EDGE COMPUTING

When you or a loved one faces surgery, you naturally want to make sure that you have the most skilled surgeon. Not to mention that it is in the most up-to-date facility with the most sophisticated technology to ensure the best possible outcome. After all, the stakes can be incredibly high. So it’s disconcerting to think that, until recently, surgeons lacked decision-support resources in the OR.

While medical use of technology has evolved rapidly over the past few years, the surgical field has been a little slower to adopt these advances than some other industries. Surgeons are used to relying on the skill of their hands and the knowledge gained through experience—with good reason. But medical technology isn’t all about robot arms and AI-guided surgery; there’s a lot to be gained just by freeing healthcare data from its traditional silos and giving surgeons access to that information where and when they need it most—in the OR.

We talk more about this with Dennis Kogan, Founder and CEO of digital surgery platform provider Caresyntax, as well as the dynamic challenges of the operating room, the importance of a good partner ecosystem, and how AI-assisted surgery can improve patient outcomes (Video 1).

How are technological advancements in the OR changing healthcare expectations?

My dad is a surgeon, and years ago when I was in college, I was talking to him about how much decision support athletes get around things like performance management, situational awareness, and analytics. And he told me, “We have nothing like this in surgery. We have very interesting and important medical devices, and we’re continuously getting clinical innovation into our hands, but there isn’t really a lot of data-usage and decision-making support.”

And up until a few years ago that hadn’t changed much. There was a ton of innovation around medical devices, but at the end of the day that was still helping only how surgeons operated with their hands. The advancements that we see now enable surgical teams to have better decision-support mechanisms as well.

I think there is more and more expectation that surgeons cannot just be thinking about the risks of the procedure by themselves. And they do want support; they do want additional information to stratify risks more. And doing it all in their heads is probably no longer acceptable anymore.

What are some of the challenges integrating new technologies into the OR ?

Relative to other types of therapies, patients are probably less aware of what’s happening in the OR. Naturally—they’re under anesthesia. What they want is to understand how likely they are to have a good outcome. And I think they would probably be surprised that not as much integrated decision-making support is available to their surgical teams as they would expect.

The challenge to innovating the surgical field with technology is that surgery is a real-time intervention, and you have to integrate the AI and the software so that it runs in that setting. There should be almost no lag time in the OR. And that by itself is a higher hurdle than for a lot of other information technology used in healthcare. Of course, there is also a pretty high threshold for quality and operational effectiveness.

The surgical environment is also extremely dynamic. So how does a surgeon adapt to a changing clinical picture during the procedure? And it’s not only quantifiable activities and techniques; there’s also communication and teamwork. Surgery is actually a team sport. Part of the outcome depends on how well a surgeon does a certain maneuver, but another part of it is how well they communicate with the nursing staff and anesthesiologist. It’s so complex that it’s almost impossible to foresee how it could be replaced by artificial intelligence in the foreseeable future.

But AI does have a lot to give in terms of bringing the right information and options to the fingertips of physicians, just because of that dynamism. In one day a surgical team may be operating on very different types of patients: a healthy 25-year-old female and then a very sick 85-year-old male. The team has to be able to adjust a lot of inputs and make a lot of decisions.

That cognitive overload can cause suboptimal decisions or mistakes. Probably one out of seven cases has some sort of significant complication—over 15%. And so what we’re talking about here is proactive risk management through situational awareness—through automation. It’s about reducing and removing unwarranted variability driven by cognitive overload and a changing clinical picture. The best use cases we see right now for AI are in showcasing specific information about a given patient and a given procedure to be able to guide the entire pathway for that procedure and have the outcome be better than it would have been without that support.

“The challenge to innovating the surgical field with #technology is that surgery is a real-time intervention, and you have to integrate the #AI and the #software so that it runs in that setting” – Dennis Kogan, @caresyntax via @insightdottech

What is the benefit of combining AI with patient data?

First and foremost, truly integrated surgical-decision support touches on all points of the peri-operative cycle. Because everything that happens before and after a surgery is also extremely important, the best-integrated platforms allow for connectivity between the operating room and the pre- and postoperative spaces, times, and activities.

There are decisions made right before the patient enters the operating room—preparing the right tools, the right medications, having the right people at the table. It also includes the electronic medical record, because that has a trove of data about the patient and his or her predispositions. Then there’s the situation inside the OR, where medical devices and video cameras can be connected. And then afterward: knowing what level of risk that patient is exiting the OR with may change the protocol of how they are going to be taken care of. Maybe they can go home; maybe they need to be in the ICU; maybe they need an extra dose of antibiotics.

