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Using data mining techniques to determine whether to outsource medical equipment maintenance tasks in real contexts

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dc.creatorMiguel-Cruz A.spa
dc.creatorAya-Parra P.A.spa
dc.creatorRodríguez-Dueñas, William R.spa
dc.creatorCamelo-Ocampo A.F.spa
dc.creatorPlata-Guao V.S.spa
dc.creatorCorreal O. H.H.spa
dc.creatorCórdoba-Hernández N.P.spa
dc.creatorNuñez-Cruz A.spa
dc.creatorSarmiento-Rojas J.S.spa
dc.creatorQuiroga-Torres, Daniel-Alejandrospa
dc.date.accessioned2020-05-26T00:10:53Z
dc.date.available2020-05-26T00:10:53Z
dc.date.created2019spa
dc.description.abstractThe purpose of this study was to determine whether the maintenance of medical equipment should be outsourced (or not). For this, we used data mining techniques called decision trees. We (1) collected 2364 maintenance works orders from 62 medical devices installed in a 900-bed hospital; (2) then we randomly selected 90% of the maintenance works orders to train 8 different decision tree schemas (J48 (pruned and unpruned), Naive Bayes tree, random tree, alternating decision tree, logistic model tree, decision stump, REP tree); (3) next, the remaining 10% of the works orders were used to test the decision tree schemas. The relative absolute error was used to evaluate what the tested decision tree schemas had learned; finally (4), we chose the decision tree schema with the lowest relative absolute error. Overall, the decision tree schemas performed well. 62.5% (5/8) of the decision tree schemas had less than 20% relative absolute error. 87.5% (7/8) of the decision tree schemas had more than 90% in the correct classification (whether to outsource maintenance tasks or not). The different tested decision tree schemas showed that the most important variables when making the decision whether to outsource maintenance tasks or not were: medical device, risk class (I, IIA, IIB, III), complexity, obsolescence, maintenance frequency, service time and outsourcing. The best decision tree schema was the logistic model tree (LMT) with 14.6628% relative absolute error and 94.7034% in the correct classification. © Springer Nature Singapore Pte Ltd. 2019.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1007/978-981-10-9023-3_52
dc.identifier.issn2006
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/24266
dc.language.isoengspa
dc.publisherSpringer Verlagspa
dc.relation.citationEndPage298
dc.relation.citationIssueNo. 3
dc.relation.citationStartPage295
dc.relation.citationTitleIFMBE Proceedings
dc.relation.citationVolumeVol. 68
dc.relation.ispartofIFMBE Proceedings, ISSN:2006, Vol.68, No.3 (2019); pp. 295-298spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85048276324&doi=10.1007%2f978-981-10-9023-3_52&partnerID=40&md5=af1b190bbe7db5e67cdd4146e29d24b4spa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordBiomedical engineeringspa
dc.subject.keywordBiomedical equipmentspa
dc.subject.keywordDecision treesspa
dc.subject.keywordErrorsspa
dc.subject.keywordMaintenancespa
dc.subject.keywordMedical computingspa
dc.subject.keywordObsolescencespa
dc.subject.keywordOutsourcingspa
dc.subject.keywordTrees (mathematics)spa
dc.subject.keywordAlternating decision treesspa
dc.subject.keywordClinical engineeringspa
dc.subject.keywordDecision stumpsspa
dc.subject.keywordMaintenance managementspa
dc.subject.keywordMaintenance tasksspa
dc.subject.keywordMaintenance workspa
dc.subject.keywordMedical Devicesspa
dc.subject.keywordMedical equipment maintenancespa
dc.subject.keywordData miningspa
dc.subject.keywordClinical engineeringspa
dc.subject.keywordData miningspa
dc.subject.keywordDecision treespa
dc.subject.keywordMaintenance managementspa
dc.subject.keywordOutsourcingspa
dc.titleUsing data mining techniques to determine whether to outsource medical equipment maintenance tasks in real contextsspa
dc.typeconferenceObjecteng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaDocumento de conferenciaspa
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