Development and application of simulation modelling for orthopaedic elective resource planning in England
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 or...
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BMJ Publishing Group
2023-12-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/13/12/e076221.full |
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| author | Martin Pitt Andrew Judge Tim Jones Michael R Whitehouse Thomas Monks Rebecca Wilson Chris Penfold Andrew Elliott Ashley Blom Maria Theresa Redaniel Alison Harper Emily Eyles Tim Keen |
| author_facet | Martin Pitt Andrew Judge Tim Jones Michael R Whitehouse Thomas Monks Rebecca Wilson Chris Penfold Andrew Elliott Ashley Blom Maria Theresa Redaniel Alison Harper Emily Eyles Tim Keen |
| author_sort | Martin Pitt |
| collection | DOAJ |
| description | 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 75% reduces bed utilisation to below 40%, 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. |
| format | Article |
| id | doaj-art-27053f8c7ea54e7c8e164efce9df62f2 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | BMJ Publishing Group |
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| series | BMJ Open |
| spelling | doaj-art-27053f8c7ea54e7c8e164efce9df62f22025-08-20T03:52:16ZengBMJ Publishing GroupBMJ Open2044-60552023-12-01131210.1136/bmjopen-2023-076221Development and application of simulation modelling for orthopaedic elective resource planning in EnglandMartin Pitt0Andrew Judge1Tim Jones2Michael R Whitehouse3Thomas Monks4Rebecca Wilson5Chris Penfold6Andrew Elliott7Ashley Blom8Maria Theresa Redaniel9Alison Harper10Emily Eyles11Tim Keen127 Medical School, University of Exeter, Exeter, UK7 Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences, Oxford NIHR Biomedical Research Centre, University of Oxford, Oxford, UK1 National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, University of Bristol, Bristol, UKNorth Bristol NHS Trust Southmead Hospital, Bristol, UK2 University of Exeter Medical School, University of Exeter, Exeter, Devon, UK1NIHR ARC West, Population Health Sciences, University of Bristol, Bristol, UK1 National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, University of Bristol, Bristol, UK9Caris Life Sciences, Phoenix, AZ, USA4 The University of Sheffield, Sheffield, UKPopulation Health Sciences, University of Bristol, Bristol, UKUniversity of Exeter Faculty of Health and Life Sciences, Exeter, UK1 National Institute for Health and Care Research Applied Research Collaboration West (NIHR ARC West) at University Hospitals Bristol and Weston NHS Foundation Trust, University of Bristol, Bristol, UK8 North Bristol NHS Trust, Westbury on Trym, Bristol, UKObjectives 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 75% reduces bed utilisation to below 40%, 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.https://bmjopen.bmj.com/content/13/12/e076221.full |
| spellingShingle | Martin Pitt Andrew Judge Tim Jones Michael R Whitehouse Thomas Monks Rebecca Wilson Chris Penfold Andrew Elliott Ashley Blom Maria Theresa Redaniel Alison Harper Emily Eyles Tim Keen Development and application of simulation modelling for orthopaedic elective resource planning in England BMJ Open |
| title | Development and application of simulation modelling for orthopaedic elective resource planning in England |
| title_full | Development and application of simulation modelling for orthopaedic elective resource planning in England |
| title_fullStr | Development and application of simulation modelling for orthopaedic elective resource planning in England |
| title_full_unstemmed | Development and application of simulation modelling for orthopaedic elective resource planning in England |
| title_short | Development and application of simulation modelling for orthopaedic elective resource planning in England |
| title_sort | development and application of simulation modelling for orthopaedic elective resource planning in england |
| url | https://bmjopen.bmj.com/content/13/12/e076221.full |
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