Review Article
Robotic surgical skill acquisition: What one needs to know? Akshay Sood, Wooju Jeong, Rajesh Ahlawat1, Logan Campbell, Shruti Aggarwal2, Mani Menon, Mahendra Bhandari Vattikuti Urology Institute, Henry Ford Hospital, Detroit, MI, USA, 1Kidney and Urology Institute, Medanta — The Medicity, Gurgaon, India, 2Department of Medicine, Metrowest Medical Center, Framingham, MA, USA Address for Correspondence: Dr. Akshay Sood, Vattikuti Urology Institute, Henry Ford Health System, 2799 W. Grand Boulevard, Detroit, Michigan, USA, 48202. E-mail: [email protected]
Abstract
underway. Currently, accreditation for competence in robotic surgery is institutional specific.
Robotic surgery has been eagerly adopted by patients and surgeons alike in the field of urology, over the last decade. However, there is a lack of standardization in training curricula and accreditation guidelines to ensure surgeon competence and patient safety. Accordingly, in this review, we aim to highlight ‘who’ needs to learn ‘what’ and ‘how’, to become competent in robotic surgery. We demonstrate that both novice and experienced open surgeons require supervision and mentoring during the initial phases of robotic surgery skill acquisition. The experienced open surgeons possess domain knowledge, however, need to acquire technical knowledge under supervision (either in simulated or clinical environment) to successfully transition to robotic surgery, whereas, novice surgeons need to acquire both domain as well as technical knowledge to become competent in robotic surgery. With regard to training curricula, a variety of training programs such as academic fellowships, mini-fellowships, and mentored skill courses exist, and cater to the needs and expectations of postgraduate surgeons adequately. Fellowships provide the most comprehensive training, however, may not be suitable to all surgeon-learners secondary to the long-term time commitment. For these surgeon-learners short-term courses such as the minifellowships or mentored skill courses might be more apt. Lastly, with regards to credentialing uniformity in criteria regarding accreditation is lacking but earnest efforts are Access this article online Quick Response Code:
Website: www.journalofmas.com
DOI: 10.4103/0972-9941.147662
10
Key words: Curriculum, robotics, simulation, surgical learning, training
INTRODUCTION Minimally-invasive surgery (MIS) began in the year 1987 with laparoscopic cholecystectomy.[1] The advantages and disadvantages of the MIS approach became quickly apparent. The advantages included decreased surgical site infection, blood loss and postoperative pain, shorter hospital stay, and better cosmesis. On the other hand, the disadvantages included loss of haptic feedback and hand-eye coordination.[2] These limitations made delicate dissections and anastomoses difficult if not impossible.[3] Robotic surgery was, thus, developed to overcome these limitations of the MIS and to enhance the capabilities of surgeons performing open surgery.[2] Robotic surgery, over the last decade, has been enthusiastically adopted by patients and surgeons alike in the field of urology, and today, is utilized for oncological,[4-6] reconstructive,[7,8] pediatric,[9-11] urogynecological,[12] and kidney transplantation procedures.[13-15] However, there is a lack of standardization in training curricula and accreditation guidelines to ensure surgeon competence and patient safety. Although, there have been institutional and surgical-societal level efforts at standardization of these processes, so far these efforts have met with limited success and heterogeneity in certification standards persists.[16-18] Hence, as adoption of robotic surgery continues to increase, there is an urgent need for unifying the training and credentialing requirements to ensure patient safety. Accordingly, in this review, we aim to highlight ‘who’ needs to learn ‘what’ and ‘how’, to become competent in robotic surgery.
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Sood, et al.: Robotic skill acquisition
a
b Figure 1: (a) Two types of learning scenarios in surgery; (b) The classic phases of a learning curve — learning phase, competency, proficiency and mastery (non-CUSUM learning curve)
Who Needs to Learn? Learning is an essential part of skill acquisition and of surgical apprenticeship. During the learning process, however, there is an increased propensity for error, and in the setting of clinical practice this may or may not be acceptable depending on the risk involved. A learning curve can exist in two situations in surgical practice [Figure 1a]: • When a novice surgeon learns an established procedure under supervision (surgical apprenticeship). • When a pioneering surgeon seeks to innovate and develop a new technique (surgical innovation). In both of the aforementioned scenarios, the patient maybe at an increased risk for adverse outcome; however, the former situation represents by far the more common setting, albeit a less risky one. Further, the precautions to counter the increased risk in both these scenarios vary vastly. For example, in the case of surgical innovation the pathway to ensure patient safety is to perform preclinical (animal/ cadaveric) feasibility and simulator studies before performing patient surgery.[19,20] While on the other hand, the usual pathway for ensuring uncompromised patient outcomes during training of a novice surgeon includes theoretical learning and mentoring, although occasionally simulator/ animal studies maybe utilized. In the current review, we will limit the discussion to the latter learning pathway (surgical apprenticeship), as it is the primary topic of interest to this review.
