Becoming a Data-Driven Healthcare Organization

In this episode, Tripp Johnson, CEO, and Marcus Shumate, Growth Director, discuss the challenges and successes of scaling their healthcare practice, particularly the opening of a new Chapel Hill location. They explore the importance of integrating data across their CRM and EHR systems to create a seamless patient journey from the first contact to discharge. Tripp and Marcus dive into the necessity of data literacy within their organization and the steps they’ve taken to ensure that data informs every decision, from patient-provider matching to operational efficiency. The conversation highlights the role of real-time data in improving both patient and provider experiences and the potential for AI to uncover previously hidden correlations that can enhance outcomes.

Key Topics:

• Challenges of scaling healthcare operations and opening a new location
• Integrating CRM and EHR data to improve patient and provider experiences
• The journey from spreadsheets to a centralized data warehouse
• The importance of data literacy and real-time feedback loops
• Using data to refine patient-provider matching and operational processes
• The future of AI in uncovering hidden insights in healthcare data

About Flourish by Advaita Health

Flourish by Advaita Health explores how people, providers, and communities move from suffering to flourishing. Each episode weaves together perspectives from healthcare, wellness, and human experience — from the science of mental and physical health to the art of living well.

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Transcript

Marcus Shumate (00:00.528)
You

Tripp Johnson (00:03.125)
Marcus, where does this podcast find you today?

Marcus Shumate (00:06.862)
This podcast finds me stressed probably not dissimilar from you about the Chapel Hill location opening Probably what feels like the 15 ,000 different projects we have in the air that we're trying to navigate so

Tripp Johnson (00:26.037)
Yeah, you know, I just wish like I had like this, like, I wish I had this like growth officer who is just like buttoned up and kicking ass had this like fully thought out data driven, you know, plan for for our marketing efforts because like, I mean, again, we've we've got the secret sauce in terms of all the insurance contracts, high quality providers. I mean, this should be the easiest thing. Why are you stressed?

Marcus Shumate (00:32.354)
Good boy.

Marcus Shumate (00:48.494)
I don't know I don't know, I I work from home. Listen to her, wish in one hand and shit in the other, see which one fills up first.

Tripp Johnson (00:52.449)
man. Yeah, it's gonna be... You know, like the nice thing about this, I mean, this is kinda... I forget. I mean, I have a tendency to like kind of just glaze over, gloss over something like this. But yeah, I mean, we're doing our first real expansion and...

Marcus Shumate (00:58.664)
God.

Tripp Johnson (01:21.873)
it's you know it really is basically a doubling of our our provider capacity over the next year so I guess I guess there's a lot going on yeah

Marcus Shumate (01:28.771)
No.

Yeah, yeah. I I think there's a lot that's going on. There's a lot of stuff that's pretty interesting, I think, too. You know, I think really what's burning on my mind and what feels like a big success and just step forward for us maybe is it feels like we've really maybe have mapped out the most rudimentary and basic components of like really being able to hone in on some of the data that we're getting.

So we're starting this, you know in theory what we have right now is we can see Like from the front end our like first time a client ever contacts us or gets in contact with us via our you know website or something like that and they get loaded into our CRM where we can start working with them It looks like for the first time we actually have a kind of a thread that carries us through

Tripp Johnson (02:01.823)
Mm -hmm.

Marcus Shumate (02:29.238)
that information all the way into our EHR. And we were able to look at a dashboard for the first time last night that really combines us to systems. I know next week we're actually going to have someone that's an actual expert on this stuff on. And so we'll be able to ask more questions, talk through it a little bit. I think all of us are in an exponential kind of growth phase with trying to understand this stuff.

But here's what I'm really curious about, right? Like you, in some ways you've been tenacious on this data piece for, called your, you, September of last year really called this shot with me. I mean, that was kind of the, you know, initial shot across the bow, I guess, for me was pulling me aside and saying, Hey, we, we're going in this direction of data. At the time, everything we were doing was on spreadsheets.

And we got organizationally aligned by that and that took some effort and time. So what I'm really curious about is if you can maybe inhabit what you're thinking was at that time, what it feels like now and what it kind of looks like now, where we're at given that we were able to put some of that stuff together yesterday and then potentially what do you think the future is? So I know that's a broad question. You're never supposed to triple down on questions, but I'm asking it anyway.

Tripp Johnson (03:55.335)
Yeah. So, I mean, think first thing is everyone values data to some extent, right? And I think most off the shelf software, whether it's an EHR or CRM does a pretty good job and it's one function or it's whatever functions it has. But this integrated data picture, I think is the piece that we really have latched onto and the need for kind of life cycle data.

Marcus Shumate (04:01.358)
That's it.

