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Performance Analysis of Emergency Room Episodes Through Process Mining

Author

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  • Eric Rojas

    (Department of Computer Science, School of Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile
    Department of Internal Medicine, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile)

  • Andres Cifuentes

    (Department of Computer Science, School of Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile)

  • Andrea Burattin

    (Software and Process Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark)

  • Jorge Munoz-Gama

    (Department of Computer Science, School of Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile)

  • Marcos Sepúlveda

    (Department of Computer Science, School of Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile)

  • Daniel Capurro

    (Department of Internal Medicine, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 8331150, Chile)

Abstract

The performance analysis of Emergency Room episodes is aimed at providing decision makers with knowledge that allows them to decrease waiting times, reduce patient congestion, and improve the quality of care provided. In this case study, Process Mining is used to determine which activities, sub-processes, interactions, and characteristics of episodes explain why some episodes have a longer duration. The employed method and the results obtained are described in detail to serve as a guide for future performance analysis in this domain. It was discovered that the main cause of the increment in the episode duration is the occurrence of a loop between the Examination and Treatment sub-processes. It was also found out that as the episode severity increases, the number of repetitions of the Examination–Treatment loop increases as well. Moreover, the episodes in which this loop is more common are those that lead to Hospitalization as discharge destination. These findings might help to reduce the occurrence of this loop, in turn lowering the episode duration and, consequently, providing faster attention to more patients.

Suggested Citation

  • Eric Rojas & Andres Cifuentes & Andrea Burattin & Jorge Munoz-Gama & Marcos Sepúlveda & Daniel Capurro, 2019. "Performance Analysis of Emergency Room Episodes Through Process Mining," IJERPH, MDPI, vol. 16(7), pages 1-20, April.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1274-:d:221355
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    References listed on IDEAS

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    1. Cardoen, Brecht & Demeulemeester, Erik & Beliën, Jeroen, 2010. "Operating room planning and scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 201(3), pages 921-932, March.
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    Cited by:

    1. Minsu Cho & Minseok Song & Junhyun Park & Seok-Ran Yeom & Il-Jae Wang & Byung-Kwan Choi, 2020. "Process Mining-Supported Emergency Room Process Performance Indicators," IJERPH, MDPI, vol. 17(17), pages 1-20, August.

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