Clustering Techniques

This paper investigates the use of clustering technique to characterize the providers of maintenance services in a health-care institution according to their performance. A characterization of the inventory of equipment from seven pilot areas was carried out first (including 264 medical devices). Th...

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Autores:
Tipo de recurso:
Fecha de publicación:
2010
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/26428
Acceso en línea:
https://doi.org/10.1109/memb.2009.935708
https://repository.urosario.edu.co/handle/10336/26428
Palabra clave:
Cluster Analysis
Contract Services
Data Interpretation
Statistical
Internationality
Maintenance
Rights
License
Restringido (Acceso a grupos específicos)
id EDOCUR2_a3b23bafb4cdc362b94fc90c3cd5cd7a
oai_identifier_str oai:repository.urosario.edu.co:10336/26428
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling f2e876d6-94d1-4fd7-bc85-4194ad0925a6-13c95cdb3-32f4-44a5-ad4e-f55d353553f1-1b07b6dc8-d900-419c-9938-e67c3c1589fd-12020-08-06T16:21:41Z2020-08-06T16:21:41Z2010-03This paper investigates the use of clustering technique to characterize the providers of maintenance services in a health-care institution according to their performance. A characterization of the inventory of equipment from seven pilot areas was carried out first (including 264 medical devices). The characterization study concluded that the inventory on a whole is old [exploitation time (ET)/useful life (UL) average is 0.78] and has high maintenance service costs relative to the original cost of acquisition (service cost /acquisition cost average 8.61%). A monitoring of the performance of maintenance service providers was then conducted. The variables monitored were response time (RT), service time (ST), availability, and turnaround time (TAT). Finally, the study grouped maintenance service providers into clusters according to performance. The study grouped maintenance service providers into the following clusters. Cluster 0: Identified with the best performance, the lowest values of TAT, RT, and ST, with an average TAT value of 1.46 days; Clusters 1 and 2: Identified with the poorest performance, highest values of TAT, RT, and ST, and an average TAT value of 9.79 days; and Cluster 3: Identified by medium-quality performance, intermediate values of TAT, RT, and ST, and an average TAT value of 2.56 daysapplication/pdfhttps://doi.org/10.1109/memb.2009.935708ISSN: 2154-2287EISSN: 2154-2317https://repository.urosario.edu.co/handle/10336/26428engJournal & Magazines126No. 2119IEEE PulseVol. 29IEEE Pulse, ISSN: 2154-2287 ; EISSN: 2154-2317, Vol.29, No.2 (2010-03); pp.119-126https://ieeexplore.ieee.org/document/5431943/authors#authorsRestringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ecIEEE Pulseinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURCluster AnalysisContract ServicesData InterpretationStatisticalInternationalityMaintenanceClustering TechniquesTécnicas de agrupamientoarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Cruz, Antonio MiguelUsaquén Perilla, Sandra PatriciaVanegas Pabón, Nidia Nelly10336/26428oai:repository.urosario.edu.co:10336/264282022-05-02 07:37:15.345176https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Clustering Techniques
dc.title.TranslatedTitle.spa.fl_str_mv Técnicas de agrupamiento
title Clustering Techniques
spellingShingle Clustering Techniques
Cluster Analysis
Contract Services
Data Interpretation
Statistical
Internationality
Maintenance
title_short Clustering Techniques
title_full Clustering Techniques
title_fullStr Clustering Techniques
title_full_unstemmed Clustering Techniques
title_sort Clustering Techniques
dc.subject.keyword.spa.fl_str_mv Cluster Analysis
Contract Services
Data Interpretation
Statistical
Internationality
Maintenance
topic Cluster Analysis
Contract Services
Data Interpretation
Statistical
Internationality
Maintenance
description This paper investigates the use of clustering technique to characterize the providers of maintenance services in a health-care institution according to their performance. A characterization of the inventory of equipment from seven pilot areas was carried out first (including 264 medical devices). The characterization study concluded that the inventory on a whole is old [exploitation time (ET)/useful life (UL) average is 0.78] and has high maintenance service costs relative to the original cost of acquisition (service cost /acquisition cost average 8.61%). A monitoring of the performance of maintenance service providers was then conducted. The variables monitored were response time (RT), service time (ST), availability, and turnaround time (TAT). Finally, the study grouped maintenance service providers into clusters according to performance. The study grouped maintenance service providers into the following clusters. Cluster 0: Identified with the best performance, the lowest values of TAT, RT, and ST, with an average TAT value of 1.46 days; Clusters 1 and 2: Identified with the poorest performance, highest values of TAT, RT, and ST, and an average TAT value of 9.79 days; and Cluster 3: Identified by medium-quality performance, intermediate values of TAT, RT, and ST, and an average TAT value of 2.56 days
publishDate 2010
dc.date.created.spa.fl_str_mv 2010-03
dc.date.accessioned.none.fl_str_mv 2020-08-06T16:21:41Z
dc.date.available.none.fl_str_mv 2020-08-06T16:21:41Z
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.doi.none.fl_str_mv https://doi.org/10.1109/memb.2009.935708
dc.identifier.issn.none.fl_str_mv ISSN: 2154-2287
EISSN: 2154-2317
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/26428
url https://doi.org/10.1109/memb.2009.935708
https://repository.urosario.edu.co/handle/10336/26428
identifier_str_mv ISSN: 2154-2287
EISSN: 2154-2317
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 126
dc.relation.citationIssue.none.fl_str_mv No. 2
dc.relation.citationStartPage.none.fl_str_mv 119
dc.relation.citationTitle.none.fl_str_mv IEEE Pulse
dc.relation.citationVolume.none.fl_str_mv Vol. 29
dc.relation.ispartof.spa.fl_str_mv IEEE Pulse, ISSN: 2154-2287 ; EISSN: 2154-2317, Vol.29, No.2 (2010-03); pp.119-126
dc.relation.uri.spa.fl_str_mv https://ieeexplore.ieee.org/document/5431943/authors#authors
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.acceso.spa.fl_str_mv Restringido (Acceso a grupos específicos)
rights_invalid_str_mv Restringido (Acceso a grupos específicos)
http://purl.org/coar/access_right/c_16ec
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Journal & Magazines
dc.source.spa.fl_str_mv IEEE Pulse
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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