Michael Pitt - When AI Listens Better Than We Do

The conversation this week is with   Michael Pitt, MD. Mike is an award winning educator, speaker, pediatrician, and entrepreneur. He's the co founder and CEO of Q-Rounds, a B2B SaaS for hospital systems, whose flagship product is a cloud based AI powered rounding cue, which provides notifications via text message to families of when to expect the provider for daily rounds.

This information updates in real time as rounds progress and offers one click telehealth connectivity. or family or medical consultants to join virtually. He is also a professor of pediatrics at the University of Minnesota and is a graduate of the John Hopkins School of Medicine.

If you are interested in learning about how AI is being applied across multiple industries, be sure to join us at a future AppliedAI Monthly meetup and help support us so we can make future Emerging Technologies North non-profit events!

• Emerging Technologies North
• AppliedAI Meetup

Resources and Topics Mentioned in this Episode

• Q-Rounds
• Jack's Basket
• Revenge of the Tipping Point by Malcolm Gladwell
• Discovery Launchpad
• Medical Alley
• Minnesota Founders
• Minnesota Cup

Enjoy!

Your host,
Justin Grammens

Transcript

[00:00:00] Mike Pitt: But there's a lot of work out there that shows that AI is better at empathy than doctors are. Part of the problem is doctors are, tend to be good at empathy in their real lives, but we get so Condition to the things that require empathy that we forget to do it. So, for example, if I saw you fall off a ladder, I might go, Oh, my, Oh, my gosh.

Are you okay? Like I'd run up and offer help. That looked terrifying. But if you came in the emergency room after falling off a ladder, I'd say, Did you hit your head on a scale of 1 to 10? What's your pain? Did you have any emesis? Right? I'd use of jargon word. We forget to the moment of empathy.

[00:00:36] AI Announcer: Welcome to the Conversations on Applied AI podcast where Justin Grammens and the team at Emerging Technologies North talk with experts in the fields of artificial intelligence and deep learning.

In each episode, we cut through the hype and dive into how these technologies are being applied to real world problems today. We hope that you find this episode educational and applicable to your industry and connect with us to learn more about our organization at AppliedAI. mn. Enjoy!

[00:01:06] Justin Grammens: Welcome, everyone, to the Conversations on Applied AI Podcast.

I'm your host, Justin Grammens, and our guest today is Michael Pitt, MD. Mike is an award winning educator, speaker, pediatrician, and entrepreneur. He's the co founder and CEO of Q Rounds, a B2B SaaS for hospital systems, whose flagship product is a cloud based AI powered rounding cue, which provides notifications via text message to families of when to expect the provider for daily rounds.

This information updates in real time as rounds progress and offers one click telehealth connectivity. or family or medical consultants to join virtually. He is also a professor of pediatrics at the University of Minnesota and is a graduate of the John Hopkins School of Medicine. And I'm super excited as I love talking with those who are both on the front of the medical lines of entrepreneurship and applying technology such as AI to solve challenges in healthcare, which we all know will have a real impact on making our lives better.

Thank you, podcast today. Thanks for having me. Awesome. Well, so you went to John Hopkins, right? Schooled in medicine. Did you always know that you wanted to be a doctor when you grew up?

[00:02:11] Mike Pitt: Yeah, you know, I grew up saying I did magic professionally. Actually, when I was eight years old, I started doing magic. I just came from teaching a class.

On magic in the undergraduate campus at the university of Minnesota this afternoon. So I always being involved in, in misdirection, et cetera, it was always part of my story and the place I volunteer the most was in hospital settings using magic and pretty quickly saw how magic and medicine specifically from the perspective of a pediatric patient.

Was the same thing, you know, take this potion and your symptoms disappear, et cetera. So for as long as I can remember, I used to say I wanted to be a magician, physician, pediatrician, you know, to people when I was a kid and did kind of power through all of those. So I guess the short answer is yes.

[00:02:51] Justin Grammens: I love, and the best part is they all kind of rhyme too as well.

[00:02:54] Mike Pitt: Exactly right.

[00:02:55] Justin Grammens: Yeah, that's cool. And so you still practice magic.

