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An integrated approach for scheduling health care activities in a hospital

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  • Burdett, Robert L.
  • Kozan, Erhan

Abstract

To effectively utilise hospital beds, operating rooms (OR) and other treatment spaces, it is necessary to precisely plan patient admissions and treatments in advance. As patient treatment and recovery times are unequal and uncertain, this is not easy. In response, a sophisticated flexible job-shop scheduling (FJSS) model is introduced, whereby patients, beds, hospital wards and health care activities are respectively treated as jobs, single machines, parallel machines and operations. Our approach is novel because an entire hospital is describable and schedulable in one integrated approach. The scheduling model can be used to recompute timings after deviations, delays, postponements and cancellations. It also includes advanced conditions such as activity and machine setup times, transfer times between activities, blocking limitations and no wait conditions, timing and occupancy restrictions, buffering for robustness, fixed activities and sequences, release times and strict deadlines. To solve the FJSS problem, constructive algorithms and hybrid meta-heuristics have been developed. Our numerical testing shows that the proposed solution techniques are capable of solving problems of real world size. This outcome further highlights the value of the scheduling model and its potential for integration into actual hospital information systems.

Suggested Citation

  • Burdett, Robert L. & Kozan, Erhan, 2018. "An integrated approach for scheduling health care activities in a hospital," European Journal of Operational Research, Elsevier, vol. 264(2), pages 756-773.
  • Handle: RePEc:eee:ejores:v:264:y:2018:i:2:p:756-773
    DOI: 10.1016/j.ejor.2017.06.051
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    References listed on IDEAS

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    1. Sean Harris & David Claudio, 2022. "Current Trends in Operating Room Scheduling 2015 to 2020: a Literature Review," SN Operations Research Forum, Springer, vol. 3(1), pages 1-42, March.
    2. Anjomshoa, Hamideh & Dumitrescu, Irina & Lustig, Irvin & Smith, Olivia J., 2018. "An exact approach for tactical planning and patient selection for elective surgeries," European Journal of Operational Research, Elsevier, vol. 268(2), pages 728-739.
    3. Chen, Jianfu & Chu, Chengbin & Sahli, Abderrahim & Li, Kai, 2024. "A branch-and-price algorithm for unrelated parallel machine scheduling with machine usage costs," European Journal of Operational Research, Elsevier, vol. 316(3), pages 856-872.
    4. Marynissen, Joren & Demeulemeester, Erik, 2019. "Literature review on multi-appointment scheduling problems in hospitals," European Journal of Operational Research, Elsevier, vol. 272(2), pages 407-419.
    5. Karsten Schwarz & Michael Römer & Taïeb Mellouli, 2019. "A data-driven hierarchical MILP approach for scheduling clinical pathways: a real-world case study from a German university hospital," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 597-636, December.
    6. Wu, Xiaodan & Li, Juan & Chu, Chao-Hsien, 2019. "Modeling multi-stage healthcare systems with service interactions under blocking for bed allocation," European Journal of Operational Research, Elsevier, vol. 278(3), pages 927-941.
    7. Omolbanin Mashkani & Andreas T. Ernst & Dhananjay Thiruvady & Hanyu Gu, 2023. "Minimizing patients total clinical condition deterioration in operating theatre departments," Annals of Operations Research, Springer, vol. 328(1), pages 821-857, September.
    8. F. Davarian & J. Behnamian, 2022. "Robust finite-horizon scheduling/rescheduling of operating rooms with elective and emergency surgeries under resource constraints," Journal of Scheduling, Springer, vol. 25(6), pages 625-641, December.
    9. Burdett, Robert L & Corry, Paul & Yarlagadda, Prasad & Cook, David & Birgan, Sean & McPhail, Steven M, 2023. "A mathematical framework for regional hospital case mix planning and capacity appraisal," Operations Research Perspectives, Elsevier, vol. 10(C).
    10. Dauzère-Pérès, Stéphane & Ding, Junwen & Shen, Liji & Tamssaouet, Karim, 2024. "The flexible job shop scheduling problem: A review," European Journal of Operational Research, Elsevier, vol. 314(2), pages 409-432.

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