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Characterization of the flow of patients in a hospital from complex networks

Author

Listed:
  • M. A. Miranda

    (University of Navarra)

  • S. Salvatierra

    (University of Navarra)

  • I. Rodríguez

    (University of Navarra)

  • M. J. Álvarez

    (University of Navarra)

  • V. Rodríguez

    (University of Navarra)

Abstract

We study the efficiency of operations management in a hospital from the dynamics of the flow of patients. Our principal aim is to characterize strategic departments and seasonal patterns in a hospital from a complex networks approach. Process mining techniques are developed to track out-patients’ pathways along different departments for the purpose of building weekly networks. In these networks, departments act as nodes with multiple out/in-going arrows connecting other departments. Strategic departments are classified into target and critical departments. On the one hand, target departments, which in this study belong to the oncology area, correspond to those affected by new management policies whose impact is to be assessed. On the other hand, critical departments correspond to the most active departments, the hubs of the networks. Using suitable networks parameters, strategic departments are shown to be highly efficient regardless of the season, which naturally translates into a high level of service offered to patients. In addition, our results show conformance with the new objectives concerning target departments. The methodology presented is shown to be successful in evaluating the efficiency of hospital services in order to enhance process performances, and moreover, it is suitable to be implemented in healthcare management systems at a greater scale and the service industry whenever the flow of clients or customers are involved.

Suggested Citation

  • M. A. Miranda & S. Salvatierra & I. Rodríguez & M. J. Álvarez & V. Rodríguez, 2020. "Characterization of the flow of patients in a hospital from complex networks," Health Care Management Science, Springer, vol. 23(1), pages 66-79, March.
    • Handle: RePEc:kap:hcarem:v:23:y:2020:i:1:d:10.1007_s10729-018-9466-2
    DOI: 10.1007/s10729-018-9466-2
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    References listed on IDEAS

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    1. Daniel Gartner, 2014. "Scheduling the Hospital-Wide Flow of Elective Patients," Lecture Notes in Economics and Mathematical Systems, in: Optimizing Hospital-wide Patient Scheduling, edition 127, chapter 0, pages 33-54, Springer.
    2. Shoshana Hahn-Goldberg & Michael Carter & J. Beck & Maureen Trudeau & Philomena Sousa & Kathy Beattie, 2014. "Dynamic optimization of chemotherapy outpatient scheduling with uncertainty," Health Care Management Science, Springer, vol. 17(4), pages 379-392, December.
    3. Brian Denton & James Viapiano & Andrea Vogl, 2007. "Optimization of surgery sequencing and scheduling decisions under uncertainty," Health Care Management Science, Springer, vol. 10(1), pages 13-24, February.
    4. Jan Vissers, 2006. "A Logistics Approach for Hospital Process Improvements," International Series in Operations Research & Management Science, in: Randolph W. Hall (ed.), Patient Flow: Reducing Delay in Healthcare Delivery, chapter 0, pages 393-427, Springer.
    5. Gartner, Daniel & Kolisch, Rainer, 2014. "Scheduling the hospital-wide flow of elective patients," European Journal of Operational Research, Elsevier, vol. 233(3), pages 689-699.
    6. Yasin Gocgun & Martin Puterman, 2014. "Dynamic scheduling with due dates and time windows: an application to chemotherapy patient appointment booking," Health Care Management Science, Springer, vol. 17(1), pages 60-76, March.
    7. Meltzer, David & Chung, Jeanette & Khalili, Parham & Marlow, Elizabeth & Arora, Vineet & Schumock, Glen & Burt, Ron, 2010. "Exploring the use of social network methods in designing healthcare quality improvement teams," Social Science & Medicine, Elsevier, vol. 71(6), pages 1119-1130, September.
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    Cited by:

    1. Zarrin, Mansour, 2022. "Inferring causal networks of health care resilience and safety performance indicators: A two-stage fuzzy cognitive map approach," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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