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dc.contributor.authorArmas, Jimmy
dc.contributor.authorCoronado Torres, André
dc.contributor.authorEvangelista Pescoran, Misael
dc.contributor.authorAguirre Mayorga, Santiago
dc.date.accessioned2019-08-17T03:07:59Z
dc.date.accessioned2022-02-22T12:03:09Z
dc.date.available2019-08-17T03:07:59Z
dc.date.available2022-02-22T12:03:09Z
dc.date.issued2019-07
dc.identifier.isbn978-958-52071-4-1
dc.identifier.issn2414-6390
dc.identifier.otherhttp://laccei.org/LACCEI2019-MontegoBay/meta/FP286.html
dc.identifier.urihttp://dx.doi.org/10.18687/LACCEI2019.1.1.286
dc.identifier.urihttp://axces.info/handle/10.18687/20190101_286
dc.description.abstractIn this paper, a reference model is proposed for the evaluation of operational processes variables in healthcare using process mining and data visualization techniques. For this reason, the PM2 methodology is used as a reference to conduct projects oriented to the evaluation of data collected in business processes, including data visualization techniques, with the purpose of reducing the acquisition time of knowledge related to the processes of institutions of the healthcare sector. The proposed model is based on the application of a set of data visualization techniques to reduce the knowledge acquisition gap presented by process mining. The model consists of 5 stages: 1. Extraction, 2. Event processing, 3. Process mining, 4. Data visualization and 5. Evaluation of results. A testing scenario was defined in a Clinic network in Lima (Peru) to validate the proposed model and the surgery process was chosen, since it is critical for the organization. The results showed the existing bottleneck in the surgery process, between the activities of registering and preparing the patient. This allowed to take corrective measures between the activities to optimize the process cycle time. Likewise, a sequence was identified in the activities that had not been previously detected in the process documentation; these represented 2.6% difference, so the documented process was modified to achieve a 99.6% affinity.en_US
dc.language.isoEnglishen_US
dc.publisherLACCEI, Inc.en_US
dc.rightsLACCEI License
dc.rights.urihttps://laccei.org/blog/copyright-laccei-papers/
dc.subjectProcess miningen_US
dc.subjectdata visualization techniquesen_US
dc.subjecthealthcareen_US
dc.subjectoperational processen_US
dc.titleEvaluation of operational process variables in healthcare using process mining and data visualization techniques
dc.typeArticleen_US
dc.description.countryPeruen
dc.description.institutionUniversidad Peruana de Ciencias Aplicadasen
dc.description.trackSoftware Engineering, Telecommunications, Cybersecurity and Computational toolsen
dc.journal.referatopeerReview


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