THE INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY ORIGINAL Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. Published online 19 December 2013 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/rcs.1562
ARTICLE
Training to maintain surgical skills during periods of robotic surgery inactivity
Loredana M. Guseila Archana Saranathan Eric L. Jenison Karen M. Gil John J. Elias* Department of Obstetrics and Gynecology, Akron General Medical Center, Akron, OH, USA * Correspondence to: John J. Elias, PhD, Department of Research, Akron General Medical Center, 1 Akron General Ave., Akron, OH 44307, USA. Email: [email protected]
Abstract Background The study was performed to establish a level of practice needed for newly-trained residents to maintain robotic surgical skills during periods of robotic inactivity. Methods Ten surgical residents were trained to a standardized level of robotic surgery proficiency with inanimate models. At the end of two, four and six weeks, the residents practiced with the models for a total of one hour. Each resident performed a timed tissue closure task immediately after reaching the proficiency standards and twice in succession at eight weeks. Time to completion was compared between the three trials with a repeated measures ANOVA and a post-hoc test. Results Average time to complete the tissue closure task decreased by more than 25% over the period between reaching the proficiency standards and the trials at eight weeks, with the difference significant (P < 0.004). Conclusions Biweekly practice for one hour was sufficient to maintain robotic surgical skills. Copyright © 2013 John Wiley & Sons, Ltd. Keywords
robotic surgery; training; surgical skills
Introduction
Accepted: 14 November 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Minimally invasive robotic surgery is increasingly becoming a standard of care for some procedures within the specialties of gynecology, urology, and general surgery (1). As the number of medical institutions and training programs implementing robotic surgery grows, increasing attention is being paid to developing effective robotic surgery training methods. Training methods typically include practice with inanimate models, focusing on maneuvers needed during robotic surgery. Several training programs utilizing inanimate models have been developed and evaluated by comparing surgical skills of trainees to experienced robotic surgeons (2–7). For surgeons who have undergone a training program to become proficient at robotic surgery, but have limited opportunities to perform robotic procedures in their practice, maintenance of surgical skills is a concern. Newly trained surgical residents and surgeons adding robotic procedures to their practice are vulnerable to skill degradation due to periods of robotic inactivity. Factors such as limited access to a surgical robot, a clinical practice with few patients requiring robotic surgery, and professional or recreational travel can contribute to periods of robotic inactivity that last for several weeks. Based on an evaluation with inanimate models, four weeks of inactivity can increase the time needed for a newly trained surgeon to perform robotic surgery
L. M. Guseila et al.
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exercises by 25% to 100%, and increase the number of surgical errors (4). Skill degradation related to inactivity could compromise patient safety. Maintaining robotic skills during extended periods without operative activity requires non-operative practice. Unfortunately, access to robotic systems for practice is limited by many factors, such as high surgical demand within hospitals, the need for technical assistance during practice, and the cost of training instruments. Establishing the level of activity required by newly trained surgeons to maintain robotic skills is critical to minimize the risk of surgical complications, but also minimize the expense of continued practice. The current study was performed to establish a level of practice needed to maintain robotic surgery skills following an initial training program.
Materials and methods Ten resident physicians in the Departments of Obstetrics/ Gynecology, Urology and General Surgery were enrolled in this IRB approved study (Table 1). None had prior formal training to perform robotic surgery, although all had participated in other forms of surgical skills training, including laparoscopic skills. To encourage enrollment, the study was presented to the residents at educational conferences. The study was reviewed with each resident and all were assured that participation was voluntary prior to giving informed consent. Each resident received an educational stipend of $500 at completion of the study. Each resident participated in an initial series of steps to become familiar with the surgical robot (da Vinci S Surgical System, Intuitive Surgical Inc., Sunnyvale, CA) prior to robotic training. The initial step was an on-line didacticstraining module developed by the manufacturer that provided an overview of the robotic surgical system (Figure 1). The second step was training sessions on a virtual reality robotic surgery simulator (dV Trainer S, Mimic Technologies Inc., Seattle, WA). The simulator includes foot pedals, endowrists, and a high definition stereoscopic display based on the S model robotic surgery system. The simulator provides a wide array of training exercises and a scoring system to evaluate performance based on parameters such as time to completion, economy of motion, instrument collisions, and surgical errors. The dV trainer has previously been shown to provide content, face, Table 1. Characteristics of subjects and mean timing (± standard deviation) of evaluations
Ob/Gyn
Urology
Specialty
General surgery
5 3 2 1 2 3 4 Post grad year 4 5 0 1 Male Female Gender 4 6 2 weeks 4 weeks 6 weeks 8 weeks Days to evaluation 13.2 ± 0.4 27.7 ± 1.3 41.8 ± 1.3 55.9 ± 1.5
Copyright © 2013 John Wiley & Sons, Ltd.
