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Executive Interview: How Real-Time Location Data Could Transform Hospitals with Philipp von Gilsa

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Learn more at this week, help. com slash Kontakt dash IO. That's K O N T a K T dash IO.

I'm Bill Russell, creator [00:01:00] of this Week Health, where our mission is to transform healthcare, one connection at a time. This is an executive interview

quick powerful Conversations with Leaders Driving Change. So let's get started.

Bill: All right. It's an executive interview and today I'm joined by Philippp Von Gilsa, the founder and CEO of kontakt io and one of the people in the industry that I've reached out to discuss AI and where it's going and those kinds of things.

I love the conversations that we end up having. And Philipp, you have so many things behind you right now. Your team is brainstorming and thinking. Let's start real quick with kontakt io. Some people might not understand what kontakt IO is. I want to talk about ai, but I want to start with the foundation for what?

kontakt io.

Phillip: Thanks Bill. And I think for the record we just started chatting 10 minutes and Bill forgot to hit the record button, so we'll redo some of that now on the record. But look like kontakt AO in very simple terms is next [00:02:00] generation. R-T-L-S-R-T-L-S.

Bill: I mean, it is just basic RTLS something, by the way, that we hadn't gotten right as an industry, but you guys have gotten right. But where I, I mean, where's it going from here?

Phillip: Exactly like the, let's anchor on the terms that everyone knows and nobody likes because that creates both an understanding of the swimming lane and an emotion.

And typically I was just with, you know, a bunch of investors earlier today. They have done a market research where they've interviewed 70 CIOs and CTOs across the industry, across sort of the state of location data within healthcare. And the NPS score for the legacy systems out there is minus 20.

Bill: We hadn't gotten it right.

Phillip: Has had,

Exactly. We haven't gotten it right. And now on the flip side, so kontakt io deployed in 400 hospitals. All of that happened over the last three years, not the last 10, the last three years. An NPS score of [00:03:00] above 60.

And the technology has evolved. Yeah. And I'm here, you know, you have to go back 10, 15, 20 years. Technology has evolved from on-prem. Proprietary hardware heavy. Here is sort of the hardware. Here's the maintenance contracts here, the batteries right from extremely sort of, cumbersome data creation capabilities too.

Cloud to standardization of the networking stack to essentially in pure CFO terms, the cost of creating data has got dropped by probably 80%, 90% right? Plus all of these capabilities now in the cloud as a service, not the problem of the hospital anymore. Our problem, we don't deliver. You don't pay us, right?

Like that's the agreement here. And, I think the acceleration and now kind of closing the loop of like why we are talking is out of the, probably let's say five [00:04:00] top 10 health systems that have made the switch, that have consolidated points, solution efforts from staff safety to their asset management domain to patient flow on the kontakt DEO platform over the last 18 months.

The one reason they're choosing us as a partner is because we put the use of the data and the application of the data in the age of AI as sort of front and center of what can be done, kind of beyond the mundane sort of solving for one very specific problem which each of these, you know, swimming lifts.

And that's obviously in the age of ai, where I think over the last couple of. Years. The education levels have advanced. I mean, I recall Bill when we spoke a year ago and I got the brief from my VP marketing, he told me to not use the term gentech because the broad understanding in the market wasn't there.

Now I got the same brief again, by the way, to [00:05:00] not use the term agentic because there's a fat of like, over ai you know, everything. So we kind of went full circle. But what everyone has learned is it's the data Yeah. That allows you to take decisions to make recommendations or to allow the agents to take decisions and make recommendations on the spot.

And in our case, when you are within the operations of a hospital. It's about the real time data because nobody needs more dashboards at the end of the day. Everybody needs at the moment. Something breaks at the moment, like something goes wrong. You want immediate interventions and actions, and that's what we are enabling across domains.

We call it, you know, orchestration of care operations and orchestration of care operations is only possible. Through realtime data from the physical world, get an understanding and, and, and you put it into using. So, so let great ai,

Bill: Let's talk about that a little bit. I mean, once you get the data right and you're now getting that, that [00:06:00] location data correct and getting it into the real time, getting it into, a format that can be utilized. Give you an example. This morning I'm working with the events team and they're like, well, you know, where do we go to do this? Where do we go to do this? And essentially, I spun up a dashboard in less than five minutes. Like you could spin these things up, spin 'em down, you can ask it questions.

You could have different interfaces to this data. You could have agents ping this data. Looking at the data I'm not sure we as in healthcare, understand the impact that AI is going to have. On once we have that quality data together, I mean, give us an idea. So location data agents sitting on top of it strong IT teams there, who can who, who can essentially interact with that data through AI mechanisms.

Be those traditional methods or what we would consider non-traditional today. I, what are they able to do? What does it look like?

