Open access peer-reviewed chapter - ONLINE FIRST

# Present Challenges of Robotics in Gynecology

By Pranjal H. Desai and Ryan J. Gillentine

Submitted: January 31st 2021Reviewed: February 23rd 2021Published: March 14th 2021

DOI: 10.5772/intechopen.96780

## Abstract

Hysterectomy is one of the most common operations performed in gynecology. In the last decade and a half, the da Vinci robotic system has gained widespread acceptance in gynecology due to enhanced visualization and excellent dexterity compared to conventional laparoscopic techniques. The rapid adoption of the technology comes with unique challenges. Excluding initial acquisition cost and maintenance cost, surgery performed robotically is expensive than laparoscopic surgery. Higher cost on each case questions many about the viability of the robotic platform. Several hospitals have successfully established the robotic program, but many are reluctant to acquire expensive technology, and some are rolling back on their decision due to various reasons. This chapter expands on those challenges, mainly needs assessment, team building, culture of safety, learning curve, business strategy, and return of investment.

### Keywords

• Robotic hysterectomy
• need assessment
• team building
• learning curve
• culture of safety

## 1. Introduction

Hysterectomy is the surgical procedure to remove the uterus surgically. The word ‘Hysterectomy’ is invented based on Ancient Greek hustéra, “womb” and ektomía-“a cutting out of,” and, thus, means the removal of the uterus. Hysterectomies can be performed by open incision, vaginally, or minimally invasively—either by laparoscopy or robotically. Around 600,000 hysterectomies are performed in the United States annually [1]. Out of them, 85% are for non-cancerous lesions [2]. The traditional open approach to perform hysterectomies involves making a large incision around 10–15 cm above the pubic bone horizontally or vertically. Studies have demonstrated that hysterectomies with open approaches have higher blood loss, increased average length of hospital stay, and more postoperative complications in comparison to minimal invasive approach, including laparoscopic and robotic. The laparoscopic approach has been used for more than three decades and has become standard of care for many gynecological procedures. In 2005, the US Food and Drug Administration approved the use of the da Vinci robotic system for gynecologic surgeries. The use of this technology has allowed surgeons to perform gynecologic procedures with improvements in visualization, including 3D stereoscopic visualization, increased range of motion with enhanced wrist movements, and improved ergonomics with excellent dexterity compared to conventional laparoscopic techniques [3, 4]. However, studies have not shown any difference in operative or postoperative outcomes for patients undergoing robotic hysterectomies compared to laparoscopic hysterectomies [5, 6]. The robotic approach, indeed, has longer operative times [7] for certain operations and is more expensive, not exclusively limited to only operative cost (6–25% more than laparoscopy) [8] but also initial acquisition cost and maintenance cost compared to the standard laparoscopic approach [9]. The da Vinci system requires an initial investment of $1.5 to$2.5 million, depending on the model and configuration. Ongoing costs include annual service contracts (ranging in price from $150 to$170 K), instrument and accessory costs (ranging from $700–$3,500 per procedure).

## 3. Team building - the cornerstone of a robotic program often neglected

Teams in the operating room have conventionally been trained in traditional open or laparoscopic surgery where the flow of the surgery is largely directed by surgeons. The mere presence of the da Vinci platform in the operating room changes many aspects of surgery as we know it, including the dynamics of the operating room along with the order of events preoperatively, intraoperatively, and postoperatively. In robotic surgery, the surgeon sits on a robotic console almost 5–10 feet away from the patient. The absence of the surgeon at the patient’s bedside adds additional complexity and anxiety in the operating room among the team members. These new arrangements, including surgeon console, robotic arms, and robotic tower, require an operating room with a surgical team that is well-trained and understands the intricacies that go along with robotic surgeries, as well as the ability to share the burden of problem-solving and troubleshooting any issues that may arise throughout the process. The robotic platform brings unique challenges for the team. For instance, in nonrobotic surgery, surgeons often communicate with their team by signaling or often using not more than a single word [21]. Many a time, assistants understand the need before the surgeon even utters a word. However, in a robotic procedure, communication involves more detailed and clear instructions like pilots communicating with each other or with a control room, and everything needs to be loud and clear. The team needs to be trained to have effective bilateral communication and acknowledgment of all the instructions given by the surgeon or other way around. While traditional surgery has somewhat painted operating rooms as very strict and technical with the surgeon as the chief of events, the robotics platform enforces more of a team approach with a unique chronology of events. Thus, building an efficient team is very crucial for the success of a robotic program. This aspect can often be overlooked by either the hospital administration, the surgeon, or the operating room team. This may be overlooked because the territory of minimally invasive surgery seems familiar, but there remains the aspect of the robotic platform, which is not so familiar including the change in dynamics of the operating room with the integration of robotics. Therefore, the ability to have a successful robotic program depends not only on a surgeon who is well-versed in these technologies and surgical processes, but also a team made of members who feel like they too are an integral part of the robotic program.

