Lumeon CEO and Founder Robbie Hughes sat down with Karen Jagoda of The Empowered Patient podcast show to discuss Lumeon’s Care Orchestration and the technology driving health systems forward. Listen to learn more about how Lumeon systematic approach is being used by leading hospitals to be more efficient and effective in their day-to-day tasks.
Karen Jagoda 0:09
Welcome to the Empowered Patient Podcast.com show. I’m Karen Chegada. And my guest today is Robbie Hughes. He is the founder and CEO of Lumeon. That’s lumeon.com. And Robbie, I want to welcome you to the show today. I appreciate you taking a few minutes to be with us
Robbie Hughes 0:27
It’s a pleasure to be here. Thank you for having me.
Karen Jagoda 0:28
Thank you. Let’s start with a bit of a description of the business model at Lumeon.
Robbie Hughes 0:33
We’re a SaaS platform, we sell software to medical professionals, principally healthcare providers that are interested in bearing risk and trend interested in transforming the account operations. What the solution does is it it really helps providers coordinate care at a fundamentally different level. The problem really is we see it as the care that’s better coordinated, is cares better delivered, but care coordination is hard. In fact, some people would say it’s broken. And the challenges that particularly in times, sort of post COVID are in fact, any environment where you care about the consumer experience, you really need to focus on the proper proactive coordination of care. And to do that is expensive, difficult, often unreliable. And so we decided that there was a need for a solution that would proactively coordinate care algorithmically, and so do so at very low cost. And thus, you can use that system to coordinate care everywhere. And what we see now from our providers, and our partners is that they use it to coordinate everything from electro surgery to discharge planning to hospital at home and everything in between.
Karen Jagoda 1:49
So tell us a little bit more about your platform, and what you’re sort of hinting at there. What’s included in this whole world of care orchestration?
Robbie Hughes 1:59
So I think the final kind of step into the problem was solving traditionally, what we’re really doing is combining two or three different categories that have previously been separated. So if you imagine care delivery as a funnel, at the top of the funnel was this idea of cohort selection. So which patients should I be focused on? Then in the middle of the funnel was What should I do for which patient? So what are the tasks activities, undertakings that need to happen? And then finally, the bottom of the funnel is how do I ensure reliably and at scale that the right things, those things I’ve already determined are the right things that happen every single time. And clearly, this is all personalized to the individual patient. Now, each one of those tasks were tasks that were already happening at the top of the funnel, this is kind of a pop health and analytics problem at the middle of the funnel is CDs problems. In other words, how do I get providers to make the right decisions, and at the bottom of the funnel, making sure that things happen? Well, that’s, you know, that’s something that happens around automation, typically rpa, but each one of them is necessary, but none of them sufficient. So if I focus on the bottom of the funnel, that RPA piece, well, it’s all very well to automate the same thing over and over again. But that’s not how care delivery works, you need to personalize it patient, equally, providing CDs and physicians is fantastic. So they can they can benefit from all the advice and evidence around the world. But how do I do that for the entire care team and then guiding, guiding the care team to the right patient, and using analytics to do that is fantastic. But if it’s based on yesterday’s data, then you know, it’s not enough, I need to do all of this in real time. So what we’re doing is we’re combining all of these things together into a single solution. And it really allows us to do something transformative in terms of the personalization, scaling of care. And it’s tasking the care team specifically with activities. And it’s automating those, and that’s engaging the patient and making them an equal participant in their care. What’s critical is that this isn’t just patient engagement, we’re not just sending notifications out to the patient saying do this or that. It’s actually using the patient engagement loop as a as a way of understanding what’s working and what’s not, and then guiding the care team appropriately.
Karen Jagoda 1:41
We talk a lot on the show about data interoperability. And I’m hearing you say that’s part of your solution, but it’s not the whole of the solution. So tell us the difference between orchestration and interoperability.
Robbie Hughes 4:30
So interoperability is is a necessary condition for doing what we do. As you probably inferred, what we’re doing is taking data in real time from multiple different places, synthesizing that into a sort of synthetic record and then using that to drive engagement tasking, decisioning, etc. So interoperability the ability to take data in clean, normalized form from multiple places, is an absolute key and to be candid, what we’re doing today could not have been done. Biotech years ago without some of the the interoperability movements that are, that have happened and the foundational sort of system of record that exists underneath. But orchestration, at least as we see it is this idea of taking that data and using it to drive action across multiple components of the system. So you know, simply put, taking data, you’re synthesizing it and making decisions and rules about what to do. And then you’re delegating that and coordinating it out across various different actors, and then measuring the output and and starting again, and that kind of endless cycle that I’ve just described, is really the core of all humans doing.
