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Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance †
Background: Process mining is a relatively new discipline that helps to discover and analyze actual process executions based on log data. In this paper we apply conformance checking techniques to the process of surveillance of melanoma patients. This process consists of recurring events with time co...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313414/ https://www.ncbi.nlm.nih.gov/pubmed/30544735 http://dx.doi.org/10.3390/ijerph15122809 |
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author | Rinner, Christoph Helm, Emmanuel Dunkl, Reinhold Kittler, Harald Rinderle-Ma, Stefanie |
author_facet | Rinner, Christoph Helm, Emmanuel Dunkl, Reinhold Kittler, Harald Rinderle-Ma, Stefanie |
author_sort | Rinner, Christoph |
collection | PubMed |
description | Background: Process mining is a relatively new discipline that helps to discover and analyze actual process executions based on log data. In this paper we apply conformance checking techniques to the process of surveillance of melanoma patients. This process consists of recurring events with time constraints between the events. Objectives: The goal of this work is to show how existing clinical data collected during melanoma surveillance can be prepared and pre-processed to be reused for process mining. Methods: We describe an approach based on time boxing to create process models from medical guidelines and the corresponding event logs from clinical data of patient visits. Results: Event logs were extracted for 1023 patients starting melanoma surveillance at the Department of Dermatology at the Medical University of Vienna between January 2010 and June 2017. Conformance checking techniques available in the ProM framework and explorative applied process mining techniques were applied. Conclusions: The presented time boxing enables the direct use of existing process mining frameworks like ProM to perform process-oriented analysis also with respect to time constraints between events. |
format | Online Article Text |
id | pubmed-6313414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63134142019-06-17 Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance † Rinner, Christoph Helm, Emmanuel Dunkl, Reinhold Kittler, Harald Rinderle-Ma, Stefanie Int J Environ Res Public Health Article Background: Process mining is a relatively new discipline that helps to discover and analyze actual process executions based on log data. In this paper we apply conformance checking techniques to the process of surveillance of melanoma patients. This process consists of recurring events with time constraints between the events. Objectives: The goal of this work is to show how existing clinical data collected during melanoma surveillance can be prepared and pre-processed to be reused for process mining. Methods: We describe an approach based on time boxing to create process models from medical guidelines and the corresponding event logs from clinical data of patient visits. Results: Event logs were extracted for 1023 patients starting melanoma surveillance at the Department of Dermatology at the Medical University of Vienna between January 2010 and June 2017. Conformance checking techniques available in the ProM framework and explorative applied process mining techniques were applied. Conclusions: The presented time boxing enables the direct use of existing process mining frameworks like ProM to perform process-oriented analysis also with respect to time constraints between events. MDPI 2018-12-10 2018-12 /pmc/articles/PMC6313414/ /pubmed/30544735 http://dx.doi.org/10.3390/ijerph15122809 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rinner, Christoph Helm, Emmanuel Dunkl, Reinhold Kittler, Harald Rinderle-Ma, Stefanie Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance † |
title | Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance † |
title_full | Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance † |
title_fullStr | Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance † |
title_full_unstemmed | Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance † |
title_short | Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance † |
title_sort | process mining and conformance checking of long running processes in the context of melanoma surveillance † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313414/ https://www.ncbi.nlm.nih.gov/pubmed/30544735 http://dx.doi.org/10.3390/ijerph15122809 |
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