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EVENT DATA VISUALIZATION THROUGH PROCESS MINING: A CASE FOR EMERGENCY MEDICAL SERVICE SYSTEM IN ADANA

Yıl 2019, Cilt: 9 Sayı: 2, 320 - 329, 30.12.2019
https://doi.org/10.36222/ejt.575564

Öz

Increasing amount of data enables researchers the
opportunity of applying new scientific methods to manage and visualize the
systems and processes. Process mining is an emerging tool for discovering real
processes using event data of complex systems such as communication,
information, health care systems, transportation and etc. Emergency Medical
Service (EMS) system is an integral part of health care systems and aims to
respond cases on time in order to decrease mortality. Although the EMS system
process is assumed to be known, related data may indicate some deviations from
the real process. Aim of this study is to discover and visualize EMS system in
Adana city, in Turkey. EMS system event logs are filtered and visualized by
using plug-ins in ProM platform such as Simple Heuristic Filtering plug-in and
Log visualizer, respectively. Other plug-ins such as Fuzzy Miner and Inductive
Miner are used for discovering process model. The deviations are obtained in
EMS system process model showing irregular or rare events that cannot be
representable throughout the process. The results indicate that the process of
transportation between hospitals should be investigated in order to improve the
process of Adana EMS system.

Destekleyen Kurum

TÜBİTAK

Proje Numarası

1059B191601225

Teşekkür

This study is a part of research granted by The Scientific and Technical Research Council of Turkey (TUBITAK) International Post-Doctoral Research Fellowship Program in the framework of TUBITAK-BIDEB 2219. Thanks to Data Science Centre in Technology University of Eindhoven for their support and hospitality and also Adana Provincial Directorate of Health Center for providing data.

Kaynakça

  • [1] Dick, W.F., (2003). Anglo-American vs. Franco-German emergency medical services system. Prehosp. Disaster Med., 18 (1), 29-35.
  • [2] Van der Aalst, W.M.P., Process mining: data science in action. Springer, Verlag Berlin Heidelberg, 2016.
  • [3] Van der Aalst, W.M.P., Weijters ,A.J.M.M., Maruster, L., (2004). Workflow mining: discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering, 16 (9), 1128–1142.
  • [4] Weijters, A.J.M.M., Van der Aalst, W.M.P., De Medeiros, A.K.A., (2006).Process mining with the heuristics miner-algorithm. Technische Universiteit Eindhoven Technical Report WP , 166, 1-34.
  • [5] De Medeiros, A.K.A., Weijters, A.J.M., Van der Aalst, W.P.M., (2005). Genetic process mining: a basic approach and its challenges. BPM 2005 International Workshops; 5 September 2005; Nancy, France. Heidelberg, Germany: Springer, 203-215.
  • [6] Van der Aalst, W.M.P., Rubin ,V., Verbeek, H.M.W., Van Dongen, B.F., Kindler, E., Günther, C.W., (2010). Process mining: a two-step approach to balance between underfitting and overfitting. Software and Systems Modeling, 9(1), 87–111.
  • [7] Leemans, S.J.J., Fahland, D., Van der Aalst, W.M.P., Discovering block-structured process models from event logs: A constructive approach. In J.M. Colom and J. Desel, editors, Applications and Theory of Petri Nets, volume 7927 of Lecture Notes in Computer Science, Springer, Berlin, 2013, 311-329.
  • [8] Yurek, I., Birant, D., Birant, K.U., (2018). Interactive process miner: a new approach for process mining. Turkish Journal of Electrical Engineering & Computer Sciences; 26, 1314-1328.
  • [9] Mans, R., Schonenberg, H., Leonardi, G., Panzarasa, S., Cavallini, A., Quaglini, S., Van der Aalst, W.M.P.,(2008). Process mining techniques: an application to stroke care. Studies in Health Technology and Informatics, 136, 573–578.
  • [10] Xiong, H.H., Zhou, M.C., Manikopoulos, C.N., (1994). Modeling and performance analysis of medical services systems using petri nets. In: IEEE Int. Conf. on Systems, Man and Cybernetic, 1994, .2339-2342.
  • [11] Rojas, E., Munoz-Gama, J., Sepulveda, M., Capurro, D., (2016). Process mining in healthcare: a literature review. Journal of Biomedical Informatics, 61, 224-236. [12] Mans, R.S., Schonenberg, M.H., Song, M., Van der Aalst, W.M.P., Bakker, P.J.M.,(2008) Application of process mining in healthcare – a case study in a Dutch hospital. International Joint Conference on Biomedical Engineering Systems and Technologies, 425-438.
  • [13] Baker, K., Dunwoodie, E., Jones, R.G., Newsham, A., Johnson, O., Price, C.P., Wolstenholme, J., Leal, J., McGinley, P., Twelves, C., Hall, G., (2019). Process mining routinely collected electronic health records to define real-life clinical pathways during chemotherapy. International Journal of Medical Informatics, 103, 32–41.
  • [14] Alvarez, C., Rojas, E., Arias, M., Munoz-Gama, J., Sepulveda, M., Herskovic, V., Capurro, D., (2018). Discovering role interaction models in the emergency room using process mining. Journal of Biomedical Informatics, 78, 60-77.
  • [15] Yooa, S., Cho, M., Kima, E., Kima, S., Simb, Y., Yooc, D., Hwanga, H., Song, M., (2016). Assessment of hospital processes using a process mining technique: Outpatient process analysis at a tertiary hospital. International Journal of Medical Informatics, 88, 34-43.
  • [16] Yongzhong, C., Zhu, J., Guo, Y., Shi, C., (2018). Process mining-based medical program evolution. Computers and Electrical Engineering, 68, 204-214.
  • [17] Van der Aalst, W.M.P., (2012). Process mining: overview and opportunities. ACM Transactions on Management Information Systems, 3, 1-17.
  • [18] Buijs, J.C.A.M, Mapping Data Sources to XES in a Generic Way. Doctoral Dissertation, Eindhoven University of Technology, Netherlands, 2010.
Yıl 2019, Cilt: 9 Sayı: 2, 320 - 329, 30.12.2019
https://doi.org/10.36222/ejt.575564

