Current Commentary
Milestones to Optimal Adoption of Robotic Technology in Gynecology Pranjal H. Desai,
MD,
Jeff F. Lin,
MD,
and Brian M. Slomovitz,
Minimally invasive technology, especially robotics, is gaining widespread acceptance and is becoming the standard approach for the treatment of both benign and malignant gynecologic conditions in centers across the country. However, there are challenges on a systemsbased level to the implementation of a robotic program. Prominent among the concerns is the length of the learning curve, team-building, quality of life, and financial and various organizational challenges. The purpose of this review article is to address those challenges as milestones on the progress to a successful robotics program and explore possible solutions. (Obstet Gynecol 2014;123:13–20) DOI: 10.1097/AOG.0000000000000055
T
he da Vinci robotic system received U.S. Food and Drug Administration approval for gynecologic surgery in 2005. The improved visualization and dexterity of this platform over conventional laparoscopy have allowed surgeons to perform gynecologic procedures. In 2010, 433,621 hysterectomies were performed in the United States for benign and malignant indications.1 Over the past decade, a minimally invasive surgical technique has gained widespread acceptance as a result of increased adoption of both conventional See related editorials on pages 1 and 3.
From the Department of Obstetrics and Gynecology, Morristown Medical Center and Overlook Medical Center, Atlantic Health System, and the Women’s Cancer Center, Carol G. Simon Cancer Center, Morristown, New Jersey; and the Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Sciences, Magee-Women’s Hospital of the University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania. Corresponding author: Brian M. Slomovitz, MD, Women’s Cancer Center, Carol G. Simon Cancer Center, 100 Madison Avenue, Morristown, NJ 07962; e-mail: mailto:[email protected]. Financial Disclosure None of the authors have any conflict of interest to report. © 2013 by The American College of Obstetricians and Gynecologists. Published by Lippincott Williams & Wilkins. ISSN: 0029-7844/14
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laparoscopy as well as robotic-assisted laparoscopy. Minimally invasive hysterectomy has definitely demonstrated the advantages with reduced blood loss, length of stay, and postoperative complications compared with laparotomy. Multiple studies have demonstrated the safety of robotic-assisted laparoscopic procedures and comparable results for intraoperative and postoperative morbidities compared with laparoscopic procedures with the caveat of longer operative times and cost.2,3 For robotic-assisted laparoscopic myomectomy, Advincula and colleagues4 found better results compared with laparotomies, whereas Bedient5 found comparable results with a laparoscopic group. In a study comparing robotic-assisted laparoscopic sacrocolpopexy with laparoscopic sacrocolpopexy, Tan-Kim et al6 found that length of stay, blood loss, complication, and objective cure rates did not differ between the groups. However, operative time was longer in the robotic group as was the cost. One major drawback in these studies is that surgeons under study had more experience in traditional laparoscopic surgeries than robotic-assisted procedures. Sarlos et al3 demonstrated that despite certain shortcomings, surgeons enjoyed the better ergonomics and wider range of motion of robotic instruments. With advancement of the learning curve, operating time can be minimized, potentially decreasing the cost. Several studies have demonstrated the feasibility of using the robotic platform to perform adnexal surgery,7 endometriosis surgery,8 and tubal reanastomosis9,10; however, the differential advantage to the use of the robotic platform in these procedures has been questioned and more data on cost and long-term outcomes are needed. Minimally invasive surgery is becoming the standard approach for the treatment of patients with endometrial cancer in many centers across the country.11 It is estimated that there have been 49,560 new cases of endometrial cancer in 2013 with 8,190 attributable deaths resulting from this disease.12 Reports from the LAP2 study by the Gynecologic Oncology Group have demonstrated improved short-term outcomes and comparable cancer control outcomes.13,14 Various small-scale
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case series have documented the initial experience with and success of the robotic platform for the treatment of early cervical and ovarian cancers as well.15 Specifically, investigators have documented similar outcomes for minimally invasive radical hysterectomy compared with traditional laparotomy.16 For endometrial cancer, studies have shown that minimally invasive hysterectomy is safe and associated with shorter hospital stays, faster return to normal activity, and improved short-term quality-of-life measures compared with conventional laparoscopy and traditional laparotomy.17,18 Gehrig and colleagues19 have shown that robotic-assisted surgery offers decreased blood loss, transfusion requirements, laparotomy conversion, operative time, and hospital length of stay in obese patients compared with conventional laparoscopy. Recently, the Clinical Practice Robotics Task Force of the Society of Gynecologic Oncology has published a consensus statement stating that the use of robotic-assisted surgery in gynecology oncology offers a distinct advantage over traditional methods.20 Despite proven advantages, challenges to widespread implementation of robotics programs nationwide exist. Prominent among the concerns for the surgeon is the length and shape of the learning curve and for the health care administration are ways to optimize patient outcomes while minimizing associated costs (eg, time, training) because both the physical size and financial costs of the robotic platform pose numerous unappreciated organizational challenges (Fig. 1). The purpose of this review article is to address those challenges as milestones on the progress to a successful robotics program and explore possible solutions.
MILESTONE 1: TEAM BUILDING—THE CORNERSTONE OF A ROBOTICS PROGRAM Robotic-assisted surgery is a disruptive technology in many aspects, chief among which is a change in the operating room dynamics and chronology of events. Compared with conventional laparoscopy, where operative cadence and success is dependent mostly on the surgeon, the robotics platform, with its three components—bedside robot and instruments, tower, and surgeon console—requires a team well versed in the complexities of the system and distributes the burden of troubleshooting throughout the team. Although the operating room has always been seen by some as a highly technical, highly choreographed theatrical arena, an adoption of the robotics platform brings the team aspect and unique sequence of events to the forefront that had not been necessary previously. This aspect of the robotics program—building an efficient team—is crucial but can sometimes be neglected by the surgeon and administration, because the platform is appreciated to be at times both familiar—ie, “it is still minimally invasive surgery”—and foreign—“it is a robot and advanced technology; therefore, it must require less than conventional laparoscopy once the surgeon is up and running.” The success of a robotic program depends heavily on a surgeon and leader who recruits team members who believe themselves to be stakeholders in the program and actively promotes learning and communication. A variety of roadblocks are often in place to hinder this process. The surgeon must step into his or her role as not only the surgical leader, but also as
Final product after successfully addressing challenges
ac tic
es
Innovation induced
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Final product after failure to adopt best practices
Fig. 1. Natural course of any innovative procedure. Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
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a manager to efficiently troubleshoot and optimize the operation with the new technology. In addition, the surgeon as well as the team members, all of whom may have very carefully and efficiently practiced routines over years or decades, needs to embrace the new approach and be willing to adapt or formulate new routines. Edmonson conducted a study published in Harvard Business Review comparing 16 different institutions that adopted minimally invasive cardiac surgery and found that some organizations seem to capitalize on their experience more effectively than others.21 The investigators found that team learning did not correlate with conventional predictors such as case volume or surgical experience. Instead, staff interviews revealed that the most consistent characteristic of a successful team was a high level of motivation to learn. This motivation stemmed from leaders who were willing to admit mistakes and elicit feedback. Furthermore, members of successful teams were deliberately selected based on competence as well as personality traits correlated with openness to change.22 Contrarily, programs with prolonged learning curves tended to have leaders who, although technically superb, were less adept at creating a learning environment and managing teams or whose members were less open to adapt. The technical complexity involved in robotic high-risk gynecologic and gynecologic oncologic procedures is no less than cardiac surgery, and therefore we stress the importance of selection and team-building as an essential milestone in optimizing the adoption of robotic technology for gynecologic procedures.