To address the concern of training a novice surgeon, mentors/ credentialing committees have traditionally relied on learning curves[21,22] which help estimate the number of cases a surgeon-learner must perform under supervision to become competent (and avoid compromising patient outcomes). An ideal learning curve is shown in Figure 1b. Each new task a novice surgeon acquires will have an associated learning curve. Depending on the magnitude of difference in the tasks being learnt, the surgeon may or may not need supervision for each new task. For example, if a surgeon has learnt to perform iliac vessel anastomoses, he should presumably be competent to perform anastomoses of other similar-sized blood vessels without supervision. While on the other hand, if a surgeon has learnt to perform iliac vessel anastomoses via open surgery would he be capable of performing the same via robotic surgery without supervision? Does he need to learn anything? These questions are applicable to the case of experienced open surgeons adopting robotic surgery. The answer to the earlier-given questions lie in distinguishing between domain knowledge and technical knowledge (please see the next section). Many open surgeons hold the notion that secondary to their acclimation with the open surgical technique they will be able to perform the same given task equally well robotically. However, recently, it has been shown that skilled open surgeons adopting robotic surgery have a substantial learning phase that varies with the task being learnt. Specifically, in the study of robotic kidney transplantation
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Sood, et al.: Robotic skill acquisition
a
b
c
d
Figure 2: Learning curve assessment using CUSUM method for technical outcomes. (a) for venous anastomosis; (b) for arterial anastomosis; (c) for uretero-vesical anastomosis; (d) for re-warming time (Reproduced with permission from Elsevier Inc., European Urology; 2014 Mar 4; Application of the Statistical Process Control Method for Prospective Patient Safety Monitoring During the Learning Phase: Robotic Kidney Transplantation with Regional Hypothermia [IDEAL Phase 2a-b]; Sood et al.)
was a minimal-to-nil learning phase. However, for group 3 there was a significant learning phase. Learning phase lasted until case 9 and 12 for venous and arterial anastomoses, respectively [Figures 2a and b]. Similarly, for the ureterovesical anastomosis, the learning phase continued beyond patient 14 [Figure 2c]* and for re-warming time, competency was achieved after case 11 [Figure 2d]. For graft function, the learning phase was short, and competency and mastery were achieved after case 3 and 13, respectively [Figures 3a and b]. Hence, there is a clear role of mentoring and/or precepting in even the experienced open surgeons during early phases of the adoption of robotic technology to ensure patient safety.[23]
a
[The graphs are cumulative summation (CUSUM) derived learning curves, for details on methodology and how to interpret them accurately please refer to the original text, but essentially the plateau denotes the end of learning phase].[23]
b Figure 3: Learning curve assessment using CUSUM method for functional outcomes. (a) for POD 7 serum creatinine; (b) for POD 7 estimated GFR (Reproduced with permission from Elsevier Inc., European Urology; 2014 Mar 4; Application of the Statistical Process Control Method for Prospective Patient Safety Monitoring During the Learning Phase: Robotic Kidney Transplantation with Regional Hypothermia [IDEAL Phase 2a-b]; Sood et al.)
(RKT) with regional hypothermia, three surgeon groups were evaluated with varying open and robotic experience/ training.[23] Group-1: robotic trained with limited kidney transplantation (KT) experience (patients=7); Group-2: robotic trained and KT experienced (patients=20); and Group-3: KT experienced with limited robotic training (patients=14). It was demonstrated that for surgeons in group 1 and 2, there 12
Lastly, in robotic surgery, in addition to training of the surgeon there is a clear place for learning of the skill by the team as a whole.[24] Thiel et al.[25] in their study of robotic prostatectomy evaluated the role of training bedside assistants — in this study, the participants underwent a three-phase learning course including teaching regarding the basics of robot functionality (phase-1), a step-by-step video showing the optimal role of an assistant during robotic prostatectomy (phase-2), and lastly, a hands-on practice session (phase-3). The authors noted that all 13 participants who underwent the 3-phase learning course recorded improved spatial orientation during surgery and felt that the training made
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Sood, et al.: Robotic skill acquisition
them a better assistant (100% response rate). The module that was most useful was the ‘hands-on’ drill. Hence, while setting up a robotic surgery program, it might be worthwhile to keep in consideration the training of assistants to further improve patient outcomes. What Needs to be Learned and when? For successful performance of any task a person needs to have the knowhow of what to do (domain knowledge) and how to do it (technical knowledge; Figure 4), as David Eddy pointed out in his landmark paper.[26] Domain knowledge, also alluded to as functional knowledge sometimes, refers to the understanding of a concept while technical knowledge represents the acquaintance of an individual with the steps in execution of a task. Domain knowledge is primarily acquired from theory whereas technical knowledge is acquired by practice. We briefly alluded to these concepts in the previous section, and using the same example, we highlight that the reason why open surgeons cannot transition into robotic surgery without going through a learning phase is because of lack of technical knowledge. An experienced open surgeon possesses the domain knowledge, but to achieve competency in technical knowledge — the surgeon needs to practice either in a simulated environment or under mentorship in a clinical environment, much akin to training of a novice surgeon. However, a resident/fellow learning a robotic procedure will need to acquire both domain and technical knowledge. Lastly, the time to learn is also important when acquiring a new technical skill, as prior studies show.[27] We humbly
