Evaluation of operational process variables in healthcare using process mining and data visualization techniques

Jimmy Armas Aguirre, André Coronado Torres, Misael Evangelista Pescoran, Santiago Aguirre Mayorga

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In 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.

Original languageEnglish
Title of host publication17th LACCEI International Multi-Conference for Engineering, Education, and Technology
Subtitle of host publication"Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019
PublisherLatin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)9780999344361
DOIs
StatePublished - 2019
Event17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica
Duration: 24 Jul 201926 Jul 2019

Publication series

NameProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume2019-July
ISSN (Electronic)2414-6390

Conference

Conference17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
Country/TerritoryJamaica
CityMontego Bay
Period24/07/1926/07/19

Keywords

  • Business process
  • Data visualization
  • Healthcare
  • Process mining

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