[00:02:57] Mike Pitt: Yeah. So I, I teach, you know, I show pediatricians how to use magic at the bedside, both. Practically how to use a trick to distract a patient, but more philosophically how we use misdirection already. And I think like a magician, a hundred percent of the time I'm at the bedside, even if I only do a trick for 5 percent of patients.

So I still do that. I still, I just emcee the gala last Friday night for organization I support called Jack's basket and use magic in that as well. So short answer to that is yes, I still get to do magic most of the time, sneaking it into my professional life.

[00:03:32] Justin Grammens: So my dad was a physician for his entire career, actually, uh, oncologist, hematologist at the University of Minnesota.

Actually, I guess it was M Health Fairview now, but it was way back when it was like St. Mary's. But you know, it's interesting. I got together with him this weekend and he likes magic tricks with cards, like card decks, right? So my two sons, they're 10 and 12 years old, and he's showing them all these new magic tricks.

So I'm just wondering if there's something there. Do you know any other doctors that are I'd like this. So

[00:03:58] Mike Pitt: there are several physician, believe it or not. I read this in a, in a Malcolm Gladwell book. Magic is disproportionately represented among Nobel prize winners across all professions. So I actually think there is something about the way you view the world differently, you're, you're actually looking at.

A solution that is not so front of mind that, you know, that it's obvious to everybody else that might set you up for success in the sciences, et cetera, for sure. Crazy,

[00:04:25] Justin Grammens: crazy. And I think there's also a tie with like music, you know, as well, I think it's that sort of abstract thinking. When we start thinking about abstract thinking, you obviously had this idea for this product.

I mentioned a little bit at the beginning, maybe you want to elaborate a little bit on what Q rounds is first, and then I'm curious to know about sort of like the genesis of it.

[00:04:41] Mike Pitt: Yeah, in short, if you've ever been waiting for the doctor in the hospital, that moment called rounds, when the doctor shows up and has that most important discussion, you felt a pain point that I felt when my father and father in law were hospitalized and I spent every day for hours a day waiting for that doctor.

I'm also the doctor. I do that. I go from room to room and often show up in the family is not there or the nurse isn't there. All of this team sport that is necessary of getting everybody in the room at the same time for what's called multidisciplinary family centered rounds. That's the best practice that almost never happens.

And ultimately our solution was saying, what if we knew when the doctor would be there? We've come to expect time transparency in every arena of our lives. Yeah. Where is my package? When is my haircut turn? When is the table ready at the Olive Garden? But we abandoned that expectation of knowing when the doctor will be there.

So we built a solution that's a software that sends real time updates that integrates with the electronic health record. The doctor drags and drops their patients into the order they plan to see them. And as they go from room to room, families and nurses get a text message. Families get a text that says, You're 8th to be seen, 6th to be seen, next to be seen.

And then families, without having to download an app, with one click, can RSVP. So they can say, I'm not able to be there in person today, but when you enter the room, call me. And now as the doctor, as I'm going from room to room, when I enter the room and the family's not there, and they've RSVP'd, with one click, I bring them on the line.

So we've built this at our, we've been live in Masonic Children's Hospital for over a year. We've had over 10, 000 family members join rounds remotely. We've tripled nurses being present at the bedside, which is known to decrease errors, uh, when the nurse is there for rounds. We've had families join rounds who wouldn't have been able to be there.

Otherwise, we would have to have chosen between quitting their job to be present for rounds every day or be having this option to do so remotely. So it's been really exciting to build that out. And I think it's that. Perfect type of solution where every user thinks it was made for them. The doctors are describing their days as being more efficient and feeling more connected.

Nurses are telling us they're eating lunch again for the first time in a decade because they know when to expect the doctor. And then families describe this as a game changer. Kind of why has this not existed before?

[00:07:01] Justin Grammens: Yeah, fabulous. So, and you were living on the both sides of it. You said you sounds like you had a family member here.

So, you were. Feeling the frustration as a patient, right, as well?

[00:07:10] Mike Pitt: Feeling the frustration, I was sitting in a Great Clips waiting room, and I got a text from Great Clips that my haircut was three rooms, you know, three turns away, and that I realized I had time to run next door and get coffee, and thought, my gosh, if they can give me the respect to value my time enough to come back and be on demand, essentially, why aren't we doing that in healthcare?

