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Managing the patient portfolio using mathematical programming: decision support guidelines using a real-world use case at a university hospital

Author

Listed:
  • Milena Grieger

    (University of Augsburg)

  • Steffen Heider

    (Augsburg University Hospital)

  • Sebastian McRae

    (Klinikum rechts der Isar)

  • Thomas Koperna

    (Ludwig-Maximilian University Hospital)

  • Jens O. Brunner

    (University of Augsburg
    Technical University of Denmark
    Next Generation Technology)

Abstract

Many hospitals in Germany are facing escalating economic pressures. After several years of stagnation, the number of inpatient hospital treatments dropped by $$\:13\%$$ in 2020 compared to the previous year. This negative tendency can also be seen in operating theaters (OTs). Strategic management of the case mix in hospital OTs now necessitates a solid data foundation. The case mix and the case mix index have become central economic indicators in contemporary hospital operations. In this work, we develop a mathematical model for case mix optimization at Augsburg University Hospital in Germany, which is based on an extensive data analysis with descriptive methods. The optimization model is subject to rigorous testing and evaluation through an extensive series of scenario analyses. The primary objective is to calculate a revenue-maximizing patient mix while respecting the available scarce personnel resources in the OT and intensive care unit. This research marks a pioneering effort in delineating the practical integration of case mix planning into a hospital’s routine operations using mathematical optimization. The analyses reveal a strong correlation between an upsurge in revenue and an increased number of cases. Furthermore, the results demonstrate that strategic planning of the patient mix has the potential to enhance revenue with existing resources. Even though the optimal patient mix may not be directly implementable in practice, the findings yield valuable insights for managerial decision-making. A critical examination of these results also fosters a nuanced discourse on the utilization of optimization models as decision support tools within hospital management.

Suggested Citation

  • Milena Grieger & Steffen Heider & Sebastian McRae & Thomas Koperna & Jens O. Brunner, 2024. "Managing the patient portfolio using mathematical programming: decision support guidelines using a real-world use case at a university hospital," Journal of Business Economics, Springer, vol. 94(9), pages 1245-1260, November.
    • Handle: RePEc:spr:jbecon:v:94:y:2024:i:9:d:10.1007_s11573-024-01201-y
    DOI: 10.1007/s11573-024-01201-y
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    References listed on IDEAS

    as
    1. Sebastian McRae & Jens O. Brunner & Jonathan F. Bard, 2020. "Analyzing economies of scale and scope in hospitals by use of case mix planning," Health Care Management Science, Springer, vol. 23(1), pages 80-101, March.
    2. Sebastian Hof & Andreas Fügener & Jan Schoenfelder & Jens O. Brunner, 2017. "Case mix planning in hospitals: a review and future agenda," Health Care Management Science, Springer, vol. 20(2), pages 207-220, June.
    3. Steffen Heider & Jan Schoenfelder & Thomas Koperna & Jens O. Brunner, 2022. "Balancing control and autonomy in master surgery scheduling: Benefits of ICU quotas for recovery units," Health Care Management Science, Springer, vol. 25(2), pages 311-332, June.
    4. 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.
    5. McRae, Sebastian & Brunner, Jens O., 2020. "Assessing the impact of uncertainty and the level of aggregation in case mix planning," Omega, Elsevier, vol. 97(C).
    6. Peter J H Hulshof & Nikky Kortbeek & Richard J Boucherie & Erwin W Hans & Piet J M Bakker, 2012. "Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS," Health Systems, Taylor & Francis Journals, vol. 1(2), pages 129-175, December.
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