Figure 4: The two types of knowledge required for successful execution of a task
submit that open surgeons should only consider taking robotic training modules when they have the desire and the setup to perform robotic surgery on a regular basis, as many of the courses (detailed in next section) offer short-term training, can be expensive and might not leave a lasting impression unless robotic surgery in continued afterwards. How can it be Learned? And When Can a New Skill Be Considered Learned? An ideal curriculum for teaching technical skills (technical knowledge) requires, foremost, setting of clear goals and objectives that can be achieved by trainees with the help of targeted interventions. The next crucial step is designing and incorporating these interventions along with assessment tools that can certify the surgeon-learner’s competency.[28] Assessment is a critical part of learning, not only because it ensures surgeon competence but also because it helps learning by the virtue of feedback (operant conditioning).[29] As stated previously, there have been several institutional and surgical-societal level efforts to develop and standardize the training curriculum and certification requirements in minimally-invasive surgical training. Although, these processes have met with limited success so far, the hospitals, credentialing committees/associations and program directors are increasingly recognizing the need for formal MIS training and credentialing, and the adoption of these processes is increasing.[17,18,30,31] Further, with regards to certification — there has been a tremendous overhaul in the way competency is evaluated. Traditionally, a trainee’s competence was measured based on time-based apprentice-type system where time spent within a specialty was the defining factor in skill acquisition. However, in the contemporary system a trainee’s progress is determined by instating specific benchmarks for him/her to achieve which lead to more objective and evidence-based credentialing.[28] Table 1 details the various training programs that exist for training surgeons in robotic surgery. The current generation
Table 1: Various training curricula for acquiring minimally invasive surgical skills Program
Surgeon training
Surgeon assessment
Duration
Training
Details/Methods
Cost
Subjective
Objective
Fellowship
1-2 years
Simulation studies Clinical setting
Nil
Proctoring by mentors
Mini-Fellowship
5 days
Simulation studies
~$3,800
Proctoring by mentors
Mentored skills course
2 days
Simulation studies
Long-term one to one mentoring, precepting and teaching Short-term mentoring, case observation and teaching Short-term mentoring and teaching
NA
Proctoring by mentors
GEARS for simulation; CUSUM for prospective learning curve evaluation* GEARS for simulation; CUSUM for prospective learning curve evaluation* GEARS for simulation; CUSUM for prospective learning curve evaluation*
GEARS: Global evaluative assessment of robotic skills, CUSUM: Cumulative summation [*not used currently but could be used based on recent studies], NA: Not available
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Sood, et al.: Robotic skill acquisition
of resident surgeons has some degree of robotic experience (at least in the United States). However, mostly the experience is insufficient to warrant independent practice. Hence, the training programs described in the following are applicable to all surgeons with varying degrees of open/laparoscopic/ robotic surgical experience. There are primarily three types of training programs (curricula):[32] • Fellowships. • Mini-fellowships. • Mentored skills courses. Depending on the time a surgeon can devote for training and the desired level of learning intended, one of the aforementioned courses might be more suitable. A fellowship is the most comprehensive course which includes one-toone mentoring, precepting, and teaching in both simulated and clinical environments. The training duration usually ranges between 1 to 2 years. However, a fellowship might not be suitable for most post-graduate surgeons due to time constraints. A mini-fellowship or a mentored skills course maybe more ideal in this situation. A mini-fellowship (developed at the University of California Irvine, USA) is a 5 day teaching and mentor-mentee course during which the mentee’s attends didactic sessions, live OR-cases, and hands-on lab sessions.[33,34] Whereas, the mentored skills course combines online learning with a 2-day mentored course.[32,35] Both of these programs have been demonstrated to have excellent content and construct validity; however, the performance predictive validity has not been evaluated.[17,28] Further, despite the short duration of the latter two courses, approximately 70-80% of the trainees successfully transition to robotic surgery, and are regularly practicing it at 3 years post-training.[18,32] Lastly, somewhat related to this topic is the Food and Drug Administration (FDA) mandated basic robot-handling training required for all surgeons performing robot-assisted procedures. The FDA training necessitates the knowhow on how to safely and rapidly remove the device in an emergency, what to do if the system stops responding, and how to respond if the system makes movements that are potentially unsafe to the patient. This training is offered by the Institutive Surgical Inc.[36] The guidelines on credentialing for robotic competency are more opaque at this time and vary from institution to institution.[18] Currently, most commonly, the surgeonlearner is subjectively assessed by the mentor (proctoring), which might be an acceptable way of evaluation over the long-term mentor-mentee relationship during a fellowship, however, may not represent a valid method of assessment during the short-term courses. Accordingly, there are certain tools such as the global evaluative assessment of robotic 14
skills (GEARS)[37] which permit objective assessment and can be used to grade performance during simulation exercises. However, there is a lack of consensus on what the cutoffs for competency, proficiency and mastery should be (the different phases of a learning curve; Figure 1B). We believe that these cutoffs need to be devised based on consensus-performance of experienced surgeons according to the GEARS tool at a multi-institutional level. Further, more recently, in the study of RKT with regional hypothermia, referred to previously [23] — the authors described a novel method of assessing competence by evaluating learning curves prospectively, objectively at an individual level utilizing cutoffs based on outcomes from previous kidney transplant series. By setting a target value (for technical [operative/anastomoses times] and functional [graft function] outcomes) prospectively and utilizing the mathematical cumulative summation (CUSUM) method, allowed the authors to evaluate the learning curve for each surgeon-learner continuously, objectively, and prospectively. This in turn permitted competency declaration at an individual level instead of utilizing an arbitrary cutoff of a standard number of cases for each surgeon-learner irrespective of their learning capabilities and training background. This methodology, theoretically speaking, combined with GEARS-cutoffs derived from experienced surgeons (as proposed earlier) can be used to monitor learning curves of surgeon-learners adopting robotic surgery continuously and prospectively during simulation training, and might allow recommendations regarding their learning status to be made in a more objective and individualized manner.
CONCLUSION In conclusion, both novice and experienced open surgeons require supervision and mentoring during the initial phases of robotic surgery skill acquisition. The experienced open surgeons possess domain knowledge, however, need to acquire technical knowledge under supervision (either in simulated or clinical environment) to successfully transition to robotic surgery, whereas, novice surgeons need to acquire both domain as well as technical knowledge to become competent in robotic surgery. A variety of training programs such as academic fellowships, mini-fellowships and mentored skill courses exist, and cater to the needs and expectations of postgraduate surgeons thoroughly and adequately. With regards to credentialing uniformity in criteria regarding accreditation is lacking but earnest efforts are underway. Currently, accreditation for competence in robotic surgery is institutional specific.
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Sood, et al.: Robotic skill acquisition
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Menon M, Abaza R, Sood A, Ahlawat R, Ghani KR, Jeong W, et al. Robotic Kidney Transplantation with Regional Hypothermia: Evolution of a Novel Procedure Utilizing the IDEAL Guidelines (IDEAL Phase 0 and 1). Eur Urol 2014;65:1001-9. Hopper AN, Jamison MH, Lewis WG. Learning curves in surgical practice. Postgrad Med J. 2007;83:777-9. Abboudi H, Khan MS, Guru KA, Froghi S, de Win G, Van Poppel H, et al. Learning curves for urological procedures: A systematic review. BJU Int 2013 [In Press]. Sood A, Ghani KR, Ahlawat R, Modi P, Abaza R, Jeong W, et al. Application of the Statistical Process Control Method for Prospective Patient Safety Monitoring During the Learning Phase: Robotic Kidney Transplantation with Regional Hypothermia (IDEAL Phase 2a-b). Eur Urol 2014;66:371-8. Yule S, Rowley D, Flin R, Maran N, Youngson G, Duncan J, et al. Experience matters: Comparing novice and expert ratings of non-technical skills using the NOTSS system. ANZ J Surg 2009;79:154-60. Thiel DD, Lannen A, Richie E, Dove J, Gajarawala NM, Igel TC. Simulationbased training for bedside assistants can benefit experienced robotic prostatectomy teams. J Endourol 2013;27:230-7. Eddy DM. Clinical decision making: From theory to practice. Anatomy of a decision. JAMA 1990;263:441-3. Lendvay TS, Brand TC, White L, Kowalewski T, Jonnadula S, Mercer LD, et al. Virtual reality robotic surgery warm-up improves task performance in a dry laboratory environment: A prospective randomized controlled study. J Am Coll Surg 2013;216:1181-92. Shepherd W, Arora KS, Abboudi H, Shamim Khan M, Dasgupta P, Ahmed K. A review of the available urology skills training curricula and their validation. J Surg Educ 2014;71:289-96. Skinner BF. Are theories of learning necessary? Psychol Rev 1950;57:193-216. Forster JA, Browning AJ, Paul AB, Biyani CS. Surgical simulators in urological training--views of UK Training Programme Directors. BJU Int 2012;110:776-8. Le CQ, Lightner DJ, VanderLei L, Segura JW, Gettman MT. The current role of medical simulation in american urological residency training programs: An assessment by program directors. J Urol 2007;177:288-91. Hay D, Khan MS, Van Poppel H, Van Cleynenbreugel B, Peabody J, Guru K, et al. Current Status and Effectiveness of Mentorship Programmes in Urology — A Systematic Review. BJU Int 2014 [In Press]. McDougall EM, Corica FA, Chou DS, Abdelshehid CS, Uribe CA, Stoliar G, et al. Short-term impact of a robot-assisted laparoscopic prostatectomy ‘mini-residency’ experience on postgraduate urologists’ practice patterns. Int J Med Robot 2006;2:70-4. Gamboa AJ, Santos RT, Sargent ER, Louie MK, Box GN, Sohn KH, et al. Long-term impact of a robot assisted laparoscopic prostatectomy mini fellowship training program on postgraduate urological practice patterns. J Urol 2009;181:778-82. Patel SR, Hedican SP, Bishoff JT, Shichman SJ, Link RE, Wolf JS Jr, et al. Skill based mentored laparoscopy course participation leads to laparoscopic practice expansion and assists in transition to robotic surgery. J Urol 2011;186:1997-2000. Herron DM, Marohn M; SAGES-MIRA Robotic Surgery Consensus Group. A consensus document on robotic surgery. Surg Endos 2008;22:313-25. Goh AC, Goldfarb DW, Sander JC, Miles BJ, Dunkin BJ. Global evaluative assessment of robotic skills: Validation of a clinical assessment tool to measure robotic surgical skills. J Urol 2012;187:247-52.
Cite this article as: Sood A, Jeong W, Ahlawat R, Campbell L, Aggarwal S, Menon M, et al. Robotic surgical skill acquisition: What one needs to know?. J Min Access Surg 2015;11:10-5. Date of submission: 25/09/2014, Date of acceptance: 26/09/2014 Source of Support: Nil, Conflict of Interest: None declared.
Journal of Minimal Access Surgery | January-March 2015 | Volume 11 | Issue 1
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Robotic surgical skill acquisition: What one needs to know? Akshay Sood, Wooju Jeong, Rajesh Ahlawat1, Logan Campbell, Shruti Aggarwal2, Mani Menon, Mahendra Bhandari Vattikuti Urology Institute, Henry Ford Hospital, Detroit, MI, USA, 1Kidney and Urology Institute, Medanta — The Medicity, Gurgaon, India, 2Department of Medicine, Metrowest Medical Center, Framingham, MA, USA Address for Correspondence: Dr. Akshay Sood, Vattikuti Urology Institute, Henry Ford Health System, 2799 W. Grand Boulevard, Detroit, Michigan, USA, 48202. E-mail: [email protected]
Abstract
underway. Currently, accreditation for competence in robotic surgery is institutional specific.
Robotic surgery has been eagerly adopted by patients and surgeons alike in the field of urology, over the last decade. However, there is a lack of standardization in training curricula and accreditation guidelines to ensure surgeon competence and patient safety. Accordingly, in this review, we aim to highlight ‘who’ needs to learn ‘what’ and ‘how’, to become competent in robotic surgery. We demonstrate that both novice and experienced open surgeons require supervision and mentoring during the initial phases of robotic surgery skill acquisition. The experienced open surgeons possess domain knowledge, however, need to acquire technical knowledge under supervision (either in simulated or clinical environment) to successfully transition to robotic surgery, whereas, novice surgeons need to acquire both domain as well as technical knowledge to become competent in robotic surgery. With regard to training curricula, a variety of training programs such as academic fellowships, mini-fellowships, and mentored skill courses exist, and cater to the needs and expectations of postgraduate surgeons adequately. Fellowships provide the most comprehensive training, however, may not be suitable to all surgeon-learners secondary to the long-term time commitment. For these surgeon-learners short-term courses such as the minifellowships or mentored skill courses might be more apt. Lastly, with regards to credentialing uniformity in criteria regarding accreditation is lacking but earnest efforts are Access this article online Quick Response Code:
Website: www.journalofmas.com
DOI: 10.4103/0972-9941.147662
10
Key words: Curriculum, robotics, simulation, surgical learning, training
INTRODUCTION Minimally-invasive surgery (MIS) began in the year 1987 with laparoscopic cholecystectomy.[1] The advantages and disadvantages of the MIS approach became quickly apparent. The advantages included decreased surgical site infection, blood loss and postoperative pain, shorter hospital stay, and better cosmesis. On the other hand, the disadvantages included loss of haptic feedback and hand-eye coordination.[2] These limitations made delicate dissections and anastomoses difficult if not impossible.[3] Robotic surgery was, thus, developed to overcome these limitations of the MIS and to enhance the capabilities of surgeons performing open surgery.[2] Robotic surgery, over the last decade, has been enthusiastically adopted by patients and surgeons alike in the field of urology, and today, is utilized for oncological,[4-6] reconstructive,[7,8] pediatric,[9-11] urogynecological,[12] and kidney transplantation procedures.[13-15] However, there is a lack of standardization in training curricula and accreditation guidelines to ensure surgeon competence and patient safety. Although, there have been institutional and surgical-societal level efforts at standardization of these processes, so far these efforts have met with limited success and heterogeneity in certification standards persists.[16-18] Hence, as adoption of robotic surgery continues to increase, there is an urgent need for unifying the training and credentialing requirements to ensure patient safety. Accordingly, in this review, we aim to highlight ‘who’ needs to learn ‘what’ and ‘how’, to become competent in robotic surgery.
