Abstract
Background
Prioritizing patient health is essential, and given the risk of mortality, surgical techniques should be objectively evaluated. However, there is no comprehensive cross-disciplinary system that evaluates skills across all aspects among surgeons of varying levels. Therefore, this study aimed to uncover universal surgical competencies by decomposing and reconstructing specific descriptions in operative performance assessment tools, as the basis of building automated evaluation system using computer vision and machine learning-based analysis.
Methods
The study participants were primarily expert surgeons in the gastrointestinal surgery field and the methodology comprised data collection, thematic analysis, and validation. For the data collection, participants identified global operative performance assessment tools according to detailed inclusion and exclusion criteria. Thereafter, thematic analysis was used to conduct detailed analyses of the descriptions in the tools where specific rules were coded, integrated, and discussed to obtain high-level concepts, namely, “Skill meta-competencies.” “Skill meta-competencies” was recategorized for data validation and reliability assurance. Nine assessment tools were selected based on participant criteria.
Results
In total, 189 types of skill performances were extracted from the nine tool descriptions and organized into the following five competencies: (1) Tissue handling, (2) Psychomotor skill, (3) Efficiency, (4) Dissection quality, and (5) Exposure quality. The evolutionary importance of these competences’ different evaluation targets and purpose over time were assessed; the results showed relatively high reliability, indicating that the categorization was reproducible. The inclusion of basic (tissue handling, psychomotor skill, and efficiency) and advanced (dissection quality and exposure quality) skills in these competencies enhanced the tools’ comprehensiveness.
Conclusions
The competencies identified to help surgeons formalize and implement tacit knowledge of operative performance are highly reproducible. These results can be used to form the basis of an automated skill evaluation system and help surgeons improve the provision of care and training, consequently, improving patient prognosis.
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Acknowledgements
We gratefully acknowledge the work of past and present members of our laboratory.
Funding
This research was supported by the Japan Agency for Medical Research and Development (AMED) under Grant Number: JP21vk0124001.
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Takahiro Igaki, Shin Takenaka, Yusuke Watanabe, Shigehiro Kojima, Kei Nakajima, Yuya Takabe, Daichi Kitaguchi, Nobuyoshi Takeshita, Masafumi Inomata, Hiroya Kuroyanagi, Yusuke Kinugasa, and Masaaki Ito have no conflicts of interest or financial ties to disclose.
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Igaki, T., Takenaka, S., Watanabe, Y. et al. Universal meta-competencies of operative performances: a literature review and qualitative synthesis. Surg Endosc 37, 835–845 (2023). https://doi.org/10.1007/s00464-022-09573-4
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DOI: https://doi.org/10.1007/s00464-022-09573-4