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Objective assessment tools in laparoscopic or robotic-assisted gynecological surgery: A systematic review

Tesfai, Freweini Martha; Nagi, Jasleen; Morrison, Iona; Boal, Matt; Olaitan, Adeola; Chandrasekaran, Dhivya; Stoyanov, Danail; ... Francis, Nader; + view all (2024) Objective assessment tools in laparoscopic or robotic-assisted gynecological surgery: A systematic review. Acta Obstetricia et Gynecologica Scandinavica 10.1111/aogs.14840. (In press). Green open access

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Abstract

INTRODUCTION: There is a growing emphasis on proficiency-based progression within surgical training. To enable this, clearly defined metrics for those newly acquired surgical skills are needed. These can be formulated in objective assessment tools. The aim of the present study was to systematically review the literature reporting on available tools for objective assessment of minimally invasive gynecological surgery (simulated) performance and evaluate their reliability and validity. MATERIAL AND METHODS: A systematic search (1989-2022) was conducted in MEDLINE, Embase, PubMed, Web of Science in accordance with PRISMA. The trial was registered with the Prospective Register of Systematic Reviews (PROSPERO) ID: CRD42022376552. Randomized controlled trials, prospective comparative studies, prospective single-group (with pre- and post-training assessment) or consensus studies that reported on the development, validation or usage of assessment tools of surgical performance in minimally invasive gynecological surgery, were included. Three independent assessors assessed study setting and validity evidence according to a contemporary framework of validity, which was adapted from Messick's validity framework. Methodological quality of included studies was assessed using the modified medical education research study quality instrument (MERSQI) checklist. Heterogeneity in data reporting on types of tools, data collection, study design, definition of expertise (novice vs. experts) and statistical values prevented a meaningful meta-analysis. RESULTS: A total of 19 746 titles and abstracts were screened of which 72 articles met the inclusion criteria. A total of 37 different assessment tools were identified of which 13 represented manual global assessment tools, 13 manual procedure-specific assessment tools and 11 automated performance metrices. Only two tools showed substantive evidence of validity. Reliability and validity per tool were provided. No assessment tools showed direct correlation between tool scores and patient related outcomes. CONCLUSIONS: Existing objective assessment tools lack evidence on predicting patient outcomes and suffer from limitations in transferability outside of the research environment, particularly for automated performance metrics. Future research should prioritize filling these gaps while integrating advanced technologies like kinematic data and AI for robust, objective surgical skill assessment within gynecological advanced surgical training programs.

Type: Article
Title: Objective assessment tools in laparoscopic or robotic-assisted gynecological surgery: A systematic review
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/aogs.14840
Publisher version: http://dx.doi.org/10.1111/aogs.14840
Language: English
Additional information: © 2024 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG). This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Keywords: minimally invasive gynecological surgery, objective assessment tools, surgical training
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10191272
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