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Development and application of simulation modelling for orthopaedic elective resource planning in England
Alison Harper1,2, Thomas Monks3,2, Rebecca Wilson4,5
1University of Exeter Medical School, NIHR Applied Research Collaboration South West Peninsula, Exeter, UK a.l.harper@exeter.ac.uk.
BMJ Open
|December 22, 2023
Summary
Developing a simulation model for orthopaedic elective surgery capacity planning revealed that current patient flow requires more beds than proposed. Optimizing length of stay and reducing delayed discharges significantly impacts bed utilization and theatre capacity.
Area of Science:
- Health Services Research
- Operations Research
- Medical Simulation
Background:
- National Health Service (NHS) Trusts face increasing pressure to reduce elective orthopaedic surgical backlogs.
- Effective capacity planning is crucial for optimizing resource allocation, including beds and operating theatres.
- Existing planning methods may not adequately account for dynamic factors influencing patient flow and resource demand.
Purpose of the Study:
- To develop a generalisable discrete-event simulation model for orthopaedic elective capacity planning.
- To support health service planners and clinicians in making informed decisions regarding resource allocation and productivity improvements.
- To investigate the impact of varying resourcing and productivity scenarios on meeting new NHS targets.
Main Methods:
- Developed an open-source, generalisable discrete-event simulation model with a web-based application.
- Utilized anonymised patient records from 2016-2019 for elective orthopaedic procedures at an NHS Trust.
- Investigated scenarios related to bed and theatre resourcing, length of stay, delayed discharges, and theatre activity.
Main Results:
- Current patient flow indicates a need for 65-70 beds, exceeding the proposed 40 beds, if length of stay and delayed discharge rates remain constant.
- Reducing length of stay to national benchmarks decreases bed utilization to approximately 60%, enabling increased theatre activity.
- A 75% reduction in delayed discharges lowers bed utilization below 40%, even with weekend theatre operations.
Conclusions:
- The simulation model effectively supports orthopaedic elective capacity planning by balancing theatre and bed capacity.
- It predicts the impact of productivity enhancements on capacity requirements, aiding in strategic decision-making.
- The model's generalisable nature allows for adaptation to other surgical specialties and healthcare settings.
