TY - JOUR
T1 - Development and application of simulation modelling for orthopaedic elective resource planning in England
AU - Harper, A
AU - Monks, T
AU - Wilson, R
AU - Redaniel, MT
AU - Eyles, E
AU - Jones, T
AU - Penfold, C
AU - Elliott, A
AU - Keen, T
AU - Pitt, M
AU - Blom, A
AU - Whitehouse, MR
AU - Judge, A
N1 - © 2023 Author(s) (or their employer(s)). Re-use permitted under CC BY. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made.
PY - 2023/12/22
Y1 - 2023/12/22
N2 - Objectives This study aimed to develop a simulation model to support orthopaedic elective capacity planning. Methods An open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016 and 2019 of elective orthopaedic procedures from a National Health Service (NHS) Trust in England. In this paper, it is used to investigate scenarios including resourcing (beds and theatres) and productivity (lengths of stay, delayed discharges and theatre activity) to support planning for meeting new NHS targets aimed at reducing elective orthopaedic surgical backlogs in a proposed ring-fenced orthopaedic surgical facility. The simulation is interactive and intended for use by health service planners and clinicians. Results A higher number of beds (65–70) than the proposed number (40 beds) will be required if lengths of stay and delayed discharge rates remain unchanged. Reducing lengths of stay in line with national benchmarks reduces bed utilisation to an estimated 60 allowing for additional theatre activity such as weekend working. Further, reducing the proportion of patients with a delayed discharge by 750 even with weekend working. A range of other scenarios can also be investigated directly by NHS planners using the interactive web app. Conclusions The simulation model is intended to support capacity planning of orthopaedic elective services by identifying a balance of capacity across theatres and beds and predicting the impact of productivity measures on capacity requirements. It is applicable beyond the study site and can be adapted for other specialties.
AB - Objectives This study aimed to develop a simulation model to support orthopaedic elective capacity planning. Methods An open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016 and 2019 of elective orthopaedic procedures from a National Health Service (NHS) Trust in England. In this paper, it is used to investigate scenarios including resourcing (beds and theatres) and productivity (lengths of stay, delayed discharges and theatre activity) to support planning for meeting new NHS targets aimed at reducing elective orthopaedic surgical backlogs in a proposed ring-fenced orthopaedic surgical facility. The simulation is interactive and intended for use by health service planners and clinicians. Results A higher number of beds (65–70) than the proposed number (40 beds) will be required if lengths of stay and delayed discharge rates remain unchanged. Reducing lengths of stay in line with national benchmarks reduces bed utilisation to an estimated 60 allowing for additional theatre activity such as weekend working. Further, reducing the proportion of patients with a delayed discharge by 750 even with weekend working. A range of other scenarios can also be investigated directly by NHS planners using the interactive web app. Conclusions The simulation model is intended to support capacity planning of orthopaedic elective services by identifying a balance of capacity across theatres and beds and predicting the impact of productivity measures on capacity requirements. It is applicable beyond the study site and can be adapted for other specialties.
U2 - 10.1136/bmjopen-2023-076221
DO - 10.1136/bmjopen-2023-076221
M3 - Article
SN - 2044-6055
VL - 13
JO - BMJ Open
JF - BMJ Open
IS - 12
ER -