And so I met a colleague who I was doing some research with, who's actually a AI and machine learning specialist at the University of Minnesota, John Sartori, and said, could you build me the Great Clips app for health care? And that was the start. We got a 5, 000 grant and the rest is history.

[00:07:48] Justin Grammens: Wow, that's fabulous.

And so you were able to bring it into, you said, the Masonic Children's Hospital over there as just as like a pilot, I guess, right? Were they very receptive to it?

[00:07:59] Mike Pitt: Yes. So, you know, the value of being a professor of the University of Minnesota and in the Fairview system is kind of being an employee of that whole Venn diagram here was an opportunity to say, let's we're building something the same way.

If we had found a substance that we thought might lower blood pressure, help us test this in our home setting. It was help us test this. You know, we had to do the integration with epic way to work with their informatics team. So it was a big lift. In kind of that co development, but a key to our success to be able to figure this out.

I've had people say, gosh, how is this not invented already? It's such a common sense idea. I had somebody say, you know, it's like with FedEx. I know where my package is. I can watch the turns. Well, the difference in health care is the packages burst into flames in the middle of the route. New ones get added to the truck, the truck crashes.

So it's such a complex problem to solve those nuanced what happens as things change that I think others had started and given up and we kind of powered through solving this.

[00:08:58] Justin Grammens: And so, like you said, you got some, a little bit of, uh, funding to get this thing started. Like how many years ago was that?

[00:09:04] Mike Pitt: The first time we started building this was about 2019 in COVID.

We had a working prototype. We ran it in the NICU during COVID in a period where families weren't allowed at the bedside. So this was their visitor restriction was they weren't allowed to the bedside of their own child or the med student wasn't a lot of bedside because there wasn't enough personal protective equipment.

So the very first patient The text message went out to the family in Duluth, the nurse was at the bedside, and the med student was in St. Paul, and they were all triangulated at that point with a Zoom call. So we were using kind of existing technology and have now built out a full version that integrates with the EHR.

[00:09:42] Justin Grammens: Gotcha, okay. It takes some time to sort of pull all the pieces together, I'm sure, especially around integration with Epic and obviously people have to sign up and get their phone numbers in there, right? It sounds like it's very text based right now.

[00:09:53] Mike Pitt: Yeah, so the beauty of it is the nurses and the patients don't have to download anything.

The nurses, you know, when they're admitting the patient in through Epic or through the EHR, one of the questions they ask the family is what number would you like to receive text from the doctor? So by asking that in Epic, that enrolls them in Q rounds. And then the family, if you've ever been to a hotel and you get a text that your room is ready, You didn't have to download anything.

It's analogous to that. They get a text from to their phone. So there's nothing for them to learn. I think that the fact I'm the most proud of the doctor is the one that has to do something. They have to build the queue and order the queue and hit next as they go from room to room. I was always worried we could have the greatest idea in the world, but if it didn't make doctors lives better, they wouldn't use it.

We've been live for over a year. We've not had a single day in the NICU that the doctors get together. have chosen not to use Q Rap. It's become the standard of care and is rolling out to other parts of the hospital as well.

[00:10:48] Justin Grammens: Fabulous. Now, you mentioned a little bit about multidisciplinary. So like, actually my younger son, when he was born, he had some problems with his glucose.

And so he actually had to go into the NICU and he was in the NICU for a couple of weeks actually before his body kind of kicked in and started working properly. But I remember sitting there and you had all these specialists around, right? There were six, six different ones, right? That had actually looked at all of his vitals and stuff like that.

Are you dealing with those situations too? Yeah,

[00:11:16] Mike Pitt: yes. So one thing we're doing in the NICU is a perfect example. You know, you might have the neonatologist, but you also have the dieticians, the pharmacist and maybe the cardiologist, you know, other people that are involved. So Q rounds also pushes that Q in real time to the electronic health record.

