← Becker’s Healthcare Podcast
Loading summary
Transcript13 lines
- [00:01]
A
Philips is a health tech leader focused on innovation that improves the health and well being of people. Our healthcare technology and informatics solutions help care teams diagnose, treat and manage more patients with greater precision, speed and confidence. Across the care journey with Philips, clinicians are empowered with streamlined insights in the moments that matter for every patient. Better care for more people Philips.
- [00:29]
B
This is Grace Lynn Keller with the Beckers Healthcare Podcast and we are recording live at the 10th annual Health IT Digital Health and RCM meeting. I'm currently joined by Yasser Tarabishi who is the Chaio and CMIO of Ovations with Metro Health. So Yasser, thanks for being here. Would love to have you start by telling us a little bit more about yourself and your work in healthcare.
- [00:50]
C
Sure. So I would identify myself as a physician informaticist first and foremost. So I'm a pulmonary and critical care doc who still practices. I've had progressive roles in the informatics space over the last decade or so and at this point in time in my life I am Chief Health AI Officer at Metro Health. So thinking about how to strategically steward all of these new health innovations into the healthcare space, both responsibly and with good ROI and outcome monitoring. And I'm also CMIO of a virtual care startup called Ovation, which is actually a shared platform that we're developing with leaders at MUSC Health. And so it's a virtual care platform that serves patients in different states in an integrated fashion where you're seen online and you can get follow up care and downstream opportunities at the brick and mortar facilities that we integrate with. So it's integrated virtual first care as opposed to point solutions, keeping patients in your system rather than losing them.
- [01:51]
B
And let's start our conversation today talking about AI, because nearly half of medical practices reported using AI in some capacity in the last year and it remains a key topic for health IT leaders. So from your perspective, what are the use cases that are making a difference right now and how are you leveraging them in your organization?
- [02:10]
C
Yeah, so we've been doing predictive AI for several years now when we've had a lot of use cases that we've published. We've spoken about a lot of energy around sepsis being a good one as a, as a frame of reference for the work that we've done. So from the predictive perspective we obsess about, are the models accurate, fair, and more importantly as a safety net system, Metro Health is worried about equitable implementations and outcomes. So can you use a reasonable AI model in a way that Actually enhances care for all and in a way that does not exacerbate disparities that we see and deal with on a regular basis amongst our patient population or within our patient population. And so we've had a decent track record of getting those innovations and solutions out, implementing them in a safe and responsible and reliable way. And they do drive several aspects of our business. Obviously with generative AI there's been a big, there's been an increase, I should say in opportunity and also along with that risk, risk for safety, reliability and risk as it pertains to spending money in the wrong, wrong place. So lot of potential sunken costs there as well. The way we've approached the this, the second part of the AI coin here, the generative AI solutions, we are focused on enterprise wide solutions, a rising tide that can lift many boats. Rather than point solutions, we focus on integrated solutions with a clear value proposition that touches multiple aspects of our business. Clinical care efficiency, clinical outcomes and even yes, ROI in terms of revenue, either generation or recovery. And I can talk about a few of those. So obviously we, several other health care systems are moving forward in a big way with ambient AI. We are optimistic about where this is going in terms of relieving the burden on our clinicians and providers at the point of care, improving documentation and even potentially revenue as a result of that. And the other aspect is we're optimistic that with computer vision and other ambient technologies, that input aspect of care is going to become easier, the bar becomes lower, we have richer, more accurate information entering our electronic health records and as a result better detail on our patients, how we're doing. Ideally also in the future, some guardrails around clinical decision support that know in an ideal universe happens in near real time. So optimistic about that strategy, optimistic about that technology. We're also using generative AI to summarize and retrieve information from our clinical documentation, so getting clinicians up to speed in a quick fashion. With medicine today, there's a lot of shift work. So providers, nurses are coming in and out of care, cycling through on a regular basis, having to understand their patients quickly. So we're using this technology to surface pertinent information at the point of care in real time. We're using the technology to help us draft progress notes and discharge summaries to again reduce the burden on our providers. Also with the potential prospect of improving documentation to the point of, you know, accurately reflecting our case mix index and billing more appropriately, concordant with the actual complexity that we see within our healthcare system. And that is a solution that's again enterprise wide, starting inpatient, moving to ambulatory, ultimately with a very solid vendor partner who's been really focused on the seamlessness of the integration. And so those are, I would say, the two big spaces that we've moved into. We work with other vendors, with several other AI solutions, including things like computer vision. And so there's other solutions that we're evaluating in real time. And what we're trying to build are really responsible, reliable partnerships with companies that are forward thinking, that are open to feedback and co development and opportunity, and even potentially partnering.