Adoption of properly designed curriculum-based training is extremely important. This training should be subjected to all team members, including console surgeon, anesthesiologist, bedside assistance, assistance holding the uterine manipulator, and circulator. Initial training should include set up, docking, undocking, emergency shut down, and both mechanical and electrical troubleshooting [22]. Further training should be procedure-specific, and surgeons need to be involved in training the staff [23]. Some challenges come into play when trying to effectively build a team capable of performing these robotic procedures correctly and efficiently. For one, the surgeon must play the role of both the leader of the surgical procedure along with the leader who can effectively troubleshoot any problems which may arise through the process and can optimize operating with advanced technology. Moreover, the surgical team, including the surgeon and team members, must be willing to embrace this new technology and new approach to surgery after many years of training and practicing in ways that are totally different. A study published in Harvard Business Review by Edmonson compared 16 institutions that employed a minimally invasive approach to cardiac surgery. This study showed that some of these institutions were better able to use their experience for their advantage than others. The study demonstrated that motivation to learn was the most consistent characteristic with the ability to build a successful team, not the conventional predictors like case volume or experience level [24]. Personality traits of members of a successful team are not limited to openness to change, willingness to seek and elicit feedback, and readiness to recognize when they make a mistake. On the contrary, less successful programs employed leaders who were not as open to change and were not as effective at creating an environment conducive to learning. While this study primarily focused on cardiac surgery, the same parameters should apply to gynecologic procedures [25]. Thus, this idea of team building serves as an important cornerstone in the advancement of robotic procedures in the field of gynecologic surgery.

## 4. Culture of safety

The Institute of Medicine identifies patient safety as one of the key issues that are critical for health care delivery [26]. Changes to practice patterns that are well-established and proven to be effective always raise concerns about how they affect the safety of the patient. The same is true, to maybe an even higher degree, in the process of implementing complex and advanced technologies like robotic-assisted surgical procedures. These concerns come from healthcare personnel in every aspect of the patients’ care, including operating room staff, perioperative nursing staff, anesthesia team members, and many others. While these concerns may be unfounded and unproven, they could affect morale and consequently patient outcomes [27]. Often, many hospitals implement Enhanced Recovery After Surgery (ERAS) program with robotic procedures. Many surgeons discharge robotic hysterectomy in a few hours after surgery. Nursing staff who are traditionally trained to keep minimal invasive surgery patients at least one-night inpatient may feel a little less safe to operate Enhanced Recovery After Surgery (ERAS) program and help to discharge patients home in few hours after major surgery. Studies have found that teamwork and collaboration, meetings to provide opportunities for clarification [28, 29], and staff education [30, 31] are key elements for the success of ERAS, which again supports our argument to develop an adequate culture of safety by proper communications with all stakeholders involved in postoperative care, including patients. Similarly, this has been shown in several studies that have shown that scoring higher on questions about teamwork and better communication/co-ordination is correlated with shorter length of stay and associated postoperative morbidities and mortalities. A study by Hughes et al. highlighted that 40% of US hospital nursing staff think that making changes to make improvements is difficult most of the time or all the time, which is very relevant to the implementation of advanced technologies in medical practice [32]. Recognizing that errors are sometimes inevitable, incorporating nonpunitive error reporting and analysis systems, a platform for open discussion, a willingness to learn from errors, and identifying latent threats are all characteristics of strong cultures of safety.