Phillip: I want to use a different [00:07:00] analogy that I think everyone can relate to and we talked about just a moment ago. I've told you that I'm currently building internally with some of my folks, what I call a chief of stuff agent.

Essentially, I'm evaluating do I need to hire for that role or do I build a set of agents that are essentially, you know, listening to calls. Condensing down decisions and then providing me with a lock book on update over a slack message. Right. And if you look at this workflow or an alternative workflow, which I think every executive and every CIO is exposed to is your reports.

Yeah. Today you have somebody on your team every Friday, you know, 5:00 PM they're sending a report, 70% of the time they send it on time. Sometimes they don't send it at all. Like, why would that have to be a human like doing that? Can, can't we automate that? And you schedule it and you prompt, you know, you either, either using Zapier or like Google Vertex or whatever it [00:08:00] is, the tools that you're using.

And within the digital world, we have a very good understanding of what you can now do with specific agents that are, you know, condensing information, understanding what is happening. You're applying um, some sort of logic to it and then you're outputting it on a preferred sort of timeline. And some of these things might be real time.

'cause you just get that, you know, decision block book summary, the moment the call happened. Yeah. If you apply this now to the physical world and sadly speaking the reality of running a hospital, it is not about, you know, planning the day and then things kind of go as they're supposed to go. It's.

Chaos and 90 minutes, an hour in thinking about how do you plan for, you know, what levels of equipments are needed, how do you think about your bad management? How do you think about, you know, stuffing, how do you think about managing the timetable and the schedule of a cleaning crew, of a transport, like all these [00:09:00] different domains.

there's only so much do you can do in better planning. And if you had Yeah, a real time. Operating view of the physical reality through at the end? Yeah. An understanding of location. Where is the patient at any point in time? How long has the patient been waiting in front of radiology? Has the patient already left?

And nevertheless, we haven't triggered cleaning and EBS to kind of turn the room over. Right? All of these things you can capture by. Making location data available. And if you have then a data fabric. Yeah. That essentially is, you know, time series data across sort of these different domains. We always categorize them in understanding of space.

Yeah. And then understanding of assets, equipment, everything that's on wheels. Understanding of stuff, interaction with things in space. And last but not least, the patient is the most [00:10:00] important reason why we're doing all of this. Yeah. Then you are now in a very unique position to enrich that data fabric with some of the called clinical context or EHR context, which is essentially a view of, you know, a lot of demand based signals.

Yeah. And I sometimes for the lack of, like if, 'cause I'm an economist. Yeah. I'm using sort of RTLS as the supply side here. You understand like what is actually happening here. You have the demand side. You put those two things together. Now we provide agents, yeah. To these different service slides that are not showing them dashboard, that are not giving them additional analytics like that you'll figure out yourself.

I mean you'll get it from us for free, but like that's not the point. But we will surface the actions that can be taken on the spot in the moment. You know, something breaks and. That's the same logic. Going to back to my Chief of staff example, there was a call [00:11:00] recorded. I get my summary. Yeah. Yeah. And there was an IV pump requested.

Nobody brought it. Yeah. Like what happens next?

Bill: Two thoughts. One is it would be amazing to me to see how this data would be applied to like a Lean six Sigma. Process within a health system. I think it would unearth a lot of insights that would lead to a lot of inefficiencies that would be identified.

I mean, you're talking about just from a technical standpoint, you know, lost equipment, where's it at, patient flow, that kinda stuff. We know that there's an awful lot of waste there. But the second thing it causes me to think about is, you know, a majority of your growth has been in the last three years.

What would the pandemic have looked like if this were widely deployed across all the health systems? I mean, we were trying to figure things out in real time during the pandemic. You know, turning rooms into med surg rooms, patients, patient flow equipment ventilators. I mean, we we were trying to figure it out as we went. [00:12:00] Having this kind of realtime data, I think would've helped the response pretty significantly.

Phillip: I'm always trying to be very cautious around using sort of buzzwords, but like the one item is obviously the realtime sort of interventions that we are enabling.

The second piece is. The forecast, it's the 24 hours to 48 hour simulation of like what is happening and taking that data into account. How do we now take decisions on, for example, you know, bad assignments and so forth. And so I think internally, and it's a term, you know, we're using a lot sort of with, in sort of the product team how this should feel like for the hospital, the patient Yeah.

To begin with. Everything should feel in flow. Everything should feel like I'm coming in here and I'm less anxious because I know what's going to happen and some of that information gets resurfaced back to me for hospital, for staff. Yeah. If you like, before we kind of elevate to the, [00:13:00] to, to the executive team for staff it's the same thing.

It's less bottom of the license work. It's less running around, it's less being the master of chaos. Which is sort of the superpower, you know, everyone who's providing frontline care has in that, right? Like, 'cause that's how you serve, that's how you sort of survive. But you don't have the decision support systems that are you know, actually guiding you within sort of the broader kind of context of the organization.