And I didn't know how valuable that was until one day that connection didn't work. And it was the dieticians, the social workers, the respiratory therapist who said they were relying on that real time update to know when to join those teams to get everybody ready. Yeah. Yeah. We're also working on a feature that would allow you to, you know, the number one question nurses are asked in the hospital is when will the doctor be here?

We're answering that question. The number two question they ask is among those six consultants. They say, do you even talk to each other? You know, they were in the room. They said this, you were in the room, you said this. What we're aiming to do is that cardiologist gets the text message that knows when we're going to be there.

They can join remotely. So I can say, Oh, you know, the cardiologist is actually able to join for this question and the family sees me have that conversation. That leads to not just more satisfied patients, but better outcomes and more satisfied team members because we're more effectively collaborating.

[00:12:27] Justin Grammens: Fabulous. Yeah, this is, this is awesome. So you guys have a working thing right now. It's being used, people are loving it. Who's paying for it? I guess, uh, you know, there's, there's a whole business side to this. I'm curious.

[00:12:38] Mike Pitt: And, and the, and the hard part about this is again, this wasn't, I want to be an entrepreneur when I grew up.

You know, I'm a pediatrician. I was an English major. I chose English as a major. In college, because I cared about how we communicate with patients that I wanted to work on being an effective communicator and realize you could be the smartest doctor in the world. But unless you're communicating effectively and your patients understand what you're saying, you're useless.

And that's been a huge part of my research career is looking at jargon and how doctors confuse patients. The reason I say that not wanting to be an entrepreneur when we grow up is I wanted it to be good enough that look. Doctors love this. Nurses love this. Patients love this. You should have this learning the medical business side of things.

That's not enough that like being something that every stakeholder wants and is the most common sense thing that any person in a room would say. I want that when my loved one is hospitalized. I would want that isn't enough. We have to show how this affects the bottom lines of hospitals. And so we just published our first paper that showed it.

Tripling of nurse presence more than doubling of family presence, both of which are known to decrease errors. So we're starting to look at things. Can we lead to fewer malpractice claims because we're getting everybody together? Can we turn beds over faster because everybody's getting together? Those are things those pulling in the consultants.

Can we generate billable consults for the hospital system that are otherwise being left on the table? Cause somebody just asks a question on the side. So we're looking at ways to affect top and bottom line. The short answer is we're expecting hospitals to pay for this because it can move the needle on all of those things and wouldn't want this to ever be a cost that's shouldered by patients.

But learning to make that case and show them that ROI has been a huge learning curve.

[00:14:22] Justin Grammens: Yeah, for sure. And I mean, that's pretty much for any business, I guess, and especially even more in this AI space, you know, so my, I have a software company and we build AI solutions for companies, but a lot of them, they're not ready to take a big bite.

They're kind of nibbling around the edges because there haven't been enough of these studies, frankly, done to show what is the ROI on us bringing a more efficient system into your business. And I think the bigger challenges are things the way that they've always been done in the past. And I, I feel like healthcare is probably just a prime example of that, right?

[00:14:52] Mike Pitt: It is the worst example of change management, you know, of slow to change, you know, archaic systems. And I think this is a perfect example with Q rounds is something that in every arena of our lives, we're used to this. And so I do think that's where we'll start to see change happen a little faster.

Healthcare is going to go, yeah, well, I'm doing this in every other space. Why are we not? Doing this here. The interesting thing, and I'm curious, your take on this too as a AI software company, is I find myself leaning away from the AI moniker a little bit. Like for a while. And actually I think in the bio you read, we would say an AI powered virtual queue.

Yeah. And I remember doing a, when we were raising capital a VC saying, oh, come on, everybody's saying that, you know, cinnamon Toast Crunch could be saying AI powered at this point. And recognizing that, you know, in many ways, at the barest definition of AI, of just computing, like replacing human thinking with computing, everybody can say that, you know, it's getting into when you start getting into the machine learning and LLM stuff, that's interesting.

But I found myself leaning away from the AI pitch and more, this is something that takes the cognitive load away. Doctors are telling us. Man, I'm doing this anyway. I'm having to track these families down. I don't get to walk in a room if a seven month old is there by themselves and the parents are there.

