Regardless of the surgical approach that predominates, a successful CABG program drives patient traffic and acceptable levels of patient satisfaction because of the impact of this procedure on patient quality of life. Nevertheless, patients have shown a strong preference to know about less invasive surgery. Oftentimes, patients that require referral to a cardiac surgeon learn about their options from their medical providers and the surgeons to whom they are referred. Wide variability in the use of less invasive techniques suggests that centers only offering the traditional approach may not notify patients about all surgical alternatives [1, 2]. This lack of disclosure may result because physicians are unable to provide confident advice about a procedure for which they have no personal experience. Alternatively, the perceived advantages of r-CABG may be less meaningful to physicians than they are to patients. In either case, the assumption that a physician’s rank order of priorities to be achieved from surgery is always the same as the patient’s undermines patient decision making for preference-sensitive conditions. Instead, preferences of the surgeon and their referral sources have led r-CABG to be underutilized compared to what patients would otherwise demand [8, 9].

Because most patients referred for elective CABG have sufficient time to participate in the decision about where they receive their care [4], knowledge about r-CABG drives patients into programs offering this distinctive service that otherwise would not have come. As a result, these patients appreciate the clinical benefits derived from the procedure itself and that they were provided with information that might not have been discussed at other centers. Such a discussion is meaningful because it alleviates their vulnerability caused by asymmetry of information and empowers them with alternatives relevant to their personal needs, principles on which patient-centered care is based [5]. Patients and their families often become engaged in the idea that success for these novel programs helps foster transparency and beneficial competition in healthcare. For all these reasons, initiating a robotic cardiac surgical program drives up patient satisfaction scores and creates loyal advocates of the program. Supplemental strategies are also effective at improving satisfaction scores such as communicating with respect, sitting instead of standing at the bedside, the AIDET tool, face cards given to patients that describe the members of their care team, and follow-up phone calls. While these tools enhance the patient experience, none have the same fundamental impact of providing patients with a distinctive option that they highly value but cannot get elsewhere.

Patient satisfaction scores have become increasingly relevant because these data are publically reported [10] and influence pay-for-performance programs. Moreover, high scores have been shown to reduce legal exposure to malpractice suits [11]. Patient have demonstrated strong preferences for less invasive surgery [12], underscoring the role for surgical innovation as key part of a strategy for achieving patient-centered care [7, 13–17]. In addition to technical aspects of care (such as whether surgery is performed less invasively), overall patient satisfaction is also driven by ambiguous issues such as hospital experience, access to care, personality of the physician, and honest communication and other. Because ambiguous issues are difficult for the patient to judge, many patients will assimilate their opinions on these other issues to fit with their favorable first impressions about a distinctive service like rCABG, driving up satisfaction scores across the board.

A prolonged period of inefficiency that must be endured before the team establishes proficiency at r-CABG is known as the “learning curve.” A major weakness of rCABG is that difficulties with the learning curve can translate into more risk for the cardiac surgical patient than in other surgical specialties. Complications during the learning curve that occur often could have been prevented by more experience with technique and/or communication. This creates a stark contrast to the incumbent procedure where few are deemed to be preventable [18]. Despite the inherent bias from comparing a nascent r-CABG program in its early stages against a mature sternotomy CABG program, such comparisons often occur and lead critics to conclude that the challenges of r-CABG are not safely surmountable.

Because of the vulnerability that the learning curve causes for patients and the program, an important focus for the r-CABG team is to make rapid progress during this period. There are many examples of complex cardiovascular procedures that have endured lengthy learning curves to become accepted alternatives that compare quite favorably with the incumbent procedure. However, current training paradigms require at least 100 cases of experience that accumulate within time frames often exceeding a year in order to demonstrate proficiency [13]. The predominant training strategy has been experiential learning, or “learning by doing” on actual clinical cases. Under normal circumstances, educational theory suggests that experiential learning is more effective than other formal methods of training [19]. But team morale can be affected by preventable complications during the learning curve, which creates a poor learning environment [19]. Ineffective team learning aggravates the risks of the new rCABG program and limits the chances for sustainable success.

