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A mixed integer programming approach to the patient admission scheduling problem

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  • Bastos, Leonardo S.L.
  • Marchesi, Janaina F.
  • Hamacher, Silvio
  • Fleck, Julia L.

Abstract

Among the many challenges involved in efficient healthcare resource planning, the Patient Admission Scheduling Problem is of particular significance, impacting organizational decisions at all planning levels. The problem of scheduling patient admissions involves assigning patients to beds over a given time horizon so as to maximize treatment efficiency, patient comfort and hospital utilization, while satisfying all necessary medical constraints and taking into consideration patient preferences as much as possible. A number of different variants of the Patient Admission Scheduling Problem exist at the strategic, tactical, and operational levels. In this paper, we consider a static offline operational level variant for which we propose a comprehensive mixed integer programming formulation and advance an exact solution method. We generate new best found solutions for 9 out of 13 benchmark instances from a publicly available repository. Additionally, we prove the optimality of two best known solutions reported in the literature.

Suggested Citation

  • Bastos, Leonardo S.L. & Marchesi, Janaina F. & Hamacher, Silvio & Fleck, Julia L., 2019. "A mixed integer programming approach to the patient admission scheduling problem," European Journal of Operational Research, Elsevier, vol. 273(3), pages 831-840.
    • Handle: RePEc:eee:ejores:v:273:y:2019:i:3:p:831-840
    DOI: 10.1016/j.ejor.2018.09.003
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    References listed on IDEAS

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    1. Christiane Barz & Kumar Rajaram, 2015. "Elective Patient Admission and Scheduling under Multiple Resource Constraints," Production and Operations Management, Production and Operations Management Society, vol. 24(12), pages 1907-1930, December.
    2. Vissers, Jan M.H. & Adan, Ivo J.B.F. & Dellaert, Nico P., 2007. "Developing a platform for comparison of hospital admission systems: An illustration," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1290-1301, August.
    3. Kusters, Rob J. & Groot, Petra M. A., 1996. "Modelling resource availability in general hospitals design and implementation of a decision support model," European Journal of Operational Research, Elsevier, vol. 88(3), pages 428-445, February.
    4. James C. Riley, 2005. "Estimates of Regional and Global Life Expectancy, 1800–2001," Population and Development Review, The Population Council, Inc., vol. 31(3), pages 537-543, September.
    5. Range, Troels Martin & Lusby, Richard Martin & Larsen, Jesper, 2014. "A column generation approach for solving the patient admission scheduling problem," European Journal of Operational Research, Elsevier, vol. 235(1), pages 252-264.
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    Cited by:

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    9. Zhaohui Li & Haiyue Yu & Zhaowei Zhou, 2024. "Scheduling of elective operations with coordinated utilization of hospital beds and operating rooms," Journal of Combinatorial Optimization, Springer, vol. 47(5), pages 1-29, July.

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