Figure 1. Outline of the training, practice and evaluation sessions performed by the enrolled residents
construct and concurrent validity as a robotic surgery training system (8–13), and training on the simulator has been shown to improve the skills of novice robotic surgeons (14,15). Residents performed a series of exercises focused on endowrist manipulation, needle driving, knot tying, camera targeting, and clutching to reposition instruments. Residents spent at least one hour training on the simulator, but were allowed as much time as desired to feel acclimated to the system before using the surgical robot. Training on the surgical robot occurred within two days of the final session on the virtual reality trainer. Residents trained on the surgical robot until they reached a standardized level of proficiency with inanimate models. Robotic training was performed in an operating room or an adjacent hallway. The first three tasks focused on object manipulation, dissection and transection. The procedures and proficiency standards for these tasks have previously been described within published training curricula (16–18). Object manipulation required moving rings between hooks spread along an outer and inner ring, with variations in the vertical position of the hooks. Dissection required freeing a representation of a blood vessel from a gelatinous medium. Transection required cutting a sheet along a curved path. These tasks were only performed during initial training. Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
Training to maintain robotic surgery skills
Training included three additional tasks that were repeated during the practice sessions throughout the course of the study. The tasks, which were utilized previously for robotic training (4), were a needle passage task, a rocking peg board ring transfer task, and a running suture pod task (Figure 2(A)–(C)). The tasks were scored based on the time to completion, with 5 s penalties added for errors. The proficiency standards were based on previously recorded times during robotic training (4). Four investigators were trained to grade the trials, with at least two present to agree on the time recorded and documented errors during training. The needle passage task required hitting two entrance and exit dots with a needle using each hand on a training model (Robotic Dots and Numbers Pad, the Chamberlain group, Great Barrington, MA). Penalties were assigned for dropping the needle, hitting the targets out of order, instrument collisions, and entering or exiting outside of the target. The standard for passing was 148 s. The peg board required using both hands to move ten rings from home pegs to numbered pegs distributed along a moving platform. Penalties were assigned for manipulating the camera so that the instruments or board were out of view, placing a ring on the wrong peg, dropping a ring, failure to pass the ring between hands, instrument collision, and touching one of the numbered pegs with an instrument. The standard for passing was 280 s. The suture pod task required passing a sutured needle (0 coated vicryl, Ethicon, Somerville, NJ) through dots on a simulated tissue pad (Skin Suturing Pad, the Chamberlain Group, Great Barrington, MA), tying three knots, and running suture through two additional sets of dots. Penalties were assigned for dropping
239
the needle, hitting the targets out of order, instrument collision, breaking the suture and entering or exiting outside of the target. The standard for passing was 95 s. After meeting the proficiency standards, a final tissue closure task (evaluation task) was performed to incorporate all learned skills into a single exercise. The evaluation task required closing an arc of simulated tissue on a pad (Tissue Suture Pad, Simulab, Seattle, WA) that was wrapped over a hemisphere, requiring running suture in three dimensions (Figure 2(D)). The tissue was closed by passing a needle with suture (1 Ti-Cron, Covidien, Mansfield, MA) through five sets of rings with an inner diameter of 2 mm that were embedded on the pad. Three knots were tied after passing through the first set of rings. Each participant completed the task driving the needle with their preferred hand (right hand for all). Nine of the ten also completed the task driving the needle with the opposite hand. The score for the test was time to completion, without adding time for errors. Two evaluators observed all tissue closure tasks. One trial with each hand was performed prior to recording the time. Following the initial training session on the surgical robot, residents participated in biweekly practice until the evaluation at eight weeks (Table 1, Figure 1). At the end of two, four and six weeks, residents participated in one hour of practice on the surgical robot. At the beginning of the practice session, the residents performed the needle passage, peg board and suture pod tasks once, with the time to completion and errors recorded. The order of the tasks was varied for three sessions, so that each of the tasks was performed first at one session. The order of the first task for the three sessions was also varied
Figure 2. Inanimate models used for the needle passage (a); rocking peg board (b); running suture pod (c); and tissue closure tasks (d) Copyright © 2013 John Wiley & Sons, Ltd.
Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
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among the residents. Following completion of the three tasks once, residents continued to practice the three tasks up to a total of one hour. The participants were not allowed access to the virtual reality simulator or robot for practice beyond that required for the study, and attending surgeons and chief residents restricted the participants from utilizing the surgical robot clinically over the course of the study. A final evaluation was performed at the end of eight weeks. The first step of the evaluation was a repeat of the tissue closure task (evaluation task), which had not been performed since the end of the initial training session. The tissue closure task was performed once with the preferred and once with the opposite hand, with the times recorded. The task was repeated with each hand to evaluate the influence of a warm-up on the performance. The needle passage, peg board, and suture pod tasks were performed after the tissue closure was completed. Statistical tests were performed to examine for significant changes in the recorded times throughout the study. A repeated measures ANOVA and a post-hoc StudentNewman-Keuls test was used to test for significant (P < 0.05) differences in the time to completion, with and without time penalties for errors, for the needle passage, peg board, and suture pod tasks between the time that met each proficiency standard and times at two, four, six and eight weeks. The same test was used to determine if the time for the tissue closure task varied significantly between the time immediately after reaching the proficiency standards and the two tests performed at eight weeks.
Results The residents had to develop their skills to meet the proficiency standards. The mean (± standard deviation) number of trials needed to reach the proficiency standard was 2.4 ± 1.3, 4.9 ± 2.0, and 7.3 ± 4.3 for the needle passage, peg board and suture pod tasks, respectively. The most common errors during initial training were missed targets for the needle passage and suture pod tasks, and touching a peg with the instrument for the rocking peg board. These errors occurred an average of 2.8 ± 1.9, 2.9 ± 2.5, and 0.5 ± 0.8 times per trial during training for the needle passage, peg board and suture pod tasks, respectively. These errors occurred more than twice as often as the other errors for the three tasks. For the three tasks performed throughout the study, the time to completion at the end of eight weeks was similar to or better than the time that met the proficiency standard. For the needle passage task, the time needed to complete the task and the time including penalties for errors decreased during the study, with the significant change (P < 0.02) occurring between weeks 2 and 4 (Figure 3). The mean values for both measures decreased by approximately 40% from the initial test to week 8. For the peg board task, no significant changes (P > 0.09) were noted for the time needed to complete the task or the time Copyright © 2013 John Wiley & Sons, Ltd.