And last but not least and to, to some extent, the pandemic has been an accelerator for our adoption for the post pandemic sort of time. As well I think the common thing we see is that hospitals that are working with us are having real operating margin improvements, not exclusively because of us, but we are one of the kind of you know, initiatives as part of getting, you know, to the 10% operating margin.

And I think pre pandemic, that wasn't [00:14:00] most of the time. The focus and the center of the conversation given the pandemic, then the inflation, and now obviously also kind of the cuts and what we're seeing, you know, coming outta Washington. Uncertainty is high and the need to rethink how you run your core of the lib operations is is of essence.

Yeah. And that is further accelerating. I think the idea of, oh, we have these old, outdated, expensive systems. Here's some, you know, some newer solutions. The largest for-profits from HCA have deployed it, you know, system-wide across every single hospital. And over the last sort of 18 months, you know, the leading non-for-profits, academic medical centers, but even small regional health systems

Bill: let me close this out, out with this. We did talk earlier and we were talking, how do you get the, so we're talking to CIOs now. How do you get the executive team to really understand, and you have an interesting model that you're doing right now.

I'd love for you to talk about the, I don't know if it was a hackathon or [00:15:00] what you called it, but where you're pairing the executives with an engineer. Talk about that a little bit. I thought that was really interesting.

Phillip: I mean, look, I think that 80% to 90% of the executives out there, and I'm including my team, right?

And the little organization I run. Have not completely realized and internalized the magnitude,

sort of the AI models and capabilities and frameworks that are being provided there. And it's an, it's a problem that I think you cannot grasp intellectually. You cannot like read about it or like watch another video of Sam Altman, like, announcing this or, you know, Jensen Huang blowing through his like quarterly earnings.

And this by the way has nothing to do with the question of whether there's an ai, ai bubble or not, but if you experience some of these capabilities, especially as a non-engineer yourself, you will be blown away. And things have evolved so fast. [00:16:00] Yeah. Over the last 12, you know, 18 months, again it's almost like you have to do it on a monthly or quarterly basis because the speed of adoption is crazy.

And because of that, what we are doing, like next Friday internally is we're doing an AI hackathon for the entire executive leadership team where we're teaming up one of the executives with one engineer, and they get 24 hours. They should use AI to solve one of their internal sort of problems. Right.

And going back to one of the earlier conversation we're working on BI agents procurement agents, interview agents. There's just a lot that you can do. What you will find very commonly is it's about what is the backend data that I have, right? Like, what are the data sources I'm going to kind of connect to?

Then you will see, and this everyone can experience firsthand like the no code, vibe, code kind of prototyping tools from lovable replid whatever. You know, you've been using Cursor. [00:17:00] Anyone? My daughter or my wife. And she's a creative. Yeah. They can play with it. They'll experience it. Yeah. And what's the underlying sort of then capability. What you can actually build or not build will depend on the data sources you have available to, to automate against. Which brings me back to, you know, inducing a little second kontaktor pitch here, right? If you then have a real-time view of the physical world, well, your mind can go crazy.

What else can I build in terms of. Automations prompts interfaces et cetera. But the value is not so much in the system of engagement or the interface layer anymore.

Bill: I I think there's gonna be a renaissance of creatives because we used to look at computer screens and go, man, I wish you could do this, and.

You know, my experience over the last couple months has been, you can speak those things into existence now as creatives. Like you can, I mean, not, and when I say creatives, I'm talking about in our world, I'm not necessarily talking, although in the other [00:18:00] world you're seeing it as well. I mean, they can create movies, they can create those kinds of things.

But in our world it's like. Imagine it and then develop it with just some words and some knowledge of how data works and structure and those kinds of things.

Phillip: Just like one closing thought on my end, I think as anyone is kind of going through this kind of experience themself as you or others have been.

I don't think it is necessarily, then the implication is, oh, well great, I have to build all of this myself. But I think by seeing what's possible, and this is not three years, two years, one year out, I think it's going to change your expectations of what do I want to kind of tackle next? And some of these things that feel like, you know, greatly sort of heavy lifting are maybe much closer than you think.

I feel that's sort of true, but again, very hard to internalize unless you experience it yourself.

Bill: Fantastic. Phillip, always great to catch up and look forward to the next time we're in the same room. It's been a little while you've been hanging out with Drex and Sarah. We'll have to get you at [00:19:00] one of the events that I'm hosting.

Phillip: Perfect. Thanks Bill. Happy holidays.

Thanks for joining us for this executive interview with me, bill Russell. Every healthcare leader needs a community they can lean on and learn from. Subscribe at this week, health.com/subscribe and share this conversation with your team. Together we're transforming healthcare.

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