I don't get to say to the seven month old, tell your mom and dad what we talked about, right? I have to find that. So by showing them, look, we're saving you time that you can easily wrap your mind. But not trying to oversell it as AI. I'm feeling like I'm having more success. So I wonder if that pendulum is going to swing it back a little bit and then people will be more comfortable with it.

[00:16:31] Justin Grammens: That's a great point. Yeah. Lots to, lots to digest, you know, so we talked about applied AI at the very beginning before we kind of went on the air here, where, you know, we've been doing stuff and I've been working since 2019 in this space. And it seems very early, not early for AI. Like we said, AI has been around for a long time, but I think that the key word here is generative AI.

And so I think the explosion of Gen GPT has made people call everything AI, you know. And so you're right. What your system really is a prediction algorithm, it feels like in a lot of ways. It's, you know, machine learning, deep learning. It's those types of techniques that make predictions on where people are at and where they're going to be and bring all that together.

Now AI as a, I like to call it a portfolio of technologies as, uh, underneath this AI umbrella. Certainly it's underneath there, but you're right, people were slapping AI on everything because of the new hot gen AI wave. I think that hit and yeah, I would, I would definitely agree that, you know, uh, I would say over the past couple of years we've seen everybody put ai, AI on all sorts of stuff, and it's like, you're right.

Come on, what are you serious?

[00:17:31] Mike Pitt: And I think that's the part when you realize that simplest definition of AI is already doing everything that we, you know, in every interaction we're having in life, it is start to fun to think of, like, where will we as key rounds be using machine learning more, for example, and it is in that.

The doctor gets to make the decision of the order they're seeing patients in, but we recommend it based on, for example, that if more than one patient has the same nurse, it's going to be inefficient for you have to track that nurse down twice. So we'll suggest grouping those together. We'll also be able to suggest based on your decision.

So if you if I'm saying, you know what, I need 10 minutes per patient, and it knows, Hey, Mike, You're not as efficient as you think. You usually need 14 minutes for patients. We can start to actually make it based on our own practice. The generative AI stuff that's exciting. You know, we are having conversations with families now that aren't able to be at rounds.

Thousands of families who previously couldn't have been there are participating in this discussion. That is an audio conversation that could generative AI summary. A jargon list summary of what rounds discussion was, because if you think about it, we know patients were retained about 10 percent of what the doctor says in the room.

If I could all of a sudden go back and have a summary of that, it was texted to me right after the call via Q rounds. That's the type of work we're looking at. That's kind of in that next gen AI space, I

[00:18:52] Justin Grammens: guess that I was going to get at is, is yeah. Where do you guys go in next? So, you know, the doctor makes.

Their selection is or her makes her selection on sort of the ordering of this. They do this through a mobile app, you said, or

[00:19:02] Mike Pitt: yeah, they could do it through the app in the app store or they can log in through the computer that they're working on in the hospital.

[00:19:07] Justin Grammens: And then as they're walking through the meeting with patients, do they actually pull up the app and say, Don, move on?

[00:19:11] Mike Pitt: Yeah, that is. So as you're going from room to room, you'll hit next that updates everything downstream. You could also rearrange the queue. If something came up, you could pause rounds, which texts everybody downstream. That the doctor has been pulled away and all those times are going to adjust. You know, there's a lot of work out there already that shows that just saying an order to rounds, committing to that in the morning leads to faster turnover, more efficiency, etc.

But that order is often obsolete. You literally, these studies involve somebody writing it and faxing it to a charge nurse. Ours is in real time. As you're going from room to room, it's updating. We had played with a version that used a beacon and Wi Fi. You know, that knew that you were leaving the room and automatically updated the cube, but we found we didn't need it because doctors needed to know where to go next anyway.

So they were looking at it accidental benefit. We found his doctors are learning the names of nurses that they've worked with for decades because they're physically seeing. That when I hit next, okay, I'm waiting for Sandra to come to this room. Sandra has been pinged and it's just this real time. I don't have to hope that the badge is facing the right way and get caught reading it.

I've looked at it right before they come to the room,

[00:20:22] Justin Grammens: which can lead to more personal interaction. And just, you know, like I said, which is kind of a piece that I'm thinking of right now is, you know, where are humans the best, right? Humans are the best in this bedside manner, right? Bring the AI in around these repetitive tasks.

