Factors associated with readmission to a general hospital in Brazil
Autor(a) principal: | |
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Data de Publicação: | 2005 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Cadernos de Saúde Pública |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2005000400021 |
Resumo: | The objective of this study was to compare different modeling strategies to identify individual and admissions characteristics associated with readmission to a general hospital. Routine data recorded in the Hospital Information System on all admissions to the Regional Public Hospital of Betim, Minas Gerais State, Brazil, from July 1996 to June 2000 were analyzed. Cox proportional hazards model and variants designed to deal with multiple-events data, like Andersen-Gill (AG), Prentice, Williams and Peterson (PWP), and random effects models were fitted to time between hospital admissions or censoring. For comparison purposes, a Poisson model was fitted to the total number of readmissions, using the same covariates. We analyzed 31,648 admissions of 26,198 patients, including 17,096 adults and 9,102 children. Estimates for the PWP and frailty models were very similar, and both approaches should be fitted and compared. If clinical characteristics are available, the PWP model should be used. Otherwise the random effects model can account for unmeasured differences, particularly some related to severity of the disease. These methodologies can help focus on various related readmission aspects such as diagnostic groups or medical specialties. |
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Factors associated with readmission to a general hospital in BrazilGeneral HospitalsHospital ReadmissionSurvival AnalysisThe objective of this study was to compare different modeling strategies to identify individual and admissions characteristics associated with readmission to a general hospital. Routine data recorded in the Hospital Information System on all admissions to the Regional Public Hospital of Betim, Minas Gerais State, Brazil, from July 1996 to June 2000 were analyzed. Cox proportional hazards model and variants designed to deal with multiple-events data, like Andersen-Gill (AG), Prentice, Williams and Peterson (PWP), and random effects models were fitted to time between hospital admissions or censoring. For comparison purposes, a Poisson model was fitted to the total number of readmissions, using the same covariates. We analyzed 31,648 admissions of 26,198 patients, including 17,096 adults and 9,102 children. Estimates for the PWP and frailty models were very similar, and both approaches should be fitted and compared. If clinical characteristics are available, the PWP model should be used. Otherwise the random effects model can account for unmeasured differences, particularly some related to severity of the disease. These methodologies can help focus on various related readmission aspects such as diagnostic groups or medical specialties.Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz2005-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2005000400021Cadernos de Saúde Pública v.21 n.4 2005reponame:Cadernos de Saúde Públicainstname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZ10.1590/S0102-311X2005000400021info:eu-repo/semantics/openAccessCastro,Mônica Silva Monteiro deCarvalho,Marilia SáTravassos,Cláudiaeng2005-07-11T00:00:00Zoai:scielo:S0102-311X2005000400021Revistahttp://cadernos.ensp.fiocruz.br/csp/https://old.scielo.br/oai/scielo-oai.phpcadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br1678-44640102-311Xopendoar:2005-07-11T00:00Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ)false |
dc.title.none.fl_str_mv |
Factors associated with readmission to a general hospital in Brazil |
title |
Factors associated with readmission to a general hospital in Brazil |
spellingShingle |
Factors associated with readmission to a general hospital in Brazil Castro,Mônica Silva Monteiro de General Hospitals Hospital Readmission Survival Analysis |
title_short |
Factors associated with readmission to a general hospital in Brazil |
title_full |
Factors associated with readmission to a general hospital in Brazil |
title_fullStr |
Factors associated with readmission to a general hospital in Brazil |
title_full_unstemmed |
Factors associated with readmission to a general hospital in Brazil |
title_sort |
Factors associated with readmission to a general hospital in Brazil |
author |
Castro,Mônica Silva Monteiro de |
author_facet |
Castro,Mônica Silva Monteiro de Carvalho,Marilia Sá Travassos,Cláudia |
author_role |
author |
author2 |
Carvalho,Marilia Sá Travassos,Cláudia |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Castro,Mônica Silva Monteiro de Carvalho,Marilia Sá Travassos,Cláudia |
dc.subject.por.fl_str_mv |
General Hospitals Hospital Readmission Survival Analysis |
topic |
General Hospitals Hospital Readmission Survival Analysis |
description |
The objective of this study was to compare different modeling strategies to identify individual and admissions characteristics associated with readmission to a general hospital. Routine data recorded in the Hospital Information System on all admissions to the Regional Public Hospital of Betim, Minas Gerais State, Brazil, from July 1996 to June 2000 were analyzed. Cox proportional hazards model and variants designed to deal with multiple-events data, like Andersen-Gill (AG), Prentice, Williams and Peterson (PWP), and random effects models were fitted to time between hospital admissions or censoring. For comparison purposes, a Poisson model was fitted to the total number of readmissions, using the same covariates. We analyzed 31,648 admissions of 26,198 patients, including 17,096 adults and 9,102 children. Estimates for the PWP and frailty models were very similar, and both approaches should be fitted and compared. If clinical characteristics are available, the PWP model should be used. Otherwise the random effects model can account for unmeasured differences, particularly some related to severity of the disease. These methodologies can help focus on various related readmission aspects such as diagnostic groups or medical specialties. |
publishDate |
2005 |
dc.date.none.fl_str_mv |
2005-08-01 |
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=S0102-311X2005000400021 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2005000400021 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0102-311X2005000400021 |
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 |
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz |
publisher.none.fl_str_mv |
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz |
dc.source.none.fl_str_mv |
Cadernos de Saúde Pública v.21 n.4 2005 reponame:Cadernos de Saúde Pública instname:Fundação Oswaldo Cruz (FIOCRUZ) instacron:FIOCRUZ |
instname_str |
Fundação Oswaldo Cruz (FIOCRUZ) |
instacron_str |
FIOCRUZ |
institution |
FIOCRUZ |
reponame_str |
Cadernos de Saúde Pública |
collection |
Cadernos de Saúde Pública |
repository.name.fl_str_mv |
Cadernos de Saúde Pública - Fundação Oswaldo Cruz (FIOCRUZ) |
repository.mail.fl_str_mv |
cadernos@ensp.fiocruz.br||cadernos@ensp.fiocruz.br |
_version_ |
1754115723758665728 |