MILESTONE 2: CULTURE OF SAFETY Patient safety is one of the key issues prioritized by the Institute of Medicine as critical for effective health care delivery.23 Although adoption of any change to well-established practice patterns will raise some questions about patient safety, incorporating as complex and novel a technology as the robotic platform often arouses concerns and doubts in the staff, from the preoperative nursing staff, to the anesthesia team, to the recovery room staff and beyond. Whether warranted or not, these concerns can affect morale and influence outcomes. The importance of staff attitude and morale on patient safety has been quantified by a culture of safety survey. The results of this survey reveal a strong and statistically significant relationship between staff morale and patient outcomes.24 Studies have shown that higher scores on questions about teamwork and coordination are associated with shorter total length of stay as well as morbidities and mortality after complex surgeries. A particular concern for
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incorporating innovative changes in medical practice highlighted by the study by Hughes and Lapane25 found that 40% of nursing staff in U.S. hospitals find it difficult to make changes to improve things most or all of the time. Characteristics of a strong culture of safety include: recognition of the inevitability of errors, incorporation of nonpunitive error reporting and analysis systems, commitment to transparent discussion of and open learning from errors, and proactive identification of latent threats. Similar to its counterparts in the airline and nuclear energy industries, a culture of safety in health care is likely to have a profound effect on outcomes after robotic-assisted surgical procedures, and the changes should be addressed as part and parcel of the integration of robotic technology. Regular outcomes review, multidisciplinary discussions, and ready implementation of recommendations and management strategies should be part of the development of the robotic program from its inception. Because this requires action and commitment from all levels of the health care delivery team, we identify culture of safety as milestone 2 in the building of a successful robotic program for gynecologic surgery.
MILESTONE 3: LEARNING CURVE To date, more than 1,200 robotic systems have been installed across the United States, and more than 1,500 gynecologic surgeons have been trained. The learning curve phenomenon is well recognized and, in the present health care economy, its parameters are oftentimes a critical first question in the adoption of any novel, costly technology, or both. The costs of learning is not only limited to instrumentation and operating room time, but also staffing, training as well as personal ego; the errors and mistakes are the norm before proficiency. Because of its importance in the decision-making process for surgeons and hospital administrators considering adoption of robotic technology, the learning curve, and its assessment, has been increasingly addressed in various studies.26 One should be aware, however, that the statistical approach taken in most studies of learning curve—discretizing the cases into groups such as tertiles or quartiles and applying standard statistical methods of comparison—is a suboptimal method to assess learning, because it does not assess the change on a case-to-case basis. The case-by-case change and progress in learning is an important indicator of successful team development and adoption of the technology. The use of cumulative sum failure analysis is a sensitive way to illustrate the cluster of surgical failures indicative of the early learning curve as well as postlearning curve assessment.27–29
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The cumulative sum technique recognizes the importance of time as a hidden variable in clinical studies and avoids the depreciation of statistical significance that is associated with repeated testing. Thus, cumulative sum and standard statistical methods are both recommended to provide new teams with accurate and objective feedback regarding their progress (Fig. 2). The cumulative sum curve is plotted by using the following formula: Sn5S (Xi–Xo), where Xi50 for success and 1 for an observed failure. Xo is the predicted risk of major adverse events. In the cumulative sum curve, X-axis represents number of progressive cases, and the Y-axis represents cumulative sum of failure. Figure 2A represents components of the normal cumulative sum curve of any procedure. Line trending above baseline represents the state of the learning curve or performance is worse than expected; the graph going toward baseline represents the state of the postlearning curve or performance is getting better; and the graph trending below and away from baseline represents the state of adequate experience or performance is trending toward better or equivocal to the counterparts. Figure 2A–C demonstrates cumulative sum analysis for a hypothetical procedure that has different outcomes. Figure 2B has a cumulative sum curve that goes above and away from baseline representing a unsuccessful procedure or a surgeon’s inability to surpass the learning curve. Figure 2C exhibits the cumulative sum curve of the procedure in which the surgeon was producing excellent results from the beginning and the escaped stage of the learning curve. Figure 2D demonstrates our institu-
tional cumulative sum analysis of 50 robotic cases performed by three gynecologic oncologists after having an average experience of 200 robotic procedures corresponding to area below baseline in Figure 2A and corresponds to Figure 2C. One can easily glean from the cumulative sum curve at our institution that there is not an initial learning curve, because the surgeons have already surpassed their learning curve and in the phase of adequate experience. The graphical representation yields much more information than traditional statistical methods with discretized groups. Accurate assessment of learning and continued monitoring is a critical part of learning and thus is our third milestone.
