Department of Upper Gastrointestinal Surgery, Portsmouth Hospitals University NHS Trust, Portsmouth, UK.
Surg Endosc. 2023 Oct;37(10):7608-7615. doi: 10.1007/s00464-023-10210-x. Epub 2023 Jul 20.
The adoption of new surgical technologies is inevitably accompanied by a learning curve. With the increasing adoption of robotic techniques in benign foregut surgery, it is imperative to define optimal learning pathways, to ensure a clinically safe introduction of such a technique. The aim of this study was to assess the learning curve for robotic hiatal hernia repair with a pre-defined adoption process and proctoring.
The learning curve was assessed in four surgeons in a high-volume tertiary referral centre, performing over a 100 hiatal hernia repairs annually. The robotic adoption process included simulation-based training and a multi-day wet lab-based course, followed by robotic operations proctored by robotic upper GI experts. CUSUM analysis was performed to assess changes in operating time in sequential cases.
Each surgeon (A, B, C and D) performed between 22 and 32 cases, including a total of 109 patients. Overall, 40 cases were identified as 'complex' (36.7%), including 16 revisional cases (16/109, 14.7%). With CUSUM analysis inflection points for operating time were seen after 7 (surgeon B) to 15 cases (surgeon B).
The learning curve for robotic laparoscopic fundoplication may be as little as 7-15 cases in the setting of a clearly organized learning pathway with proctoring. By integrating these organized learning pathways learning curves may be shortened, ensuring patient safety, preventing detrimental outcomes due to longer learning curves, and accelerating adoption and integration of novel surgical techniques.
新手术技术的采用不可避免地伴随着学习曲线。随着机器人技术在良性前肠手术中的应用日益广泛,定义最佳学习途径至关重要,以确保该技术的临床安全引入。本研究旨在评估机器人食管裂孔疝修补术的学习曲线,该手术采用了预先确定的采用过程和指导。
在一家高容量的三级转诊中心,四名外科医生每年进行超过 100 例食管裂孔疝修补术,评估学习曲线。机器人采用过程包括基于模拟的培训和为期多天的基于湿实验室的课程,随后由机器人上消化道专家指导机器人手术。使用累积和 (CUSUM) 分析评估连续病例手术时间的变化。
每位外科医生 (A、B、C 和 D) 完成了 22 到 32 例手术,总共涉及 109 名患者。总体而言,40 例被确定为“复杂”(36.7%),包括 16 例翻修病例(16/109,14.7%)。使用 CUSUM 分析,手术时间的拐点出现在第 7 例(外科医生 B)到第 15 例(外科医生 B)。
在有指导的明确组织学习途径的情况下,机器人腹腔镜胃底折叠术的学习曲线可能短至 7-15 例。通过整合这些有组织的学习途径,学习曲线可能会缩短,确保患者安全,防止由于学习曲线较长而导致的不良后果,并加速新手术技术的采用和整合。