus disease Compartmental model |
description |
ABSTRACT BACKGROUND: The fragility of healthcare systems worldwide had not been exposed by any pandemic until now. The lack of integrated methods for bed capacity planning compromises the effectiveness of public and private hospitals’ services. OBJECTIVES: To estimate the impact of the COVID-19 pandemic on the provision of intensive care unit and clinical beds for Brazilian states, using an integrated model. DESIGN AND SETTING: Experimental study applying healthcare informatics to data on COVID-19 cases from the official electronic platform of the Brazilian Ministry of Health. METHODS: A predictive model based on the historical records of Brazilian states was developed to estimate the need for hospital beds during the COVID-19 pandemic. RESULTS: The proposed model projected in advance that there was a lack of 22,771 hospital beds for Brazilian states, of which 38.95% were ICU beds, and 61.05% were clinical beds. CONCLUSIONS: The proposed approach provides valuable information to help hospital managers anticipate actions for improving healthcare system capacity. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-04-01 |
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=S1516-31802021000200178 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-31802021000200178 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1516-3180.2020.0517.r1.0212020 |
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 Paulista de Medicina - APM |
publisher.none.fl_str_mv |
Associação Paulista de Medicina - APM |
dc.source.none.fl_str_mv |
Sao Paulo Medical Journal v.139 n.2 2021 reponame:São Paulo medical journal (Online) instname:Associação Paulista de Medicina instacron:APM |
instname_str |
Associação Paulista de Medicina |
instacron_str |
APM |
institution |
APM |
reponame_str |
São Paulo medical journal (Online) |
collection |
São Paulo medical journal (Online) |
repository.name.fl_str_mv |
São Paulo medical journal (Online) - Associação Paulista de Medicina |
repository.mail.fl_str_mv |
revistas@apm.org.br |
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1754209267733233664 |