MILESTONE 4: QUALITY OF LIFE Once the hurdles of implementation and quality assurance of a new medical technology are passed, the surgeon must ask him- or herself the most important question: “Does the novel intervention improve the quantity and quality of the patient?” The most established method of assessing quality of life is expressed as quality-adjusted life-years (QALYs) based on various aspects of physical and mental health of the patients ascertained by sets of validated questionnaires, and it is a more precise and meaningful measurement derived by a formula incorporating two important variables: life expectancy and quality of life for remaining years. The QALY is defined as a “measure of a person’s length of life weighted by a valuation of their health-related quality of life” after any intervention.30,31 Utility score is given
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Fig. 2. Cumulative sum curves. Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
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based on time spent in a particular health state. So for instance, if intervention X allows someone to live for 5 more additional years, a utility score of 0.6 provides one more QALY than intervention Y that provides 5 more additional years at a utility ratio of 0.4. EQ-5D is the tool for health state evaluation objectively.31–33 Furthermore, QALYs’ another meaningful use is to calculate cost-utility ration; an economic analysis reflects effects of relative cost on the effects of interventions, which can be calculated by dividing difference between cost and QALY resulting from two different interventions in question.31 The primary reason for pursuing minimally invasive surgery from the perspective of the patient is the potential for an improvement in quality of life (QOL) during the early recovery period. Ellstrom et al34 have shown that laparoscopic hysterectomy confers a better QOL compared with abdominal hysterectomy at 1, 3, and 6 months after surgery. In the Gynecologic Oncology Group LAP2 trial,35 patients in the laparoscopy group (various assisted-laparoscopy procedures allowed) had better short-term QOL outcomes compared with the total abdominal hysterectomy group up to 6 weeks after surgery. By 6 months after surgery, both groups had similar QOL, apart from body image, in favor of the laparoscopic procedure. However, these studies lack the assessment of QALY and cost-utility ratio in the long run to be performed compared with the traditional technology to justify not only the efficacy, but also to answer the critiques of technology. Qualityadjusted life-years need to be analyzed rigorously because it may be gained but with poor QOL and vice versa. Different hypothetical models of QALY have been shown in Figure 3. However, to our knowledge, no studies have been published assessing QALY or cost-utility ratio for robotic technology pertaining to benign or malignant gynecologic conditions. Such
studies would be integral in justifying the use of any new complex technology against the well-established traditional counterpart. We believe that although the robotic platform is a disruptive technology, its incremental gains on conventional laparoscopy may be more difficult to assess directly compared with the gains conventional laparoscopy made on laparotomy; because of this, we urge the study of improvements in QOL measures, whether it be in terms of QALY or other standardized, meaningful measures, and we see this as milestone 4 in the widespread adoption and embrace of the robotic platform.
MILESTONE 5: BUSINESS PERSPECTIVE Because the financial gain during the learning curve period is inconsistent, a business model is absolutely required to institute and nurture a successful robotic program. Contrary to other business sectors in which the focus has changed from long-term business strategy to transient advantage strategy,36 the health care industry still holds onto the concept of a longterm strategy, especially because advancements in medical and surgical technology take years to become a part of standard of care. An addition of costly new technology into a hospital or surgical center’s surgical armamentarium still essentially requires the organization to progress through traditional business development phases such as launching (acquiring the robot and marketing; financial loss), ramping up (learning curve for the surgeons; financial loss), exploitation (postlearning curve phase; financial gain for institution), reconfigure (change in technology or redefine the business model resulting from loss of competitive advantage; still in financial gain), advance (introduction of new technology), or terminate (with introduction of superior technology). Administrators have to keep in mind that competitive advantage is transient, not QALY gained
QALY gained
QALY gained
QALY lost
QALY lost
QALY lost
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Fig. 3. Hypothetical models of quality-adjusted life-years (QALYs). Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
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Model for financial prediction
Early phase: 1–2 years Financial loss • Learning curve • Marketing cost
Financial gain • Improved payer mix • Increase in case turnover • Increase in case load and referrals • Market share negotiating contract • Post–learning–curve phase
Late phase: 2–5 years
Fig. 4. Financial model. Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
sustainable. Hence, business strategies need to evolve over time. Monitoring and incentivizing the ramp-up and maximizing the exploitation and reconfiguration phases are key to optimizing the financial returns from investment in new surgical technologies. Bell et al37 analyze the cost difference in performing a hysterectomy among the three modalities. They demonstrated that the total average cost for hysterectomy with staging completed by laparotomy was almost 30–40% higher than the robotic group (P,.005), whereas robotic was nearly 10% higher than the laparoscopic
group (P5nonsignificant) (for traditional laparotomy, $12,943.60; for standard laparoscopy, $7,569.80; and for robotic assistance $8,212.00). Major components for the higher cost of laparotomy were pharmacy, laboratory, hospital stay, and in turn indirect overhead cost. However, for robotics, the major component was the operating room supply.37 Our prediction is that in the learning curve phase, major cost burden would be the operating room time, initial complications, prolonged hospital stay for selected cases, conversion to open, and indirect overhead cost including part of initial acquisition cost. This would offset the cost advantage for the robotics in the learning period significantly. Based on our experience, we have predicted a business model for revenue gain in Figure 4. With the proposed financial model, the administration has to be aware of the dynamicity of the financial model that includes the initial loss during the “early phase-learning curve phase” and they have to have a strategy in place to compensate for financial loss with gain when the learning curve phase is over. In the early phase, the administration has to emphasize on low-risk case selection, which would yield a better outcome that minimizes financial loss; excellent patient satisfaction would gain further popularity of the program and strengthen staff morale, building a stronger team from the start. While moving from the early to the late phase, marketing of the program with patient outcomes should be an integral part of the program. In the late phase- post learning curve phase, the administration should be prepared to acquire advantages like optimizing the payer mix to
Leader • Only surgeon • Strong affiliation with team • Faith in procedure • Open to suggestions Leader’s attitude • Take as challenge, not as a plug in component • Praise team member for accomplishment • Accepts that mistakes are inevitable; willing to openly discuss with team Culture of safety • Successful teams built based on fearless suggestions from team members Real-time learning • Better than after action analysis • Evolution of new skills by chance
Successful robotics team
Team • High level of motivation to learn • Leader recruits team members as stakeholders • Leader actively promotes learning and communication • Open to suggestions • Stability and consistency
Surgical audit • An essential component • With use of CUSUM and statistical methods • Perform periodically
Fig. 5. Pillars of a successful robotic team. CUSUM, cumulative sum. Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
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ensure continued financial success (ready to expect more private payers than government Medicare and Medicaid). Early return to work would be appreciated by private employers and, hence, the hospital should have leverage to renegotiate the contract with managed care organization and eventually increase the reimbursement. In addition, safety of the procedure needs to be analyzed by the multidisciplinary team by reviewing the results. Studies have already demonstrated the safety of the robotic procedure for endometrial cancers,13,14,17,18 which should provide the medical rationale for adoption of the platform; understanding of the natural cycle of a transparent dynamic business model of adopting an innovative technology as delineated here and capitalizing on the long tail should provide the health care economics rationale for adopting the technology and establishing a successful robotic program.
