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Finally, given the initial investment necessary to acquire robotic consoles, instruments, and continued
system maintenance, there must be support from the hospital administration [30-32] . Early on, surgeons will
take longer to perform operations, which may result in a decrease in their overall productivity. Studies have
attempted to define the cost-to-benefit ratio of robotic surgery, but there is significant heterogeneity in these
cost calculations. These studies demonstrate that while robotics resulted in higher peri-operative expenses
(e.g., longer operative times) and had a reduced reimbursement profile, the favorable clinical outcomes (e.g.,
shorter length of stay, decreased 90-day mortality, lower EBL, and quicker return to daily activities) may
ultimately result in a savings benefit [33-35] . Furthermore, advertisement of the robotic program could
potentially increase overall surgical volume in the long term, thereby providing an additional revenue
[36]
stream for the hospital . While not all of these patients will be candidates for robotic surgery, many will
continue their care at the hospital.

PATIENT SELECTION
The third pillar of building a robotic program is patient selection. Prior to starting a robotic liver program,
the hospital should already be a high-volume hepatopancreatobiliary center with an experienced
multidisciplinary tumor board. This will aid in appropriately selecting patients for early cases based on
anatomy and tumor location. Additionally, the clinical staff will be accustomed to caring for these patients
in pre- and post-operative settings and familiar with what is needed to quickly convert to an open case in an
emergency. Scoring systems, such as the IWATE criteria, can be used as a tool to guide surgeons on
[37]
operative difficulty and patient selection early in the learning curve . Difficult cases with aberrant
anatomy, suspected vascular involvement, or that require hilar dissection should be avoided in the
beginning. Furthermore, certain patient characteristics, such as a history of multiple abdominal surgeries,
severe co-morbidities, or very low or high body mass index (due to the difficulty in obtaining enough
working space or having adequate exposure) should be taken into account. Finally, a time limit should be
set for how long the surgical team can continue before deciding to convert to an open operation. This time
limit should be set for different components of the operation, ensuring forward progress is made without
subjecting the patient to additional risk from extended anesthesia time, and a well-experienced open liver
surgeon should be present to guide the timing of conversion to an open procedure. Quality assessment
measures, including complication rate, readmission rate, EBL, operative time, conversion rate, and early
mortality, should be performed at regular intervals. Case review of each component of patient care,
including the pre-operative, operative, and post-operative setting should be performed to identify areas of
improvement. As the surgeons and clinical team become comfortable and demonstrate competency without
compromising patient safety, then case difficulty can gradually increase.

CONCLUSION
The robotic platform is safe and versatile with many technical advantages for complex operations. As
more hospitals adopt robotic technology, it is critical that patient safety and quality measures are upheld.
This is especially true for liver operations that already carry an elevated morbidity and mortality risk. To
successfully establish and maintain a robotic liver program, it is imperative to have the support of the
hospital administration and multidisciplinary team. This is accomplished through a combination of
experienced hepatopancreatobiliary surgeons, recruited surgeons with robotic experience, and a clinical
team dedicated to completing a standardized curriculum that includes competency assessments. Patient
safety and quality measures should be evaluated at regular intervals. Finally, patients with ideal anatomy,
tumor characteristics, and clinical components (e.g., body mass index, no history of previous surgery)
should be selected for early cases. The difficulty level can gradually increase as surgeons overcome the
learning curve and demonstrate proficiency. When employed by a dedicated team with strong mentorship,
these strategies are proven to help overcome the obstacles of building a successful robotic liver program
[Table 1].