Three vital organizational factors are responsible for a strong environment of culture of safety: (1) environmental structures and processes within the organization, (2) the attitudes and perceptions of workers, and (3) the safety-related behaviors of individuals [33]. Institute of Medicine (US) Committee on the Work Environment for Nurses and Patient Safety narrated the following essential elements of an effective safety culture. These include a commitment of leadership to safety, empowerment and engagement of all employees in ongoing vigilance, communication, non-hierarchical decision making, constrained improvisation, training, confidential error reporting, fair and just responses to reported errors, reporting near misses as well as errors, etc. [34]. Two major barriers have been identified in adopting culture of safety. First is ‘A nursing culture that fosters unrealistic expectations of clinical perfection.’ Nurses are trained to believe that there is no alternative to clinical perfection, and error is the result of their carelessness that makes them less than good nurses. Higher standards and error-free care are always appreciated, but when that belief becomes counterproductive, it affects the overall care and goals of any program. Therefore, it is imperative to communicate with nurses that error is a systemic problem and not an individual one. Their minds need to be trained not to think any less of their colleagues when they make errors. Second is ‘litigation and regulatory barriers.’ Unfortunately, regulatory boards and the court of law or peer review processes at hospitals again reinforce the idea of clinical perfection. Therefore, it is very difficult for nursing staff to deviate from the routine practice and adopt changes that come with new technology. The culture of safety will play a large role in the outcomes of robotic-assisted surgeries, and therefore, it is both necessary and vital to address the changes that come with the implementation of novel technology. To develop a successful robotic program, it is important to implement frequent reviews of outcomes, multidisciplinary discussions, development of parameter-based new postoperative care protocols, and consideration of recommendations and management strategies from all the team members. This is a crucial part of the process of building a gynecologic surgical robotic program, and it requires commitment from members at all levels in the health care delivery system with a strong sense of culture of safety.

## 5. Learning curve

In 1885, German psychologist Herman Ebbinghaus described the concept of the learning curve, saying, “By a sufficient number of repetitions their final mastery is ensured. [35]” In 1936, Wright endorsed the concept of the learning curve by hypothesizing that by increasing production one achieves perfection and, consequently, requires less time to produce aircrafts. Over 1,200 robotic programs have been established across the United States, with over 1,500 gynecologic surgeons being trained in the technology. Along with this training, there obviously comes a learning curve. This phenomenon is well-established with robotic surgery in all specialties, and multiple studies have been published to discuss the learning curve and minimum cases require to surpass the learning curve [36, 37]. The learning curve could be different for surgeons with advanced surgical skills [38] and variable for different portions of the same surgical procedure [39]. Acquisition and maintenance of a robotic program is a costly venture [16]. Not including initial acquisition, robotic hysterectomies cost roughly \$2000 more than laparoscopic hysterectomies. This increased cost difference is attributed to the cost of instruments (Intuitive surgical has restricted the number of instruments in use), the costs of operating room time, costs of staffing, costs of training, and costs of personal egos. Out of these, the learning curve certainly accounts for the costs of increased operating room time, costs of personal egos, costs of the number of instruments used, costs associated with complications, etc. Therefore, before adopting a robotic program, surgeons and hospital administration should have proper understanding of the phenomenon of ‘the learning curve,” and its implications on the balance sheet of the hospitals. Typically, the learning curve has been described as an S-curve or sigmoid shape (Figure 2A). The Y-axis represents learning, and the x-axis represents experience. Classical sigmoid behavior represents an initially slow, then rapid, and subsequently slow improvement [40]. In most medical studies of learning curves, the statistical approach discretizes cases into groups and uses standard statistical methods to compare the variables. This methodology provides the statistical significance values, but it is not always the optimal way to assess the learning curve which is a dynamic process in which improvement occurs on a case-to-case basis.

