Robotics has started boosting surgery in ways not dreamed about not so long ago. Robotic-assisted surgical systems have claimed a space in healthcare and are evolving before surgeons’ very eyes.
Brian Miller is chief digital officer at Intuitive, a medical technology company known for its da Vinci robotic-assisted surgical systems. He is one of the leading experts in the field.
Healthcare IT News sat down with Miller to discuss the genesis of the robotic surgery industry and how new technology combined with AI will transform what’s possible in healthcare.
Q. You started your career in robotics developing software for robotic surgical systems such as AESOP and ZEUS. What were the early capabilities of these systems?
A. We always knew we were onto something in those early days – but it is humbling to see how far the robotic surgical field has grown. With AESOP and its successor, ZEUS, our goal was to help enhance the ability of laparoscopic surgeons, who spent long days standing next to – and over – patients, and had to hold the endoscope and multiple instruments for very long stretches of time.
AESOP essentially was a voice-activated robotic arm that held an endoscope – a job usually performed by a surgical intern. This was the first FDA-cleared scope holder, in 1994 – and was the technology foundation used to develop ZEUS.
ZEUS added two robotic arms that held surgical instruments so surgeons could manipulate remotely to perform certain tasks.
AESOP provided the surgeon with a steady camera view throughout the entire procedure and allowed the surgeon to directly control the field of view by issuing voice commands. In helping develop robotic surgical technology, I’ve had the privilege of watching thousands of surgical procedures over the years. I’m often struck by the fact that our aim then – to enhance a surgeon’s ability to deliver the best minimally invasive care – continues to guide our development today.
We continue to refine the systems, services and software that surround and support surgeons and their teams, and it grew from that first automated endoscope assistant.
Q. What are the benefits of robotic-assisted surgeries?
A. Much of the benefit that robotics brings to a surgeon is about vision, precision and control: It enables a three-dimensional view of the procedure, the ability to use fluorescence technologies to see the surgical field in much greater detail, and the very sensitive control of instruments to operate in tight spaces that traditional surgical instruments might not.
We’re in the business of making it easier for surgeons to be their very best. The ergonomic benefit of having them operate sitting down looking through an immersive console, versus standing for hours next to a table, is part of the appeal of robotics-assisted procedures, and it’s another reason I think we’re seeing such strong interest in robotics from new surgeons.
If you look at the vast universe of quality clinical research – more than 24,000 peer-reviewed publications – the preponderance of those data points, depending on the procedure, toward better outcomes such as less blood loss, fewer complications, fewer conversions to open surgeries, shorter average hospital stays and post-operative recovery metrics.
We’re seeing measurable improvements for many patients, for surgeons, for the hospitals investing in this technology and for payers that are covering procedure costs – it’s a virtuous cycle.
When I think about the ongoing research and development that continues to inform how we innovate robotic surgical platforms – ways to improve vision, enhanced ways to identify tissue, getting more of the right information to surgeons at the right time – the benefits of robotic surgery will continue to build.
Q. You’ve said there is a significant data opportunity from robotic surgical systems, like da Vinci. What can this data tell surgeons, hospital leaders and patients?
A. A single procedure generates a rich set of data for surgeons and their institutions – such as how a surgeon changes the positions of instruments during the procedures to the surgical images themselves, which can tell us a lot.
As we develop machine learning algorithms and apply them to tens of thousands of these procedures, you end up with insights that physicians can use to improve efficiency and potentially outcomes. We are deeply motivated to find these insights to support even better outcomes for patients, physicians, care teams and hospitals.
Surgeon training is one area that we’re likely to see enhanced by this kind of data analysis, where we can benchmark performance and come back to customers with very specific insights into how surgeons are working through each procedure.
In the future, systems will likely map every movement of the arms during a procedure and compare that to the movements of the most efficient procedures in its database. What a surgeon will ultimately receive is a customized training suggestion that points toward how they used a certain instrument or how they approached sealing a blood vessel, and that training will sharpen their skills over time.
For hospitals, the data already is revealing the strengths and opportunities of their respective robotic-assisted practices because they can compare it to non-robotic options and see the value. Even the operating room choreography can get mapped and optimized with data analysis, and that could lead toward smoother and more efficient procedures.
Q. What’s to come through the marriage of robotic surgery and AI?
A. It’s one thing to understand which sets of procedure data are relevant; it’s another to take what’s meaningful and build predictive tools that are truly useful in the OR and help support better patient care.
The impactful application here is aimed at building tools that surround the surgeon with information that gives them real-time feedback to support their surgery, their teams and their patients.
AI and machine learning will drive real-time insights based on video analysis technologies. For example, the system sees how a surgeon sutures two vessels together, makes an assessment of how well it is sealed and could advise the surgeon of the probability of an anastomotic leak by comparing what it saw in thousands of other similar procedures. That kind of real-time guidance could help with clinical decision making that could translate into better outcomes.
When I think about how AI will help surgeons in the near term, it won’t displace their clinical decision making, but instead make it sharper and better informed. There are moments in procedures where choices need to be made quickly, and that’s the frontier where the most interesting AI pieces are seeing development. In many areas we’re just getting started, but the potential is very real.
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