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Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems

The definition of efficient and accurate health processes in hospitals is crucial for ensuring an adequate quality of service. Knowing and improving the behavior of the surgical processes in a hospital can improve the number of patients that can be operated on using the same resources. However, the...

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Autores principales: Fernandez-Llatas, Carlos, Lizondo, Aroa, Monton, Eduardo, Benedi, Jose-Miguel, Traver, Vicente
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721690/
https://www.ncbi.nlm.nih.gov/pubmed/26633395
http://dx.doi.org/10.3390/s151229769
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author Fernandez-Llatas, Carlos
Lizondo, Aroa
Monton, Eduardo
Benedi, Jose-Miguel
Traver, Vicente
author_facet Fernandez-Llatas, Carlos
Lizondo, Aroa
Monton, Eduardo
Benedi, Jose-Miguel
Traver, Vicente
author_sort Fernandez-Llatas, Carlos
collection PubMed
description The definition of efficient and accurate health processes in hospitals is crucial for ensuring an adequate quality of service. Knowing and improving the behavior of the surgical processes in a hospital can improve the number of patients that can be operated on using the same resources. However, the measure of this process is usually made in an obtrusive way, forcing nurses to get information and time data, affecting the proper process and generating inaccurate data due to human errors during the stressful journey of health staff in the operating theater. The use of indoor location systems can take time information about the process in an unobtrusive way, freeing nurses, allowing them to engage in purely welfare work. However, it is necessary to present these data in a understandable way for health professionals, who cannot deal with large amounts of historical localization log data. The use of process mining techniques can deal with this problem, offering an easily understandable view of the process. In this paper, we present a tool and a process mining-based methodology that, using indoor location systems, enables health staff not only to represent the process, but to know precise information about the deployment of the process in an unobtrusive and transparent way. We have successfully tested this tool in a real surgical area with 3613 patients during February, March and April of 2015.
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spelling pubmed-47216902016-01-26 Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems Fernandez-Llatas, Carlos Lizondo, Aroa Monton, Eduardo Benedi, Jose-Miguel Traver, Vicente Sensors (Basel) Article The definition of efficient and accurate health processes in hospitals is crucial for ensuring an adequate quality of service. Knowing and improving the behavior of the surgical processes in a hospital can improve the number of patients that can be operated on using the same resources. However, the measure of this process is usually made in an obtrusive way, forcing nurses to get information and time data, affecting the proper process and generating inaccurate data due to human errors during the stressful journey of health staff in the operating theater. The use of indoor location systems can take time information about the process in an unobtrusive way, freeing nurses, allowing them to engage in purely welfare work. However, it is necessary to present these data in a understandable way for health professionals, who cannot deal with large amounts of historical localization log data. The use of process mining techniques can deal with this problem, offering an easily understandable view of the process. In this paper, we present a tool and a process mining-based methodology that, using indoor location systems, enables health staff not only to represent the process, but to know precise information about the deployment of the process in an unobtrusive and transparent way. We have successfully tested this tool in a real surgical area with 3613 patients during February, March and April of 2015. MDPI 2015-11-30 /pmc/articles/PMC4721690/ /pubmed/26633395 http://dx.doi.org/10.3390/s151229769 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fernandez-Llatas, Carlos
Lizondo, Aroa
Monton, Eduardo
Benedi, Jose-Miguel
Traver, Vicente
Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems
title Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems
title_full Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems
title_fullStr Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems
title_full_unstemmed Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems
title_short Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems
title_sort process mining methodology for health process tracking using real-time indoor location systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721690/
https://www.ncbi.nlm.nih.gov/pubmed/26633395
http://dx.doi.org/10.3390/s151229769
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