Tiger Buford and Mark Maloney discuss AI adoption in healthcare, where data sharing remains the biggest barrier. They cover practical near-term uses like automating documentation and EMR tasks, plus recent industry moves including Medtronic's Nanovis acquisition and developments at Bone Factory and Bonebridge.
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Foreign.
So this is an open, this is Bone Chat 63. It's open discussion time. Yeah, we had. And anybody can bring up anything they want to talk about. I'll throw out a few topics. You know, Medtronic bought Nanovis, nano titanium technology. That's kind of interesting. Then Mark Maloney did his AI webinar yesterday. I'd love to hear about that. I can talk about the Bone Factory. I've got a group of people where we're helping surgeons take ideas and turn them into products kind of fast and cheap. And it's kind of interesting. We've got four things going on right now. I don't know. Jesse can talk, tell us about Bonebridge. But where does everybody want to go?
I'll tell you, I'll tell you about the webinar when you're ready. Go ahead.
Yeah, let's just, let's kick off with that. Unfortunately, I got double booked and I missed it. But it looked like you had a great turnout.
We had a good turnout and major kudos. Mark, great conversation. Oh, thanks. Sit in on some of his really impressive folks you have on there. So I know I was, I was, I was pretty humbled. Some of my guests are pretty bright people. And so the panel was Ron Navarro from Kaiser Permanente. He's chief of the Central Region. He's a pretty practical guy. President of Hispanic American Orthopedic Surgeon Group and pretty, you know, he's very active in the academy too and always interested in new stuff, new technology. I think he's mostly sports, probably does some total joints. Kishore Tempernini from Arizona, another orthopedic surgeon. It was kind of, it was orthocentric. He also is CEO of Tempeda. Kishore wrote the software that we use to build E Trauma, the original digital imaging company we sold to Stryker. So he's been like a coder guy. In fact, he wanted to go to computer science school at UC Berkeley, but his father wouldn't let him because a good Indian goes to medical school and he made him go to medical school. So Kashore did like a six year md, you know, undergrad program and he kept on coding and he's doesn't, he's written a lot of apps through the years. And so his program, tempeda, is an AI enabled templating system which literally increases revenue by 40% over the last two years. He didn't really get too much and I told him to go light on that, you know, not brag too much, but that's how much time he Saves and then the. Let's see, we had Roy Buarno, who is the CEO of Scale Healthcare. He's a very bright guy, very extensive network, super connected. Former investment banker. Roy's grandparents were one of the. On were signed the original document of independence of the state of Israel. So he's pretty, pretty interesting background in that regard. Nassim Aryanpu is a PhD in Computer Science machine learning. She's out of Vancouver, Canada. So she was on there. Julia Komisarchak, whose specialty is also machine learning. And she does. Her focus is de identification of data and she's all about building data lakes, data sharing, data access. You know, it's like Robin Young said at a dinner I hosted about three or four years ago, he said if you want to make a lot of money in orthopedics, he said make a lot of money in data. I mean that's kind of what he, you know, he was kind of exaggerating, but he was pretty much a prep. He was pretty prescient on that. And then third doctor was kind of like Dr. Everyman and that's why he was there. He's a regular good guy in here in Atlanta and very normal. He's trying to use AI. He's struggling with it. And he was on, he was there as sort of the representative of the people, so to speak. And let's see. And then we had Drew DeAngelos because he publishes orthopedics this week and he's got a big network now. What came out of it was the, the biggest challenge that they, everybody agreed that they saw is data sharing. Data access, where do you get. It is greatly limited. Most medical data just comes out of two or three big cities, big universities like Boston and New York. And it's. There's not as much there as you think there is and there's not any more to be had unless people share data. And they're. There's varying degrees of pessimism and optimism on that. It was generally agreed that the easiest and most practical way for physicians to use AI in 2025 is to save time on documentation. You know, EMRs that they love to hate, okay, they just spend so much time either during the day or at the end of the day on their, you know, EMR documentation. And AI can greatly relieve that. So that was generally agreed as the number one. The number two was using AI for marketing and like, you know, everyday receptionist duties, things like that in your practice. And it's already out there. I took my wife on Tuesday to the urgent care for bad cold, sinus infection, and it was part of Emory University's urgent care center, where I live. I called up aft. I called up to make the appointment. And to my great surprise, because I didn't realize it was this prevalent already, I wound up talking to an AI she was very nice. She made the appointment. You know, I felt like saying, so, what'd you have for lunch?
But yeah, yeah.
So, yeah, what are you doing after work? But anyway. And the week before, I had had coffee with the VP Senior vice president of supply and logistics at Piedmont Healthcare, which is the biggest hospital system here in Georgia. And to my surprise, they just signed a contract with an AI Company to do, you know, receptionist, clerical, that kind of stuff. Because as we all know, in every company, personnel is your highest.