Journal of Minimal Access Surgery | January-March 2015 | Volume 11 | Issue 1
Sood, et al.: Robotic skill acquisition
a
b Figure 1: (a) Two types of learning scenarios in surgery; (b) The classic phases of a learning curve — learning phase, competency, proficiency and mastery (non-CUSUM learning curve)
Who Needs to Learn? Learning is an essential part of skill acquisition and of surgical apprenticeship. During the learning process, however, there is an increased propensity for error, and in the setting of clinical practice this may or may not be acceptable depending on the risk involved. A learning curve can exist in two situations in surgical practice [Figure 1a]: • When a novice surgeon learns an established procedure under supervision (surgical apprenticeship). • When a pioneering surgeon seeks to innovate and develop a new technique (surgical innovation). In both of the aforementioned scenarios, the patient maybe at an increased risk for adverse outcome; however, the former situation represents by far the more common setting, albeit a less risky one. Further, the precautions to counter the increased risk in both these scenarios vary vastly. For example, in the case of surgical innovation the pathway to ensure patient safety is to perform preclinical (animal/ cadaveric) feasibility and simulator studies before performing patient surgery.[19,20] While on the other hand, the usual pathway for ensuring uncompromised patient outcomes during training of a novice surgeon includes theoretical learning and mentoring, although occasionally simulator/ animal studies maybe utilized. In the current review, we will limit the discussion to the latter learning pathway (surgical apprenticeship), as it is the primary topic of interest to this review.
To address the concern of training a novice surgeon, mentors/ credentialing committees have traditionally relied on learning curves[21,22] which help estimate the number of cases a surgeon-learner must perform under supervision to become competent (and avoid compromising patient outcomes). An ideal learning curve is shown in Figure 1b. Each new task a novice surgeon acquires will have an associated learning curve. Depending on the magnitude of difference in the tasks being learnt, the surgeon may or may not need supervision for each new task. For example, if a surgeon has learnt to perform iliac vessel anastomoses, he should presumably be competent to perform anastomoses of other similar-sized blood vessels without supervision. While on the other hand, if a surgeon has learnt to perform iliac vessel anastomoses via open surgery would he be capable of performing the same via robotic surgery without supervision? Does he need to learn anything? These questions are applicable to the case of experienced open surgeons adopting robotic surgery. The answer to the earlier-given questions lie in distinguishing between domain knowledge and technical knowledge (please see the next section). Many open surgeons hold the notion that secondary to their acclimation with the open surgical technique they will be able to perform the same given task equally well robotically. However, recently, it has been shown that skilled open surgeons adopting robotic surgery have a substantial learning phase that varies with the task being learnt. Specifically, in the study of robotic kidney transplantation
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Sood, et al.: Robotic skill acquisition
a
b
c
d
Figure 2: Learning curve assessment using CUSUM method for technical outcomes. (a) for venous anastomosis; (b) for arterial anastomosis; (c) for uretero-vesical anastomosis; (d) for re-warming time (Reproduced with permission from Elsevier Inc., European Urology; 2014 Mar 4; Application of the Statistical Process Control Method for Prospective Patient Safety Monitoring During the Learning Phase: Robotic Kidney Transplantation with Regional Hypothermia [IDEAL Phase 2a-b]; Sood et al.)
was a minimal-to-nil learning phase. However, for group 3 there was a significant learning phase. Learning phase lasted until case 9 and 12 for venous and arterial anastomoses, respectively [Figures 2a and b]. Similarly, for the ureterovesical anastomosis, the learning phase continued beyond patient 14 [Figure 2c]* and for re-warming time, competency was achieved after case 11 [Figure 2d]. For graft function, the learning phase was short, and competency and mastery were achieved after case 3 and 13, respectively [Figures 3a and b]. Hence, there is a clear role of mentoring and/or precepting in even the experienced open surgeons during early phases of the adoption of robotic technology to ensure patient safety.[23]
a
[The graphs are cumulative summation (CUSUM) derived learning curves, for details on methodology and how to interpret them accurately please refer to the original text, but essentially the plateau denotes the end of learning phase].[23]
b Figure 3: Learning curve assessment using CUSUM method for functional outcomes. (a) for POD 7 serum creatinine; (b) for POD 7 estimated GFR (Reproduced with permission from Elsevier Inc., European Urology; 2014 Mar 4; Application of the Statistical Process Control Method for Prospective Patient Safety Monitoring During the Learning Phase: Robotic Kidney Transplantation with Regional Hypothermia [IDEAL Phase 2a-b]; Sood et al.)
