Evidence map›Paper›PMID 38135323›Full record

ArticleBMJ open2023

Development and application of simulation modelling for orthopaedic elective resource planning in England.

Alison Harper, Thomas Monks, Rebecca Wilson, Maria Theresa Redaniel, Emily Eyles, Tim Jones, Chris Penfold, Andrew Elliott, Tim Keen, Martin Pitt and 3 more

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Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Alison HarperUniversity of Exeter Medical School, NIHR Applied Research Collaboration South West Peninsula, Exeter, UK a.l.harper@exeter.ac.uk.ORCID 0000-0001-5274-5037
Thomas MonksUniversity of Exeter Medical School, NIHR Applied Research Collaboration South West Peninsula, Exeter, UK.ORCID 0000-0003-2631-4481
Rebecca WilsonNIHR Applied Research Collaboration West, Bristol, UK.ORCID 0000-0003-4709-7260
Maria Theresa RedanielNIHR Applied Research Collaboration West, Bristol, UK.ORCID 0000-0002-0668-0874
Emily EylesNIHR Applied Research Collaboration West, Bristol, UK.ORCID 0000-0002-2695-7172
Tim JonesNIHR Applied Research Collaboration West, Bristol, UK.ORCID 0000-0002-1199-8668
Chris PenfoldNIHR Bristol Biomedical Research Centre, Bristol, UK.ORCID 0000-0001-8654-353X
Andrew ElliottNorth Bristol NHS Trust Southmead Hospital, Bristol, UK.
Tim KeenNorth Bristol NHS Trust Southmead Hospital, Bristol, UK.ORCID 0009-0005-6230-2455
Martin PittUniversity of Exeter Medical School, NIHR Applied Research Collaboration South West Peninsula, Exeter, UK.ORCID 0000-0003-4026-8346
Ashley BlomThe University of Sheffield, Sheffield, UK.ORCID 0000-0002-9940-1095
Michael R WhitehouseNorth Bristol NHS Trust Southmead Hospital, Bristol, UK.ORCID 0000-0003-2436-9024
Andrew JudgeNIHR Bristol Biomedical Research Centre, Bristol, UK.ORCID 0000-0003-3015-0432

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to develop a simulation model to support orthopaedic elective capacity planning.

methodsAn 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.

resultsA 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.

conclusionsThe 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.

Indexed as

OrthopedicsComputer SimulationElective Surgical ProceduresEnglandHumansState MedicineInformation managementOrganisation of health servicesOrthopaedic & trauma surgeryORTHOPAEDIC & TRAUMA SURGERYWorld Wide Web technology

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.