Tripp Johnson (04:23.642)
from our patients, but also from our providers. You know, if our mission is to, you know, demonstrate that there's like a good model of care that's financially sustainable and raises what's possible in healthcare, like we need the data to back that up.

Marcus Shumate (04:41.902)
Right.

Tripp Johnson (04:42.317)
so I think like the, the, the one, the interesting thing is that to me is even though we have greatly increased our kind of data literacy across the organization, or at least we're reporting well, I don't know if we've always increased the data literacy. but there's, know, we really haven't, there haven't been necessarily these like major, major unlocks yet.

Marcus Shumate (05:07.021)
Yeah.

Tripp Johnson (05:07.337)
And we're not even close to talking about really nuanced patient data and some of the interesting correlations that we'll be looking for over time. Right now, it's kind of just basic process metrics and making sure that we first and foremost are

you know, able to see kind of what our providers are doing, making sure that we're drawing any appropriate insights that may be there. A quick example being there was a kind of anecdotal report, someone's kind of struggling, they've, you know, they're feeling like a little overwhelmed right now. And then you go look at the data and it's like, yeah, they've actually seen twice as many patients in the first two days of the week than their counterpart over here.

Like that's a, know, like, it's, it's no surprise that they're feeling a little bit stressed and they're seeing more than we would expect them to see. So, you know, I think for me right now, it's just about this basic clarity and, and, trying to really shift our conversations to even if the data is not perfect, you know, let's first go to the data to have this conversation. Let's not just start talking about, you know, the, feelings and the anecdotes.

Marcus Shumate (05:56.429)
Yeah.

Tripp Johnson (06:25.025)
right off the bat. Because I think like more often times than not, I mean, I'd go so far as to say, you know, close to 100 % of the time, just data doesn't lie in the story it tells isn't that surprising. It just matters like how you, you know, what you're looking for. So

Marcus Shumate (06:25.197)
Right, right.

Tripp Johnson (06:45.045)
Anyway, so last year, mean, data is going to be a big thing in terms of your role. What happened last year is just the fundamental recognition that we are not going to be an organization that lives or dies by business development. That that is an important component, but that we want to be doing more kind of direct to consumer direct to patient marketing over the long term, because that's how people are finding our services predominantly is just

looking for options for help that are maybe in network or close by. And so I think we've made a big push towards bringing in -house some of this kind digital marketing data literacy that you've been working on the last six months or so.

Marcus Shumate (07:33.142)
Yeah. So what do you see this going in the future? Like, I mean, you can Google or YouTube, any sort of videos on data and healthcare and like what that looks like AI and like into healthcare. And it's always sort of focused around data. But, you know, if you had to call a shot right now, right? Like, I'm not going to hold you to it or anything like that. at least, I will. You're not opposed to that. But,

Tripp Johnson (07:38.133)
Ahem.

Tripp Johnson (07:55.867)
I'll call my shots.

Marcus Shumate (08:01.206)
No, just in general, right? We don't want to get too pie in the sky about this sort of stuff or get over our skis on it. But I am curious, what's the bet here in terms of data and the future of healthcare?

Tripp Johnson (08:02.635)
Yeah.

Tripp Johnson (08:13.183)
Well, mean, every so the the initial bet is I think we've talked about this at some length before, but I believe that there are two fundamental components in behavioral health of the organizations of the future. One side is going to just be data analytics, personalized information about the providers, about the patients so that we can do a great job matching people and matching interventions with what's actually going on. The other side of that is the connection piece.

Marcus Shumate (08:23.095)
Yeah.

Marcus Shumate (08:33.356)
Mm

Tripp Johnson (08:41.683)
and that's just the humanity, us being social primates, how do we have meaningful connection? But I actually think like even on the connection piece, we can really look to the data, right? So I really do believe that what we're going to see over time, I mean, everyone's gonna talk about data.

Marcus Shumate (08:52.46)
Nice.

Tripp Johnson (09:02.709)
But the truth is, and what we found firsthand is you cannot actually leverage any of our existing systems, top notch EHR, I'll say an OK CRM. But in order to really draw the insights, you need a consolidated data picture from the first contact to when they discharge and really beyond.

Marcus Shumate (09:13.901)
Yeah.

Tripp Johnson (09:27.465)
So I really think that most people have fundamentally put the cart before the horse in terms of they want to start talking about outcomes measures and this and that. And I'm like, but there's not even anything worth measuring yet. So I think part of it's like, you know, how do we build a system that theoretically stands up to measurement? But then how do we start to draw these like basic correlations? I think what's been super interesting for me is this, you know, we meet with Donnie a lot and

Marcus Shumate (09:33.24)
Bye.

Marcus Shumate (09:42.338)
Yeah.

Tripp Johnson (09:57.119)
He always says like bubble tape, bubble gum and Band -Aid solutions.