Karen Jagoda 5:37
And would you say that this is really empowering the providers to provide better care? Or is it really just a function of how many patients they can handle during a day or during a month?
Robbie Hughes 5:53
Well, I would say, I mean, it’s both you, I think the problem that we’re solving exists, because in the old days, when you had, you know, a generally qualified PCP or a physician looking after a small number of patients, and, and they were, they had a broad set of broad span of control, or both broad set of responsibilities, they could do this on a sort of one on one basis. And this was fine. But what we’ve seen as the, the knowledge and the the industry of healthcare have been sort of balkanized and fragmented. And so everyone is getting more and more sub specialized. As a result, the administration of care increases. And so the, I guess, the relative percentage of the physicians time or accountings time that they’re spending on things that add value to the patient journey, versus things that are necessary, conditions of creating that value, sort of the administration engagement, the handoff, all those sorts of things, that that sort of got up out of kilter, and the balance has shifted. And so what Lumeon is doing is, on the one hand, eliminating a lot of that administrative, if you like but on the other hand, it’s also making sure that we get it right first time that we’re using the benefit of the data, I’m using the benefit of the protocols that we’ve got, so that what time we do spend with the patient as, as, as best used as it can possibly be, when it comes to the patient experience. And I think a lot of people focus on trying to add a sort of an overlay to making care, care a better experience. And I think that’s the right thing to do. The challenge is that in order to actually truly make an impact on, on on care delivery, and to make it a better version experience, you need to simplify it, you need to get rid of a lot of this waste and error and fragmentation behind the scenes. That’s its kind of mastery of what happens behind the scenes that will deliver a better better patient experience, keeping your promises doing the things you’re supposed to doing them reliably. And in a way that’s specific to that patient. And overlay doesn’t give you that it’s not sufficient.
Karen Jagoda 7:56
It also seems to me when we’re talking particularly about a critically ill patients, or patients with undiagnosed diseases, that the time factor is extremely important. And when I hear you describing the environment, it seems to me, a doctor might come to the right diagnosis a little sooner than they might have in the past, is that also a function of what you’re trying to achieve?
Robbie Hughes 8:19
So up to a point, I think it would be a little unfair of me to say that we’re making a massive impact in terms of how the doctor is reaching a diagnosis, that isn’t what we’re doing, what we are doing is reorienting the journey that the patient goes on such that we can collect more information from disparate sources and synthesize it and present it to the physician such that they have better information and are thus able to to be more effective with their time. So I think you’ve got to be a little careful. In case of an acute MI or some some sort of event where time is a factor, the idea that a patient is going to engage up front and self screen and all that that’s just not realistic, that’s not going to happen. But in the case of things like chronic disease management in the case of potentially some types of IDI admissions in the case of discharge planning, in the case of elective or planned procedures, where you have an ability to, to engage and coordinate better than yes, we can make a massive impact there. But there are certain activities like in an hour where, you know, there’s very little impact, we can reasonably have that.
Karen Jagoda 9:34
And is artificial intelligence, machine learning a big part of your model so that as you’re gathering data, you’re also getting smarter.
Robbie Hughes 9:43
Again, so yes, up to a point. We use machine learning like technology, but it’s got it’s got to be really clear that everything that our system is doing is explainable. So I think one of the challenges with with artificial intelligence and how And there’s the sort of black boxes as the information goes in, and some sort of decision comes out. And nobody can, can understand why you got to that decision. And the more complex these models get, and the more data they input, then the less explainable they become. It is absolutely critical for our customers and for our patients that we can explain the decisions that we’re coming to, and the recommendations that are surfacing. And so I think, in time, machine learning may be able to play a bigger role in what we’re doing. But for the moment, there are certain types of models and certain types of analytics that we’re using to create recommendations, but they must always be explainable. That’s the critical requirement.
Karen Jagoda 10:41
That seems very grounded in reality. And I’m wondering what the reaction has been from the payer side, I know it’s different around the world. But are they also seeing some advantage to having this kind of clarity in the in the process?
