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Cost Evaluation for Capacity Planning Based on Patients’ Pathways via Semi-Markov Reward Modelling

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  • Christina Chatzimichail

    (Department of Mathematics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Pavlos Kolias

    (Department of Mathematics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

  • Alexandra Papadopoulou

    (Department of Mathematics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece)

Abstract

In the present paper, we develop a non-homogeneous semi-Markov reward model, deriving expressions for a healthcare system’s expected structure along with the expected costs generated by medical services and patients’ holding times in the states. We provide a novel definition and investigation for states’ availability, which is critical for capacity planning based on service demand in an environment of limited resources. The study is based on patients’ mobility through hospital care, where each patient spends an amount of time in every state of the hospital (emergency room, short-term acute care, hospitalization, surgery room, and intensive care unit). Multiple outcomes, such as discharge or death, can also be taken into account. We envisage a situation where any discharges are immediately replaced by a number of new admissions that carry on the pathways of the patients who exit. By assuming an expanding system, the new idea of states’ inflows is considered due to new patients who create pathways through hospital care, along with internal entrances. The theoretical results are illustrated numerically with simulated hospital data informed by aggregated public data of the Greek public health sector. The framework can be used for both strategic planning and cost evaluation purposes for hospital resources.

Suggested Citation

  • Christina Chatzimichail & Pavlos Kolias & Alexandra Papadopoulou, 2024. "Cost Evaluation for Capacity Planning Based on Patients’ Pathways via Semi-Markov Reward Modelling," Mathematics, MDPI, vol. 12(10), pages 1-15, May.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:10:p:1430-:d:1389811
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    References listed on IDEAS

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    1. M. J. Faddy & S. I. McClean, 1999. "Analysing data on lengths of stay of hospital patients using phase‐type distributions," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 15(4), pages 311-317, October.
    2. K Cooper & S C Brailsford & R Davies, 2007. "Choice of modelling technique for evaluating health care interventions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 168-176, February.
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