Marcus Shumate (10:02.828)
Duh.

Tripp Johnson (10:04.287)
You know, I think so much of this is not about like for us as an organization, like we're not, we're not a tech company. We're not full of like, you know, people with advanced analytics understanding, but we do understand kind of the challenges we run into as a company and, you know, with patients and there's a lot of existing data that we have, but we just don't know how to look at it. Right. So, so there's just, I mean, and it's across the board. It's everything from how quickly you're getting patients

Marcus Shumate (10:10.808)
Right.

Marcus Shumate (10:27.863)
Yeah.

Tripp Johnson (10:34.281)
scheduled to did you schedule a follow -up visit? What's the length between visits? What's the no -show rate by diagnosis? There are so many different correlations that we can look for that may be meaningful. And that's where AI will be extremely helpful to just look for the correlations without specifying what it is ahead of time we're looking for to test. So that's really what's changed.

That wasn't a good way to answer the question. What I would say we're focused on right now is a consolidated data model. Once that model is built, we will use it to generate more insights and to tell us where we need to dive deeper.

You know, we don't actually need to, we don't need to plant a flag and say, we are going to have the best outcomes measures by doing X, Y and Z. Because really that should be an emergent property of what the data tells us we need to do or to change in our treatment.

Marcus Shumate (11:26.99)
Right.

Tripp Johnson (11:35.273)
So I think the, you know, people often, I mean, I'll just say like, I've often kind of conflated this like data driven approach or even like innovation around this is like, you, you know, something's going to work. you build the something and then you measure to see that it works. Whereas

Marcus Shumate (11:35.32)
Yeah.

Marcus Shumate (11:54.115)
Right.

Tripp Johnson (11:55.089)
the nature of reality is everything's connected. And so what's probably going to be more effective is this iterative approach that brings us closer to a full understanding. And I think we've seen that again, just basic information in terms of like measuring utilization and what insights we can draw from that upfront.

But it's easy to do and there's a lot of value in it. So I think like for anyone who's interested in the kind of taking a data driven approach, like it's not always super complex and you can do it on spreadsheets, right? The problem is like that doesn't that doesn't scale and there's no potential for

Marcus Shumate (12:30.232)
Right.

Tripp Johnson (12:36.319)
the data that's captured in spreadsheets, if you're managing a company on this, it's really impossible to then integrate that into the entire understanding. So what we've now done is like all of our clinical data, all of our financial data, all of our marketing data is getting piped into one place, which is pretty cool.

Marcus Shumate (12:56.195)
Yeah.

Tripp Johnson (13:00.649)
What's been the biggest because I mean, quite frankly, is like, I still feel like we're using, I feel like the data that we're using right now is is still primarily operated around like how we operate as a as a practice and the expectations we have for providers like and the scheduling team, the marketing team.

So I don't feel like we're doing anything super advanced, but I, and I think we've spent like a tremendous effort to get to kind of where we are now, which is probably for the first time. mean, it took us, let's call it the last four months and for $45 ,000 or so to get to where we are right now, which is I think just like a baseline trust that the metrics we're reporting on are

Marcus Shumate (13:51.0)
Yeah.

Tripp Johnson (13:52.807)
across the board accurate. So I kind of feel like I just spent 45k to get us to a place where we don't have to fill out a spreadsheet, but the information is not necessarily different.

Marcus Shumate (14:01.966)
Yeah, Yeah, I mean, it's, think us acquiring the information and tracking the information, like that's better. Is that a $45 ,000 better? Like, not sure if it's the values there quite yet, but you know, these are, I think these things are really fascinating to me at just a human level in the sense that like very often we're just walking around the world and we're

when you don't know any better, you're interfacing with hidden architecture, I guess. I'm still struggling to find the language for this, but you jump on a website or something and you start navigating it, moving around on it, and you don't realize that that usability of the website or why it appeals to you or why it's useful. You don't realize that there was man hours and...

people throwing their heads against the wall to try to figure out how to have data speaking to itself and overlapping so that you can get to a better experience. And it's just one of those things, if you don't know any better, you just assume that it's always been there. You don't understand the processes that necessarily go there. I think that's been one the things that's absolutely captivating to me about this. like you pull the curtain back and there's a...

It's not just a wizard behind the curtain, but it's like 10 ,000 wizards and they're all throwing their heads into a wall or something.

Tripp Johnson (15:34.335)
Yeah, I think that, you know, the other piece with that is I think like so much of this is actually about, for me, the difference is like I used to want to just get data to like, I need this data to make a decision and taking a little bit more of like an explorative, a curious mindset to it and just saying, hey, like I want to see all of this and see if there's anything interesting.

Marcus Shumate (15:48.781)
Right.

