Length of Hospital Stay and Quality of Care

Bibliographic Details
Main Author: Neves, José
Publication Date: 2016
Other Authors: Abelha, Vasco, Vicente, Henrique, Neves, João, Machado, José
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10174/17411
https://doi.org/10.1007/978-3-319-27478-2_19
Summary: The relationship between Length Of hospital Stay (LOS) and Quality-of-Care (QofC) is demanding and difficult to assess. Indeed, a multifaceted intertwining network of countless services and LOS factors is available, which may range from organizational culture to hospital physicians availability, without discarding the possibility of lifting the foot on intermediate care services, to the customs and cultures of the people. On health policy terms, LOS remains a measurable index of efficiency, and most of the studies that have been undertaken show that QoC or health outcomes do not appear to be compromised by reductions in LOS times. Therefore, and in order to assess this statement, a Logic Programming based methodology to Knowledge Representation and Reasoning, allowing the modeling of the universe of discourse in terms of defective data, information and knowledge is used, being complemented with an Artificial Neural Networks based approach to computing, allowing one to predict for how long a patient should remain in a hospital or at home, during his/her illness experience.
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spelling Length of Hospital Stay and Quality of CareLength of Hospital StayLogic ProgrammingKnowledge Representation and ReasoningArtificial Neural NetworksThe relationship between Length Of hospital Stay (LOS) and Quality-of-Care (QofC) is demanding and difficult to assess. Indeed, a multifaceted intertwining network of countless services and LOS factors is available, which may range from organizational culture to hospital physicians availability, without discarding the possibility of lifting the foot on intermediate care services, to the customs and cultures of the people. On health policy terms, LOS remains a measurable index of efficiency, and most of the studies that have been undertaken show that QoC or health outcomes do not appear to be compromised by reductions in LOS times. Therefore, and in order to assess this statement, a Logic Programming based methodology to Knowledge Representation and Reasoning, allowing the modeling of the universe of discourse in terms of defective data, information and knowledge is used, being complemented with an Artificial Neural Networks based approach to computing, allowing one to predict for how long a patient should remain in a hospital or at home, during his/her illness experience.Springer International Publishing2016-02-17T18:05:36Z2016-02-172016-01-01T00:00:00Zbook partinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10174/17411http://hdl.handle.net/10174/17411https://doi.org/10.1007/978-3-319-27478-2_19engNeves, J., Abelha, A., Vicente, H., Neves, J. & Machado, J., Length of Hospital Stay and Quality of Care. In S. Kunifugi, G. Papadopoulos, A. Skulimowski & J. Kacprzyk, Eds., Advances in Intelligent Systems and Computing, Vol. 416, pp. 273–287, Springer International Publishing, Cham, Switzerland, 2016.Cham978-3-319-27477-52194-5357http://link.springer.com/chapter/10.1007/978-3-319-27478-2_191519DQUIjneves@di.uminho.ptvascoabelha91@gmail.comhvicente@uevora.ptjoaocpneves@gmail.comjmac@di.uminho.ptNeves, JoséAbelha, VascoVicente, HenriqueNeves, JoãoMachado, Joséinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-01-03T19:04:41Zoai:dspace.uevora.pt:10174/17411Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T12:08:55.760158Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Length of Hospital Stay and Quality of Care
title Length of Hospital Stay and Quality of Care
spellingShingle Length of Hospital Stay and Quality of Care
Neves, José
Length of Hospital Stay
Logic Programming
Knowledge Representation and Reasoning
Artificial Neural Networks
title_short Length of Hospital Stay and Quality of Care
title_full Length of Hospital Stay and Quality of Care
title_fullStr Length of Hospital Stay and Quality of Care
title_full_unstemmed Length of Hospital Stay and Quality of Care
title_sort Length of Hospital Stay and Quality of Care
author Neves, José
author_facet Neves, José
Abelha, Vasco
Vicente, Henrique
Neves, João
Machado, José
author_role author
author2 Abelha, Vasco
Vicente, Henrique
Neves, João
Machado, José
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Neves, José
Abelha, Vasco
Vicente, Henrique
Neves, João
Machado, José
dc.subject.por.fl_str_mv Length of Hospital Stay
Logic Programming
Knowledge Representation and Reasoning
Artificial Neural Networks
topic Length of Hospital Stay
Logic Programming
Knowledge Representation and Reasoning
Artificial Neural Networks
description The relationship between Length Of hospital Stay (LOS) and Quality-of-Care (QofC) is demanding and difficult to assess. Indeed, a multifaceted intertwining network of countless services and LOS factors is available, which may range from organizational culture to hospital physicians availability, without discarding the possibility of lifting the foot on intermediate care services, to the customs and cultures of the people. On health policy terms, LOS remains a measurable index of efficiency, and most of the studies that have been undertaken show that QoC or health outcomes do not appear to be compromised by reductions in LOS times. Therefore, and in order to assess this statement, a Logic Programming based methodology to Knowledge Representation and Reasoning, allowing the modeling of the universe of discourse in terms of defective data, information and knowledge is used, being complemented with an Artificial Neural Networks based approach to computing, allowing one to predict for how long a patient should remain in a hospital or at home, during his/her illness experience.
publishDate 2016
dc.date.none.fl_str_mv 2016-02-17T18:05:36Z
2016-02-17
2016-01-01T00:00:00Z
dc.type.driver.fl_str_mv book part
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/17411
http://hdl.handle.net/10174/17411
https://doi.org/10.1007/978-3-319-27478-2_19
url http://hdl.handle.net/10174/17411
https://doi.org/10.1007/978-3-319-27478-2_19
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Neves, J., Abelha, A., Vicente, H., Neves, J. & Machado, J., Length of Hospital Stay and Quality of Care. In S. Kunifugi, G. Papadopoulos, A. Skulimowski & J. Kacprzyk, Eds., Advances in Intelligent Systems and Computing, Vol. 416, pp. 273–287, Springer International Publishing, Cham, Switzerland, 2016.
Cham
978-3-319-27477-5
2194-5357
http://link.springer.com/chapter/10.1007/978-3-319-27478-2_19
15
19
DQUI
jneves@di.uminho.pt
vascoabelha91@gmail.com
hvicente@uevora.pt
joaocpneves@gmail.com
jmac@di.uminho.pt
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Springer International Publishing
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dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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