Back to Search
Start Over
Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems
- Source :
- Sensors (Basel, Switzerland), r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe, instname, RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, Sensors, Vol 15, Iss 12, Pp 29821-29840 (2015), Sensors, Volume 15, Issue 12, Pages 29821-29840, Sensors; Volume 15; Issue 12; Pages: 29821-29840
- Publication Year :
- 2015
- Publisher :
- MDPI AG, 2015.
-
Abstract
- [EN] 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.<br />The authors want to acknowledge the work MySphera Company and Hospital General for their invaluable support. This work was supported in part by several projects; FASyS-Absolutely Safe and Healthy Factory (Spanish Ministry of Industry. CEN-20091034), MOSAIC-Models and simulation techniques for discovering diabetes influence factors (ICT-FP7-600914) and HEARTWAYS-Advanced Solutions for Supporting Cardiac Patients in Rehabilitation (ICT-SME-315659) EU Projects; and organizations like Tecnologias para la Salud y el Bienestar (TSB S.A.) and the Universitat Politecnica de Valencia.
- Subjects :
- Computer science
Process (engineering)
Medical Informatics Computing
media_common.quotation_subject
Process mining
lcsh:Chemical technology
Biochemistry
Article
Analytical Chemistry
TECNOLOGIA ELECTRONICA
Computer Communication Networks
indoor location systems
process mining
health process
Humans
lcsh:TP1-1185
Electrical and Electronic Engineering
Instrumentation
media_common
Measure (data warehouse)
Forcing (recursion theory)
Health professionals
Equipment Design
Data science
Atomic and Molecular Physics, and Optics
Radio Frequency Identification Device
Work (electrical)
Software deployment
LENGUAJES Y SISTEMAS INFORMATICOS
Welfare
Algorithms
Subjects
Details
- ISSN :
- 14248220
- Database :
- OpenAIRE
- Journal :
- Sensors (Basel, Switzerland), r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe, instname, RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, Sensors, Vol 15, Iss 12, Pp 29821-29840 (2015), Sensors, Volume 15, Issue 12, Pages 29821-29840, Sensors; Volume 15; Issue 12; Pages: 29821-29840
- Accession number :
- edsair.doi.dedup.....262a4cc2ecf1ad86e1b6af6389422bc3