Marcus Shumate (16:00.236)
Yeah.

Tripp Johnson (16:01.601)
Because I think it's actually what I've found is, you know, we want to, you know, we can't have the tail wagging the dog. And that's often, I think that's like the fundamental distrust, I think, especially of data in behavioral health is, you know, is it just going to be using the data for, you know, more, a better business proposition or

Marcus Shumate (16:10.733)
Right.

Tripp Johnson (16:27.367)
are we creating data to support what we're doing versus looking at the data on what we're doing to see if what we're doing makes sense? And so.

And it takes a lot of pressure off when you approach it like that. Like, hey, this is the like, again, just take the digital marketing. Okay, this is the amount of traffic we're getting to the website. And from that, there are so many people that are clicking on, you know, start here to become a new patient. And now we can say, well, what can we do to increase the number of people that sign up there? But the you know, the the

What is going to be so fascinating about this? I could list like 30 thought experiments that we'll be able to quantify in the future. I think about things like, how does the person scheduling affect attendance? So you could easily have someone who's scheduling a crazy amount of patients. They're getting on the books, but what if they only show up 25 % of the time?

Marcus Shumate (17:18.198)
Mm -hmm. Yeah.

Marcus Shumate (17:32.322)
Right. Yeah.

Tripp Johnson (17:32.479)
Like now all of a sudden, if you were saying your job is to schedule patients and you're saying I'm crushing it, right, but they're not showing up, then we can use that data to say, Hey, you did accomplish the goal in theory, but now that's disconnected from the ultimate outcome. So what do we need to do to change in that front end process? Either maybe you're scheduling the wrong type of people or you know, like there's something going on versus

Marcus Shumate (17:40.716)
Right. Yeah.

Marcus Shumate (17:52.856)
Right.

Tripp Johnson (18:05.003)
Another example would be thinking about what information can we collect from our providers on the front end to help match them with the appropriate patients. Because one of the things that I think we're really sensitive to is the idea that our team generally doesn't like the idea and we don't offer just online self scheduling right now.

Marcus Shumate (18:13.645)
Mm -hmm.

Marcus Shumate (18:29.101)
Yeah.

Tripp Johnson (18:29.461)
But I disagree with that as an organization. And I think we need to get to a place where we can offer online scheduling. It's more convenient. If we want to be as easy as calling an Uber, then you've got to be able to schedule yourself. And understandably, though, that could be scary. I say scary, but that could be upsetting for a provider.

because they are worried that they're just gonna have anyone who signed, you know, once the next appointment will sign up, whether they're in acute psychosis or this or that. So it's like understandable that they don't, they want there to be some sort of vetting before the appointment, essentially. But what if we could do all of that ahead of time through leveraging technology better? Because really their concern is that they're gonna be matched with the wrong patient.

Marcus Shumate (19:00.642)
Right.

Marcus Shumate (19:07.459)
Yeah.

Tripp Johnson (19:20.641)
And that's a very understandable concern, but there's a percentage of that that happens if a human's collecting all the information upfront anyway. So now we just have to figure out how, again, that's the data. How do we match patients and providers correctly? I mean, for all we know, like we could have a hundred question or a 500 question survey, and it may be your favorite band. You know, if a provider loves, you know, Metallica,

Marcus Shumate (19:20.782)
Exactly.

Marcus Shumate (19:45.91)
Yes. Yes.

Tripp Johnson (19:49.183)
they really jive well with patients who like Jack Johnson. And I would be like, what the fuck? And it doesn't mean that's what we're looking for. But like, again, there's just, there are so many potential rabbit holes to go down. Again, you know, we think about this, because I sent you the link to like, what was like, we thought like a really good buttoned up PPC kind of click funnel to just get someone with a telehealth appointment, right?

Marcus Shumate (19:53.474)
Yeah. Where did that shit come from?

Marcus Shumate (20:16.78)
Yeah.

Tripp Johnson (20:18.625)
and they're saying, we have a patient provider matching algorithm. And it's like, bitch, please. Your patient provider matching algorithm has like three components. The diagnosis is treated, the availability and the insurance is accepted. Maybe you went crazy and added in gender, right?

Marcus Shumate (20:23.522)
Yeah.

Marcus Shumate (20:28.014)
Yeah.

Marcus Shumate (20:32.352)
Enterance accepted.

Marcus Shumate (20:39.192)
Yeah, yeah, yeah.

Tripp Johnson (20:40.853)
But like in today's world, we're again, going back to that connection piece, right? Like we're thinking about the flip side of data and we're thinking about the connection. What attributes of what characteristics of a patient and of a provider are going to lead to that connection? And that's to me, what gets so exciting about data is that there could be these like things we should look for that are beneath the surface that have this outsized impact. Like, you know, the moon, you know,

affects the tides, but we didn't know that, right? Well, I'm sorry, were today's year old, right? No.

