Artificial Intelligence Driven Tools for Objective Surgical Performance Improvement

人工智能驱动工具可客观提高手术表现

• 批准号: 10279444
• 负责人: Shameema Sikder
• 金额: $ 46万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10279444
• 关键词: Active Learning; Acute; Address; Adoption; Adult; Ambulatory Care; Artificial Intelligence; Automation; Behavioral; COVID-19 pandemic; Capsulorhexis; Caring; Cataract; Cataract Extraction; Competence; Complication; Computer Vision Systems; Data; Data Science; Development; Devices; Education; Effectiveness; Elements; Ensure; Evaluation; Faculty; Feedback; Foundations; Goals; Image; Incentives; Information Retrieval; Institution; Intention; Intuition; Learning; Libraries; Machine Learning; Measures; Methodology; Methods; Operative Surgical Procedures; Ophthalmology; Outcome; Pathway interactions; Patient Care; Patient-Focused Outcomes; Patients; Performance; Procedures; Process; Reproducibility; Research; Residencies; Resources; Risk; Risk Estimate; Structure; Supervision; Surgeon; System; Technical Expertise; Testing; Time; Training; Translating; Work; adverse event risk; base; care outcomes; career; computer human interaction; dashboard; deep learning; deep learning algorithm; effectiveness evaluation; experience; improved; improved outcome; instrument; learning progression; multidisciplinary; novel; personalized learning; prototype; response; skill acquisition; skills; statistics; tool; usability; user centered design

Abstract / Summary Currently, supervised surgical training provides only a small fraction of surgical experience in the career of a practicing surgeon. Surgeons’ skill develops throughout their career. Surgeons benefit from supervised feedback from experts during training, but they lose such structured and specific feedback once they begin independent practice. Surgical skill is associated with patient outcomes. Therefore, supporting surgeons’ continuous professional learning through automated structured resources can improve patient care. The status quo for surgeons in practice is to measure patient outcomes or other process of care variables as indirect measures of their skill. These measures do not inform surgeons how to improve. The goal in this project is to develop tools to analyze videos of the surgical field to provide surgeons with unbiased skill assessments and specific feedback on how to improve. This project includes integration of these tools into a personalized surgical learning platform and evaluation of its effectiveness for surgeons’ skill acquisition. To achieve this goal, this project includes a multi-disciplinary team to include expertise in ophthalmology, surgical education, surgical data science, computer vision, machine learning and deep learning, statistics, and human-computer interaction. The video analysis tools developed in this project will enable the following for cataract surgery, one of the most common surgical procedures in the U.S. and across the world: 1) objective assessments of surgeons’ skill; 2) provide surgeons with specific feedback on how to improve that is personalized given their past performance; and 3) preliminary evidence of effectiveness of a personalized learning platform for surgeons’ skill acquisition. The anticipated impact of our work is to create a pathway in which the surgeon is incentivized to see themselves and their performance as part of the process of improving outcomes and value in care, and institutions have access to objective tools to create reproducible standards for surgical competency.

摘要 /摘要 目前，受监督的手术训练在实践的职业中仅提供一小部分手术经验 外科医生。外科医生在整个职业生涯中的发展。外科医生受益于专家的监督反馈 培训，但是一旦他们开始独立实践，他们就会失去这种结构化和具体的反馈。手术技能是 与患者预后相关。因此，通过自动化支持外科医生的持续专业学习 结构化资源可以改善患者护理。实践中外科医生的现状是衡量患者的预后或 护理变量的其他过程是其技能的间接测量。这些措施不会告知外科医生如何改善。 该项目的目标是开发工具来分析手术领域的视频，以为外科医生提供无偏见的技能 评估和有关如何改进的具体反馈。该项目包括将这些工具集成到个性化 外科学习平台及其对外科医生技能获取的有效性的评估。为了实现这一目标，这个项目 包括一个多学科团队，包括眼科专业知识，外科教育，外科数据科学，计算机 视觉，机器学习和深度学习，统计和人力计算机的互动。开发了视频分析工具 在该项目中，将使白内障手术（美国最常见的外科手术之一）和 全世界：1）对外科医生技能的客观评估； 2）为外科医生提供有关如何改进的具体反馈 鉴于他们过去的表现，这是个性化的； 3）个性化学习有效性的初步证据 外科医生的技能获取平台。我们工作的预期影响是创建一条外科医生所在的途径 激励人们将自己及其表现视为改善护理结果和价值的过程的一部分， 机构可以使用客观的工具来创建可重复的手术能力标准。