SUMMARY Despite convincing interim results, the various surgeon, team, and administrative obstacles remain in the widespread acceptance of robotic technology in gynecologic surgery. We frame these obstacles in the context of milestones to overcome and outlined ways to approach and analyze team-building, culture of safety, learning as well as outcome-driven practice and business perspective. Not overcoming these milestones in the adoption of the technology eventually results in suboptimal patient care and outcomes as well as the perception of the platform as a gimmick or sophisticated marketing tool rather than the game-changing technology that it really is. Success of the robotic team depends on a multifactorial process (Fig. 5). Once a successful team is in place, quality assurance, both in terms of surgical team learning as well as patient outcome, must be in place and frequently monitored. In the era of declining reimbursement, adoption of novel and especially million dollar technologies such as the robot is often viewed with skepticism. The authors feel that rigorous assessment of validated outcomes, in terms of QALY or other methods, should be the most important factor in the decisionmaking process and requires careful thought before recommending any technique for a patient. For the success of the program, complete understanding of the business model is extremely important for the administration. We delineated milestones based on our experience of a high-volume gynecologic oncology program; however, these basic challenges also apply very well to benign gynecologic surgery programs. With improved ergonomics and maneuvering capabilities, robotic-assisted laparoscopy has emerged
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as an answer for the challenges of complex gynecologic procedures in high-risk patients with an acceptable learning curve with a hope to deliver improved QALY and thereby achieve its place as a best practice for benign and malignant gynecologic conditions. REFERENCES 1. Wright JD, Herzog TJ, Tsui J, Ananth CV, Lewin SN, Lu YS, et al. Nationwide trends in the performance of inpatient hysterectomy in the United States. Obstet Gynecol 2013;122: 233–41. 2. Payne TN, Dauterive FR. A comparison of total laparoscopic hysterectomy to robotically assisted hysterectomy: surgical outcomes in a community practice. J Minim Invasive Gynecol 2008;15:286–91. 3. Sarlos D, Kots L, Stevanovic N, Schaer G. Robotic hysterectomy versus conventional laparoscopic hysterectomy: outcome and cost analyses of a matched case-control study. Eur J Obstet Gynecol Reprod Biol 2010;150:92–6. 4. Advincula AP, Xu X, Goudeau St, Ransom SB. Robot-assisted laparoscopic myomectomy versus abdominal myomectomy: a comparison of short-term surgical outcomes and immediate costs. J Minim Invasive Gynecol 2007;14:698–705. 5. Bedient CE, Magrina JF, Noble BN, Kho RM. Comparison of robotic and laparoscopic myomectomy. Am J Obstet Gynecol 2009;201:566.e1–5. 6. Tan-Kim J, Menefee SA, Luber KM, Nager CW, Lukacz ES. Robotic-assisted and laparoscopic sacrocolpopexy: comparing operative times, costs and outcomes. Female Pelvic Med Reconstr Surg 2011;17:44–9. 7. Magrina JF, Espada M, Munoz R, Noble BN, Kho RM. Robotic adnexectomy compared with laparoscopy for adnexal mass. Obstet Gynecol 2009;114:581–4. 8. Nezhat C, Lewis M, Kotikela S, Veeraswamy A, Saadat L, Hajhosseini B, et al. Robotic versus standard laparoscopy for the treatment of endometriosis. Fertil Steril 2010;94:2758–60. 9. Dharia Patel SP, Steinkampf MP, Whitten SJ, Malizia BA. Robotic tubal anastomosis: surgical technique and cost effectiveness. Fertil Steril 2008;90:1175–9. 10. Goldberg JM, Falcone T. Laparoscopic microsurgical tubal anastomosis with and without robotic assistance. Hum Reprod 2003;18:145–7. 11. Wright JD, Burke WM, Wilde ET, Lewin SN, Charles AS, Kim JH, et al. Comparative effectiveness of robotic versus laparoscopic hysterectomy for endometrial cancer. J Clin Oncol 2012;30:783–91. 12. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin 2013;63:11–30. 13. Walker JL, Piedmonte MR, Spirtos NM, Eisenkop SM, Schlaerth JB, Mannel RS, et al. Recurrence and survival after random assignment to laparoscopy versus laparotomy for comprehensive surgical staging of uterine cancer: Gynecologic Oncology Group LAP2 Study. J Clin Oncol 2012;30:695–700. 14. Walker JL, Piedmonte MR, Spirtos NM, Eisenkop SM, Schlaerth JB, Mannel RS, et al. Laparoscopy compared with laparotomy for comprehensive surgical staging of uterine cancer: Gynecologic Oncology Group Study LAP2. J Clin Oncol 2009;27:5331–6. 15. Reynolds RK, Burke WM, Advincula AP. Preliminary experience with robot-assisted laparoscopic staging of gynecologic malignancies. JSLS 2005;9:149–58.
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16. Frumovitz M, dos Reis R, Sun CC, Milam MR, Bevers MW, Brown J, et al. Comparison of total laparoscopic and abdominal radical hysterectomy for patients with early-stage cervical cancer. Obstet Gynecol 2007;110:96–102. 17. Falcone T, Paraiso MF, Mascha E. Prospective randomized clinical trial of laparoscopically assisted vaginal hysterectomy versus total abdominal hysterectomy. Am J Obstet Gynecol 1999;180:955–62. 18. Gemignani ML, Curtin JP, Zelmanovich J, Patel DA, Venkatraman E, Barakat RR. Laparoscopic-assisted vaginal hysterectomy for endometrial cancer: clinical outcomes and hospital charges. Gynecol Oncol 1999;73:5–11. 19. Gehrig PA, Cantrell LA, Shafer A, Abaid LN, Mendivil A, Boggess JF. What is the optimal minimally invasive surgical procedure for endometrial cancer staging in the obese and morbidly obese woman? Gynecol Oncol 2008;111:41–5. 20. Ramirez PT, Adams S, Boggess JF, Burke WM, Frumovitz MM, Gardner GJ, et al. Robotic-assisted surgery in gynecologic oncology: a Society of Gynecologic Oncology consensus statement. Developed by the Society of Gynecologic Oncology’s Clinical Practice Robotics Task Force. Gynecol Oncol 2012; 124:180–4. 21. Edmondson A, Bohmer R, Pisano G. Speeding up team learning. Harvard Bus Rev 2001;79:125–32. 22. Desai PH, Tran R, Steinwagner T, Poston RS. Challenges of telerobotics in coronary bypass surgery. Expert Rev Med Devices 2010;7:165–8. 23. Kohn LT, Corrigan J, Donaldson MS. To err is human: building a safer health system. Washington (DC): National Academy Press; 2000. 24. Singer S, Lin S, Falwell A, Gaba D, Baker L. Relationship of safety climate and safety performance in hospitals. Health Serv Res 2009;44:399–421. 25. Hughes CM, Lapane KL. Nurses’ and nursing assistants’ perceptions of patient safety culture in nursing homes. Int J Qual Health Care 2006;18:281–6. 26. Seamon LG, Fowler JM, Richardson DL, Carlson MJ, Valmadre S, Phillips GS, et al. A detailed analysis of the learn-