Marcus Shumate (21:14.11)
Yeah, yeah here I mean

Yeah, yeah, Yeah, I mean, so I think about this, like we talked about this offline at some point, like, you know, like provider burnout, especially like medical, like physician burner, provide out, it's like a real thing. And, some of that, in some of the literature, they call it like moral injury or something like, know, the right thing or, but you just can't do it or you're not empowered to do it or just whatever. Right. Like, and I think about myself as a former therapist and the

hundreds and thousands of hours or whatever that I spent sitting with clients and working with them. And you would sit down and there's certain clients that like if I knew that they were on my schedule for that day, there was excitement, right? Like I can't wait to meet and sit with this person. And very often the feeling was reciprocal. And I had a really funny supervision session earlier in my career and someone said, how do you know when your patient's getting better? And you're like, well, how? they said, well, when they start to sound a lot more like they're there.

And there's this tongue -in -cheek sort of piece with it. But I think what's interesting about that is I'm not sure that they're entirely wrong. Probably what's happening to some degree is that there's some sort of synergy or matching happening around these variables that were previously undetected. No one would connect Jack Johnson fandom and Metallica fandom. But hey, there might be some sort of desperate data points on that that that's capturing and it becomes predictively important.

or useful. And so what I think about that is you give me 10 clients in a day that I enjoy spending time with just at a very human level. Now work becomes energizing. It becomes self -supporting and self -sustaining versus like crap. I have to work with this dude or this person that I just don't enjoy seeing. They have issues that I don't feel confident in. It's taxing.

Marcus Shumate (23:15.534)
I don't know if they're getting better. They don't feel like they're getting better. What the hell are we doing? Is this just some sort of like weird play acting that we're doing? I sit back, stroke my face and try to look like I know what I'm talking about and convey some sort of sagely presence and then you play the, you your perspective role and on and on we go. So I think about that in terms of data, right? Like how do we, there's this great study that I just read called something called Super Shrinks.

and it was looking at head -to -head interventions, controlled for various variables, really, really interesting study. Essentially what it came down to was there's this subsect of therapists that get a disproportionate amount of change outcome with the clients that they're working with. And it really just does seem to come down to some, interventions, this isn't to say that

empirically based interventions aren't important, but we may not know why they're important or how to get them to be more important or whatever it may be. We just don't know. But then you're finding this sort of, you're just saying this person for some reason has better outcomes with their clients or clients feel better. when compared to other therapists, these people are just way more ahead, like way further ahead. And I think that is

Man, can we get to the data that was previously undetectable that allows for better patient experience, a better provider experience, better outcomes, and better patient matching, and better just marketing and business practices, and all of a sudden you start to see this whole picture humming together in the way that it should? That's fucking exciting.

Tripp Johnson (25:05.557)
Yeah, and I think like to, cause you brought in a few other points there that I think, you know, I think like there's an overemphasis potentially on the patient provider matching component of this. and an under emphasis on all of the other factors that go into someone thinking they have a good relationship with their therapist or psychiatrist. Right. Because like you said, the patient experience is so important. So I mean, if you're

Marcus Shumate (25:17.368)
Yeah.

Marcus Shumate (25:26.734)
Right, yeah.

Tripp Johnson (25:35.133)
If the scheduling team are assholes on the phone or dismissive or you know, like all of that leads up to that them being in the office or being online with their provider and then just being mad and having a sour taste in their mouth anyway. So as we go, like I, you know, some of the things we're looking at, I don't know if you actually, you probably don't even know this because I just learned about it the other day.

And so for us, actually, you know, we've got, and this is like, this is like one of the most interesting pieces for me with organizational design, and where we'll be able to leverage a lot of interesting data in the future, is I think we're going to run some different experiments about how we structure the company. And what I mean, specifically, or the example I would give right now is, you know, we historically have had a couple people in the admissions or scheduling department that handle

you know, new patient scheduling. And then you've got your kind of patient support. They might be at the front desk, but they might also be upstairs running prior office doing these support tasks for our patients, outbound referrals, that kind of thing. But what what what our new office manager has done is kind of break down the administrative team into the little pods that support support a group of providers. So

you know, a few people may have one kind of central point of contact for their questions and thus their patients will be able to correlate, you know, the patients with the administrative staff they're most frequently interacting with and see like where we can enhance our customer experience and things like that, you know, as opposed to having a dedicated, you know, so I think we're trying to look at this because as we grow, again, the philosophical question is like,

How do you grow big, but feel small? small being a proxy for that disconnection, right? But how do you make it, again, if you showed up to your individual therapist, you got a therapist, and you show up and they work out an office at their home, and they got the plumber over that day, and you're like, hey, I'm sorry.

