Simulation modelling of delayed discharge from hospital

Abeysooriya, Ranga P., Amarasinghe, Nirmani, Boyle, Laura, Currie, Christine S.M. and Lamas-Fernandez, Carlos (2025) Simulation modelling of delayed discharge from hospital. Harper, Alison, Luis, Martino, Monks, Thomas and Mustafee, Navonil (eds.) In Proceedings of the Operational Research Society Simulation Workshop 2025 (SW25). The Operational Research Society. 10 pp . (doi:10.36819/SW25.040).

Abstract

Delayed discharge happens when patients remain in hospital despite being medically fit for discharge. This situation negatively impacts patients for example through loss of mobility and independence, and creates operational difficulties for hospitals, such as reduced bed availability. This study presents a discrete event simulation model of the hospital discharge process in England’s NHS, where patients are discharged to one of four pathways. The aim is to create a simulation model that tackles both capacity-related and non-capacity-related discharge delays and identifies the acceptance probability of difficult-to-place patients along with the estimations of their daily discharge capacities at four discharge pathways. The model captures the proportion of delayed patients who are considered to be difficult to place in onwards care and might be still delayed even when there is onward care capacity available. The simulation model is parameterised using published NHS England data. Two of the parameters were not known from the data and an optimisation approach is presented to estimate their value. We describe the model and computational experiments applied to five large NHS Foundation Trusts in the South East region of England. We fit the model both globally (for all five trusts) and locally (for each trust individually). The findings show that locally fitted parameters best match the data, revealing variations in patient placement challenges across trusts.

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Contributors

Author: Christine S.M. Currie

Author: Carlos Lamas-Fernandez

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