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ing curve: robotic hysterectomy and pelvic-aortic lymphadenectomy for endometrial cancer. Gynecol Oncol 2009;114: 162–7. 27. Maguire T, Mayne CJ, Terry T, Tincello DG. Analysis of the surgical learning curve using the cumulative sum (CUSUM) method. Neurourol Urodyn 2013;32:964–7. 28. Young A, Miller JP, Azarow K. Establishing learning curves for surgical residents using Cumulative Summation (CUSUM) Analysis. Curr Surg 2005;62:330–4. 29. Wohl H. The cusum plot: its utility in the analysis of clinical data. N Engl J Med 1977;296:1044–5. 30. Earnshaw J, Lewis G. NICE Guide to the Methods of Technology Appraisal: pharmaceutical industry perspective. Pharmacoeconomics 2008;26:725–7. 31. Ceri P. What is QALY? Available at: http://www.medicine.ox. ac.uk/bandolier/painres/download/whatis/QALY.pdf. Retrieved November 4, 2013. 32. WHAT IS EQ-5D. Available at: www.euroqol.org/home.html. Retrieved March 24, 2009. 33. Fallowfield L. What is quality of life? 2nd ed. London (UK): Hayward Medical Communications; 2009. 34. Ellström M, Ferraz-Nunes J, Hahlin M, Olsson JH. A randomized trial with a cost-consequence analysis after laparoscopic and abdominal hysterectomy. Obstet Gynecol 1998;91:30–4. 35. Kornblith AB, Huang HQ, Walker JL, Spirtos NM, Rotmensch J, Cella D. Quality of life of patients with endometrial cancer undergoing laparoscopic international federation of gynecology and obstetrics staging compared with laparotomy: a Gynecologic Oncology Group study. J Clin Oncol 2009;27: 5337–42. 36. McGrath RG. Transient advantage. Harvard Bus Rev 2013;91: 62–72. 37. Bell MC, Torgerson J, Seshadri-Kreaden U, Suttle AW, Hunt S. Comparison of outcomes and cost for endometrial cancer staging via traditional laparotomy, standard laparoscopy and robotic techniques. Gynecol Oncol 2008;111:407–11.
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Milestones to Optimal Adoption of Robotic Technology in Gynecology Pranjal H. Desai,
MD,
Jeff F. Lin,
MD,
and Brian M. Slomovitz,
Minimally invasive technology, especially robotics, is gaining widespread acceptance and is becoming the standard approach for the treatment of both benign and malignant gynecologic conditions in centers across the country. However, there are challenges on a systemsbased level to the implementation of a robotic program. Prominent among the concerns is the length of the learning curve, team-building, quality of life, and financial and various organizational challenges. The purpose of this review article is to address those challenges as milestones on the progress to a successful robotics program and explore possible solutions. (Obstet Gynecol 2014;123:13–20) DOI: 10.1097/AOG.0000000000000055
T
he da Vinci robotic system received U.S. Food and Drug Administration approval for gynecologic surgery in 2005. The improved visualization and dexterity of this platform over conventional laparoscopy have allowed surgeons to perform gynecologic procedures. In 2010, 433,621 hysterectomies were performed in the United States for benign and malignant indications.1 Over the past decade, a minimally invasive surgical technique has gained widespread acceptance as a result of increased adoption of both conventional See related editorials on pages 1 and 3.
From the Department of Obstetrics and Gynecology, Morristown Medical Center and Overlook Medical Center, Atlantic Health System, and the Women’s Cancer Center, Carol G. Simon Cancer Center, Morristown, New Jersey; and the Division of Gynecologic Oncology, Department of Obstetrics, Gynecology and Reproductive Sciences, Magee-Women’s Hospital of the University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania. Corresponding author: Brian M. Slomovitz, MD, Women’s Cancer Center, Carol G. Simon Cancer Center, 100 Madison Avenue, Morristown, NJ 07962; e-mail: mailto:[email protected]. Financial Disclosure None of the authors have any conflict of interest to report. © 2013 by The American College of Obstetricians and Gynecologists. Published by Lippincott Williams & Wilkins. ISSN: 0029-7844/14
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laparoscopy as well as robotic-assisted laparoscopy. Minimally invasive hysterectomy has definitely demonstrated the advantages with reduced blood loss, length of stay, and postoperative complications compared with laparotomy. Multiple studies have demonstrated the safety of robotic-assisted laparoscopic procedures and comparable results for intraoperative and postoperative morbidities compared with laparoscopic procedures with the caveat of longer operative times and cost.2,3 For robotic-assisted laparoscopic myomectomy, Advincula and colleagues4 found better results compared with laparotomies, whereas Bedient5 found comparable results with a laparoscopic group. In a study comparing robotic-assisted laparoscopic sacrocolpopexy with laparoscopic sacrocolpopexy, Tan-Kim et al6 found that length of stay, blood loss, complication, and objective cure rates did not differ between the groups. However, operative time was longer in the robotic group as was the cost. One major drawback in these studies is that surgeons under study had more experience in traditional laparoscopic surgeries than robotic-assisted procedures. Sarlos et al3 demonstrated that despite certain shortcomings, surgeons enjoyed the better ergonomics and wider range of motion of robotic instruments. With advancement of the learning curve, operating time can be minimized, potentially decreasing the cost. Several studies have demonstrated the feasibility of using the robotic platform to perform adnexal surgery,7 endometriosis surgery,8 and tubal reanastomosis9,10; however, the differential advantage to the use of the robotic platform in these procedures has been questioned and more data on cost and long-term outcomes are needed. Minimally invasive surgery is becoming the standard approach for the treatment of patients with endometrial cancer in many centers across the country.11 It is estimated that there have been 49,560 new cases of endometrial cancer in 2013 with 8,190 attributable deaths resulting from this disease.12 Reports from the LAP2 study by the Gynecologic Oncology Group have demonstrated improved short-term outcomes and comparable cancer control outcomes.13,14 Various small-scale
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case series have documented the initial experience with and success of the robotic platform for the treatment of early cervical and ovarian cancers as well.15 Specifically, investigators have documented similar outcomes for minimally invasive radical hysterectomy compared with traditional laparotomy.16 For endometrial cancer, studies have shown that minimally invasive hysterectomy is safe and associated with shorter hospital stays, faster return to normal activity, and improved short-term quality-of-life measures compared with conventional laparoscopy and traditional laparotomy.17,18 Gehrig and colleagues19 have shown that robotic-assisted surgery offers decreased blood loss, transfusion requirements, laparotomy conversion, operative time, and hospital length of stay in obese patients compared with conventional laparoscopy. Recently, the Clinical Practice Robotics Task Force of the Society of Gynecologic Oncology has published a consensus statement stating that the use of robotic-assisted surgery in gynecology oncology offers a distinct advantage over traditional methods.20 Despite proven advantages, challenges to widespread implementation of robotics programs nationwide exist. Prominent among the concerns for the surgeon is the length and shape of the learning curve and for the health care administration are ways to optimize patient outcomes while minimizing associated costs (eg, time, training) because both the physical size and financial costs of the robotic platform pose numerous unappreciated organizational challenges (Fig. 1). The purpose of this review article is to address those challenges as milestones on the progress to a successful robotics program and explore possible solutions.
