Artificial intelligence is still in its infancy when it comes to the orthopedic surgery space, but has already had a significant impact on all three phases of operative care, according to one surgeon.
New software and programs have helped surgeons in preoperative planning, intraoperative decision-making and postoperative patient care.
James Germano, MD, chair of orthopedics at Northwell’s Long Island Jewish Valley Stream Hospital, recently completed the first AI-assisted total hip replacement surgery in the U.S. using the ORTOMA platform.
He connected with Becker’s to share the biggest impacts of AI in orthopedics, how it might be applied to other aspects of orthopedic care in the future and other important industry trends
Note: Responses were lightly edited for clarity and length.
Question: How has AI made its mark on the orthopedic space so far?
Dr. James Germano: It’s still really early for the use of AI in what we’re doing. I think there’s a lot of programs that have already been in place, whether they’re preoperative planning, intraoperative decision making or post operative care of patients that we’re just starting to use AI to kind of help us in those areas. The big thing with AI is that it allows a lot less time to do stuff that was very time consuming by multiple people. With the constraints that we have on cost and all the other things that are going through the medical field right now, I think it’s a way to do stuff with a lot less cost and a lot more reliability. So I think that AI is making an impact kind of everywhere, but it’s still really in its infancy in how we’re using it.
Q: Out of pre-, intra- and post-op care, which area do you see AI impacting the most?
JG: I think it’s a very personal answer based on what part of the care continuum you’re part of. I would say maybe whatever my weak spot is. If I’m a young surgeon and I don’t have a lot of experience, it’s probably going to be most valuable for you when you’re in the operating room. But if I’m an older surgeon who’s really super busy, it’s probably going to be more valuable for me in the post-op period, because I’m doing so many surgeries, but I can have a lot of things addressed in a quick manner so my patients can get ease of care. You can’t really have one without the other, it’s really about the whole continuum of care for the individual patient and not just one aspect of it.
Q: Do you expect AI programs will be able to be used for other orthopedic procedures in the future?
JG: I think that you will see AI in other systems, absolutely without a question. Some of the robotic companies are using AI right now, trying to figure out how to use it and how to implement it into helping make surgical decisions. Using AI is a tricky thing because we can’t just trust it. It has to be proven by the FDA and all the other regulations that we have. But I know for a fact that within the next few years, you’ll be seeing AI in a lot more things than hip surgery. You’ll see it in knee, ankle, shoulder and spine, absolutely.
Q: What other industry trends are you keeping an eye on?
JG: I think robotics is growing exponentially in orthopedics, and we’ll start seeing a combination of robotics and AI working together. AI is really more of a thought process where robotics is more of a mechanical process that helps achieve more exact alignment. I think the combination of the two is a very good fit. I think we’re going to see more of that post-operative patient monitoring, where we’re looking at patients outcomes and how well they do and how functional they are by having trackers on them that can measure how many steps and how people walk and how their function is to really start understanding better how people do after surgery. Again, that’s where AI really does come in, because you get these huge databases of information that we can collect, and then we can do better analysis.
I think the biggest problem we have right now is that hip and knee replacement is such a successful operation for so many people that it’s very hard to determine how to make things better. When someone is 95% successful, that last 5% is really hard to determine. So how do we make up that last 5% to get to 99% and that’s really where we need these huge computing algorithms to help us differentiate. I think that is going to really take us to that next place of orthopedics.
