Structured and Modular Training Pathway for Robot-assisted Radical Prostatectomy (RARP): Validation of the RARP Assessment Score and Learning Curve Assessment
Structured and Modular Training Pathway for Robot-assisted Radical Prostatectomy (RARP): Validation of the RARP Assessment Score and Learning Curve Assessment
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DOI：
10.1016/j.eururo.2015.10.048
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发表时间：
2016-03-01
期刊：
影响因子：
23.4
通讯作者：
Ahmed, Kamran
中科院分区：
文献类型：
--
作者：
Lovegrove, Catherine;Novara, Giacomo;Ahmed, Kamran
背景：机器人辅助根治性前列腺切除术（RARP）治疗前列腺癌的使用正在增加。结构化的手术培训和客观评估对结果至关重要。目的：通过医疗保健失效模式和效应分析（HFMEA）为接受RARP的学员开发和验证模块化培训和评估途径，并评估手术步骤的学习曲线（LC）。设计、设置和参与者：这项多机构（欧洲、澳大利亚和美国）观察性前瞻性研究使用HFMEA识别RARP的高风险步骤。一个专家焦点小组使验证成为可能。15名接受欧洲泌尿外科协会机器人手术课程培训的学员进行了RARP，并由导师使用开发的工具进行评估。结果产生每个步骤的LC。结果测量和统计分析：我们使用模块化培训和评估工具（RARP评估评分）来评估技术技能。LC已建成。多变量Kruskal-Wallis，Mann-Whitney U和k系数分析used.Results和局限性：5名外科医生观察了42个控制台小时，以绘制RARP步骤。HFMEA确定了84种失效模式和46种潜在原因，危害评分>8。内容验证创建了RARP评估分数：17个阶段和41个步骤。RARP评估评分是可接受的（56.67%），可行的（96.67%），并具有教育影响（100%）。对15名机器人手术受训者进行了8个月的评估。在426例RARP病例（范围：4-79）中，受训者尝试了所有手术步骤。受训者由他们的专家导师用RARP评估分数进行评估，并绘制各个步骤的LC。LC显示前膀胱颈横断16例、后膀胱颈横断18例、后切除9例、前列腺蒂和精囊切除15例、吻合17例均为平台。其他步骤在数据收集期间未达到稳定状态。结论：基于HFMEA方法的RARP评估评分确定了重点RARP培训和评估外科医生的关键步骤。LC展示了必要的经验，以达到一定的能力水平的技术技能，以保护patient.Patient摘要：我们开发了一个安全和评估工具，以衡量外科医生进行机器人辅助根治性直肠癌切除术的技术技能。对改善情况进行了监测，未来可以使用进展措施来指导者培训外科医生安全操作。(C)2015年欧洲泌尿外科协会。Elsevier B. V.出版，保留所有权利。
Background: Use of robot-assisted radical prostatectomy (RARP) for prostate cancer is increasing. Structured surgical training and objective assessment are critical for outcomes.Objective: To develop and validate a modular training and assessment pathway via Healthcare Failure Mode and Effect Analysis (HFMEA) for trainees undertaking RARP and evaluate learning curves (LCs) for procedural steps.Design, setting, and participants: This multi-institutional (Europe, Australia, and United States) observational prospective study used HFMEA to identify the high-risk steps of RARP. A specialist focus group enabled validation. Fifteen trainees who underwent European Association of Urology robotic surgery curriculum training performed RARP and were assessed by mentors using the tool developed. Results produced LCs for each step. A plateau above score 4 indicated competence.Outcome measurements and statistical analysis: We used a modular training and assessment tool (RARP Assessment Score) to evaluate technical skills. LCs were constructed. Multivariable Kruskal-Wallis, Mann-Whitney U, and k coefficient analyses were used.Results and limitations: Five surgeons were observed for 42 console hours to map steps of RARP. HFMEA identified 84 failure modes and 46 potential causes with a hazard score >8. Content validation created the RARP Assessment Score: 17 stages and 41 steps. The RARP Assessment Score was acceptable (56.67%), feasible (96.67%), and had educational impact (100%). Fifteen robotic surgery trainees were assessed for 8 mo. In 426 RARP cases (range: 4-79), all procedural steps were attempted by trainees. Trainees were assessed with the RARP Assessment Score by their expert mentors, and LCs for individual steps were plotted. LCs demonstrated plateaus for anterior bladder neck transection (16 cases), posterior bladder neck transection (18 cases), posterior dissection (9 cases), dissection of prostatic pedicle and seminal vesicles (15 cases), and anastomosis (17 cases). Other steps did not plateau during data collection. Conclusions: The RARP Assessment Score based on HFMEA methodology identified critical steps for focused RARP training and assessed surgeons. LCs demonstrate the experience necessary to reach a level of competence in technical skills to protect patients.Patient summary: We developed a safety and assessment tool to gauge the technical skills of surgeons performing robot-assisted radical prostatectomy. Improvement was monitored, and measures of progress can be used in future to guide mentors when training surgeons to operate safely. (C) 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.