Evidence that programs have been able to shorten the learning curve has revealed some strategies that consistently work. The process starts with articulating how progress during this learning period will be measured, i.e., metrics of success. Standard quality assurance tools of conventional cardiac surgery include the review of incident reports, chart audits, autopsy findings, morbidity and mortality conferences, administrative data, and patient complaints. These are insensitive measures of progress with the learning curve of r-CABG. Successful programs use a much broader array of metrics that reflect performance of the surgeon (e.g., prolonged operative times, markers of myocardial injury), perioperative team (e.g., rates of postoperative morbidity or re-intubation, poor pain control, excess transfusions), and hospital (e.g., prolonged hospital stay, higher costs). Review of these data will likely reveal that the learning curve is impacted by stakeholders that extend well beyond the OR team. These team members are not passive observers of the robotic surgeon but actively influence the learning curve by accommodating their tasks to the new program. Evidence from the US Military has demonstrated that even the best teams typically have limited capacity to address the burdens of change during high tempo periods and require team debriefings to optimize learning [20]. Emulating this model with regular, multidisciplinary review of the data outside the OR is required to identify areas that need improvement and create specific action plans. These meetings signal to the team that there is the “psychological safety” needed for members to learn from mistakes and actively engage in troubleshooting [17].

Based on the irreplaceable role of the lead surgeon, it is tempting to conclude that the technical ability and experience of the surgeon are sufficient for the success of rCABG programs. However, Dhawan et al. showed that a lead surgeon with >300 cases of prior r-CABG experience at the outset when he initiated a new program was unable to avoid a substantial de novo learning curve [21]. Surrogates of the technical skill of a surgeon such as dexterity on simulators or how quickly their procedure times decline over time have not been found to correlate with the sustainability of robotic programs [21]. Instead, there are many nontechnical skills required to manage and lead change at the level of the organization that appear to be critical for success [22].

An often overlooked challenge posed by rCABG is a significant “forgetting curve.” Early cases are often scheduled infrequently until the procedure becomes recognized and popularized among those that are appropriate candidates. If the frequency of scheduling early cases is too long, skills acquired from previous cases lapse and the learning curve becomes longer than it would with higher caseloads. This leaves surgical programs in a conundrum—the requirement of up-front volume in order to solidify training in a program that is new and requires time to ramp up its volume of referrals. The forgetting curve may be mitigated to some degree by training programs, including virtual reality simulator and cadaveric training. One benefit of the robotic console is the ability to use it to create “virtual environments.” Utilizing available virtual simulators, as well as animal and human cadaveric training labs can be helpful to improve surgeon and team skill without exposing clinical patients to additional risk [23, 24]. Despite the promise of this approach and demonstrated utility in other surgical specialties, a validated curriculum for rCABG training has not been established and funding for these programs can be a challenge.

Likewise, the technical complexity of operating on the heart within the relatively tight and constrained chest cavity has given rise to safety concerns. The potential for sudden bleeding, either from the heart or vascular sources such as the IMA, cardiac fibrillation, ischemia, and hemodynamic collapse, is difficult to address when working in a closed chest and with the bulky arms of the robot hindering patient access (Fig. 25.2a, b). Indeed, to adequately address these concerns, best practices must be developed that facilitate early identification and appropriate responses to impending decompensation in the absence of direct inspection of the heart. This may include better utilizing TEE data, hemodynamics, better team communication, heightened “situational awareness,” and standardized and reliable protocols to respond to those changes. While a learning curve for physicians performing the procedure has been clearly identified, staff must also undergo technically complex training. It is often argued that the inherent complexity of the robotic approach will never afford the surgical team the ability to achieve results equivalent to those seen with a sternotomy, leading to a fixed higher risk of error. The associated learning curve and concerns about overall safety may also be demoralizing to the team which can be a latent risk factor for preventable complications. Team morale, therefore, is a critical focus of improving the safety of the procedure. Developing and validating strategies for rapid progress through the learning curve and gaining “buy-in” about the benefits of less invasive surgery will be critical in enabling programmatic success.

The added costs of less invasive CABG are widely perceived to be a disadvantage that limits its adoption. The additional time and expertise required for preparing the robotic apparatus prolong operating room times and alter the efficiency of the OR staff. Even after the learning curve is complete, multivessel revascularization by rCABG usually takes longer than sternotomy CABG. This may pose a significant hurdle to success at those hospitals where OR capacity is already a bottleneck for revenue generation and would be understandably reluctant to use this precious resource inefficiently.