Pre-Procedural Robotic Surgery Curricula: A Systematic Review and Thematic Meta-Synthesis

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Objective: This review aims to analyze robotic surgery training prior to clinical operation. Summary Background Data: In the interest of patient safety, preprocedural simulation-based training is imperative on a new medical technology prior to in vivo operation. Methods: A study protocol was developed in accordance with Preferred Items for the Reporting of Systematic Reviews and Meta-Analyses guidelines. A search of the Pubmed, Embase, and Cochrane databases was conducted. Title and abstract screening were performed. Full texts were appraised for eligibility. Data regarding platform utilized, speciality and grade of intended target training population, duration and delivery method of curriculum, and outcome measures were determined. A meta-analysis was precluded given the heterogeneity of extracted data, therefore, a meta-synthesis was performed. Results: After removal of duplicates 734 records were screened. Of these, 290 full texts were sought for retrieval and assessed for eligibility. In total, 87 records fulfilled the inclusion criteria: describing, validating, reviewing, or proposing guidelines for preprocedural curricula in robotic surgery. Almost half (47%) of records were published between 2018 and 2024. While not universal, the common components of preprocedural curricula for robotic surgery involve participants acquiring canonical (context independent) knowledge and skills. Didactic modules and bedside education of the system are typically followed by high fidelity simulation training using virtual reality, dry, and wet laboratory rudimentary platform and procedural training. Conclusion: The exponential increase in recent publications in this field highlights the evolving awareness of preprocedural training when adopting new technologies including robotic surgery, and the need for consistent standards. Though challenging to implement, a standardized framework for preprocedural curriculum will aid all stakeholders, regardless of variations in resources and service demands.

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