Marcus Shumate (27:48.161)
Exactly.

Tripp Johnson (27:49.945)
my bathrooms out and you're like, damn, I really got to pee though. This kind of sucks. You're probably not going to be angry at the therapist. You're like, this is a total like human problem that happens. Can I go outside? Whereas like if you're at if you're at right down the road from us, UNC's midwife practice, like half a mile away from us hasn't had air conditioning for the last three weeks. So you got pregnant women trying to show up to an office?

Marcus Shumate (27:53.646)
present.

Tripp Johnson (28:18.239)
without air conditioning. Like, you better damn sure believe that's going to impact the patient experience. And now you're telling people, yeah, not great. And there's a lot less like, there's a lot less. You're not gonna be that generous with UNC like get your shit together like

Marcus Shumate (28:20.034)
Yeah.

In Chapel Hill in

Alright.

Tripp Johnson (28:39.637)
You're like the biggest healthcare provider in the state and you need air conditioning. Like who dropped the ball to make that a problem? So as we grow, like you don't get the forgiveness, right? Because you're like, you're real company. You should be buttoned up on this. So anyway, I just think like it'll be interesting as we design, you know, and having a Chapel Hill location versus a Raleigh location will allow us to do some like different experiments about how we, you know, structure kind of care management teams.

Marcus Shumate (28:39.831)
Yeah.

Marcus Shumate (28:49.39)
What?

Tripp Johnson (29:07.123)
And just to go one step further with this, I've been trying to like design this in my head first, but you know, I've got this kind of like, think about a Venn diagram of, think about like all these circles with diagnoses, right? And each cluster of diagnoses, know, that might be together. So you could put all your substance use disorders in like one cluster and everyone who's comfortable working with substance use disorders.

Marcus Shumate (29:16.93)
Yeah, yeah, yeah, yeah, yeah.

Marcus Shumate (29:21.802)
Mm

Tripp Johnson (29:33.957)
are generally comfortable working with anxiety and then depression or whatever mood disorders and seeing like where those overlaps are. So then A, we build out like care teams. So we might have like a group that collaborates frequently on depression, one that collaborates frequently on substance use disorder, et cetera, et cetera. And then you start layering on top of that model. So again, you've got these overlaps where

They may fall predominantly in the substance use group, but they see some of your mood disorders. And then you've got your admin staff that maybe understands certain disorders better than others and has developed a niche in working and communicating with patients with certain diagnoses.

Marcus Shumate (30:08.813)
Right.

Marcus Shumate (30:22.36)
Yeah.

Tripp Johnson (30:23.585)
I don't think that was super coherent, but I've just I've been I have personally been like trying to visualize, like, what what all of these things like could mean for us.

Marcus Shumate (30:33.378)
Yeah, I so I think you're in the weeds a little bit, it's which isn't terribly uncommon for us. But I think one of the things where my head goes to this is you're talking about something pretty fundamental, actually. Right. Like you're just talking about all the intricate parts of the fundamental. the the fundamental is humans were contextual beings. Right. Like we are going to feel what our context is in any given moment. Right.

Yeah, and that's like one of the things DBT or ACT or any of like mindfulness or any of that sort of stuff sort of teaches is like we're not actually our context we're just The experience is arising into awareness like the experience of the context is just arising into awareness But we're not actually that right? We're just we're consciousness and that's experience that and so like I'll just make what you were saying in the most concrete sort of example that I can give my

one of the best supervisor I ever had, like terribly intimidating guy. I worked at an inpatient psych unit. This guy took supervision so seriously that he essentially went to school for an additional three years to be a good mental health clinical supervisor. And he said something I've never forgotten. It's been so much 12 years now, but he said, your job, and he ran a small practice out of his house and he said, your job as a therapist at the most fundamental level,

is to ensure that for the one hour a week that a client is seeing you, that that one hour a week, they don't have to feel crazy. That it's a respite from their life, that it's a context that's set appropriately, that when they walk in, if they get nothing else out of that, they walk into an environment for at least one hour a week that is a context that doesn't make them feel like they're hanging on by a thread.

Tripp Johnson (32:07.232)
Yeah.

Tripp Johnson (32:24.32)
Yeah.

Marcus Shumate (32:24.556)
And so essentially that's exactly what you're describing is how do we build that totality of context that allows them to walk in experience even for an hour, just to respite, just to familiarize what that even feels like. If that's all that we can do, that's valuable. And so essentially that's exactly what you're talking about, right? And you can keep slicing that ever thinner.

to get all the various components of that to create that context. But that's, to me, that's what whole data pursuit is.

