Division of Clinical and Surgical Sciences, School of Surgery, The University of Edinburgh, Edinburgh, UK
Division of Clinical and Surgical Sciences, School of Surgery, The University of Edinburgh, Edinburgh, UK.
BMJ Open. 2023 Feb 3;13(2):e064196. doi: 10.1136/bmjopen-2022-064196.
Surgeons need high fidelity, high quality, objective, non-judgemental and quantitative feedback to measure their performance in order to optimise their performance and improve patient safety. This can be provided through surgical sabermetrics, defined as 'advanced analytics of digitally recorded surgical training and operative procedures to enhance insight, support professional development and optimise clinical and safety outcomes'. The aim of this scoping review is to investigate the assessment of surgeon's non-technical skills using sabermetrics principles, focusing on digital, automated measurements that do not require a human observer.
To investigate the current methods of digital, automated measurements of surgeons' non-technical skills, a systematic scoping review will be conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, using databases from medicine and other fields. Covidence software is used for screening of potential studies. A data extraction tool will be developed specifically for this study to evaluate the methods of measurement. Quality assurance will be assessed using Quality Assessment Tool for Diverse Designs. Multiple reviewers will be responsible for screening of studies and data extraction.
This is a review study, not using primary data, and therefore, ethical approval is not required. A range of methods will be employed for dissemination of the results of this study, including publication in journals and conference presentations.
外科医生需要高保真、高质量、客观、非评判性和定量的反馈,以衡量他们的表现,从而优化他们的表现并提高患者的安全性。这可以通过手术萨比梅特里克(surgical sabermetrics)来提供,它被定义为“对数字记录的手术训练和手术过程进行高级分析,以增强洞察力、支持专业发展并优化临床和安全结果”。本综述的目的是调查使用萨比梅特里克原理评估外科医生非技术技能的情况,重点关注无需人工观察者的数字、自动化测量。
为了研究外科医生非技术技能的数字、自动化测量方法,我们将按照系统综述和荟萃分析扩展的首选报告项目(Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension)进行系统综述,使用医学和其他领域的数据库。Covidence 软件用于筛选潜在的研究。将专门为此研究开发数据提取工具来评估测量方法。使用多样化设计质量评估工具(Quality Assessment Tool for Diverse Designs)评估质量保证。多名审阅者将负责筛选研究和数据提取。
这是一项综述研究,不使用原始数据,因此不需要伦理批准。将采用多种方法传播本研究的结果,包括在期刊上发表和会议报告。