L. M. Guseila et al.
Figure 3. Mean (± standard deviation) time to completion and time to completion with penalties added for errors for the needle passage task. The final time that met the proficiency standard is provided (0 weeks), along with the times for the evaluations at weeks 2, 4, 6 and 8. Data points that are significantly larger than data at other time points are marked (*)
including penalties over the course of the study (Figure 4). The mean values at week 8 were within 7% of the values from the initial evaluation. For the suture pod task, the time needed to complete the task and the time including penalties for errors increased significantly (P < 0.001) over the first two weeks, with the mean times increasing by approximately 90% (Figure 5). From week 2 to week 8, the times decreased significantly (P < 0.002) back to near the times that met the proficiency standards. The mean values at week 8 were approximately 15% larger than the values at week 0. Mean time to complete the tissue closure task decreased from week 0 to week 8. For both the right and left hands, the time to complete the tissue closure task was significantly (P < 0.004) lower for the first trial at week 8 than for the test after the proficiency standards were met (Figure 6). The mean time to complete the task decreased by 28%
Figure 4. Mean (± standard deviation) time to completion and time to completion with penalties added for errors for the peg board task. The final time that met the proficiency standard is provided (0 weeks), along with the times for the evaluations at weeks 2, 4, 6 and 8. No significant differences were noted between time points Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
Training to maintain robotic surgery skills
Figure 5. Mean (± standard deviation) time to completion and time to completion with penalties added for errors for the suture pod task. The final time that met the proficiency standard is provided (0 weeks), along with the times for the evaluations at weeks 2, 4, 6 and 8. Data points that are significantly larger than data at other time points are marked (* + #)
Figure 6. Mean (± standard deviation) time to completion for the left and right hand for the tissue closure task. The time following meeting the proficiency standards is provided (week 0), along with the times for the two trials at week 8. Data points that are significantly larger than data at other time points are marked (*)
and 39% for the right and left hands, respectively. No significant differences were noted between the first trial and the second trial at week 8 (P > 0.7).
Discussion The results of the current study indicate that one hour of biweekly training is sufficient to maintain robotic surgical skills out to eight weeks. Robotic surgical skills were initially developed by training on a virtual reality simulator, which has been shown to improve the skills of novice robotic surgeons (14,15), and by meeting performance goals with inanimate models used previously for robotic training (4,16–18). The tissue closure task (evaluation task) performed after reaching the proficiency standards was developed to determine if the skills needed to Copyright © 2013 John Wiley & Sons, Ltd.
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perform the activity are maintained during biweekly practice with simpler models. The evaluation task required knot tying, camera manipulation and clutching, and needle driving was assessed using both hands. The test was designed to be assessed purely on time to completion, with errors naturally slowing progress through the test. The residents improved their time to completion on the first trial at week 8, with no additional benefit from repeating the task, indicating that a warm up was not necessary to prepare for the tissue closure task. Therefore, three biweekly practice sessions of one hour led to improvement in skills for an evaluation task that was not specifically practiced. Variations in surgical skills related to robotic inactivity and practice were not consistent for all tasks evaluated. For the suture pod task, which tested the ability to tie knots, hit targets with a needle and run suture, a significant decrease in skill occurred over the first two weeks of inactivity. The biweekly practice sessions improved performance on the task, with the time needed for completion returning to near the proficiency standard by eight weeks. For the peg board task, which tested the ability to manipulate the endowrists, adjust the camera, and utilize the clutch to realign instruments, the performance throughout the study period was relatively consistent. No significant differences were noted as biweekly practice maintained surgical skills. For the needle passage task, which tested the ability to drive a needle with both hands and hit targets, surgical skills were maintained following the initial two weeks of inactivity. A significant improvement in performance was noted after the first biweekly practice session at week two, with that skill level maintained for the rest of the study period. Maintenance or improvement in skill levels for all repeated tasks seems to have translated to the tissue closure task based on the noted improvement in performance between week 0 and week 8. The similar changes between week 0 and week 8 for the needle passage task and tissue closure could be an indication that the needle passage skill was disproportionately evaluated during tissue closure. Regardless, the results for the individual tasks help confirm the finding that one hour of biweekly practice is sufficient for maintenance of robotic surgical skills, although multiple courses of the biweekly practice are needed to overcome initial skill degradation related to knot tying and running suture. A comparison with previous results highlights the importance of practice to maintain robotic surgery skills. A previous study indicated that a period of four weeks of robotic inactivity following initial training leads to significant skill degradation (4). The current study used the same tasks for initial training and practice as the previous study, although a period of virtual training was added to reduce the total time needed on the robot to meet the proficiency standards. For the previous study, the mean time needed to perform the needle passage, peg board, and suture pod tasks increased by 25% to 100% over four weeks of inactivity. Further, completing each task once on the robot at four, eight and twelve weeks did not return times to the proficiency standards (4). In the current study, Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
