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...
- Autores:
- Tipo de recurso:
- 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
- Rights
- License
- Abierto (Texto Completo)
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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 |
_version_ |
1814167721612410880 |