Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/11531/20813
Registro completo de metadatos
Campo DC Valor Lengua/Idioma
dc.contributor.authorBetancourt Odio, Manuel Alejandroes-ES
dc.contributor.authorLázaro Alquezar, Angelinaes-ES
dc.contributor.authorColino Fernández, Albertoes-ES
dc.date.accessioned2017-08-28T10:30:00Z-
dc.date.available2017-08-28T10:30:00Z-
dc.date.issued27/08/2017es_ES
dc.identifier978-1-5386-1044-2es_ES
dc.identifier.urihttp://hdl.handle.net/11531/20813-
dc.descriptionRevista electrónicaes_ES
dc.description.abstractThis paper studies a scheduling problem in which patients request appointments at specific future days within a specialty definite time window. This research is inspired by a study of Ophthalmology scheduling practices at the Clinic Hospital at Santiago de Cuba (Cuba). In this hospital, patients do not know in advance neither the proximate time at which they will be seen by the doctor nor the total amount of time to be spent at the Hospital. In this article, an optimal distribution of patients during the designing scheduling process has been performed. The optimality condition obeys to two different goals: to give the appointments as soon as possible and to minimize the time that a patient would spend at the hospital to complete a protocol. We formulate this problem as a Multi-Objective Integer Problem (MOIP) and compare the performance of the resulting MOIP policies with traditional practices decision rules for the diagnosis and treatment of ophthalmology diseases. We show that this method outperforms traditional methods by far. Specifically, it reduces the total diagnosis time for cataract, cornea and glaucoma diseases by 70% on average or, in other words, by roughly two hours, relative to the standard approach. Arguably, this translates into improved patient satisfaction and efficiency in the use of resources in health services.es-ES
dc.description.abstractThis paper studies a scheduling problem in which patients request appointments at specific future days within a specialty definite time window. This research is inspired by a study of Ophthalmology scheduling practices at the Clinic Hospital at Santiago de Cuba (Cuba). In this hospital, patients do not know in advance neither the proximate time at which they will be seen by the doctor nor the total amount of time to be spent at the Hospital. In this article, an optimal distribution of patients during the designing scheduling process has been performed. The optimality condition obeys to two different goals: to give the appointments as soon as possible and to minimize the time that a patient would spend at the hospital to complete a protocol. We formulate this problem as a Multi-Objective Integer Problem (MOIP) and compare the performance of the resulting MOIP policies with traditional practices decision rules for the diagnosis and treatment of ophthalmology diseases. We show that this method outperforms traditional methods by far. Specifically, it reduces the total diagnosis time for cataract, cornea and glaucoma diseases by 70% on average or, in other words, by roughly two hours, relative to the standard approach. Arguably, this translates into improved patient satisfaction and efficiency in the use of resources in health services.en-GB
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoen-GBes_ES
dc.rightses_ES
dc.rights.uries_ES
dc.sourceDescripcion: ICPP'17 Proceedings Pagina Inicio: 281 Pagina Fin: 290es_ES
dc.titleScheduling Optimization in Ophthalmology using Multi-Objective Integer Modelses_ES
dc.typeinfo:eu-repo/semantics/otheres_ES
dc.description.versioninfo:eu-repo/semantics/publishedVersiones_ES
dc.rights.holderNormas del Congresoes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.keywordsadvance resource reservation; scheduling; multi-objective integer optimization.es-ES
dc.keywordsadvance resource reservation; scheduling; multi-objective integer optimization.en-GB
Aparece en las colecciones: Artículos

Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
FinalPaperCongress12_06_2017.pdf1,02 MBAdobe PDFVisualizar/Abrir     Request a copy


Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.