Tripp Johnson (33:03.713)
Totally. context. Again, I think so much as we're doing the Upfit over in Chapel Hill, again, so much of the healing process or that relationship is influenced by factors outside of those two individuals in a room together.

And so like we've got to set the context correct from the beginning. I got a kind of a non non sequitur on on this one and I lost my train of thought but I was really excited about it. What were you saying before that your supervisor who is so good. this is this is actually I believe this is the fundamental one of the fundamental things that has changed in my mind and thinking about data.

Marcus Shumate (33:35.785)
before we go at non -sequiturs.

Tripp Johnson (33:55.185)
And it's not about self -report. Like this, get away from the need for patients to self -report in order for you to draw insight on what you're doing. Because you can't necessarily affect their self -report. There's useful information in all of that. And I'm not saying don't use standardized scales, yada, yada, yada.

Marcus Shumate (34:05.539)
Right.

Tripp Johnson (34:19.925)
But I think like as an organization, like that's why we haven't jumped first to outcomes measures and sending surveys out and this and that. Because there is so much data for us to mine. There's so much that we're generating and there's so much that other people are generating if they don't even if they don't think about it. So.

Marcus Shumate (34:39.81)
Let's go.

Tripp Johnson (34:40.893)
Again, like the project we just, you know, we're working on some yesterday was this like we've got our CRM data and we've got our EHR data. There's a connection between the two, but we cannot get all of the information we want out of either system. And we actually have to combine those systems in our data warehouse. And then we have unique patient identifiers. And now all of a sudden we can correlate all of the front end data.

Marcus Shumate (34:56.493)
Yeah.

Tripp Johnson (35:07.657)
which means, you know, when they went to our website or filled out a form with our phone system data that's integrated, who they talked to, then, you know, we can start to look at how long until their first appointment from when they called and then how long, you know, like all of these things may play a much bigger role. Like,

This kind of boring stuff, like as a clinician, no one went to get a master's in counseling or social work or psychology because they really were interested in like the timeframe between scheduling to first appointment and how that's going to affect their relationship with their patient.

but maybe it's way more important than we think. And so I think like a lot of times like we want these reports that say, hey, everyone's sober and happy and they haven't had a hospitalization in so long. But really like there's all of this really valuable data. Like if that's the goal, there's all of this information that's very important and actually at your fingertips that you can start to leverage.

Marcus Shumate (35:52.845)
Yeah.

Tripp Johnson (36:15.553)
long before you need to talk about like longitudinal outcomes studies, right. And I guess that's been that's been one of the really interesting things from working with, you know, Donnie Bill and out in terms of like, hey, like, let's, you know, like, there's so much we can do, like, we, we get a patient survey, like our out of five stars, we have like a 4 .95 rating. And that's on hundreds of surveys, like 100 completed, you know, forms a month.

Marcus Shumate (36:20.301)
Right.

Tripp Johnson (36:45.045)
So we're generating like a very basic, you know, Likert scale data. And we will now be able to look backwards and see if there are any, like what factors may have influenced them being happy or unhappy. And that to me is like the, it's not the sexy stuff, but it may be the important stuff.

Marcus Shumate (36:59.512)
Yeah.

Marcus Shumate (37:06.892)
Yeah. Well, see, that's the thing though, right? Like I, I think the important stuff is sexy. And I, like, and I know that, right? Like it's just the stuff it's like, you know, it doesn't involve, like it's, that doesn't translate to a brochure super well, or, know, maybe that's cause I suck at my job and I can't figure out the language to make it translate to a brochure or something. like, to me, that's, yeah.

Tripp Johnson (37:28.265)
Right, you're not going to conferences and people are presenting on like, how can we limit the time between the first call to the scheduled appointment for an outpatient psychiatrist? But when Blue Cross was rolling out their value, like this attempt to do some value based work where you could get a bonus based on

Marcus Shumate (37:37.741)
Right.

Yeah.

Tripp Johnson (37:52.565)
you know, how quickly you schedule like access quality and affordability measures, like they they made you document all of this stuff along the way. So they had that data, like that did matter at scale. And they understood at scale, that data mattered. So yeah, it's it's really interesting, like, again, probably not why you go into the field. But

Marcus Shumate (37:57.219)
Yeah.

Tripp Johnson (38:18.062)
it is really sexy. Like if you can just deliver better outcomes because your scheduling is buttoned up, like that's sexy to me.

