Ep. 20: YiDing Yu, MD, Chief Medical Officer of Olive. Topic: Artificial Intelligence
Kathy: Welcome to Episode 20 of the Smarter Healthcare Podcast. Our guest is YiDing Yu, chief medical officer at Olive, a technology company that uses artificial intelligence to automate areas of healthcare. In this episode, YiDing talks to us about her history of entrepreneurism and how AI is making an impact in healthcare.
I hope you enjoy our conversation.
Kathy: Thanks, YiDing, for joining us today. Could you start by telling us a little bit about your background and how you came to your current role at Olive?
YiDing: I’d be happy to Kathy. I am Chief Medical Officer today at Olive, a healthcare AI company focused on enterprise healthcare automations and artificial intelligence deployments. My personal background is as a physician. I was trained as an internist, and I still practice today here in Boston. How I got onto the entrepreneurial/tech route, I think I was always a kid, one of those kids who loved technology, built websites when I was growing up in middle school and high school, and then I launched my first company when I was – my first investor bank company when I was in residency, so during my training, and that was a company called Twiage that accelerated communications between first responders and hospitals, so we could treat patients with heart attacks and strokes really quickly. Scaled that company, led the company as CEO, and then once I got the entrepreneurial bug, just kept on focusing on healthcare tech. Ended up joining a company called Verata Health, which was focused on using AI to solve prior authorizations in healthcare, was chief medical officer at that company, ran multiple departments, payer relationships, marketing, as well as all of our customer operations, so when we were acquired by Olive towards the end of last year, I joined the company as Chief Medical Officer, and now lead one of our core business units as well.
Kathy: And you have a long history of being involved in entrepreneurial ventures, as you just told us. What drives your desire to innovate?
YiDing: I love that question because I actually think a lot about why I do what I do and is my current day-to-day – my current responsibilities – reflective of what I want to do? Because I think making sure that your life and your career is what you want to be doing is a very active endeavor. It’s a never-ending journey. And when I was growing up, whenever I thought about what do I want to be when I grew up, I always told myself I wanted to be a doctor, because I wanted to help other people. And I still love being a doctor because of that. But I – my itch for innovation, though, is more of an impatience or a frustration with things that I think are just stupid. Because – I just don’t understand the why of why some things exist. Why does it require a fax to send records between two hospitals? Why? That just seems absolutely ridiculous in this modern age. That needs to be fixed. When I was younger I studied economics in college, even though I was a pre-med, and the reason why I loved economics was because I thought of it as a discipline that focused on – that tried to understand incentives, and human behaviors, and setting up institutions that could foster either catastrophic improvements or catastrophic harm to our society. And I always viewed that as a really powerful tool. How do we create systems, how do we incentivize people, how do we structure markets to bring out the best, to bring out the outcome that we want to see? And I find that really powerful. So I love waking up every day thinking about, wow there’s a problem I want to solve and I can solve it. So that’s how I think about innovation. I don’t think about it as cool tech or are you going to be the future Elon Musk of any industry. I think of it as “Is there a problem that you want to solve and are you passionate about solving it?” And I’m just too annoyed by what I think are inconveniences and stupid things and wasteful things and that’s why I come to work every day, it’s because I think it’s wasteful and so I’ve gotta fix it.
Kathy: That’s great. Now if we look back at the last year or so what do you think are some of the lessons learned from the pandemic regarding innovation?
YiDing: To the point I was making earlier about aligning incentives, I think one of the things I think we all saw, especially in healthcare, was how quickly a healthcare system can adapt with the right motivation. So we’ve – telehealth would be the best example of this and I’m not the first one to say it, but I launched telehealth for my health system years back. I was Chief Innovation Engineer for a $2 billion health system in Boston and that was 2015, we launched telemedicine services for our patients. And we tried to roll it out and we were trying early, and it always had some volume, but not a lot. Not a lot of patients really took it on. It was not the first thing we offered to our patients too, it was difficult to have my nurses triage a patient to telehealth, because it wasn’t our core business model. Then the pandemic hits. We couldn’t see our patients in person, and suddenly people are using FaceTime to talk with their doctors. I mean if there’s a will, there’s a way. And clearly before now the will wasn’t strong enough. I think the second thing though is not that patients weren’t interested in telehealth, but that you have to align incentives. So the moment that insurance companies said we will reimburse telehealth like a regular visit, it will be covered for all of our patients, that did it. The problem with telehealth before was sometimes it wasn’t covered, it was reimbursed at a third of what a regular office visit was, so basically, you’re saying and telling doctors, “Well, I don’t really think this is important, there’s no real incentive for you to stand up a telehealth business,” so do you think doctors were doing it? Of course, they’re not. So the moment you align incentives, people can move really quickly. And I think that’s actually a really positive thing. It just shows us that if we put money where our mouth is, we can actually really deliver some amazing outcomes, and really accelerate innovation.
