Guidance for the safe implementation of telementoring in robotic surgery

Introduction

The concept of telepresence has been present since the inception of robotic surgery. The first teleoperated robotic systems developed by SRI International and the Defence Advanced Research Projects Agency (DARPA) resulted in the surgeon console systems we are now familiar with. The impetus to develop these remotely controlled systems was driven by DARPA who identified a need to provide additional expertise in warzones to decrease morbidity and mortality. The principle of providing surgical expertise from a remote geographical location remains pertinent to learning curves, as well as emergency and “unfamiliar” situations, where the alternative is to convert to an open or laparoscopic procedure. Historically, traveling proctors aimed to bring expertise and feedback to inexperienced surgical teams; however, current travel restrictions limit this educational resource and training often lacks standardization and objective performance metrics. Other recognized benefits of telepresence services are network development and data collection, which have great potential to contribute to surgical data science (SDS) and to aid the development of predictive artificial intelligence (AI) with utilization of big data. ^,

Despite the potential for robotic surgery to enable dissemination of expertise through network development and improve training outcomes, procedural training remains largely delivered via a master-apprentice model, with potential variabilities in both surgery and educator skills. The trainee is “signed off” as competent after a suitable period of time, rather than objective assessments. Subjective assessments of surgical performance have been shown to be highly variable with poor inter-rater reliability. Skills learning is more efficient when sustained deliberate practice (SDP) is enabled. This requires skills to be defined with objective metrics of performance that are agreed upon by both the trainer and student. SDP states that repetition of skills with deliberate practice is key to success, and that the defined metrics should be able to be replicated in laboratory settings or training environments. The combination of systems thinking with a proficiency-based progression (PBP) approach delivers consistent feedback and reduced errors in aviation training. A complementary strategy to drive standardized training with a top-down approach is “train-the-trainer” courses, where trainers learn about the curriculum structure, training protocols, standardized assessment, and how to deliver feedback safely.

It is recognized that errors are more common early in the surgeon’s learning curve, and the combination of simultaneously learning about both technology and technique has inherent patient safety risks. ^, With a growing awareness of the benefits of standardized training, there are an increasing number of validated training curricula with defined metrics of surgical performance endorsed by societies and governing bodies. While different trainees benefit from varying levels of support, there are recognized weaknesses to the current gold standard, notably when the trainee has completed the training modules but still lacks experience and is confronted with a pathology, anatomical abnormality, or clinical situation that they are unfamiliar with. To improve training, we need access to expertise when required. Operative approaches should be agreed upon between the trainer and the trainee, with objective performance metrics that enable PBP training. Defining standardized metrics enables us to contrast and compare alternative approaches to training that aim to achieve equivocal training outcomes. An aim of SDS is to analyze training data collected via technologies such as telepresence, to evaluate whether novel approaches are equivocal, better, or worse. ^, Telepresence has the potential to deliver expertise locally and affordably while avoiding travel limitations. Despite the significant potential for telepresence, there remains a lack of standardized guidance for telepresence in surgery. A Delphi process was therefore completed to define the infrastructure, communication protocols, and accountability related to delivering an optimized telepresence program. The project consisted of three phases, where each phase informed the subsequent phase. First, available evidence was reviewed, which then informed the Delphi consensus questionnaire development. The consensus process then resulted in the formulation of the guidance.

Review of the literature

A systematic review of the literature and international protocols for telecommunication in both healthcare and the aviation industry was completed independently by three individuals. The systematic review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. The authors reviewed current published literature on PubMed, Scopus, and Web of Science databases for full text English language articles published between 1995 and 2020 using the key words “telepresence,” “telementoring,” “telesurgery,” “minimally invasive surgical procedure,” “robotic surgical procedure,” “education,” and “distance.” Additional significant studies cited in the reference list of selected papers were evaluated. The reviewers independently selected papers for detailed review evaluating the abstract and, if necessary, the full-text manuscript. Potential discrepancies were resolved by open discussion. The electronic search yielded a total of 6753 potential articles. Fig. 9.1 summarizes the selection process. Multiple prospective studies were identified that confirmed both feasibility and benefits from telementorship and telesurgery programs. Overall, the quality of available studies was moderate to low. Available evidence consists largely of expert opinion, consensus statements, and small qualitative studies. There were no publications identified that focused specifically on guidance for setting up and running a telepresence service for robotic surgery training. Ninety-two articles were selected by the core team and were placed into three categories related to telepresence: infrastructure, protocols, and accountability.