Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions

Detalhes bibliográficos
Autor(a) principal: Sá, Carla Angélica da Silva Pinto de
Data de Publicação: 2007
Outros Autores: Dismuke, Clara E., Guimarães, Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/7627
Resumo: The literature on length of stay and hospital discharge is often used to inform policy regarding hospital payment and quality. This literature has evolved from the use of ordinary least squares estimation of linear and log-linear models to the use of survival and competing risk models that control for unobserved patient and hospital heterogeneity. However, the authors tend to adopt different distributional assumptions and often motivate the choice of specific functional forms for the baseline hazard based on the visual inspection of the hazard rate plots. We contribute to this literature by showing that parameter estimates for patient and hospital characteristics in length of stay models are particularly sensitive to underlying assumptions regarding the hazard function. Moreover, we demonstrate that the inability to distinguish between competing risks of discharge destination may lead to distortions in the effect of important explanatory variables such as intensive care utilization.
id RCAP_44cd0c2213e3601e12a492da1c4c486d
oai_identifier_str oai:repositorium.sdum.uminho.pt:1822/7627
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptionsOutcomesHazard functionsUnobserved heterogeneityScience & TechnologyThe literature on length of stay and hospital discharge is often used to inform policy regarding hospital payment and quality. This literature has evolved from the use of ordinary least squares estimation of linear and log-linear models to the use of survival and competing risk models that control for unobserved patient and hospital heterogeneity. However, the authors tend to adopt different distributional assumptions and often motivate the choice of specific functional forms for the baseline hazard based on the visual inspection of the hazard rate plots. We contribute to this literature by showing that parameter estimates for patient and hospital characteristics in length of stay models are particularly sensitive to underlying assumptions regarding the hazard function. Moreover, we demonstrate that the inability to distinguish between competing risks of discharge destination may lead to distortions in the effect of important explanatory variables such as intensive care utilization.Fundação para a Ciência e a Tecnologia (FCT) - SFRH/BD/5054/2001; POCT/ECO/34666/2000)SpringerUniversidade do MinhoSá, Carla Angélica da Silva Pinto deDismuke, Clara E.Guimarães, Paulo20072007-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/7627eng1387-374110.1007/s10742-007-0020-9info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:38:17Zoai:repositorium.sdum.uminho.pt:1822/7627Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:34:41.918541Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions
title Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions
spellingShingle Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions
Sá, Carla Angélica da Silva Pinto de
Outcomes
Hazard functions
Unobserved heterogeneity
Science & Technology
title_short Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions
title_full Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions
title_fullStr Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions
title_full_unstemmed Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions
title_sort Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions
author Sá, Carla Angélica da Silva Pinto de
author_facet Sá, Carla Angélica da Silva Pinto de
Dismuke, Clara E.
Guimarães, Paulo
author_role author
author2 Dismuke, Clara E.
Guimarães, Paulo
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Sá, Carla Angélica da Silva Pinto de
Dismuke, Clara E.
Guimarães, Paulo
dc.subject.por.fl_str_mv Outcomes
Hazard functions
Unobserved heterogeneity
Science & Technology
topic Outcomes
Hazard functions
Unobserved heterogeneity
Science & Technology
description The literature on length of stay and hospital discharge is often used to inform policy regarding hospital payment and quality. This literature has evolved from the use of ordinary least squares estimation of linear and log-linear models to the use of survival and competing risk models that control for unobserved patient and hospital heterogeneity. However, the authors tend to adopt different distributional assumptions and often motivate the choice of specific functional forms for the baseline hazard based on the visual inspection of the hazard rate plots. We contribute to this literature by showing that parameter estimates for patient and hospital characteristics in length of stay models are particularly sensitive to underlying assumptions regarding the hazard function. Moreover, we demonstrate that the inability to distinguish between competing risks of discharge destination may lead to distortions in the effect of important explanatory variables such as intensive care utilization.
publishDate 2007
dc.date.none.fl_str_mv 2007
2007-01-01T00:00:00Z
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.uri.fl_str_mv http://hdl.handle.net/1822/7627
url http://hdl.handle.net/1822/7627
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1387-3741
10.1007/s10742-007-0020-9
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
_version_ 1799132870077317120