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residents practiced for a total time of one hour after being tested once on each task at two, four and six weeks. Another longitudinal study also showed a tendency for the time to complete a suture pod task to increase one month after an initial training session, although the time to complete a ring manipulation task tended to decrease (18). The previous study did not initially train the residents to a proficiency standard and allowed undocumented practice during the month. The current data indicates that biweekly practice can mitigate the skill degradation associated with longer periods of inactivity. The current study focused on periods of robotic inactivity following initial robotic training. For newly trained surgeons building a clinical volume, extended periods of robotic inactivity can occur. Loss of robotic skills due to inactivity is a clinical concern. While not specifically focused on robotic surgery, operative morbidity has generally been shown to increase as surgeon volume decreases (19). The current data indicates that surgical skills tend to stabilize with repeated biweekly practice sessions. Continued utilization of the robot, either for practice or surgical treatment, may reduce the likelihood of skill degradation during a period of inactivity. Unfortunately, gaining access to a surgical robot, training materials and staff to operate the robot for practice can be challenging. Utilizing virtual reality simulation may be a reasonable alternative to practicing on a robot for maintenance of skills, but further research related to the use of virtual robotic training for skill maintenance is necessary. Limitations of the study due to the training environment should be noted. Utilizing inanimate models provided the best scenario for training to a standardized level and evaluation of skill level over the course of the study. Although the tasks with inanimate models were based on previously described robotic training programs (4,17,20,21), inanimate models cannot provide all the complexity of the surgical environment or replicate the possible complications related to surgical errors. Training was also performed with surgical residents of varying skill level who were not fully prepared for independent robotic surgery. Training programs typically include additional steps that could help mitigate the effects of periods of inactivity following initial training, such as animate training with animal models (4) and performing cases with a preceptor (22). Surgical residents may also be able to play a role at the console on cases led by experienced surgeons (23,24). Surgeons should still be cautious of the time that passes between steps in the training process. In a previous study that focused on skill degradation over twelve weeks following initial training, animate training at the end of the study period still did not return performance to the levels that met proficiency standards (4). In conclusion, robotic surgery skills attained during training with inanimate models to a standardized level of proficiency can be maintained during periods of robotic surgical inactivity through periodic practice. Biweekly practice of one hour was sufficient to maintain the ability to perform a tissue closure task over a period of eight weeks. The influence of inactivity and practice on performance varies with Copyright © 2013 John Wiley & Sons, Ltd.
the surgical skill, however. In particular, skills related to knot tying and running suture degraded over the first two weeks of inactivity, but could be restored with continued biweekly practice. The study indicates that robotic surgeons who go through extended periods without utilizing the robot clinically following initial training should schedule practice sessions to maintain their surgical skills.
Acknowledgements Assistance provided by Jason Green during resident training and evaluation is greatly appreciated.
Conflict of interest The authors have stated explicitly that there are no conflicts of interest in connection with this article.
Funding Funding for the study was provided by a Robotic Research Grant from Intuitive Surgical, Inc. and Grant #W81-XWH08-1-0754 from the Department of Defense. Loredana Guseila, Archana Saranathan, Karen Gil and John Elias have no additional conflicts of interest or financial ties related to this study. Eric Jenison received speaking fees and paid travel from Intuitive Surgical, Inc. for presentations at two conferences.
References 1. Kumar R, Jog A, Malpani A, et al. Assessing system operation skills in robotic surgery trainees. Int J Med Robot 2012; 8: 118–124. 2. Dulan G, Rege RV, Hogg DC, et al. Proficiency-based training for robotic surgery: construct validity, workload, and expert levels for nine inanimate exercises. Surg Endosc 2012; 26: 1516–1521. 3. Kumar R, Jog A, Vagvolgyi B, et al. Objective measures for longitudinal assessment of robotic surgery training. J Thorac Cardiovasc Surg 2012; 143: 528–534. 4. Jenison EL, Jenison EL, Gil KM, et al. Robotic surgical skills: acquisition, maintenance, and degradation. J Soc Laparoendosc Surg 2012; 16: 218–228. 5. Jonsson MN, Mahmood M, Askerud T, et al. ProMIS™ can serve as a da Vinci® simulator--a construct validity study. J Endourol 2011; 25: 345–350. 6. Judkins TN, Oleynikov D, Stergiou N. Objective evaluation of expert and novice performance during robotic surgical training tasks. Surg Endosc 2009; 23: 590–597. 7. Tausch TJ, Kowalewski TM, White LW, et al. Content and construct validation of a robotic surgery curriculum using an electromagnetic instrument tracker. J Urol 2012; 188: 919–923. 8. Hung AJ, Zehnder P, Patil MB, et al. Face, content and construct validity of a novel robotic surgery simulator. J Urol 2011; 186: 1019–1024. 9. Kenney PA, Wszolek MF, Gould JJ, et al. A face, content, and construct validity of dV-trainer, a novel virtual reality simulator for robotic surgery. Urology 2009; 73: 1288–1292. 10. Lee JY, Mucksavage P, Kerbl DC, et al. Validation study of a virtual reality robotic simulator--role as an assessment tool? J Urol 2012; 187: 998–1002. Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
Training to maintain robotic surgery skills 11. Lendvay TS, Casale P, Sweet R, Peters C. Initial validation of a virtual-reality robotic simulator. J Robotic Surg 2008; 2: 145–149. 12. Liss MA, Abdelshehid C, Quach S, et al. Validation, correlation, and comparison of the da Vinci trainer(™) and the daVinci surgical skills simulator(™) using the Mimic(™) software for urologic robotic surgical education. J Endourol 2012; 12: 1629–1634. 13. Sethi AS, Peine WJ, Mohammadi Y, Sundaram CP. Validation of a novel virtual reality robotic simulator. J Endourol 2009; 23: 503–508. 14. Korets R, Mues AC, Graversen JA, et al. Validating the use of the Mimic dV-trainer for robotic surgery skill acquisition among urology residents. Urology 2011; 78: 1326–1330. 15. Lerner MA, Ayalew M, Peine WJ, Sundaram CP. Does training on a virtual reality robotic simulator improve performance on the da Vinci surgical system? J Endourol 2010; 24: 467–472. 16. Curry M, Malpani A, Li R, et al. Objective assessment in residency-based training for transoral robotic surgery. Laryngoscope 2012; 122: 2184–2192. 17. Geller EJ, Schuler KM, Boggess JF. Robotic surgical training program in gynecology: how to train residents and fellows. J Minim Invasive Gynecol 2011; 18: 224–229.