- [06:14]
B
And as virtual care expands from AI enabled tools and remote monitoring to broader digital health platforms, introducing these new technologies can bring challenges. So what advice do you have for leaders navigating everything from governance to patient engagement? And can you share an example of how your organization has balanced innovation with operational constraints?
- [06:35]
C
So one of my biggest pet peeves in the AI space is companies that lead with AI. So the value proposition becomes AI for the sake of AI. We are problem oriented solutions based on the problem cart, not before the horse, right? So don't tell me why I need an AI solution, tell me about the problem you're trying to solve and why AI is the answer to that problem. And so if you think about how that percolates up through the system, then you have to make sure that you know what the problems you're trying to solve are. I do not need to be sold on solutions for problems that I don't know that I had right, or people telling me that there's magically some revenue generation or money under the couch cushions that I didn't quite know about. I mean, we're obviously always looking to optimize our systems and our operations, but we know ourselves enough to know what are we trying to do strategically. So as that percolates up to the system, strategically aligns. Solutioning is exactly what we're working on. And AI is not always the answer. And actually as chief Health AI officer, more often than not I'm telling people why AI is not where you should be looking. But unfortunately, when vendors lead with AI, less informed operational leaders or clinicians will think that there is some kind of magic instilled and that it's going to be an ideal or perfect solution, or that it's an independent autonomous system, or that I'm going to be able to reduce my need on certain FTEs in the organization and unlock a whole bunch of revenue. And none of that has panned out. And so at the end of the day, I think the answer to the question is start with your strategic strategies, your operational priorities. Always start with a vendor partner, I should say core vendor partner approach first. More often than not they may already be working on something that you're trying to solve. And then make sure that you have a clear eyed view of the actual roi. So give you an example. The ambient solutions, I don't know that they're going to give us more revenue, direct hard dollars, but I do know that there's a chance that our providers are going to be able to get home on time. They're going to actually enjoy working for our organ even more than they did before and we're more likely to, less likely, I should say, to lose them to another organization that has an ambient AI solution. So the ROI is not always measurable and hard dollars, I like to know that the outcomes are not just related to finances. There's operational efficiency, there's clinical safety reliability and then obviously hard, hard dollars. And you don't have to feed all of those streams to make a case for your solution. But, but you have to hit as many, as many of those boxes as you can for it to be viable and more importantly for it to be sustainable.
- [09:29]
B
And how are you seeing recent legislation, both state and federal, affect health care organizations and healthcare IT specifically. And have you adjusted any strategy in response?
- [09:38]
C
Yeah, so we're obviously really tightly integrated in terms of strategy with our compliance and risk groups. And so we're monitoring that landscape actively. There will be an ebb and flow of regulation and deregulation depending on the political winds and the climate. But as a safety net system, we are responsible for our own fate. We are responsible for how we are perceived by our patients in our community and we take that responsibility seriously. And so what I mean to say there is we're not waiting to be told how to be safe and responsible when it comes to implementing these new technologies. We prefer to think of ourselves as leaders in that space. And so really watching it, really trying to make sure we're ahead of the game there and we're not waiting for AI assurance labs to come and go. We believe that the implementation of reliable AI solutions within our system requires our own due diligence and requires internal validation to make sure that it works for us in our setting and our patients. And we're not going to be told externally that, you know, solution A versus solution B may be better because of some analysis run at a completely different health care system or by some AI assurance group that may have different interests in mind.
- [10:57]
B
And final question, as we wrap our conversation up. What is your top piece of advice for health care leaders as they prepare for further advancements in technology and rising demands for care?
- [11:08]
C
Go back to your strategy. Go back to your operational needs. Focus on the problems you're trying to solve. AI is not always the answer, nor should it be. And I think if you really think about a solution, a problem solutioning approach or problems based approach, you're more likely to come out with a successful outcome. And so I think go back to your basics.
- [11:33]
B
Awesome. Well, Yasser, thanks so much for joining me today on the Becker's Healthcare Podcast and sharing your thoughts and insights on these topics. Again, we are recording live at the 10th annual Health IT Digital Health and Art RCM meeting.
- [11:45]
C
Thank you so much for having me.