A sensitive way to portray surgical failures that are indicative of both the early learning curve and the post-learning curve is the cumulative sum failure analysis (CUSUM) [41, 42, 43]. This technique not only recognizes time as an important, hidden variable in these studies, but it also prevents the decreased statistical significance that can sometimes accompany repeat testing. For these reasons, both the standard statistical method and cumulative sum analysis are recommended to fully assess new teams with accurate and objective feedback. The following formula is used to plot the cumulative sum curve: Sn = Σ(Xi–Xo) where Xi = 0 means success and Xi = 1 means failure. Xo represents the predicted risk of major adverse events. The X-axis portrays the number of cases, while the Y-axis represents the sum of failure. This is shown in the figure (Figure 2B). The line that trends above the baseline portrays the learning curve or a performance that does not meet expectations. Contrarily, the line trending toward or below the baseline portrays the performance that is improving or the post-learning curve, respectively. The line trending below the baseline and away from the baseline shows adequate experience or performance that is either better or equivocal. Examples of these graphs are represented in Figures 2B–D. Figure 2A shows the analysis of a hypothetical CUSUM analysis of any successful procedure as explained above. Figure 2C has a curve above and moving away from the baseline. This could represent an example of either an unsuccessful procedure or a surgeon not passing the learning curve. Figure 2D shows the curve representing either a surgeon with excellent skills from the beginning or having escaped the learning curve that happens when skillful laparoscopic surgeons start performing robotic cases. The assessment of learning not only plays a critical role in development of an effective robotics program to assess the initial learning curve, but it also provides continued monitoring by assessing the state of the learning curve of the entire division from time-to-time which is a critical part of a robotic program [44].

## 6. Business perspective and return on investment (ROI)

Recently, a study analyzed 180,230 women who underwent laparoscopic or robotic-assisted laparoscopic hysterectomies for either benign or malignant indications (specifically endometrial cancer) from 2006 to 2012 [47]. This study demonstrated that the cost of robotic-assisted hysterectomy remained high, but this cost is offset by increased procedure volume. The use of robotic assisted technology was also found to decrease cost for oncology cases but not in benign gynecological surgeries. The cost difference between hysterectomies performed by three different modalities was analyzed by Bell and colleagues [48]. Data reveals that on average, compared to robotic procedures, the total cost for hysterectomies with staging was approximately 30–40% higher in the procedures completed by laparotomy (P < .005), but robotic was 10% more expensive than laparoscopic surgeries (P=NS). It can be hypothesized that during the phase of the learning curve, there would be major cost burdens associated with the time of the operation, turn over time, initial complications, prolonged hospital stays for some cases, conversions to open laparotomy, and overhead costs associated with the initial cost of acquisition. Due to these increased cost burdens, this would potentially minimize the cost advantage of robotic-assisted surgeries over the traditional laparotomy throughout the learning period.

## 7. Conclusion

In conclusion, the adoption of a widespread robotics program for gynecological surgeries has barriers to overcome. The proposed article outlines those barriers and solutions based on literature review and our own experience. It is imperative for hospital administrators and surgeons to understand those barriers to avoid premature frustrations and proper planning for a successful robotic program to avoid the risk of suboptimal patient care and closure of the program before even it starts generating the revenue. With current health care economics, return on investment is an important concept when funds are limited, and, unlike large hospital systems with deep pockets, administrators and surgeons of small community hospital needs to understand above facts and take baby steps accordingly. Robotic platform in gynecology has continued to emerge as a very legitimate challenger to both traditional laparotomy and simple laparoscopic procedures by providing improved ergonomics and maneuvering capabilities. By overcoming the barriers outlined above, there is hope that robotic-assisted procedures will provide another legitimate option to improve outcomes for patients in the future of gynecologic operations.

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© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Pranjal H. Desai and Ryan J. Gillentine (March 14th 2021). Present Challenges of Robotics in Gynecology [Online First], IntechOpen, DOI: 10.5772/intechopen.96780. Available from: