An Analysis of Laparoscopic and Robotic Minimally Invasive Surgeries: Surgeon Experience, Learning, and Task Performance
研究利用美国大学医院数据，分析外科医生在不同手术方法（腹腔镜与机器人）中的经验如何影响手术时长，发现学习迁移不对称，机器人经验更有利于腹腔镜手术。
ABSTRACT The study examines the transfer of learning in the context of different surgical methods used to complete surgical procedures. Surgeons' total experience is characterized by the procedure (i.e., focal or different) and the surgical technology or method used (i.e., laparoscopic‐assisted minimally invasive surgery [LAS] or robot‐assisted minimally invasive surgery [RAS]). Using data from a large US university hospital with specialized surgical departments, and drawing on task‐technology fit and fit appropriation model theories, we propose three novel hypotheses that focus on different facets of how learning transfers across methods and tasks for individuals. The findings contribute to research on individual learning by distinguishing between method learning (how the task is performed) and task learning (the knowledge of the task itself). We find the following key findings. First, the experience from the RAS (LAS) method has a significant (no) effect in reducing LAS (RAS) duration for the same procedure. Second, learning from other procedures is contingent on the method used to complete the task. Specifically, the experience from other procedures completed using the LAS (RAS) method increases (decreases) the LAS (RAS) duration. Overall, the results indicate that the transfer of learning from RAS to LAS is greater than from LAS to RAS. This suggests that learning transfer across technologies is asymmetrical and requires careful consideration regarding how accumulated surgical experience from various technologies impacts task performance. From a task‐technology fit and fit appropriation model theory perspective, our study highlights the importance of technologies' capabilities in knowledge transfer across methods.