MILESTONE 1: TEAM BUILDING—THE CORNERSTONE OF A ROBOTICS PROGRAM Robotic-assisted surgery is a disruptive technology in many aspects, chief among which is a change in the operating room dynamics and chronology of events. Compared with conventional laparoscopy, where operative cadence and success is dependent mostly on the surgeon, the robotics platform, with its three components—bedside robot and instruments, tower, and surgeon console—requires a team well versed in the complexities of the system and distributes the burden of troubleshooting throughout the team. Although the operating room has always been seen by some as a highly technical, highly choreographed theatrical arena, an adoption of the robotics platform brings the team aspect and unique sequence of events to the forefront that had not been necessary previously. This aspect of the robotics program—building an efficient team—is crucial but can sometimes be neglected by the surgeon and administration, because the platform is appreciated to be at times both familiar—ie, “it is still minimally invasive surgery”—and foreign—“it is a robot and advanced technology; therefore, it must require less than conventional laparoscopy once the surgeon is up and running.” The success of a robotic program depends heavily on a surgeon and leader who recruits team members who believe themselves to be stakeholders in the program and actively promotes learning and communication. A variety of roadblocks are often in place to hinder this process. The surgeon must step into his or her role as not only the surgical leader, but also as
Final product after successfully addressing challenges
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Fig. 1. Natural course of any innovative procedure. Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
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a manager to efficiently troubleshoot and optimize the operation with the new technology. In addition, the surgeon as well as the team members, all of whom may have very carefully and efficiently practiced routines over years or decades, needs to embrace the new approach and be willing to adapt or formulate new routines. Edmonson conducted a study published in Harvard Business Review comparing 16 different institutions that adopted minimally invasive cardiac surgery and found that some organizations seem to capitalize on their experience more effectively than others.21 The investigators found that team learning did not correlate with conventional predictors such as case volume or surgical experience. Instead, staff interviews revealed that the most consistent characteristic of a successful team was a high level of motivation to learn. This motivation stemmed from leaders who were willing to admit mistakes and elicit feedback. Furthermore, members of successful teams were deliberately selected based on competence as well as personality traits correlated with openness to change.22 Contrarily, programs with prolonged learning curves tended to have leaders who, although technically superb, were less adept at creating a learning environment and managing teams or whose members were less open to adapt. The technical complexity involved in robotic high-risk gynecologic and gynecologic oncologic procedures is no less than cardiac surgery, and therefore we stress the importance of selection and team-building as an essential milestone in optimizing the adoption of robotic technology for gynecologic procedures.
MILESTONE 2: CULTURE OF SAFETY Patient safety is one of the key issues prioritized by the Institute of Medicine as critical for effective health care delivery.23 Although adoption of any change to well-established practice patterns will raise some questions about patient safety, incorporating as complex and novel a technology as the robotic platform often arouses concerns and doubts in the staff, from the preoperative nursing staff, to the anesthesia team, to the recovery room staff and beyond. Whether warranted or not, these concerns can affect morale and influence outcomes. The importance of staff attitude and morale on patient safety has been quantified by a culture of safety survey. The results of this survey reveal a strong and statistically significant relationship between staff morale and patient outcomes.24 Studies have shown that higher scores on questions about teamwork and coordination are associated with shorter total length of stay as well as morbidities and mortality after complex surgeries. A particular concern for
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incorporating innovative changes in medical practice highlighted by the study by Hughes and Lapane25 found that 40% of nursing staff in U.S. hospitals find it difficult to make changes to improve things most or all of the time. Characteristics of a strong culture of safety include: recognition of the inevitability of errors, incorporation of nonpunitive error reporting and analysis systems, commitment to transparent discussion of and open learning from errors, and proactive identification of latent threats. Similar to its counterparts in the airline and nuclear energy industries, a culture of safety in health care is likely to have a profound effect on outcomes after robotic-assisted surgical procedures, and the changes should be addressed as part and parcel of the integration of robotic technology. Regular outcomes review, multidisciplinary discussions, and ready implementation of recommendations and management strategies should be part of the development of the robotic program from its inception. Because this requires action and commitment from all levels of the health care delivery team, we identify culture of safety as milestone 2 in the building of a successful robotic program for gynecologic surgery.
MILESTONE 3: LEARNING CURVE To date, more than 1,200 robotic systems have been installed across the United States, and more than 1,500 gynecologic surgeons have been trained. The learning curve phenomenon is well recognized and, in the present health care economy, its parameters are oftentimes a critical first question in the adoption of any novel, costly technology, or both. The costs of learning is not only limited to instrumentation and operating room time, but also staffing, training as well as personal ego; the errors and mistakes are the norm before proficiency. Because of its importance in the decision-making process for surgeons and hospital administrators considering adoption of robotic technology, the learning curve, and its assessment, has been increasingly addressed in various studies.26 One should be aware, however, that the statistical approach taken in most studies of learning curve—discretizing the cases into groups such as tertiles or quartiles and applying standard statistical methods of comparison—is a suboptimal method to assess learning, because it does not assess the change on a case-to-case basis. The case-by-case change and progress in learning is an important indicator of successful team development and adoption of the technology. The use of cumulative sum failure analysis is a sensitive way to illustrate the cluster of surgical failures indicative of the early learning curve as well as postlearning curve assessment.27–29
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The cumulative sum technique recognizes the importance of time as a hidden variable in clinical studies and avoids the depreciation of statistical significance that is associated with repeated testing. Thus, cumulative sum and standard statistical methods are both recommended to provide new teams with accurate and objective feedback regarding their progress (Fig. 2). The cumulative sum curve is plotted by using the following formula: Sn5S (Xi–Xo), where Xi50 for success and 1 for an observed failure. Xo is the predicted risk of major adverse events. In the cumulative sum curve, X-axis represents number of progressive cases, and the Y-axis represents cumulative sum of failure. Figure 2A represents components of the normal cumulative sum curve of any procedure. Line trending above baseline represents the state of the learning curve or performance is worse than expected; the graph going toward baseline represents the state of the postlearning curve or performance is getting better; and the graph trending below and away from baseline represents the state of adequate experience or performance is trending toward better or equivocal to the counterparts. Figure 2A–C demonstrates cumulative sum analysis for a hypothetical procedure that has different outcomes. Figure 2B has a cumulative sum curve that goes above and away from baseline representing a unsuccessful procedure or a surgeon’s inability to surpass the learning curve. Figure 2C exhibits the cumulative sum curve of the procedure in which the surgeon was producing excellent results from the beginning and the escaped stage of the learning curve. Figure 2D demonstrates our institu-
tional cumulative sum analysis of 50 robotic cases performed by three gynecologic oncologists after having an average experience of 200 robotic procedures corresponding to area below baseline in Figure 2A and corresponds to Figure 2C. One can easily glean from the cumulative sum curve at our institution that there is not an initial learning curve, because the surgeons have already surpassed their learning curve and in the phase of adequate experience. The graphical representation yields much more information than traditional statistical methods with discretized groups. Accurate assessment of learning and continued monitoring is a critical part of learning and thus is our third milestone.