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243 18. Kumar R, Jog A, Vagvolgyi B, et al. Objective measures for longitudinal assessment of robotic surgery training. J Thorac Cardiovasc Surg 2012; 143: 528–534. 19. Birkmeyer JD, Stukel TA, Siewers AE, et al. Surgeon volume and operative mortality in the United States. N Engl J Med 2003; 349: 2117–2127. 20. Dulan G, Rege RV, Hogg DC, et al. Developing a comprehensive, proficiency-based training program for robotic surgery. Surgery 2012; 152: 477–488. 21. Suh I, Mukherjee M, Oleynikov D, Siu KC. Training program for fundamental surgical skill in robotic laparoscopic surgery. Int J Med Robotics 2011; 7: 327–333. 22. Zorn KC, Gautam G, Shalhav AL, et al. Training, credentialing, proctoring and medicolegal risks of robotic urological surgery: recommendations of the society of urologic robotic surgeons. J Urol 2009; 182: 1126–1132. 23. Palmer KJ, Lowe GJ, Coughlin GD, et al. Launching a successful robotic surgery program. J Endourol 2008; 22: 819–824. 24. Sfakianos GP, Frederick PJ, Kendrick JE, et al. Robotic surgery in gynecologic oncology fellowship programs in the USA: a survey of fellows and fellowship directors. Int J Med Robot 2010; 6: 405–412.
Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
ARTICLE
Training to maintain surgical skills during periods of robotic surgery inactivity
Loredana M. Guseila Archana Saranathan Eric L. Jenison Karen M. Gil John J. Elias* Department of Obstetrics and Gynecology, Akron General Medical Center, Akron, OH, USA * Correspondence to: John J. Elias, PhD, Department of Research, Akron General Medical Center, 1 Akron General Ave., Akron, OH 44307, USA. Email: [email protected]
Abstract Background The study was performed to establish a level of practice needed for newly-trained residents to maintain robotic surgical skills during periods of robotic inactivity. Methods Ten surgical residents were trained to a standardized level of robotic surgery proficiency with inanimate models. At the end of two, four and six weeks, the residents practiced with the models for a total of one hour. Each resident performed a timed tissue closure task immediately after reaching the proficiency standards and twice in succession at eight weeks. Time to completion was compared between the three trials with a repeated measures ANOVA and a post-hoc test. Results Average time to complete the tissue closure task decreased by more than 25% over the period between reaching the proficiency standards and the trials at eight weeks, with the difference significant (P < 0.004). Conclusions Biweekly practice for one hour was sufficient to maintain robotic surgical skills. Copyright © 2013 John Wiley & Sons, Ltd. Keywords
robotic surgery; training; surgical skills
Introduction
Accepted: 14 November 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Minimally invasive robotic surgery is increasingly becoming a standard of care for some procedures within the specialties of gynecology, urology, and general surgery (1). As the number of medical institutions and training programs implementing robotic surgery grows, increasing attention is being paid to developing effective robotic surgery training methods. Training methods typically include practice with inanimate models, focusing on maneuvers needed during robotic surgery. Several training programs utilizing inanimate models have been developed and evaluated by comparing surgical skills of trainees to experienced robotic surgeons (2–7). For surgeons who have undergone a training program to become proficient at robotic surgery, but have limited opportunities to perform robotic procedures in their practice, maintenance of surgical skills is a concern. Newly trained surgical residents and surgeons adding robotic procedures to their practice are vulnerable to skill degradation due to periods of robotic inactivity. Factors such as limited access to a surgical robot, a clinical practice with few patients requiring robotic surgery, and professional or recreational travel can contribute to periods of robotic inactivity that last for several weeks. Based on an evaluation with inanimate models, four weeks of inactivity can increase the time needed for a newly trained surgeon to perform robotic surgery
L. M. Guseila et al.
238
exercises by 25% to 100%, and increase the number of surgical errors (4). Skill degradation related to inactivity could compromise patient safety. Maintaining robotic skills during extended periods without operative activity requires non-operative practice. Unfortunately, access to robotic systems for practice is limited by many factors, such as high surgical demand within hospitals, the need for technical assistance during practice, and the cost of training instruments. Establishing the level of activity required by newly trained surgeons to maintain robotic skills is critical to minimize the risk of surgical complications, but also minimize the expense of continued practice. The current study was performed to establish a level of practice needed to maintain robotic surgery skills following an initial training program.