But at the end of the day, you want the doctor to still be more personable and be able to work.

[00:20:39] Mike Pitt: Yeah, and I think about some of the studies that are both scary and inspirational about A. I. S. You know, I think I used to say, Well, yeah, we can get them to help make the diagnosis. But you want the doctor sitting with you telling you have a cancer diagnosis holding your hand.

But there's a lot of work out there that shows that A. I. Is better at empathy than doctors are. And I think part of the problem is doctors are tend to be good at empathy in their real lives. But we get so little. Condition to the things that require empathy that we forget to do it. So for example, if I saw you fall off a ladder, I might go, Oh my, Oh my gosh, are you okay?

Like I'd run up and offer help. That looked terrifying. But if you came in the emergency room after falling off a ladder, I'd say, did you hit your head on a scale of one to 10? What's your pain? Did you have any emesis, right? I'd use a jargon word and said, we forget to the moment of empathy. Or if somebody says, gosh, I've stopped taking my blood pressure medicine ever since Sally died.

What's the point? And we say data, the point is your diastolic blood pressure was this. The point is we forget to do the empathy of, yeah, I can't imagine how hard that is, you know, before we move into that. And I, I think the fact that we could actually learn, you know, there was a study that asked people to read the summary of their labs from their doctor or from.

AI and they found that AI was more empathic 'cause it was really easy to train it. Yeah. To do that, to not forget to be empathic. So the sh the short of it is yes, we are conceptually better at the bedside, but we better watch out and we better learn how to actually really bring that skill to the table.

[00:22:10] Justin Grammens: That's good. I had not heard that study, but I totally know exact that we were talking about. 'cause like I said, I was in the ER last week and it was that exact same thing. They knew nothing about me or about the accident. It was just the questions around. What is the pain level? And then you're right, like the terms.

Oh, they had to, I had to do a CT scan of my face to make sure nothing was broken. Right? And actually the results that came out on my chart, I was like, what the hell? I don't even know what you're saying here. Like, is my face broken or not? It's

[00:22:36] Mike Pitt: infuriating. And it's so, you know, the studies we do on jargon, we go through seven categories of jargon and we've identified this because doctors say, I don't use jargon, but we're terrible at it.

And what we said, well, the reason that disconnect occurs our self perception that we're good at it and the reality that we're terrible at it is because we just forget there's a point we didn't know what those words meant. We forget that people don't know that febrile means fever. So we just say it because we think everybody knows it.

And part of the way we've studied this is we go to the fair at Minnesota, the state fair, and we survey adults and we say, If your doctor said X, Y, or Z, what do you think they mean? We ask about job titles. If a dentist takes care of teeth, what does a pediatrician take care of? Only 89 percent knew kids.

The most common wrong answer was a foot doctor, podiatrist, nephrologist, a kidney doctor. Only 20 percent of the adults knew that. The most common wrong answer was a doctor of death because I think they were thinking necro. So imagine if you're seeing a referral to the nephrologist and you're part of the group that thinks that means you're dying.

So examples that get written in charts, there are words that mean something in English. We call this the fifth category of jargon we use. called medicalized English. They mean something in English. They mean an opposite thing or different thing in medicine. A classic example is negative. The test results were negative.

That is good news in medicine, but negative in any other capacity, negative feedback at a restaurant, negative reviews, bad. We ask people at the fair, if your doctor says your tumor is progressing, is that good news or bad news? 21 percent of adults thought it was good news because progress is good. And to your point about reading a CAT scan, unremarkable.

That is good. When a doctor writes something, it's unremarkable. But in most of life, we want to be remarkable. I gave a lecture and somebody said, I got a CAT scan, I read the results, and it said, testicles unremarkable. And he said, for years, I was insecure about this. I want remarkable testicle. I went to college and for all of college I was insecure that my testicles were unremarkable until I went to medical school and realized it was normal.

So to your point, I think, I actually think that's a huge space for generative AI is. I mean, people are going to do it anyway, right? You might have copied your own, right? Dart into chat. Yes, we should escape that middleman, develop LLMs that are specific to jargon decoding and give that clear summary for people.

