A Study of Objective Skills Assessment and Learning Rates in a Septoplasty Model

描述（由申请人提供）：患者安全是所有医学学科的首要问题。外科教育工作者和执照委员会通过确保对外科住院医师进行充分的技术培训，为患者安全做出贡献。研究生医学教育认证理事会（ACGME）最近对住院医师要求进行了修改，要求从学徒式、非系统性培训转变为基于能力的培训，并进行客观的手术技能评估。到目前为止，有效的，公正的，自动化的技能评估工具主要用于评估结构化设置的技能。我们假设这些方法在现场手术条件下是稳健的，因此可以用于在执行手术时直接测量外科医生的技能。我们进一步假设，我们将能够区分四个级别的手术技能（初学者，中级，高级和专家），我们将能够确定程序特定的学习曲线。学习曲线，即，技能和案件数量之间的关系，是教育工作者的重大利益，我们推测他们将发挥重要作用，在案件数量和时间为基础的培训，以能力为基础的培训模式之间的过渡。所介绍的方法是通用的，将在鼻中隔成形术模型中进行概念验证。鼻中隔成形术被认为是所有耳鼻喉科住院医师的“索引”病例;手术的复杂性使其成为理想的原型候选人。该项目的核心科学工作是：1）创建一个客观的技能评估平台，用于开发和验证术中技能评估工具，2）证明存在可用于技能评估的确定性手术模型，并深入了解手术过程，3）验证确定性和随机性（隐马尔可夫模型）手术工具的客观技能评估和4）测量学习曲线的中隔手术。该项目通过提高外科医生的技术能力确保患者安全，与公共卫生相关。

DESCRIPTION (provided by applicant): Patient safety is of paramount concern in all disciplines of medicine. Surgical educators and licensing boards contribute to patient safety by ensuring adequate technical training of surgical residents. Recent changes to residency requirements by the accreditation Council for Graduate Medical Education (ACGME) mandate a paradigm shift from apprenticeship-style, unsystematic training to competency-based training with objective surgical skills assessment. To date, valid, unbiased, automated skills assessment tools are used primarily to assess skill in structured settings. We hypothesize that these methods are robust under live surgery conditions and therefore can be used to directly measure a surgeon's skill while performing surgery. We further hypothesize that we will be able to distinguish between four levels of surgical skill (beginner, intermediate, advanced, and expert) and that we will be able to determine procedure-specific learning curves. Learning curves, i.e., relationships between skill and case number, are of significant interest to educators; we conjecture they will play a major role during the transition between case number and time based training to competency based training paradigms. The methods presented are general, and proof of concept will be performed in a septoplasty surgery model. Septoplasty is considered an "index" case for all otolaryngology residents; the complexity of the surgery makes it an ideal proto-candidate. The core scientific work in this project is to 1) create an objective skills assessment platform for developing and validating intra-operative skills assessment tools, 2) demonstrate that deterministic models of surgery useful for skills assessment exist and give insight into the surgical process, 3) validate a deterministic and stochastic (Hidden Markov Model) surgery tool for objective skills assessment and 4) measure the learning curve for septal surgery. This project is relevant to public health by ensuring patient safety through improving technical competency of surgeons.