Materials and methods Ten resident physicians in the Departments of Obstetrics/ Gynecology, Urology and General Surgery were enrolled in this IRB approved study (Table 1). None had prior formal training to perform robotic surgery, although all had participated in other forms of surgical skills training, including laparoscopic skills. To encourage enrollment, the study was presented to the residents at educational conferences. The study was reviewed with each resident and all were assured that participation was voluntary prior to giving informed consent. Each resident received an educational stipend of $500 at completion of the study. Each resident participated in an initial series of steps to become familiar with the surgical robot (da Vinci S Surgical System, Intuitive Surgical Inc., Sunnyvale, CA) prior to robotic training. The initial step was an on-line didacticstraining module developed by the manufacturer that provided an overview of the robotic surgical system (Figure 1). The second step was training sessions on a virtual reality robotic surgery simulator (dV Trainer S, Mimic Technologies Inc., Seattle, WA). The simulator includes foot pedals, endowrists, and a high definition stereoscopic display based on the S model robotic surgery system. The simulator provides a wide array of training exercises and a scoring system to evaluate performance based on parameters such as time to completion, economy of motion, instrument collisions, and surgical errors. The dV trainer has previously been shown to provide content, face, Table 1. Characteristics of subjects and mean timing (± standard deviation) of evaluations
Ob/Gyn
Urology
Specialty
General surgery
5 3 2 1 2 3 4 Post grad year 4 5 0 1 Male Female Gender 4 6 2 weeks 4 weeks 6 weeks 8 weeks Days to evaluation 13.2 ± 0.4 27.7 ± 1.3 41.8 ± 1.3 55.9 ± 1.5
Copyright © 2013 John Wiley & Sons, Ltd.
Figure 1. Outline of the training, practice and evaluation sessions performed by the enrolled residents
construct and concurrent validity as a robotic surgery training system (8–13), and training on the simulator has been shown to improve the skills of novice robotic surgeons (14,15). Residents performed a series of exercises focused on endowrist manipulation, needle driving, knot tying, camera targeting, and clutching to reposition instruments. Residents spent at least one hour training on the simulator, but were allowed as much time as desired to feel acclimated to the system before using the surgical robot. Training on the surgical robot occurred within two days of the final session on the virtual reality trainer. Residents trained on the surgical robot until they reached a standardized level of proficiency with inanimate models. Robotic training was performed in an operating room or an adjacent hallway. The first three tasks focused on object manipulation, dissection and transection. The procedures and proficiency standards for these tasks have previously been described within published training curricula (16–18). Object manipulation required moving rings between hooks spread along an outer and inner ring, with variations in the vertical position of the hooks. Dissection required freeing a representation of a blood vessel from a gelatinous medium. Transection required cutting a sheet along a curved path. These tasks were only performed during initial training. Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
Training to maintain robotic surgery skills
Training included three additional tasks that were repeated during the practice sessions throughout the course of the study. The tasks, which were utilized previously for robotic training (4), were a needle passage task, a rocking peg board ring transfer task, and a running suture pod task (Figure 2(A)–(C)). The tasks were scored based on the time to completion, with 5 s penalties added for errors. The proficiency standards were based on previously recorded times during robotic training (4). Four investigators were trained to grade the trials, with at least two present to agree on the time recorded and documented errors during training. The needle passage task required hitting two entrance and exit dots with a needle using each hand on a training model (Robotic Dots and Numbers Pad, the Chamberlain group, Great Barrington, MA). Penalties were assigned for dropping the needle, hitting the targets out of order, instrument collisions, and entering or exiting outside of the target. The standard for passing was 148 s. The peg board required using both hands to move ten rings from home pegs to numbered pegs distributed along a moving platform. Penalties were assigned for manipulating the camera so that the instruments or board were out of view, placing a ring on the wrong peg, dropping a ring, failure to pass the ring between hands, instrument collision, and touching one of the numbered pegs with an instrument. The standard for passing was 280 s. The suture pod task required passing a sutured needle (0 coated vicryl, Ethicon, Somerville, NJ) through dots on a simulated tissue pad (Skin Suturing Pad, the Chamberlain Group, Great Barrington, MA), tying three knots, and running suture through two additional sets of dots. Penalties were assigned for dropping
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the needle, hitting the targets out of order, instrument collision, breaking the suture and entering or exiting outside of the target. The standard for passing was 95 s. After meeting the proficiency standards, a final tissue closure task (evaluation task) was performed to incorporate all learned skills into a single exercise. The evaluation task required closing an arc of simulated tissue on a pad (Tissue Suture Pad, Simulab, Seattle, WA) that was wrapped over a hemisphere, requiring running suture in three dimensions (Figure 2(D)). The tissue was closed by passing a needle with suture (1 Ti-Cron, Covidien, Mansfield, MA) through five sets of rings with an inner diameter of 2 mm that were embedded on the pad. Three knots were tied after passing through the first set of rings. Each participant completed the task driving the needle with their preferred hand (right hand for all). Nine of the ten also completed the task driving the needle with the opposite hand. The score for the test was time to completion, without adding time for errors. Two evaluators observed all tissue closure tasks. One trial with each hand was performed prior to recording the time. Following the initial training session on the surgical robot, residents participated in biweekly practice until the evaluation at eight weeks (Table 1, Figure 1). At the end of two, four and six weeks, residents participated in one hour of practice on the surgical robot. At the beginning of the practice session, the residents performed the needle passage, peg board and suture pod tasks once, with the time to completion and errors recorded. The order of the tasks was varied for three sessions, so that each of the tasks was performed first at one session. The order of the first task for the three sessions was also varied
Figure 2. Inanimate models used for the needle passage (a); rocking peg board (b); running suture pod (c); and tissue closure tasks (d) Copyright © 2013 John Wiley & Sons, Ltd.