Öz

Proje Numarası

1059B191601225

Kaynakça

  • [1] Dick, W.F., (2003). Anglo-American vs. Franco-German emergency medical services system. Prehosp. Disaster Med., 18 (1), 29-35.
  • [2] Van der Aalst, W.M.P., Process mining: data science in action. Springer, Verlag Berlin Heidelberg, 2016.
  • [3] Van der Aalst, W.M.P., Weijters ,A.J.M.M., Maruster, L., (2004). Workflow mining: discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering, 16 (9), 1128–1142.
  • [4] Weijters, A.J.M.M., Van der Aalst, W.M.P., De Medeiros, A.K.A., (2006).Process mining with the heuristics miner-algorithm. Technische Universiteit Eindhoven Technical Report WP , 166, 1-34.
  • [5] De Medeiros, A.K.A., Weijters, A.J.M., Van der Aalst, W.P.M., (2005). Genetic process mining: a basic approach and its challenges. BPM 2005 International Workshops; 5 September 2005; Nancy, France. Heidelberg, Germany: Springer, 203-215.
  • [6] Van der Aalst, W.M.P., Rubin ,V., Verbeek, H.M.W., Van Dongen, B.F., Kindler, E., Günther, C.W., (2010). Process mining: a two-step approach to balance between underfitting and overfitting. Software and Systems Modeling, 9(1), 87–111.
  • [7] Leemans, S.J.J., Fahland, D., Van der Aalst, W.M.P., Discovering block-structured process models from event logs: A constructive approach. In J.M. Colom and J. Desel, editors, Applications and Theory of Petri Nets, volume 7927 of Lecture Notes in Computer Science, Springer, Berlin, 2013, 311-329.
  • [8] Yurek, I., Birant, D., Birant, K.U., (2018). Interactive process miner: a new approach for process mining. Turkish Journal of Electrical Engineering & Computer Sciences; 26, 1314-1328.
  • [9] Mans, R., Schonenberg, H., Leonardi, G., Panzarasa, S., Cavallini, A., Quaglini, S., Van der Aalst, W.M.P.,(2008). Process mining techniques: an application to stroke care. Studies in Health Technology and Informatics, 136, 573–578.
  • [10] Xiong, H.H., Zhou, M.C., Manikopoulos, C.N., (1994). Modeling and performance analysis of medical services systems using petri nets. In: IEEE Int. Conf. on Systems, Man and Cybernetic, 1994, .2339-2342.
  • [11] Rojas, E., Munoz-Gama, J., Sepulveda, M., Capurro, D., (2016). Process mining in healthcare: a literature review. Journal of Biomedical Informatics, 61, 224-236. [12] Mans, R.S., Schonenberg, M.H., Song, M., Van der Aalst, W.M.P., Bakker, P.J.M.,(2008) Application of process mining in healthcare – a case study in a Dutch hospital. International Joint Conference on Biomedical Engineering Systems and Technologies, 425-438.
  • [13] Baker, K., Dunwoodie, E., Jones, R.G., Newsham, A., Johnson, O., Price, C.P., Wolstenholme, J., Leal, J., McGinley, P., Twelves, C., Hall, G., (2019). Process mining routinely collected electronic health records to define real-life clinical pathways during chemotherapy. International Journal of Medical Informatics, 103, 32–41.
  • [14] Alvarez, C., Rojas, E., Arias, M., Munoz-Gama, J., Sepulveda, M., Herskovic, V., Capurro, D., (2018). Discovering role interaction models in the emergency room using process mining. Journal of Biomedical Informatics, 78, 60-77.
  • [15] Yooa, S., Cho, M., Kima, E., Kima, S., Simb, Y., Yooc, D., Hwanga, H., Song, M., (2016). Assessment of hospital processes using a process mining technique: Outpatient process analysis at a tertiary hospital. International Journal of Medical Informatics, 88, 34-43.
  • [16] Yongzhong, C., Zhu, J., Guo, Y., Shi, C., (2018). Process mining-based medical program evolution. Computers and Electrical Engineering, 68, 204-214.
  • [17] Van der Aalst, W.M.P., (2012). Process mining: overview and opportunities. ACM Transactions on Management Information Systems, 3, 1-17.
  • [18] Buijs, J.C.A.M, Mapping Data Sources to XES in a Generic Way. Doctoral Dissertation, Eindhoven University of Technology, Netherlands, 2010.
Toplam 17 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Endüstri Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

Nuşin Uncu 0000-0003-3030-3363

Proje Numarası 1059B191601225
Yayımlanma Tarihi 30 Aralık 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 9 Sayı: 2

Kaynak Göster

APA Uncu, N. (2019). EVENT DATA VISUALIZATION THROUGH PROCESS MINING: A CASE FOR EMERGENCY MEDICAL SERVICE SYSTEM IN ADANA. European Journal of Technique (EJT), 9(2), 320-329. https://doi.org/10.36222/ejt.575564

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