Yu-Feng Su1,2,3, Tai-Hsin Tsai2,3,4, Keng-Liang Kuo2,4, Chieh-Hsin Wu2,4, Cheng-Yu Tsai1,2, Yen-Mou Lu5, Shiuh-Lin Hwang6, Pei-Chen Lin7, Ann-Shung Lieu2, Chih-Lung Lin1,2,4, Chih-Hui Chang1,2,4. 1. Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. 2. Department of Neurosurgery, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan. 3. Division of Neurosurgery, Department of Surgery, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan. 4. Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. 5. Department of Orthopedics, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan. 6. Department of Spinal Surgery, Chi-Hsien Spine Hospital, Kaohsiung, Taiwan. 7. Department of Oral Hygiene, College of Dental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
Abstract
Background: The aim of this study was to investigate the learning curve of robotic spine surgery quantitatively with the well-described power law of practice. Methods: Kaohsiung Medical University Hospital set up a robotic spine surgery team by the neurosurgery department in 2013 and the orthopedic department joined the well-established team in 2014. A total of consecutive 150 cases received robotic assisted spinal surgery. The 150 cases, with 841 transpedicular screws were enrolled into 3 groups: the first 50 cases performed by neurosurgeons, the first 50 cases by orthopedic surgeons, and 50 cases by neurosurgeons after the orthopedic surgeons joined the team. The time per screw and accuracy by each group and individual surgeon were analyzed. Results: The time per screw for each group was 9.56 ± 4.19, 7.29 ± 3.64, and 8.74 ± 5.77 minutes, respectively, with p-value 0.0017. The accuracy was 99.6% (253/254), 99.5% (361/363), and 99.1% (222/224), respectively, with p-value 0.77. Though the first group took time significantly more on per screw placement but without significance on the nonlinear parallelism F-test. Analysis of 5 surgeons and their first 10 cases of short segment surgery showed the time per screw by each surgeon was 12.28 ± 5.21, 6.38 ± 1.54, 8.68 ± 3.10, 6.33 ± 1.90, and 6.73 ± 1.81 minutes. The first surgeon who initiated the robotic spine surgery took significantly more time per screw, and the nonlinear parallelism test also revealed only the first surgeon had a steeper learning curve. Conclusion: This is the first study to demonstrate that differences of learning curves between individual surgeons and teams. The roles of teamwork and the unmet needs due to lack of active perception are discussed.
Background: The aim of this study was to investigate the learning curve of robotic spine surgery quantitatively with the well-described power law of practice. Methods: Kaohsiung Medical University Hospital set up a robotic spine surgery team by the neurosurgery department in 2013 and the orthopedic department joined the well-established team in 2014. A total of consecutive 150 cases received robotic assisted spinal surgery. The 150 cases, with 841 transpedicular screws were enrolled into 3 groups: the first 50 cases performed by neurosurgeons, the first 50 cases by orthopedic surgeons, and 50 cases by neurosurgeons after the orthopedic surgeons joined the team. The time per screw and accuracy by each group and individual surgeon were analyzed. Results: The time per screw for each group was 9.56 ± 4.19, 7.29 ± 3.64, and 8.74 ± 5.77 minutes, respectively, with p-value 0.0017. The accuracy was 99.6% (253/254), 99.5% (361/363), and 99.1% (222/224), respectively, with p-value 0.77. Though the first group took time significantly more on per screw placement but without significance on the nonlinear parallelism F-test. Analysis of 5 surgeons and their first 10 cases of short segment surgery showed the time per screw by each surgeon was 12.28 ± 5.21, 6.38 ± 1.54, 8.68 ± 3.10, 6.33 ± 1.90, and 6.73 ± 1.81 minutes. The first surgeon who initiated the robotic spine surgery took significantly more time per screw, and the nonlinear parallelism test also revealed only the first surgeon had a steeper learning curve. Conclusion: This is the first study to demonstrate that differences of learning curves between individual surgeons and teams. The roles of teamwork and the unmet needs due to lack of active perception are discussed.
Authors: Dennis P Devito; Leon Kaplan; Rupert Dietl; Michael Pfeiffer; Dale Horne; Boris Silberstein; Mitchell Hardenbrook; George Kiriyanthan; Yair Barzilay; Alexander Bruskin; Dieter Sackerer; Vitali Alexandrovsky; Carsten Stüer; Ralf Burger; Johannes Maeurer; Gordon D Donald; Donald G Gordon; Robert Schoenmayr; Alon Friedlander; Nachshon Knoller; Kirsten Schmieder; Ioannis Pechlivanis; In-Se Kim; Bernhard Meyer; Moshe Shoham Journal: Spine (Phila Pa 1976) Date: 2010-11-15 Impact factor: 3.468
Authors: Florian Ringel; Carsten Stüer; Andreas Reinke; Alexander Preuss; Michael Behr; Florian Auer; Michael Stoffel; Bernhard Meyer Journal: Spine (Phila Pa 1976) Date: 2012-04-15 Impact factor: 3.468