So to get the best, smartest insights you have to have a full peri-operative clinical and operational record, but the crown jewel is the intra-operative space—because that of course is the most mission-critical piece, where things can really go wrong. And because of that, and because the OR is real time, it requires an additional level of sophistication. And it’s not, in technical terms, a cloud-friendly territory. It’s all on the edge, because you cannot rely on two-second upload and download from a cloud. So edge computing and the Internet of Things technology toolkit are extremely important here.

At the same time, this technology solution has to be very robust and attractive from the perspective of deployment and cost. Because at the end of the day, anything that is overly expensive or unwieldy—another huge machine being rolled into an already very packed operating room—is just not going to work.

It took us at Caresyntax—with the help of a few technology partners—years to develop this platform in a way that achieves all these parameters. But I do know that it’s possible. Things are still sort of at the beginning, but I think the next decade will probably see every OR being equipped with these kinds of systems. And in 10 years physicians will be wondering how they were working without it.

How can hospitals future-proof this kind of investment?

Every industry goes through a cycle of having a few vendors create kind of a walled garden at first, and then gradually users expect more and more flexibility to add value and to add new applications. I think surgery and healthcare will need to undergo the same change.

The medical-device world has a lot of proprietary intellectual property, for some good reasons. Historically that’s been a dominant mindset for physicians, too—thinking of the operating room through the prism of a device and a vendor, to a certain degree. So the first investment that needs to be made is in reinventing and recalibrating that mindset. The operating room should be seen not as an extension of a leading device platform but as belonging to that horizontal process of achieving the best outcome.

Do you have any use cases or customer examples you can share?

So we’ve been able to show that using these advanced platforms in the OR can lift performance level, and not only for surgeons but also for other physicians and clinical collaborators as well. For example, nurses. After the pandemic a lot of folks entered the nursing workforce without maybe as much training as they would have had before. And then there’s a lot of surgical volume right now because so many surgeries were bumped. So there are a lot of newer nurses who need to come up to speed very quickly. We’re increasingly deploying something like an interactive, step-by-step navigation guide in the OR. Getting step-by-step support in the right moment of the procedure can be extremely helpful to someone who may still be lacking confidence or experience in that setting.

How does Caresyntax work with partners to bring these platforms into ORs?

Being surgery specialists, we have a very good view of what the end applications and use cases should be, but we don’t have as much experience building the infrastructure. We don’t have the benchmarks and comparables from other use cases that may be similar in terms of the rigor and the actual architecture. And an integrated smart-surgery platform that is plug-and-play, that is very smart but not very heavy in terms of hardware content, something that is able to generate information but also has the capability and bandwidth to receive algorithm and produce AI and showcase it in real time—that’s a pretty sophisticated set of requirements.

Intel has been one of the partners that has really plugged in with us, almost inside our team, to make this happen. Designing the architecture, finding the right components, utilizing some of their components—such as OpenVINO^™ that allows for this AI penetration and usage—all of these things are very important. Without a partner like Intel we would have been, at the very least, much slower, looking for every piece ourselves and probably making more mistakes.

Alongside Intel, of course, we also work with cloud-solution providers—AWS and Google Cloud. Because there has to be an edge-to-cloud transition. As I mentioned before, it’s a preoperative, intra-operative, and postoperative space, so you have to continuously go to the edge and back to the cloud and make the information interchangeable. And actually they all collaborate in between themselves—Intel and Google, Intel and AWS—which has been very rewarding as well.

Of course, the pandemic was an impediment to innovation, but that has subsided lately. I think everybody’s really looking at surgery and saying, “It’s not as safe as flying; it’s not as safe as even some other medical procedures. It’s time to improve it.” And it takes an ecosystem of players to achieve that.

What’s your most important takeaway about the use of AI in surgery?

I very often see that folks think of surgery as something that’s been figured out, something that’s reached maturity and doesn’t require innovation. It doesn’t give me any pleasure to say that this is not the case. But there is the opportunity to get surgery to the same place as, say, aviation. I don’t think you and I would accept getting on a plane with a 15% chance of something going wrong in that flight.

It’s a huge problem that has not only clinical implications but cost implications. Next to pharmaceutical therapies, surgical therapies are the second-most-used way of correcting a disease. It’s probably 20%, 30% of all of healthcare spend in the US.

So if we’re going into a surgery, I think we should have the feeling that everything is going to be okay. And that should be backed by real statistics. We really can make surgery safer and smarter. It will have broad impact on patient health for millions of people, and a broad impact on cost as well. There’s ample room for improvement as long as the mindset for innovation is there.

Related Content

To learn more about AI-assisted surgical technology, listen to Staffing AI in the OR: With Caresyntax and follow Caresyntax at @caresyntax and on LinkedIn.
 

This article was edited by Erin Noble, copy editor.