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among the residents. Following completion of the three tasks once, residents continued to practice the three tasks up to a total of one hour. The participants were not allowed access to the virtual reality simulator or robot for practice beyond that required for the study, and attending surgeons and chief residents restricted the participants from utilizing the surgical robot clinically over the course of the study. A final evaluation was performed at the end of eight weeks. The first step of the evaluation was a repeat of the tissue closure task (evaluation task), which had not been performed since the end of the initial training session. The tissue closure task was performed once with the preferred and once with the opposite hand, with the times recorded. The task was repeated with each hand to evaluate the influence of a warm-up on the performance. The needle passage, peg board, and suture pod tasks were performed after the tissue closure was completed. Statistical tests were performed to examine for significant changes in the recorded times throughout the study. A repeated measures ANOVA and a post-hoc StudentNewman-Keuls test was used to test for significant (P < 0.05) differences in the time to completion, with and without time penalties for errors, for the needle passage, peg board, and suture pod tasks between the time that met each proficiency standard and times at two, four, six and eight weeks. The same test was used to determine if the time for the tissue closure task varied significantly between the time immediately after reaching the proficiency standards and the two tests performed at eight weeks.
Results The residents had to develop their skills to meet the proficiency standards. The mean (± standard deviation) number of trials needed to reach the proficiency standard was 2.4 ± 1.3, 4.9 ± 2.0, and 7.3 ± 4.3 for the needle passage, peg board and suture pod tasks, respectively. The most common errors during initial training were missed targets for the needle passage and suture pod tasks, and touching a peg with the instrument for the rocking peg board. These errors occurred an average of 2.8 ± 1.9, 2.9 ± 2.5, and 0.5 ± 0.8 times per trial during training for the needle passage, peg board and suture pod tasks, respectively. These errors occurred more than twice as often as the other errors for the three tasks. For the three tasks performed throughout the study, the time to completion at the end of eight weeks was similar to or better than the time that met the proficiency standard. For the needle passage task, the time needed to complete the task and the time including penalties for errors decreased during the study, with the significant change (P < 0.02) occurring between weeks 2 and 4 (Figure 3). The mean values for both measures decreased by approximately 40% from the initial test to week 8. For the peg board task, no significant changes (P > 0.09) were noted for the time needed to complete the task or the time Copyright © 2013 John Wiley & Sons, Ltd.
L. M. Guseila et al.
Figure 3. Mean (± standard deviation) time to completion and time to completion with penalties added for errors for the needle passage task. The final time that met the proficiency standard is provided (0 weeks), along with the times for the evaluations at weeks 2, 4, 6 and 8. Data points that are significantly larger than data at other time points are marked (*)
including penalties over the course of the study (Figure 4). The mean values at week 8 were within 7% of the values from the initial evaluation. For the suture pod task, the time needed to complete the task and the time including penalties for errors increased significantly (P < 0.001) over the first two weeks, with the mean times increasing by approximately 90% (Figure 5). From week 2 to week 8, the times decreased significantly (P < 0.002) back to near the times that met the proficiency standards. The mean values at week 8 were approximately 15% larger than the values at week 0. Mean time to complete the tissue closure task decreased from week 0 to week 8. For both the right and left hands, the time to complete the tissue closure task was significantly (P < 0.004) lower for the first trial at week 8 than for the test after the proficiency standards were met (Figure 6). The mean time to complete the task decreased by 28%
Figure 4. Mean (± standard deviation) time to completion and time to completion with penalties added for errors for the peg board task. The final time that met the proficiency standard is provided (0 weeks), along with the times for the evaluations at weeks 2, 4, 6 and 8. No significant differences were noted between time points Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
Training to maintain robotic surgery skills
Figure 5. Mean (± standard deviation) time to completion and time to completion with penalties added for errors for the suture pod task. The final time that met the proficiency standard is provided (0 weeks), along with the times for the evaluations at weeks 2, 4, 6 and 8. Data points that are significantly larger than data at other time points are marked (* + #)
Figure 6. Mean (± standard deviation) time to completion for the left and right hand for the tissue closure task. The time following meeting the proficiency standards is provided (week 0), along with the times for the two trials at week 8. Data points that are significantly larger than data at other time points are marked (*)
and 39% for the right and left hands, respectively. No significant differences were noted between the first trial and the second trial at week 8 (P > 0.7).
Discussion The results of the current study indicate that one hour of biweekly training is sufficient to maintain robotic surgical skills out to eight weeks. Robotic surgical skills were initially developed by training on a virtual reality simulator, which has been shown to improve the skills of novice robotic surgeons (14,15), and by meeting performance goals with inanimate models used previously for robotic training (4,16–18). The tissue closure task (evaluation task) performed after reaching the proficiency standards was developed to determine if the skills needed to Copyright © 2013 John Wiley & Sons, Ltd.
