Quantifying the Metrics of Surgical Mastery: An Exploration in Data Science

项目总结 在外科手术中，人们公认可能需要10到20年的学习曲线才能肯定地掌握这一技能。 程序。我们相信，这一时间线可以而且应该缩短，以改善患者护理。我们的短期目标 是通过建立一个掌握的数据库，为外科数据科学的新兴领域做出重大贡献 评估手术性能，并为多模式数据收集和分析程序生成路线图。 广泛分享我们的流程、程序和结果，将有助于改变医疗保健领域的测量文化。 通过我们与美国外科医生学会新建立的伙伴关系(2019年10月)，我们已经 已经成功地通过“外科计量项目”开始了对话 (https://www.facs.org/education/surgical-metrics). 使用标准化的数据收集平台(掌握级的疝气模拟)，我们将部署和同步 多种数据捕获方法(运动跟踪、视频、音频和经过验证的手术性能核对表) 来建立我们的数据库。数据分析将量化外科手术的掌握程度，并包括新的应用和 机器学习中的新发现。 假设：使用多种同步的数据捕获方法和机器学习，有可能 创建一个精通级别的外科手术策略数据库，可以转化为增值的外科手术 外科医生的导航工具。 为了验证这一假设，我们将对以下释义的目的进行实证研究： 具体目标1：量化模拟腹腔镜术中的手术熟练程度(认知和技术) 使用从以下各项捕获的多模式性能指标的术后分析进行疝修补术 医院执业外科医生(N~125人)。 具体目标2：通过比较基于模拟的左心室肥厚建立手术掌握指标的有效性证据 性能与同一外科医生(N~60)的手术室LVH性能相同。 具体目标3：经验性地研究利用手术导航的最佳实施策略 该工具旨在将有关精通级别的手术性能策略的增值信息提供给 新一批医院执业外科医生(N~125人)。

PROJECT SUMMARY In surgery, it is accepted that there may be a ten to twenty-year learning curve to reach mastery for certain procedures. We believe this timeline can and should be shortened to improve patient care. Our short-term goal is to make a major contribution to the emerging field of Surgical Data Science by building a database of mastery level surgical performance and generating a roadmap for multimodal data collection and analysis procedures. Sharing our process, procedures and results broadly, will help to change measurement culture in healthcare. Through our newly developed partnership (October 2019) with the American College of Surgeons, we have already experienced early success in starting the conversation through the “Surgical Metrics Project” (https://www.facs.org/education/surgical-metrics). Using a standardized data collection platform (a mastery-level hernia simulation), we will deploy and synchronize multiple data capture approaches (motion tracking, video, audio and validated surgical performance checklists) to build our database. Data analysis will quantify surgical mastery and consist of new applications and discoveries in machine learning. Hypothesis: Using multiple, synchronized data capture approaches and machine learning, it is possible to create a database of mastery level surgical strategies that can be translated into a value-added, surgical navigation tool for surgeons. To test this hypothesis, we will empirically investigate the following paraphrased aims: SPECIFIC AIM 1: Quantify surgical mastery (cognitive and technical) during a simulated laparoscopic ventral hernia (LVH) repair by using a post-procedure analysis of multi-modal performance metrics captured from hospital credentialed surgeons (N~125). SPECIFIC AIM 2: Establish validity evidence for surgical mastery metrics by comparing simulation-based LVH performance with operating room LVH performance from the same surgeons (N~60). SPECIFIC AIM 3: Empirically investigate the best implementation strategy for utilization of a surgical navigation tool designed to deliver value-added information regarding mastery-level surgical performance strategies to a new group of hospital credentialed surgeons (N~125).