Kathy: Now tell us a little bit about Olive and how you’re leveraging AI to impact different areas of healthcare.
YiDing: We are thinking about this question every day. So Olive was built as an AI platform tailor-made for healthcare. We also design and deploy AI as a service. So AI can be really daunting for many hospitals, I mean, they have IT teams, but they probably don’t have AI engineers, and probably are never going to invest in the AI engineers that Google and Microsoft and Olive all have. We have hundreds of employees, all dedicated to building AI, so we’re thinking, how can we just provide AI that’s turnkey that can deliver real outcomes for our hospitals and providers right away? And it took us many years to figure that out. That was not just something that we said, Oh this is so easy we could just do it. We as a company tried for years to understand how do you make a system that’s turnkey? But today we’ve created that platform. It’s a combination of many different types of AI, because I think AI is just a catchall term, but there’s many different flavors of it. So for example, we’re able to build what I would call simple automations. Robotic process automation bots. These automate simple activities that humans might do today. They replicate clicks, they replicate tasks, they’re not very intelligent, but they can do them, and they can do them really, really fast. On top of those we’ve created the entire system to learn from each other. So imagine that I help one hospital automate claim statusing for one of their payers. Well guess what, maybe another hospital in the same state or the state over also has to do the same activity, just with a slightly different set of payers. When Olive builds it for one hospital, when we deploy one Olive, all of our Olives learn across the entire network. And today Olive is live in 46 states at over 700 hospitals and so every single innovation benefits all of the hospitals on our network, and we think that’s really important, how we’re just delivering scale over and over. It also allows something that we call self-healing. So the machine learning of Olive, another element of AI, learns from errors that come back. For example, if you get a result and you’re erring out from one payer, instead of having a human to just manually fix it every time and having one of our engineers address it, how can the AI automatically recognize what’s going wrong, troubleshoot it, and then deploy that? So that self-healing is using that machine learning. And then we also have natural language processing technology, natural language understanding to do really complex stuff like AI clinical reviews. That’s when Olive will actually read through 13 to 18 months of clinical documents in a chart, match it to medical necessity criteria from a health insurance company, and say, this patient has met medical necessity. That’s incredibly difficult to do. It’s exactly what nurses at a health insurance company are paid to do. They sift through documents, they look for clinical content. We’re training our AI to do the same so that for a health plan or even for a provider organization, they can free up their valuable nurses for patient care and true human interventions and not use their nurse time just to scour the chart. We scour the chart for them. We present it to the clinical or support staff, and we eliminate 80% of the work. So we think of AI as a full stream of work, and it goes from automations and revenue cycle to clinical reviews, all the way to possible clinical workflows, all of which are built to help everyone in healthcare work at the top of their license.
Kathy: And I really like that point, where it’s not really about AI replacing people, but rather helping them to do – like you said – work at the top of their license, as opposed to doing some of that grunt work.
YiDing: Absolutely. 100%. There’s so much valuable work that I, as a physician, should be doing, that my nurses should be doing, and unfortunately today so much of our daily lives are for documentation, coding, recording. When you look at this every time they do a study, almost half of a clinician’s time today is in front of a computer, not with a patient. And if you think about how much you pay a physician, how much money goes into investing in the education of a clinician, only for them to sit behind a computer 40% of their day, that is really not making the most use of your most valuable asset in healthcare. And I think that’s the absolute best way of unleashing it. I don’t think of it as replacing anyone, I think about unleashing people to do what they really were trained to do and get the busy work out of that.
Kathy: Now we’ve heard a lot about the promise of AI in healthcare. And you also earlier talked about some of the challenges of AI in healthcare, like hospitals not necessarily having the staff to support it. Do you think the healthcare system is ready to fully leverage the capabilities of AI?