(RKT) with regional hypothermia, three surgeon groups were evaluated with varying open and robotic experience/ training.[23] Group-1: robotic trained with limited kidney transplantation (KT) experience (patients=7); Group-2: robotic trained and KT experienced (patients=20); and Group-3: KT experienced with limited robotic training (patients=14). It was demonstrated that for surgeons in group 1 and 2, there 12
Lastly, in robotic surgery, in addition to training of the surgeon there is a clear place for learning of the skill by the team as a whole.[24] Thiel et al.[25] in their study of robotic prostatectomy evaluated the role of training bedside assistants — in this study, the participants underwent a three-phase learning course including teaching regarding the basics of robot functionality (phase-1), a step-by-step video showing the optimal role of an assistant during robotic prostatectomy (phase-2), and lastly, a hands-on practice session (phase-3). The authors noted that all 13 participants who underwent the 3-phase learning course recorded improved spatial orientation during surgery and felt that the training made
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them a better assistant (100% response rate). The module that was most useful was the ‘hands-on’ drill. Hence, while setting up a robotic surgery program, it might be worthwhile to keep in consideration the training of assistants to further improve patient outcomes. What Needs to be Learned and when? For successful performance of any task a person needs to have the knowhow of what to do (domain knowledge) and how to do it (technical knowledge; Figure 4), as David Eddy pointed out in his landmark paper.[26] Domain knowledge, also alluded to as functional knowledge sometimes, refers to the understanding of a concept while technical knowledge represents the acquaintance of an individual with the steps in execution of a task. Domain knowledge is primarily acquired from theory whereas technical knowledge is acquired by practice. We briefly alluded to these concepts in the previous section, and using the same example, we highlight that the reason why open surgeons cannot transition into robotic surgery without going through a learning phase is because of lack of technical knowledge. An experienced open surgeon possesses the domain knowledge, but to achieve competency in technical knowledge — the surgeon needs to practice either in a simulated environment or under mentorship in a clinical environment, much akin to training of a novice surgeon. However, a resident/fellow learning a robotic procedure will need to acquire both domain and technical knowledge. Lastly, the time to learn is also important when acquiring a new technical skill, as prior studies show.[27] We humbly
Figure 4: The two types of knowledge required for successful execution of a task
submit that open surgeons should only consider taking robotic training modules when they have the desire and the setup to perform robotic surgery on a regular basis, as many of the courses (detailed in next section) offer short-term training, can be expensive and might not leave a lasting impression unless robotic surgery in continued afterwards. How can it be Learned? And When Can a New Skill Be Considered Learned? An ideal curriculum for teaching technical skills (technical knowledge) requires, foremost, setting of clear goals and objectives that can be achieved by trainees with the help of targeted interventions. The next crucial step is designing and incorporating these interventions along with assessment tools that can certify the surgeon-learner’s competency.[28] Assessment is a critical part of learning, not only because it ensures surgeon competence but also because it helps learning by the virtue of feedback (operant conditioning).[29] As stated previously, there have been several institutional and surgical-societal level efforts to develop and standardize the training curriculum and certification requirements in minimally-invasive surgical training. Although, these processes have met with limited success so far, the hospitals, credentialing committees/associations and program directors are increasingly recognizing the need for formal MIS training and credentialing, and the adoption of these processes is increasing.[17,18,30,31] Further, with regards to certification — there has been a tremendous overhaul in the way competency is evaluated. Traditionally, a trainee’s competence was measured based on time-based apprentice-type system where time spent within a specialty was the defining factor in skill acquisition. However, in the contemporary system a trainee’s progress is determined by instating specific benchmarks for him/her to achieve which lead to more objective and evidence-based credentialing.[28] Table 1 details the various training programs that exist for training surgeons in robotic surgery. The current generation
Table 1: Various training curricula for acquiring minimally invasive surgical skills Program
Surgeon training
Surgeon assessment
Duration
Training
Details/Methods
Cost
Subjective
Objective
Fellowship
1-2 years
Simulation studies Clinical setting
Nil
Proctoring by mentors
Mini-Fellowship
5 days
Simulation studies
~$3,800
Proctoring by mentors
Mentored skills course
2 days
Simulation studies
Long-term one to one mentoring, precepting and teaching Short-term mentoring, case observation and teaching Short-term mentoring and teaching
NA
Proctoring by mentors
GEARS for simulation; CUSUM for prospective learning curve evaluation* GEARS for simulation; CUSUM for prospective learning curve evaluation* GEARS for simulation; CUSUM for prospective learning curve evaluation*
GEARS: Global evaluative assessment of robotic skills, CUSUM: Cumulative summation [*not used currently but could be used based on recent studies], NA: Not available
