Evidence map›Paper›PMID 37951600›Full record

SynthesisThe British journal of surgery2024

Evaluation of objective tools and artificial intelligence in robotic surgery technical skills assessment: a systematic review.

Matthew W E Boal, Dimitrios Anastasiou, Freweini Tesfai, Walaa Ghamrawi, Evangelos Mazomenos, Nathan Curtis, Justin W Collins, Ashwin Sridhar, John Kelly, Danail Stoyanov and 1 more

Abstract readSystematic Review
In one paragraph

Synthesis in The British journal of surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 3 pooled it
–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

43 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  13. Blob representation of robotic surgical scenes for position-aware video generation.International journal of computer assisted radiology and surgery · 2026
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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

11 authors.

Matthew W E BoalThe Griffin Institute, Northwick Park & St Marks' Hospital, London, UK.ORCID 0000-0002-7288-3354
Dimitrios AnastasiouWellcome/ESPRC Centre for Interventional Surgical Sciences (WEISS), University College London (UCL), London, UK.
Freweini TesfaiThe Griffin Institute, Northwick Park & St Marks' Hospital, London, UK.
Walaa GhamrawiThe Griffin Institute, Northwick Park & St Marks' Hospital, London, UK.
Evangelos MazomenosWellcome/ESPRC Centre for Interventional Surgical Sciences (WEISS), University College London (UCL), London, UK.
Nathan CurtisDepartment of General Surgey, Dorset County Hospital NHS Foundation Trust, Dorchester, UK.ORCID 0000-0001-5655-6823
Justin W CollinsDivision of Surgery and Interventional Science, Research Department of Targeted Intervention, UCL, London, UK.
Ashwin SridharDivision of Surgery and Interventional Science, Research Department of Targeted Intervention, UCL, London, UK.
John KellyDivision of Surgery and Interventional Science, Research Department of Targeted Intervention, UCL, London, UK.
Danail StoyanovWellcome/ESPRC Centre for Interventional Surgical Sciences (WEISS), University College London (UCL), London, UK.ORCID 0000-0002-0980-3227
Nader K FrancisThe Griffin Institute, Northwick Park & St Marks' Hospital, London, UK.ORCID 0000-0001-8498-9175

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a need to standardize training in robotic surgery, including objective assessment for accreditation. This systematic review aimed to identify objective tools for technical skills assessment, providing evaluation statuses to guide research and inform implementation into training curricula.

methodsA systematic literature search was conducted in accordance with the PRISMA guidelines. Ovid Embase/Medline, PubMed and Web of Science were searched. Inclusion criterion: robotic surgery technical skills tools. Exclusion criteria: non-technical, laparoscopy or open skills only. Manual tools and automated performance metrics (APMs) were analysed using Messick's concept of validity and the Oxford Centre of Evidence-Based Medicine (OCEBM) Levels of Evidence and Recommendation (LoR). A bespoke tool analysed artificial intelligence (AI) studies. The Modified Downs-Black checklist was used to assess risk of bias.

resultsTwo hundred and forty-seven studies were analysed, identifying: 8 global rating scales, 26 procedure-/task-specific tools, 3 main error-based methods, 10 simulators, 28 studies analysing APMs and 53 AI studies. Global Evaluative Assessment of Robotic Skills and the da Vinci Skills Simulator were the most evaluated tools at LoR 1 (OCEBM). Three procedure-specific tools, 3 error-based methods and 1 non-simulator APMs reached LoR 2. AI models estimated outcomes (skill or clinical), demonstrating superior accuracy rates in the laboratory with 60 per cent of methods reporting accuracies over 90 per cent, compared to real surgery ranging from 67 to 100 per cent.

conclusionsManual and automated assessment tools for robotic surgery are not well validated and require further evaluation before use in accreditation processes.PROSPERO: registration ID CRD42022304901.

Indexed as

LaparoscopyRoboticsRobotic Surgical ProceduresArtificial IntelligenceClinical CompetenceHumans

Identifiers

PMID37951600
PMCPMC10771126

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.