posted on 2017-08-18, 13:47authored byFraser Greenroyd, Rebecca Hayward, Andrew Price, Peter DemianPeter Demian, Shrikant Sharma
As the National Health Service (NHS) of England continues to face tighter cost saving and utilisation
government set targets, finding the optimum between costs, patient waiting times, utilisation of resources,
and user satisfaction is increasingly challenging. Patient scheduling is a subject which has been extensively
covered in the literature, with many previous studies offering solutions to optimise the patient schedule for a
given metric. However, few analyse a large range of metrics pertinent to the NHS. The tool presented in this
paper provides a discrete-event simulation tool for analysing a range of patient schedules across nine
metrics, including: patient waiting, clinic room utilisation, waiting room utilisation, staff hub utilisation,
clinician utilisation, patient facing time, clinic over-run, post-clinic waiting, and post-clinic patients still
being examined. This allows clinic managers to analyse a number of scheduling solutions to find the
optimum schedule for their department by comparing the metrics and selecting their preferred schedule.
Also provided is an analysis of the impact of variations in appointment durations and their impact on how a
simulation tool provides results. This analysis highlights the need for multiple simulation runs to reduce the
impact of non-representative results from the final schedule analysis.
Funding
We would like to thank the Engineering and
Physical Sciences Research Council, and Centre for
Innovative and Collaborative Construction
Engineering at Loughborough University for
provision of a grant (number EPG037272) to
undertake this research project in collaboration with
BuroHappold Engineering Ltd.
History
School
Architecture, Building and Civil Engineering
Published in
SimulTech 2017 - 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications
Citation
GREENROYD, F.L. ... et al., 2017. Maximising patient throughput using discrete-event simulation. IN: Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, pp. 204-214, Madrid, Spain.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Acceptance date
2017-05-08
Publication date
2017
Notes
This is a conference paper. Made available by kind permission of the publisher.