MILESTONE 4: QUALITY OF LIFE Once the hurdles of implementation and quality assurance of a new medical technology are passed, the surgeon must ask him- or herself the most important question: “Does the novel intervention improve the quantity and quality of the patient?” The most established method of assessing quality of life is expressed as quality-adjusted life-years (QALYs) based on various aspects of physical and mental health of the patients ascertained by sets of validated questionnaires, and it is a more precise and meaningful measurement derived by a formula incorporating two important variables: life expectancy and quality of life for remaining years. The QALY is defined as a “measure of a person’s length of life weighted by a valuation of their health-related quality of life” after any intervention.30,31 Utility score is given
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Fig. 2. Cumulative sum curves. Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
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based on time spent in a particular health state. So for instance, if intervention X allows someone to live for 5 more additional years, a utility score of 0.6 provides one more QALY than intervention Y that provides 5 more additional years at a utility ratio of 0.4. EQ-5D is the tool for health state evaluation objectively.31–33 Furthermore, QALYs’ another meaningful use is to calculate cost-utility ration; an economic analysis reflects effects of relative cost on the effects of interventions, which can be calculated by dividing difference between cost and QALY resulting from two different interventions in question.31 The primary reason for pursuing minimally invasive surgery from the perspective of the patient is the potential for an improvement in quality of life (QOL) during the early recovery period. Ellstrom et al34 have shown that laparoscopic hysterectomy confers a better QOL compared with abdominal hysterectomy at 1, 3, and 6 months after surgery. In the Gynecologic Oncology Group LAP2 trial,35 patients in the laparoscopy group (various assisted-laparoscopy procedures allowed) had better short-term QOL outcomes compared with the total abdominal hysterectomy group up to 6 weeks after surgery. By 6 months after surgery, both groups had similar QOL, apart from body image, in favor of the laparoscopic procedure. However, these studies lack the assessment of QALY and cost-utility ratio in the long run to be performed compared with the traditional technology to justify not only the efficacy, but also to answer the critiques of technology. Qualityadjusted life-years need to be analyzed rigorously because it may be gained but with poor QOL and vice versa. Different hypothetical models of QALY have been shown in Figure 3. However, to our knowledge, no studies have been published assessing QALY or cost-utility ratio for robotic technology pertaining to benign or malignant gynecologic conditions. Such
studies would be integral in justifying the use of any new complex technology against the well-established traditional counterpart. We believe that although the robotic platform is a disruptive technology, its incremental gains on conventional laparoscopy may be more difficult to assess directly compared with the gains conventional laparoscopy made on laparotomy; because of this, we urge the study of improvements in QOL measures, whether it be in terms of QALY or other standardized, meaningful measures, and we see this as milestone 4 in the widespread adoption and embrace of the robotic platform.
MILESTONE 5: BUSINESS PERSPECTIVE Because the financial gain during the learning curve period is inconsistent, a business model is absolutely required to institute and nurture a successful robotic program. Contrary to other business sectors in which the focus has changed from long-term business strategy to transient advantage strategy,36 the health care industry still holds onto the concept of a longterm strategy, especially because advancements in medical and surgical technology take years to become a part of standard of care. An addition of costly new technology into a hospital or surgical center’s surgical armamentarium still essentially requires the organization to progress through traditional business development phases such as launching (acquiring the robot and marketing; financial loss), ramping up (learning curve for the surgeons; financial loss), exploitation (postlearning curve phase; financial gain for institution), reconfigure (change in technology or redefine the business model resulting from loss of competitive advantage; still in financial gain), advance (introduction of new technology), or terminate (with introduction of superior technology). Administrators have to keep in mind that competitive advantage is transient, not QALY gained
QALY gained
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Fig. 3. Hypothetical models of quality-adjusted life-years (QALYs). Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
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Model for financial prediction
Early phase: 1–2 years Financial loss • Learning curve • Marketing cost
Financial gain • Improved payer mix • Increase in case turnover • Increase in case load and referrals • Market share negotiating contract • Post–learning–curve phase
Late phase: 2–5 years
Fig. 4. Financial model. Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
sustainable. Hence, business strategies need to evolve over time. Monitoring and incentivizing the ramp-up and maximizing the exploitation and reconfiguration phases are key to optimizing the financial returns from investment in new surgical technologies. Bell et al37 analyze the cost difference in performing a hysterectomy among the three modalities. They demonstrated that the total average cost for hysterectomy with staging completed by laparotomy was almost 30–40% higher than the robotic group (P,.005), whereas robotic was nearly 10% higher than the laparoscopic
group (P5nonsignificant) (for traditional laparotomy, $12,943.60; for standard laparoscopy, $7,569.80; and for robotic assistance $8,212.00). Major components for the higher cost of laparotomy were pharmacy, laboratory, hospital stay, and in turn indirect overhead cost. However, for robotics, the major component was the operating room supply.37 Our prediction is that in the learning curve phase, major cost burden would be the operating room time, initial complications, prolonged hospital stay for selected cases, conversion to open, and indirect overhead cost including part of initial acquisition cost. This would offset the cost advantage for the robotics in the learning period significantly. Based on our experience, we have predicted a business model for revenue gain in Figure 4. With the proposed financial model, the administration has to be aware of the dynamicity of the financial model that includes the initial loss during the “early phase-learning curve phase” and they have to have a strategy in place to compensate for financial loss with gain when the learning curve phase is over. In the early phase, the administration has to emphasize on low-risk case selection, which would yield a better outcome that minimizes financial loss; excellent patient satisfaction would gain further popularity of the program and strengthen staff morale, building a stronger team from the start. While moving from the early to the late phase, marketing of the program with patient outcomes should be an integral part of the program. In the late phase- post learning curve phase, the administration should be prepared to acquire advantages like optimizing the payer mix to
Leader • Only surgeon • Strong affiliation with team • Faith in procedure • Open to suggestions Leader’s attitude • Take as challenge, not as a plug in component • Praise team member for accomplishment • Accepts that mistakes are inevitable; willing to openly discuss with team Culture of safety • Successful teams built based on fearless suggestions from team members Real-time learning • Better than after action analysis • Evolution of new skills by chance
Successful robotics team
Team • High level of motivation to learn • Leader recruits team members as stakeholders • Leader actively promotes learning and communication • Open to suggestions • Stability and consistency
Surgical audit • An essential component • With use of CUSUM and statistical methods • Perform periodically
Fig. 5. Pillars of a successful robotic team. CUSUM, cumulative sum. Desai. Challenges of Adopting Robotics in Gynecology. Obstet Gynecol 2014.
