Igaki Takahiro, Takenaka Shin, Watanabe Yusuke, Kojima Shigehiro, Nakajima Kei, Takabe Yuya, Kitaguchi Daichi, Takeshita Nobuyoshi, Inomata Masafumi, Kuroyanagi Hiroya, Kinugasa Yusuke, Ito Masaaki
Surgical Device Innovation Office, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Department of Gastrointestinal Surgery, Tokyo Medical and Dental University Graduate School of Medicine, Bunkyo, Tokyo, Japan.
Surg Endosc. 2023 Feb;37(2):835-845. doi: 10.1007/s00464-022-09573-4. Epub 2022 Sep 12.
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.
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.
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.
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.
优先考虑患者健康至关重要，鉴于存在死亡风险，应对手术技术进行客观评估。然而，目前尚无一个全面的跨学科系统来评估不同水平外科医生各方面的技能。因此，本研究旨在通过分解和重构手术操作性能评估工具中的具体描述来揭示通用的手术能力，作为使用计算机视觉和基于机器学习的分析构建自动评估系统的基础。
研究参与者主要是胃肠外科领域的专家外科医生，研究方法包括数据收集、主题分析和验证。在数据收集方面，参与者根据详细的纳入和排除标准确定全球手术性能评估工具。此后，使用主题分析对工具中的描述进行详细分析，对特定规则进行编码、整合和讨论，以获得高级概念，即“技能元能力”。为了进行数据验证和可靠性保证，对“技能元能力”进行了重新分类。根据参与者标准选择了九个评估工具。
从九个工具描述中总共提取了189种技能表现，并归纳为以下五种能力：（1）组织处理，（2）心理运动技能，（3）效率，（4）解剖质量，以及（5）暴露质量。评估了这些能力的不同评估目标和目的随时间的演变重要性；结果显示可靠性相对较高，表明分类具有可重复性。这些能力中纳入基本技能（组织处理、心理运动技能和效率）和高级技能（解剖质量和暴露质量）增强了工具的全面性。
所确定的有助于外科医生将手术操作的隐性知识形式化并加以实施的能力具有高度可重复性。这些结果可用于形成自动技能评估系统的基础，并有助于外科医生改善护理和培训工作，从而改善患者预后。