Marcus Shumate (38:26.776)
Yeah, I want to humanize this maybe a little again in a way, right? you know, like we've talked about, like was a therapist. You pointed something out to me one time that was really helpful. You're like, man, you might have been a better economist than a therapist because you're kind of interested in human behavior, like as a species, at the species level more than you are at the individual. And that was a profound interest and insight to me was like,

man, that was like this weird, interesting blind spot that I just didn't have, but it came into the frame when I had the right context and exposure to the right sort of rat playground or whatever you want to call it. And so what I was thinking about with this, just in this moment as you were talking about it, was thinking about someone that like we look at and we see, my God, your scheduling rate is through the roof. You're so quick, you're so efficient. And on top of that,

If we see that you've scheduled someone there's an 80 % probability that they're going to have this degree of outcomes at these benchmarks or whatever. You now found your place. And so I think about this seems like a bit of a non sequitur, but I don't think it is. I'm thinking about this Rick Rubin's book and the names have completely escaped me. What is it again?

It's beautiful. love it. But it's just like the, it's on art. How do you create art? And essentially he's this, for anyone that doesn't know, he's a remarkable music producer that's just been behind some of the biggest albums of all time. But he has this theory on creating art and creativity. And it's essentially, you have to see what kind of responds to you. And I think one of the things that's like,

Tripp Johnson (39:52.974)
Yeah.

Yeah.

Tripp Johnson (40:05.835)
Yeah.

Marcus Shumate (40:19.438)
If I think about the amount of work and time I've been putting in to try to learn something, if I wasn't in some sort of alignment with the things that I have some sort of proclivities to, interest in, ability or aptitudes for to feel like they connect to something, I couldn't do this. I would lose my mind. I'm not good at paying attention to stuff that I don't enjoy. I'm not good at getting better at stuff that...

I don't enjoy or doesn't tie together these things. so I think about, you know, again, like patient experience, but that patient experience is so closely tied to the organization, like the provider experience, not just like the med provider or the therapist, but the front office staff, right? And all of a sudden, if you have this data that's telling someone, hey, you're really good at what you do, you're really valuable, and you really improve people's life and you're part of a system that's making the world better. It's like, man, that's

That's awesome, right? And that becomes this orienting thing that allows people to have some sort of direction of what they want to do with their life and how they want to help people. And all of a sudden you start finding your aptitudes and you start finding the context that lets those flourish. And then that kind of lets you know when you're in this really nice zone of experience.

Tripp Johnson (41:37.727)
Let me, yeah, like to draw on, even though I think positive psychology has been overhyped in the last, you know, recently. But, you know, one of the one of the fundamental aspects of whether whether or not you subscribe to positive psychology, I do really like the book Flow, Mikhail, Cheeks and Mihai. I think it's just awesome. And and they, know, just how do how do we enter flow states or what?

Marcus Shumate (41:43.061)
Yeah, yeah, yeah.

Tripp Johnson (42:05.225)
What is common across people in flow states? And one of those is the clarity of goals and the reward in mind coupled with immediate feedback.

So what we're talking about and how we're leveraging data now is on a daily basis. This is not something that requires someone to plug in numbers in a spreadsheet and then check in to make sure they did it correctly, blah, blah. It's all ported directly from the operating system of our EHR, CRM, our website, our phone system, into the central repository that shows real -time feedback. So all of our data is updated every six hours.

meaning that we have really shortened the feedback loop, again, whether you're a provider or whether you're someone who's scheduling. So I think that's one of the other. The speed at which you're getting data out there is the other really big one. Because if you just sit on data, it's useless to you. Anyway, yeah. So I think, yeah, there's so many opportunities to.

Marcus Shumate (43:03.203)
Yeah.

Right.

Tripp Johnson (43:13.737)
you know, find out why we're enjoying an experience and use data to help us have more of those experiences. And I think that's the real, that's like the real hope and promise of our data initiatives.

Marcus Shumate (43:20.109)
Yeah.

Marcus Shumate (43:28.355)
good.

Tripp Johnson (43:29.811)
I think that went pretty well. I don't know. I'm excited. I'm excited to have Alphonse. We're to have to think through like he's I think we we've done some cool stuff and it'll be interesting to have our analytics developer on and talking about what's what's been interesting and challenging about you know he's never done a lot of healthcare analytics so getting used to a whole new kind of data model should be cool next week. So let's boogie.

Marcus Shumate (43:31.81)
Yeah.

Marcus Shumate (43:55.47)
Now, so, that's boogie. So for our 12 listeners, please download, tune in next week for all of that stuff. All of that stuff. Yeah, go leave a nice Google review on our AIM Chapel Hill website, because we're all nervous.

Tripp Johnson (44:04.213)
Download, like, subscribe. All of it, please.

Tripp Johnson (44:15.195)
we, we're, we, yeah, we, want to make sure people can find us. Yeah. And if not, we'll have the data to support Marcus's departure.

Marcus Shumate (44:18.722)
Yeah.

Marcus Shumate (44:25.166)
Next Friday you have a co -host. A new co -host. All right. Yeah.

Tripp Johnson (44:30.529)
Alright, well until next time.