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ensure continued financial success (ready to expect more private payers than government Medicare and Medicaid). Early return to work would be appreciated by private employers and, hence, the hospital should have leverage to renegotiate the contract with managed care organization and eventually increase the reimbursement. In addition, safety of the procedure needs to be analyzed by the multidisciplinary team by reviewing the results. Studies have already demonstrated the safety of the robotic procedure for endometrial cancers,13,14,17,18 which should provide the medical rationale for adoption of the platform; understanding of the natural cycle of a transparent dynamic business model of adopting an innovative technology as delineated here and capitalizing on the long tail should provide the health care economics rationale for adopting the technology and establishing a successful robotic program.
SUMMARY Despite convincing interim results, the various surgeon, team, and administrative obstacles remain in the widespread acceptance of robotic technology in gynecologic surgery. We frame these obstacles in the context of milestones to overcome and outlined ways to approach and analyze team-building, culture of safety, learning as well as outcome-driven practice and business perspective. Not overcoming these milestones in the adoption of the technology eventually results in suboptimal patient care and outcomes as well as the perception of the platform as a gimmick or sophisticated marketing tool rather than the game-changing technology that it really is. Success of the robotic team depends on a multifactorial process (Fig. 5). Once a successful team is in place, quality assurance, both in terms of surgical team learning as well as patient outcome, must be in place and frequently monitored. In the era of declining reimbursement, adoption of novel and especially million dollar technologies such as the robot is often viewed with skepticism. The authors feel that rigorous assessment of validated outcomes, in terms of QALY or other methods, should be the most important factor in the decisionmaking process and requires careful thought before recommending any technique for a patient. For the success of the program, complete understanding of the business model is extremely important for the administration. We delineated milestones based on our experience of a high-volume gynecologic oncology program; however, these basic challenges also apply very well to benign gynecologic surgery programs. With improved ergonomics and maneuvering capabilities, robotic-assisted laparoscopy has emerged
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as an answer for the challenges of complex gynecologic procedures in high-risk patients with an acceptable learning curve with a hope to deliver improved QALY and thereby achieve its place as a best practice for benign and malignant gynecologic conditions. REFERENCES 1. Wright JD, Herzog TJ, Tsui J, Ananth CV, Lewin SN, Lu YS, et al. Nationwide trends in the performance of inpatient hysterectomy in the United States. Obstet Gynecol 2013;122: 233–41. 2. Payne TN, Dauterive FR. A comparison of total laparoscopic hysterectomy to robotically assisted hysterectomy: surgical outcomes in a community practice. J Minim Invasive Gynecol 2008;15:286–91. 3. Sarlos D, Kots L, Stevanovic N, Schaer G. Robotic hysterectomy versus conventional laparoscopic hysterectomy: outcome and cost analyses of a matched case-control study. Eur J Obstet Gynecol Reprod Biol 2010;150:92–6. 4. Advincula AP, Xu X, Goudeau St, Ransom SB. Robot-assisted laparoscopic myomectomy versus abdominal myomectomy: a comparison of short-term surgical outcomes and immediate costs. J Minim Invasive Gynecol 2007;14:698–705. 5. Bedient CE, Magrina JF, Noble BN, Kho RM. Comparison of robotic and laparoscopic myomectomy. Am J Obstet Gynecol 2009;201:566.e1–5. 6. Tan-Kim J, Menefee SA, Luber KM, Nager CW, Lukacz ES. Robotic-assisted and laparoscopic sacrocolpopexy: comparing operative times, costs and outcomes. Female Pelvic Med Reconstr Surg 2011;17:44–9. 7. Magrina JF, Espada M, Munoz R, Noble BN, Kho RM. Robotic adnexectomy compared with laparoscopy for adnexal mass. Obstet Gynecol 2009;114:581–4. 8. Nezhat C, Lewis M, Kotikela S, Veeraswamy A, Saadat L, Hajhosseini B, et al. Robotic versus standard laparoscopy for the treatment of endometriosis. Fertil Steril 2010;94:2758–60. 9. Dharia Patel SP, Steinkampf MP, Whitten SJ, Malizia BA. Robotic tubal anastomosis: surgical technique and cost effectiveness. Fertil Steril 2008;90:1175–9. 10. Goldberg JM, Falcone T. Laparoscopic microsurgical tubal anastomosis with and without robotic assistance. Hum Reprod 2003;18:145–7. 11. Wright JD, Burke WM, Wilde ET, Lewin SN, Charles AS, Kim JH, et al. Comparative effectiveness of robotic versus laparoscopic hysterectomy for endometrial cancer. J Clin Oncol 2012;30:783–91. 12. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin 2013;63:11–30. 13. Walker JL, Piedmonte MR, Spirtos NM, Eisenkop SM, Schlaerth JB, Mannel RS, et al. Recurrence and survival after random assignment to laparoscopy versus laparotomy for comprehensive surgical staging of uterine cancer: Gynecologic Oncology Group LAP2 Study. J Clin Oncol 2012;30:695–700. 14. Walker JL, Piedmonte MR, Spirtos NM, Eisenkop SM, Schlaerth JB, Mannel RS, et al. Laparoscopy compared with laparotomy for comprehensive surgical staging of uterine cancer: Gynecologic Oncology Group Study LAP2. J Clin Oncol 2009;27:5331–6. 15. Reynolds RK, Burke WM, Advincula AP. Preliminary experience with robot-assisted laparoscopic staging of gynecologic malignancies. JSLS 2005;9:149–58.
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