Measured Effects of User and Clinical Engineer Training Using a Queuing Model

This article puts forward a new proposal to calculate count, turnaround, response, and service time of work orders in a clinical engineering (CE) department. These are calculated by means of a queuing model as a measurement tool. This proposal was tested in a 600-bed hospital with an inventory of 10...

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Fecha de publicación:
2003
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/28118
Acceso en línea:
https://repository.urosario.edu.co/handle/10336/28118
Palabra clave:
Measured Effects
User and Clinical Engineer
Training Using a Queuing Model
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id EDOCUR2_7d4349c74086ce360049fe9a6d5541c6
oai_identifier_str oai:repository.urosario.edu.co:10336/28118
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 86df94cc-ee81-4184-9796-b48a3a384794-15c3366fa-5e11-471f-bada-bca838f7dba7-13b2fe2aa-200b-43fa-aed6-d953f4bf3ff5-148ff03ca-193a-42ee-bc19-1d7b20ee2273-1b749a0e2-774d-4c27-b60c-63cd34c9f787-12020-08-19T14:45:53Z2020-08-19T14:45:53Z2003-01-01This article puts forward a new proposal to calculate count, turnaround, response, and service time of work orders in a clinical engineering (CE) department. These are calculated by means of a queuing model as a measurement tool. This proposal was tested in a 600-bed hospital with an inventory of 1094 medical devices and with 6 full-time clinical engineers. In April 1999, a simulation (with ARENA 3.01 developed by System Modeling Corporation) of the working of this proposal was performed with desired values being applied to the queuing model. At the end of 2002, real work order data from the database was recorded. As predicted, the results showed that all the indicators of nonscheduled work orders decreased. Response and turnaround time were reduced from 27 to 0.56 hours and 27.48 to 1.13 hours, respectively. From a backlog of 22 outstanding repair orders per month between April 1999 and January 2000, the number was reduced to 4 in December 2002. The queuing model also helped to measure the positive effects on arrival and service rates when users and CE were trained. The difference between simulated and real values was under 5%.application/pdfISSN: 0899-8205https://repository.urosario.edu.co/handle/10336/28118engAssociation for the Advancement of Medical Instrumentation421No. 6405Biomedical Instrumentation and TechnologyVol. 37Biomedical Instrumentation and Technology, ISSN: 0899-8205, Vol.37, No.6 (November, 2003); pp. 405-421 https://www.aami-bit.org/doi/abs/10.2345/0899-8205(2003)37%5B405%3AMEOUAC%5D2.0.CO%3B2?mobileUi=0Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Biomedical Instrumentation and Technologyinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURMeasured EffectsUser and Clinical EngineerTraining Using a Queuing ModelMeasured Effects of User and Clinical Engineer Training Using a Queuing ModelEfectos medidos de la formación de usuarios e ingenieros clínicos mediante un modelo de colasarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501A. Miguel CruzE. Rodríguez DenisC. Sánchez VillarE. T. Pozo PuñalesI. Vergara Perez10336/28118oai:repository.urosario.edu.co:10336/281182021-06-03 00:51:12.181https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Measured Effects of User and Clinical Engineer Training Using a Queuing Model
dc.title.TranslatedTitle.spa.fl_str_mv Efectos medidos de la formación de usuarios e ingenieros clínicos mediante un modelo de colas
title Measured Effects of User and Clinical Engineer Training Using a Queuing Model
spellingShingle Measured Effects of User and Clinical Engineer Training Using a Queuing Model
Measured Effects
User and Clinical Engineer
Training Using a Queuing Model
title_short Measured Effects of User and Clinical Engineer Training Using a Queuing Model
title_full Measured Effects of User and Clinical Engineer Training Using a Queuing Model
title_fullStr Measured Effects of User and Clinical Engineer Training Using a Queuing Model
title_full_unstemmed Measured Effects of User and Clinical Engineer Training Using a Queuing Model
title_sort Measured Effects of User and Clinical Engineer Training Using a Queuing Model
dc.subject.keyword.spa.fl_str_mv Measured Effects
User and Clinical Engineer
Training Using a Queuing Model
topic Measured Effects
User and Clinical Engineer
Training Using a Queuing Model
description This article puts forward a new proposal to calculate count, turnaround, response, and service time of work orders in a clinical engineering (CE) department. These are calculated by means of a queuing model as a measurement tool. This proposal was tested in a 600-bed hospital with an inventory of 1094 medical devices and with 6 full-time clinical engineers. In April 1999, a simulation (with ARENA 3.01 developed by System Modeling Corporation) of the working of this proposal was performed with desired values being applied to the queuing model. At the end of 2002, real work order data from the database was recorded. As predicted, the results showed that all the indicators of nonscheduled work orders decreased. Response and turnaround time were reduced from 27 to 0.56 hours and 27.48 to 1.13 hours, respectively. From a backlog of 22 outstanding repair orders per month between April 1999 and January 2000, the number was reduced to 4 in December 2002. The queuing model also helped to measure the positive effects on arrival and service rates when users and CE were trained. The difference between simulated and real values was under 5%.
publishDate 2003
dc.date.created.spa.fl_str_mv 2003-01-01
dc.date.accessioned.none.fl_str_mv 2020-08-19T14:45:53Z
dc.date.available.none.fl_str_mv 2020-08-19T14:45:53Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.issn.none.fl_str_mv ISSN: 0899-8205
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/28118
identifier_str_mv ISSN: 0899-8205
url https://repository.urosario.edu.co/handle/10336/28118
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 421
dc.relation.citationIssue.none.fl_str_mv No. 6
dc.relation.citationStartPage.none.fl_str_mv 405
dc.relation.citationTitle.none.fl_str_mv Biomedical Instrumentation and Technology
dc.relation.citationVolume.none.fl_str_mv Vol. 37
dc.relation.ispartof.spa.fl_str_mv Biomedical Instrumentation and Technology, ISSN: 0899-8205, Vol.37, No.6 (November, 2003); pp. 405-421
dc.relation.uri.spa.fl_str_mv https://www.aami-bit.org/doi/abs/10.2345/0899-8205(2003)37%5B405%3AMEOUAC%5D2.0.CO%3B2?mobileUi=0
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Association for the Advancement of Medical Instrumentation
dc.source.spa.fl_str_mv Biomedical Instrumentation and Technology
institution Universidad del Rosario
dc.source.instname.none.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.none.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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