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Sood, et al.: Robotic skill acquisition
of resident surgeons has some degree of robotic experience (at least in the United States). However, mostly the experience is insufficient to warrant independent practice. Hence, the training programs described in the following are applicable to all surgeons with varying degrees of open/laparoscopic/ robotic surgical experience. There are primarily three types of training programs (curricula):[32] • Fellowships. • Mini-fellowships. • Mentored skills courses. Depending on the time a surgeon can devote for training and the desired level of learning intended, one of the aforementioned courses might be more suitable. A fellowship is the most comprehensive course which includes one-toone mentoring, precepting, and teaching in both simulated and clinical environments. The training duration usually ranges between 1 to 2 years. However, a fellowship might not be suitable for most post-graduate surgeons due to time constraints. A mini-fellowship or a mentored skills course maybe more ideal in this situation. A mini-fellowship (developed at the University of California Irvine, USA) is a 5 day teaching and mentor-mentee course during which the mentee’s attends didactic sessions, live OR-cases, and hands-on lab sessions.[33,34] Whereas, the mentored skills course combines online learning with a 2-day mentored course.[32,35] Both of these programs have been demonstrated to have excellent content and construct validity; however, the performance predictive validity has not been evaluated.[17,28] Further, despite the short duration of the latter two courses, approximately 70-80% of the trainees successfully transition to robotic surgery, and are regularly practicing it at 3 years post-training.[18,32] Lastly, somewhat related to this topic is the Food and Drug Administration (FDA) mandated basic robot-handling training required for all surgeons performing robot-assisted procedures. The FDA training necessitates the knowhow on how to safely and rapidly remove the device in an emergency, what to do if the system stops responding, and how to respond if the system makes movements that are potentially unsafe to the patient. This training is offered by the Institutive Surgical Inc.[36] The guidelines on credentialing for robotic competency are more opaque at this time and vary from institution to institution.[18] Currently, most commonly, the surgeonlearner is subjectively assessed by the mentor (proctoring), which might be an acceptable way of evaluation over the long-term mentor-mentee relationship during a fellowship, however, may not represent a valid method of assessment during the short-term courses. Accordingly, there are certain tools such as the global evaluative assessment of robotic 14
skills (GEARS)[37] which permit objective assessment and can be used to grade performance during simulation exercises. However, there is a lack of consensus on what the cutoffs for competency, proficiency and mastery should be (the different phases of a learning curve; Figure 1B). We believe that these cutoffs need to be devised based on consensus-performance of experienced surgeons according to the GEARS tool at a multi-institutional level. Further, more recently, in the study of RKT with regional hypothermia, referred to previously [23] — the authors described a novel method of assessing competence by evaluating learning curves prospectively, objectively at an individual level utilizing cutoffs based on outcomes from previous kidney transplant series. By setting a target value (for technical [operative/anastomoses times] and functional [graft function] outcomes) prospectively and utilizing the mathematical cumulative summation (CUSUM) method, allowed the authors to evaluate the learning curve for each surgeon-learner continuously, objectively, and prospectively. This in turn permitted competency declaration at an individual level instead of utilizing an arbitrary cutoff of a standard number of cases for each surgeon-learner irrespective of their learning capabilities and training background. This methodology, theoretically speaking, combined with GEARS-cutoffs derived from experienced surgeons (as proposed earlier) can be used to monitor learning curves of surgeon-learners adopting robotic surgery continuously and prospectively during simulation training, and might allow recommendations regarding their learning status to be made in a more objective and individualized manner.
CONCLUSION In conclusion, both novice and experienced open surgeons require supervision and mentoring during the initial phases of robotic surgery skill acquisition. The experienced open surgeons possess domain knowledge, however, need to acquire technical knowledge under supervision (either in simulated or clinical environment) to successfully transition to robotic surgery, whereas, novice surgeons need to acquire both domain as well as technical knowledge to become competent in robotic surgery. A variety of training programs such as academic fellowships, mini-fellowships and mentored skill courses exist, and cater to the needs and expectations of postgraduate surgeons thoroughly and adequately. With regards to credentialing uniformity in criteria regarding accreditation is lacking but earnest efforts are underway. Currently, accreditation for competence in robotic surgery is institutional specific.
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Cite this article as: Sood A, Jeong W, Ahlawat R, Campbell L, Aggarwal S, Menon M, et al. Robotic surgical skill acquisition: What one needs to know?. J Min Access Surg 2015;11:10-5. Date of submission: 25/09/2014, Date of acceptance: 26/09/2014 Source of Support: Nil, Conflict of Interest: None declared.
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