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It is. Bill. I am looking forward to this too.

It's surprising we haven't had a chance to talk before.

Well, I've talked to a lot of clear sense people, vibe and hymns people are probably thinking, oh my gosh, this platform can do a lot of things. We've talked to to Terry about data governance. We talked to actually I'm not gonna remember all the people I talked to.

Yeah. But I remember U P M C was in here and we talked about intelligent interoperability. We talked about fire endpoints, we talked about research and creating cohorts of data. And it, it's actually a lot of really exciting things. And your booth at both events has been.

Really active and people saying, all right, tell me about, but here's my question to you, chief Strategy officer. What does Clear Sense do? What do you tell people? In a sense? Cuz it does a lot of things.

You know, we make it easy for your average analyst, your average human to interact with their data.

It is way too hard. For these healthcare organizations, they're trying to provide care. They're trying to chase down revenue. They're trying to manage the friction with their payers. They're trying to do all these initiatives, but it still takes too long. It still requires too many engineers, data scientists.

Highly technical resources that is not gonna work in the future. We already have generated AI and chat. G P T is taken the world by storm. And I talk about the Google unification of our human society or where we're doing this today. Taking that one step further, allowing an average person to actually manage their data, establish trust in their data, build out effective.

The fabric of their data so that then they can put it to use in whatever use case they want in a really simple, intuitive way.

At the level it's being asked for. Correct. Right, because if you wanna scale the use of data, there has to be a little piece of everybody's job that is utilizing the data.

And, but in order to do that, when they pull that data down, they have to know what the definition is. They have to know how they can use that data.

that's the tie in with Terry and data governance, right? That's the contributions of a data steward, right? The building of that analytics community, being able to have the people that are going to be producing the data.

Using the data, contributing to the definitions of it, the trust of it, establishing the metadata, the relationships, the connections. So if you are asking more and more of the business users who are not traditional IT staff, technologists, data scientists, computer scientists, if you're asking them to contribute to their data, it's gotta be really easy for them to contribute to their data.

Yeah. You know, I go back a long ways with clear sense cuz when, when I was at St. Joe's we brought clear sense in and the narrative we were talking to our clinicians about and the people who used data was, and, and this is kind of dated now, we would say, we want it to be like Google.

We want you to be able to ask a question of the data and have that data returned to you. Like, give me the census of St. Jude's Hospital. For children between the age of blah, blah blah, between these states and, and you just in a narrative form, you put it in there and Google spits it back. That was the, that was the thought.

It's a little dated now cuz we're now seeing this. It's happening. It's, it's happening. Yeah. And I, I guess my question is this whole idea concept, and I don't want to, I don't What, clear sense down to one thing because you do a lot of different things. The research aspect is, is really fascinating to me.

But there's, you know, this, concept of unlocking it. Yeah. And I've talked to a couple people about this is how far away are we from you know, the Star Trek? Image where we're talking to the computer and saying, Hey, you know, gimme the vitals for, or, I'm, I'm supposed to see 10 patients, or what, how far away are we from querying the data like that?

We're not that far. You know, the ability to query the data is happening in real time now, right? We're talking about that this year. Right? Generative AI is again, taking the world by storm. The problem is, is you still are left with a garbage in, garbage out problem. It's the quality of the data, the quality of the data, it's the ability to have the context of the data that you have for your use case or for your business need and your ability to interpret it, right?

And so even if you can have a computer interpret it, it can interpret it incorrectly. It's interpreting it with its own interpretation or context. Now it's not necessarily a registration clerk or a networking administrator or the like, right? So, what we're doing with the data fabric architecture ultimately is the, core of what we're doing.

And then with having the business domains friendly, business attributes, names, first name, last name. You're not looking at field names or definitions. You're not taking that junk from every single database. You're normalizing it, you're organizing it, you're categorizing it in the words and, and ways that your average person can understand and add their.

Own definitions to and interpretations of and be able to share those across their communities. 📍

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📍  

Well, and that's, you talked about the data fabric, the conversation with Terry was so important because that's what it is. It's putting the policies around it, it's putting the metadata around it, it's not losing its context.

And that's one of the things that happens we talked about this yesterday. I'm trying to remember who we talked about it with. But we were talking about script data. And script data goes from the health system or the physician. It goes to the pharmacy. And the pharmacy says, well, I don't really need all that information.

I'm just gonna do this. And they put their stuff in, they move it back. And when they move it back, it just lost a whole bunch of its context because one person viewed it through, Hey, here's what I'm prescribing for you for your condition. And then the pharmacy said, Hey, I'm only really concerned about the, appropriate dispensing of those medications.

And now the data just lost some of its context. The platform with, the different work streams and domains. Allows you to keep that context no matter where the data's being used.

It allows you to retain that context, maintain the changes in that context over time. Be able to allow role-based access or individuals to, interact with it, inter operate with it in their context if they're humans or systems.

APIs, and ultimately, right. You talk about what maybe a new future might look like, where, what I'd really love to see is it's not just being able to talk into the computer, it's to use it to drive realignment of incentives because that, even that simple scenario with your, your pharmacist getting the prescription from the provider, the human.

The patient getting the need for the services in that entire scenario, right? The person is not yet incentivized to provide their information in a way that keeps their, prescriptions from creating adverse reactions with them. They, you think that they would be, however, there isn't an easy way to interchange that data or share that data and the.

Pharmacist is not necessarily collaborating with the provider. In part it's because they miss some of that context. They're not all operating in their contexts.

Well, one of the things I liked about Clear Sense at the time when I looked at it, people were like, well, you know, your EHR has a data, I afraid we were probably calling it Data Warehouse back then.

We were trying to support the physician with information real time. Yep. At their fingertips. If you look at a clinician, when they sit down at a workstation, they log into like 10 different. Listings. Yeah. And so without, all, without the ability to bring it in. That's one of the things I liked about, having a, separate data fabric that went across the entire enterprise.

That's what we're doing. We're supporting it across the enterprise, especially in some of the providers that have health plans. They have a whole new set of challenges there.

So you guys, do you guys do health plan?

We do work with health plans. And you know what we are also talking about here now is working directly with payers who are.

Working with their providers and establishing better ways to share data that reduces friction. So maybe they don't have to request a itemized bill for your, you know, long stay high dollar claim. They can just automatically aggregate that information. We're also seeing opportunities where organizations wanna work outside of their four walls, work with the community.

Some of these counties actually have great information on social determinants for their communities, and you see different research entities coming up and. Wanting to share and aggregate data so that they can drive broader research initiatives inside of their local communities.

We could talk a lot, but I've stacked my day with interviews, so, hey,

I appreciate you making time for us, as always.

Oh, my good supporter. Rick, we could, we could talk for a while. I'd love to do that. I'd, I'd love to have you and Charles in a room and just geek out for a little while. I think that'll be a lot of fun.

It would be a lot of fun. Thank you for the time, bill. Thank you.

    another great interview. I wanna thank everybody who spent time with us at the conference. I love hearing from people on the front lines and it's phenomenal that they've taken the time to share their wisdom and experience with the community. It is greatly appreciated.

We wanna thank our partners, CDW, Rubrik, Sectra and Trellix, who invest in our mission to develop the next generation of health leaders. Thanks for listening. That's all for now.