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Assessing the impact of uncertainty and the level of aggregation in case mix planning

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  • McRae, Sebastian
  • Brunner, Jens O.

Abstract

In this article, we present a framework for evaluating the impact of uncertainty and the use of different aggregation levels in case mix planning on the quality of strategic decisions regarding the case mix of a hospital. In particular, we analyze the effect of modeling (i) demand, (ii) resource use, and (iii) resource availability as stochastic input parameters on the performance of case mix planning models. In addition, the consequences of taking the weekly structure with inactive days without surgeries into account are assessed (iv). The purpose of this paper is to provide a guideline for the decision-maker planning the case mix on the consideration of stochastic aspects and different aggregation levels. We formulate a mixed integer programming model for case mix planning along with different stochastic and deterministic extensions. The value of the different extensions is analyzed using a factorial design. The resulting stochastic models are solved using sample average approximation. Simulation is used to evaluate the strategies derived by the different models using real-world data from a large German hospital. We find that highly aggregated basic case mix planning models can overestimate the objective value by up to 10% and potentially lead to biased results. Refining the problem decreased the gap between projected case mix planning results and simulated results considerably and led to improved solutions.

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  • 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).
    • Handle: RePEc:eee:jomega:v:97:y:2020:i:c:s0305048318307059
    DOI: 10.1016/j.omega.2019.07.002
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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. A, Augustin & P, Jouvet & N, Lahrichi & A, Lodi & LM, Rousseau, 2022. "A data-driven approach to include availability of ICU beds in the planning of the operating room," Omega, Elsevier, vol. 109(C).
    3. 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.

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