[00:25:06] Justin Grammens: Love it for sure. So you're thinking that then this app, the doctor as you're meeting with the patient could just push record and potentially.

[00:25:13] Mike Pitt: Well, right. And so what went because a lot of our families are joining remotely. They're in the NICU, for example, where these length of stays might be for two or three months.

The families are back to work. They're RSVP ing for a call. And so that call with the family's permission could be recorded. And Jenna, you know, an LLM used to summarize that into a jargon, less report for the family.

[00:25:36] Justin Grammens: Fabulous. That's cool. Lots to think about and talk about, Mike. So yeah, so you guys, were you guys a part of any of like what the Minnesota cup or any, any of those other things in town?

[00:25:45] Mike Pitt: The Minnesota landscape is such an amazing place for. It's obviously a great place for entrepreneurs, but it's a great place for the accidental entrepreneur. And that's what I would consider myself. This again. It wasn't what I went to school for playing to learn and had a lot of on the job learning of how do you tell your story?

How do you raise money? How do you hire a team? And that was Through work through the Office of Tech Commercialization and the Discovery Launchpad at the University of Minnesota through the Medical Alley and Founders Club. And yes, we actually won the health care category for Minnesota Cup two years ago.

And for your listeners who may not know, that's that entrepreneur competition for startups in the state of Minnesota often have up to two to three thousand entries in that. It's a great place. where you get coached along the way and have opportunities at mentoring and prizes.

[00:26:33] Justin Grammens: Yeah, I will for sure. I've got liner notes as a part of the podcast.

So I'll be sure to put links off to Minnesota Cup, obviously your guys website. And how do people find you, Mike?

[00:26:43] Mike Pitt: So q rounds. com, you know, the concept being you're waiting in a queue, like you're queuing up and we're making that. available for people in real time. You can email me at mike at q rounds dot com.

I am here in the Twin Cities. I still practice medicine. It is important for us all along to not be a scenario where we said, I was a doctor. I knew this problem. It's very important for me to be able to say I am a doctor. I know this problem. I feel it every day. I use Q rounds when I round and it's been really fun to bring it into our hospital system.

We have our first contracts that are being finalized at other systems outside of Fairview. So we're hoping in the next few months that this will be at multiple hospital systems.

[00:27:23] Justin Grammens: Yeah, I hope so too. I mean, like you said, it's as long as you guys can sort of show the ROI on this, which, and sometimes it's just one vector, like, oh, we're just going to make this thing be more efficient, but it feels like you mentioned there's four or five different ways, right?

That I think hospitals can show a positive benefit of this.

[00:27:39] Mike Pitt: For sure. And we've been talking to hospital systems that said, you know, often with technology, we need to see a 30 X return on investment. And what we're hearing from the C suite when they get this problem is just show us one X, just show that you can cover the cost of this.

Cause it's so obvious that this is valuable. And again, that could be one less malpractice claim in a year. That could be turning a bed over. You know, of three tenths of a day faster generates the entire cost for the year. So we're really looking to capture those things, including engagement. Nurse turnover is one of the most expensive parts of hospital systems now, and we're creating a way to make nurses feel part of the team empowered, valued, automatically included that we imagine what would actually have a point of positive impact on burnout and engagement.

[00:28:25] Justin Grammens: Fabulous. No, this is great. This is great. I'm so thrilled you were able to make the time to be on the program today, Mike, and wish you nothing but the best. In fact, I'll have to have you potentially come and speak at one of our applied AI events. We do these monthly meetups and we have this conference and stuff.

So definitely want to keep in touch with you, have you more engaged with our community here in the Twin Cities, but your product is fabulous and Obviously, you're very passionate about it. I can just tell in your voice and the stories that you've been telling. So, I mean, it's, this is the perfect situation, right?

You have an entrepreneur that has a problem that they need to, an itch they need to scratch, right? And you've been able to bring the technology component in just at the right time for it. So, super excited for you.

[00:29:04] Mike Pitt: Appreciate it. Thanks for having me and thanks for the great work you do.

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