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perform the activity are maintained during biweekly practice with simpler models. The evaluation task required knot tying, camera manipulation and clutching, and needle driving was assessed using both hands. The test was designed to be assessed purely on time to completion, with errors naturally slowing progress through the test. The residents improved their time to completion on the first trial at week 8, with no additional benefit from repeating the task, indicating that a warm up was not necessary to prepare for the tissue closure task. Therefore, three biweekly practice sessions of one hour led to improvement in skills for an evaluation task that was not specifically practiced. Variations in surgical skills related to robotic inactivity and practice were not consistent for all tasks evaluated. For the suture pod task, which tested the ability to tie knots, hit targets with a needle and run suture, a significant decrease in skill occurred over the first two weeks of inactivity. The biweekly practice sessions improved performance on the task, with the time needed for completion returning to near the proficiency standard by eight weeks. For the peg board task, which tested the ability to manipulate the endowrists, adjust the camera, and utilize the clutch to realign instruments, the performance throughout the study period was relatively consistent. No significant differences were noted as biweekly practice maintained surgical skills. For the needle passage task, which tested the ability to drive a needle with both hands and hit targets, surgical skills were maintained following the initial two weeks of inactivity. A significant improvement in performance was noted after the first biweekly practice session at week two, with that skill level maintained for the rest of the study period. Maintenance or improvement in skill levels for all repeated tasks seems to have translated to the tissue closure task based on the noted improvement in performance between week 0 and week 8. The similar changes between week 0 and week 8 for the needle passage task and tissue closure could be an indication that the needle passage skill was disproportionately evaluated during tissue closure. Regardless, the results for the individual tasks help confirm the finding that one hour of biweekly practice is sufficient for maintenance of robotic surgical skills, although multiple courses of the biweekly practice are needed to overcome initial skill degradation related to knot tying and running suture. A comparison with previous results highlights the importance of practice to maintain robotic surgery skills. A previous study indicated that a period of four weeks of robotic inactivity following initial training leads to significant skill degradation (4). The current study used the same tasks for initial training and practice as the previous study, although a period of virtual training was added to reduce the total time needed on the robot to meet the proficiency standards. For the previous study, the mean time needed to perform the needle passage, peg board, and suture pod tasks increased by 25% to 100% over four weeks of inactivity. Further, completing each task once on the robot at four, eight and twelve weeks did not return times to the proficiency standards (4). In the current study, Int J Med Robotics Comput Assist Surg 2014; 10: 237–243. DOI: 10.1002/rcs
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residents practiced for a total time of one hour after being tested once on each task at two, four and six weeks. Another longitudinal study also showed a tendency for the time to complete a suture pod task to increase one month after an initial training session, although the time to complete a ring manipulation task tended to decrease (18). The previous study did not initially train the residents to a proficiency standard and allowed undocumented practice during the month. The current data indicates that biweekly practice can mitigate the skill degradation associated with longer periods of inactivity. The current study focused on periods of robotic inactivity following initial robotic training. For newly trained surgeons building a clinical volume, extended periods of robotic inactivity can occur. Loss of robotic skills due to inactivity is a clinical concern. While not specifically focused on robotic surgery, operative morbidity has generally been shown to increase as surgeon volume decreases (19). The current data indicates that surgical skills tend to stabilize with repeated biweekly practice sessions. Continued utilization of the robot, either for practice or surgical treatment, may reduce the likelihood of skill degradation during a period of inactivity. Unfortunately, gaining access to a surgical robot, training materials and staff to operate the robot for practice can be challenging. Utilizing virtual reality simulation may be a reasonable alternative to practicing on a robot for maintenance of skills, but further research related to the use of virtual robotic training for skill maintenance is necessary. Limitations of the study due to the training environment should be noted. Utilizing inanimate models provided the best scenario for training to a standardized level and evaluation of skill level over the course of the study. Although the tasks with inanimate models were based on previously described robotic training programs (4,17,20,21), inanimate models cannot provide all the complexity of the surgical environment or replicate the possible complications related to surgical errors. Training was also performed with surgical residents of varying skill level who were not fully prepared for independent robotic surgery. Training programs typically include additional steps that could help mitigate the effects of periods of inactivity following initial training, such as animate training with animal models (4) and performing cases with a preceptor (22). Surgical residents may also be able to play a role at the console on cases led by experienced surgeons (23,24). Surgeons should still be cautious of the time that passes between steps in the training process. In a previous study that focused on skill degradation over twelve weeks following initial training, animate training at the end of the study period still did not return performance to the levels that met proficiency standards (4). In conclusion, robotic surgery skills attained during training with inanimate models to a standardized level of proficiency can be maintained during periods of robotic surgical inactivity through periodic practice. Biweekly practice of one hour was sufficient to maintain the ability to perform a tissue closure task over a period of eight weeks. The influence of inactivity and practice on performance varies with Copyright © 2013 John Wiley & Sons, Ltd.
the surgical skill, however. In particular, skills related to knot tying and running suture degraded over the first two weeks of inactivity, but could be restored with continued biweekly practice. The study indicates that robotic surgeons who go through extended periods without utilizing the robot clinically following initial training should schedule practice sessions to maintain their surgical skills.
Acknowledgements Assistance provided by Jason Green during resident training and evaluation is greatly appreciated.
Conflict of interest The authors have stated explicitly that there are no conflicts of interest in connection with this article.
Funding Funding for the study was provided by a Robotic Research Grant from Intuitive Surgical, Inc. and Grant #W81-XWH08-1-0754 from the Department of Defense. Loredana Guseila, Archana Saranathan, Karen Gil and John Elias have no additional conflicts of interest or financial ties related to this study. Eric Jenison received speaking fees and paid travel from Intuitive Surgical, Inc. for presentations at two conferences.
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