Robbie Hughes 10:57
Yes, in short answer, yes. Long answer depends on the type of payer. So I think you’ll obviously be familiar with things like medical loss ratio, you’ll be familiar with some of the ways in which payers are kind of make a margin in the US around things like claims, administration, etc. So we are absolutely reducing the volume of care that’s required. And a payer that is interested in the overall level of risk in their cohorts, and the overall amount of, of money that they’re spending on care would have a serious interest in what we’re doing. And we certainly see that in the in Europe, in the US, again, full risk plans, ACOs, employer, employer back bands, where they get the benefit of the reduced volume of care, they have a very keen interest in this because we are we are eliminating waste to a considerable degree. But I will say when we started in the US a few years ago, it was actually it was very interesting as a as an English person coming into the US understanding the mechanics of how payers made money and where the interests lay. And it wasn’t at all obvious that they would have an interest in reducing the number of claims. Because it turns out that for every claim, they get paid a fee. And that’s often where, where they will make a margin. And as you as you think about kind of the insurance challenge, there’s there’s kind of two critical factors and in the US healthcare system, one is the medical loss ratio where the amount of money that they spend or they receive, a certain percentage has to be spent on care. And so their profits are have essentially kept the other is annual enrollment. And so the idea of being proactive and and I guess, nurturing your population, so they have a lower level of risk and are better engaged in a more healthy, that doesn’t always have the right incentives, because again, they will probably be someone else’s patient and in 12 months time. So unfortunately, there’s there, there exists a bunch of perverse kind of incentives in the payer market today, which I hope we’ll see ironed out over time, but directionally, we’re certainly doing the right thing from a cost containment point of view and a quality point of view.
Karen Jagoda 13:11
And also, it seems to me from an early warning point of view it I know that payers like to find things earlier, rather than later when the patient’s already been hospitalized or has a serious chronic condition. So is that also part of the mission here to find early signs, early biomarkers, perhaps to give doctors more information about earlier treatment plans?
Robbie Hughes 13:38
Yes, I would say that that is somewhat. That isn’t where the focus of our customers tends to be today. The challenges that we see on the ground today are more about ensuring that the right things that I’ve done systematically reliably. So I’ll give you an example things like colonoscopy is mammography is any kind of screening event is is in principle, the right thing to do to address long term kind of cancer risk, etc. But the the operational challenge, and the real short term focus is actually a slightly more mundane one, which is the when patients undergo some of these screenings, they’re just not followed up. So how do you make sure that someone who’s got a diagnosis is actually getting the care that they need? The problem is not how do you screen them? It’s actually once you’ve screened them and identified a problem, how do you follow up? How do you personalize their care beyond that, equally, for example, at the point of discharge, there are many, many conditions where we know what the follow up protocol should be. And we know that patients should come come back and visit their PCP but they just disappear. So from a cost point of view, it’s right to invest in primary care. It’s right to invest in screening, it’s right to invest in all these things. But sadly, many of the issues that can impact had the quality of care delivered. And in fact, the impact at a population level on very, very basic things, just making sure that the basics happen as they should. And so many of our customers just focused on getting that kind of basic, basic level right? Before they get into some of the more advanced solutions that we have. In other areas.
Karen Jagoda 15:21
You’re talking about basic human behavior there, which is always a challenge from the people I talk with. So my last question, I’m just curious, what are the other big challenges that are ahead, you’ve pointed out a few of them here. But there must be some other big obstacles that are in the way for you, in order to really implement this fully.
Robbie Hughes 15:42
I think we’re in an interesting spot, we have a solution that works we have, we have a set of customers that are exploiting it to deliver phenomenal outcomes for their, for their patients and their care teams. The challenge in doing anything in our industry is that change takes time. And that doing anything that is different takes time to be accepted. Now. This is a journey we’ve been on both internationally and in the US for some time. And so we kind of went past a lot of those challenges. But it’s very easy to underestimate the size of the of the healthcare market and, and the diversity of both maturity and opinion within the market. So you know, it’s very easy to look at big logos and fancy health systems as shining beacons of opportunity and change. But they’ll have the same kind of challenges on the ground that everyone else does. And today, those are workforce, those are around reimbursement. And those are trying to put around trying to do the right things for their patients when they’re struggling in many cases to keep the lights on because the people who deliver that care are either moving out of the workforce or are getting hit by COVID, like the rest of us. So I think to the extent that we provide a solution that provides a sort of safety net to their care teams, guiding them to do the right things that allows them to focus on the right activities, so that they’re not wasting the precious time and resources that they have on things that aren’t necessary, then we have an amazing opportunity. But like everyone else, you know, it’s difficult for them to plan, when at any day, a certain percentage of their workforce can be taken out because of an unexpected infection. So you know, all of these things are opportunities depending on how you look at them. But it would be naive to think that anything that happens today is is necessarily plain sailing. I think we have an amazing opportunity we got from the model clients, but the market remains true stay interesting for the time being.
Karen Jagoda 17:54
Thanks to my guest today. Robbie Hughes, founder and CEO of Lumeon Lumeon.com. Follow them on Twitter at Lumeon underscore, I’m caring to go to and you’ve been listening to the Empowered patient podcast.com. So follow me on Twitter at Karen Jagoda, like us on Facebook at empowered patient radio. Thanks for listening, and we’ll see you next time.