YiDing: I think we are. But I also think that we need to do a better job of educating, and helping the healthcare industry understand how to use AI, and actually understand what AI is. Anytime there’s a new technology, people are excited, but if you don’t quite understand it you might have too much wishful thinking, or you might actually apply it in the wrong places, and that could be just as harmful because you could have a great technology but if you don’t use it in the right areas it kind of never lived up to its potential. And then you might just think, “Ugh, what a waste of my time.” Right? So that’s a lose-lose. So I do think, though, that there are the right ways to apply AI. So part of what we do at Olive is for every single one of our partners and our customers, we do an assessment. And we do that completely for free. So we come in with our experts, we’ve done this across hundreds of hospitals, and we help identify what are fantastic candidates for automations, candidates for AI. And we’ll identify that for you. We’ll also build the business case around it. Because it’s really daunting, especially when you’re first working with AI, to say, well what type of value will this deliver for me? How should I even think about the future? What should I anticipate? You don’t want to overestimate, but you also don’t want to underestimate that as you’re investing. So we do all that work, we work with you to make sure we’re all bought in into what it will look like, so you have that full view. And then that makes it successful. Because we find that if we don’t do that, if we don’t do – we don’t help our customers identify the right candidates for automation, and if we don’t look at the business case with it, AI applications tend to fail in those areas. You kind of have to guide it to the right area. But on the flip side, I would say the positive of that, is in the beginning – we’ve been doing this for several years now – in the beginning, everything felt consultative. Everything was a learning experience, even for Olive. But today, we’ve made it like products. These are like SKUs, just like a bar code on a yogurt. If you want us to help you with prior authorizations, we’ve got an end-to-end platform that you can plug in, that we integrate with your EMR, we already have all that code built. Once you just install the software, it just starts working in the background. We do that for claims and eligibility and we’re even in different parts of the market starting to assure payments, or assure claims, so that, imagine as a provider you don’t have to worry about wondering if you’re going to get paid. And maybe the insurance company’s going to deny something. You’ll know because of Olive that we’ll guarantee their payment and we’ll just automate and make sure that all of the activities required for you to get paid, that we handle by AI. So eventually it feels more and more turnkey. And that’s what we’ve created now. And we’ve started in that fully consultative mode and now across all applications of healthcare you have more plug and play AI applications.
Kathy: Let’s look ahead five-to-ten years. What areas of healthcare do you think will have seen the greatest impact from technology investments?
YiDing: This is such an exciting question, it’s also a really hard question for me. Because to me, especially as a practicing physician, a clinician, I want that answer to be in clinical medicine. I want to see amazing breakthroughs in biotech, in therapeutics, wouldn’t it be amazing to say we’ve cured cancer. I mean that – that’s so much better than any kind of software technology because frankly that is being able to give years of life to families. So I want to say I hope that’s the case. I can’t wait for those cutting edge tech breakthroughs, and I think there’s so much just on the cusp of that. But I also think that there is massive opportunity to replace a lot of the really archaic parts of healthcare. The fact that healthcare is the only industry that still uses fax machines routinely. Like not even as a corner use case but as the standard of care use case. I mean I think just the other day I was trying to request my medical records to send to another physician. And the only way I was allowed to authorize my doctor to send my records was to fill out a form, sign it, and fax it back. They didn’t accept it by e-mail, they wouldn’t accept an electronic docusign. I had to fax a physical form. I mean I just couldn’t – or I mail it. Those were my two options. And then I’d have to wait two weeks for that transaction to happen. I mean, this is ridiculous. It’s as if the industry wants to lose money and wants to annoy patients like myself. I hope that we, especially as we do more interoperability, especially as we push secure technologies, we can’t let things like HIPPA be an excuse to not innovate. And if we remove those barriers that keep technology from really working for the patient, technology from really working for the health system, I think we could do so much. Going back to the story of how much of healthcare today is on bureaucracy, I think that we can easily unleash a trillion dollars in healthcare waste and overhead by doing that. And that’s actually one part of the mission statement of Olive is to unleash a trillion dollars of potential. Because rather than spend timing on pushing paper, you should be using that energy and effort to accelerate patient care and even lower the cost of care, right? So I think that is critical. And the areas I see the fastest movement to that, just to get really specific to your question, Kathy, is a lot of that is happening in revenue cycle. Because, I mean, it’s all paper pushing, it’s all just financial transactions, it should be all electronic, and I think there’s more and more pressure to reduce the overhead there faster than anywhere else. I’m really motivated. We’ve done some amazing work at Olive to achieve that, and I think I’m seeing great solutions across the market to make health systems more efficient.
Kathy: YiDing, I really enjoyed this conversation. Thanks for joining us today.
YiDing: Thank you so much, Kathy.
Kathy: Thank you for joining me for this episode of the Smarter Healthcare Podcast.
If you’d like to learn more about YiDing, you can follow her on Twitter @YiDingYu.
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