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A stochastic optimization model for shift scheduling in emergency departments

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  • Omar EL-Rifai
  • Thierry Garaix
  • Vincent Augusto
  • Xiaolan Xie

Abstract

Excessive waiting time in Emergency Departments (ED) can be both a cause of frustration and more importantly, a health concern for patients. Waiting time arises when the demand for work goes beyond the facility’s service capacity. ED service capacity mainly depends on human resources and on beds available for patients. In this paper, we focus on human resources organization in an ED and seek to best balance between service quality and working conditions. More specifically, we address the personnel scheduling problem in order to optimize the shift distribution among employees and minimize the total expected patients’ waiting time. The problem is also characterized by a multi-stage re-entrant service process. With an appropriate approximation of patients’ waiting times, we first propose a stochastic mixed-integer programming model that is solved by a sample average approximation (SAA) approach. The resulting personnel schedules are then evaluated using a discrete-event simulation model. Numerical experiments are then performed with data from a French hospital to compare different personnel scheduling strategies. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Omar EL-Rifai & Thierry Garaix & Vincent Augusto & Xiaolan Xie, 2015. "A stochastic optimization model for shift scheduling in emergency departments," Health Care Management Science, Springer, vol. 18(3), pages 289-302, September.
    • Handle: RePEc:kap:hcarem:v:18:y:2015:i:3:p:289-302
    DOI: 10.1007/s10729-014-9300-4
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    Cited by:

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    3. Amir Elalouf & Guy Wachtel, 2022. "Queueing Problems in Emergency Departments: A Review of Practical Approaches and Research Methodologies," SN Operations Research Forum, Springer, vol. 3(1), pages 1-46, March.
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    6. Renata Mansini & Roberto Zanotti, 2020. "Optimizing the physician scheduling problem in a large hospital ward," Journal of Scheduling, Springer, vol. 23(3), pages 337-361, June.
    7. Ezzah Suraya Sarudin & Wan Nor Munirah Ariffin & Siti Suhana Jamaian, 2024. "Mapping the Landscape: A Bibliometric Analysis of Staff Scheduling Optimization Research Trends and Keywords Evolution," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(8), pages 358-372, August.
    8. Kraul, Sebastian & Brunner, Jens O., 2023. "Stable annual scheduling of medical residents using prioritized multiple training schedules to combat operational uncertainty," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1263-1278.
    9. Erhard, Melanie & Schoenfelder, Jan & Fügener, Andreas & Brunner, Jens O., 2018. "State of the art in physician scheduling," European Journal of Operational Research, Elsevier, vol. 265(1), pages 1-18.
    10. Tohidi, Mohammad & Kazemi Zanjani, Masoumeh & Contreras, Ivan, 2021. "A physician planning framework for polyclinics under uncertainty," Omega, Elsevier, vol. 101(C).
    11. Farzad Zaerpour & Marco Bijvank & Huiyin Ouyang & Zhankun Sun, 2022. "Scheduling of Physicians with Time‐Varying Productivity Levels in Emergency Departments," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 645-667, February.
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