Ep.27 - Danneelle Crisp I Healthcare Journeys I S2M Health Podcast

Meet Danneelle Crisp.

Danneelle Crisp is the Founder and CEO of ElleLogic AI, a Canadian health-tech company focused on transforming how hospitals operate by using artificial intelligence to improve patient flow, operational efficiency, and clinical decision-making.

With a strong background in operations, strategy, and systems design, Danneelle has built her career at the intersection of technology, people, and process—helping healthcare institutions tackle one of their biggest challenges: doing more with limited resources while maintaining quality care. Her work is centered on reducing inefficiencies within hospital systems, enabling better coordination, and supporting scalable, sustainable growth in healthcare delivery.

Currently pursuing her EMBA and already holding an MBA, Danneelle brings both academic depth and practical experience to solving real-world healthcare problems—making her a powerful voice in the future of AI-driven hospital operations.

In this episode of Healthcare Journeys, Danneelle shares how AI can move beyond hype to deliver tangible impact inside hospitals—especially in areas like patient flow, system bottlenecks, and decision support.

Here’s what we discussed:

How AI is improving hospital operations and patient flow
The role of systems thinking in solving healthcare inefficiencies
Supporting clinicians with better, faster decision-making tools
Scaling healthcare operations sustainably in resource-constrained environments
Bridging technology, people, and processes to drive real-world impact

Danneelle’s perspective highlights how operational excellence and intelligent systems can come together to create more efficient, responsive, and patient-centered healthcare environments.

✨ Exclusively, only on Healthcare Journeys!

Don’t miss this opportunity to gain insights from a leader dedicated to making healthcare more effective, accessible, and patient-focused.

🎧 Streaming on all platforms. Podcast link in the comments.
#HealthcareJourneys | A Podcast by S2M Health

Transcript

SPEAKER_00 0:00

What we have realized emergence departments aren't broken because of people, they're broken because of systems.

SPEAKER_01 0:05

Was there anything you saw, like some sort of a moment that that you witnessed in in healthcare that made you realize that the technology wasn't being used to its full potential for hospital operations?

SPEAKER_00 0:17

So that was the moment for me when I realized there needs to be a system that supports patients but also clinicians.

SPEAKER_01 0:25

Is there any particular component of uh healthcare of the operational side that you feel is the most overlooked?

SPEAKER_00 0:33

Yes. Having data in real time.

SPEAKER_01 0:35

What we have learned is hospitals have a lot of data, a lot of how do you define the line between AI making a decision and AI supporting the human decision-making process?

SPEAKER_00 0:47

Our goal is to help clinicians see what matters faster so they can make decisions better on their pressure.

SPEAKER_01 0:54

Hello and welcome to Healthcare Journeys. I am your host, Kevin Rosenchris. Thanks for joining me today. This podcast is brought to you by S2M Health, a trusted partner for U.S. healthcare payers and providers. From accurate risk adjustment coding to full spectrum RCM services, S2M Health combines clinical expertise with precision operations to drive better outcomes across the healthcare ecosystem. Our guest today is the architect of a new kind of air traffic control for healthcare. Danielle Crisp is the founder and CEO of L Logic AI, a Canadian health tech company that's moving hospital operations from reactive firefighting to predictive precision. With a deep background in systems design and operations, and recently recognized as a 2025 startup test student entrepreneur, Danielle isn't just looking at the data, she's looking at how patients move through a system that was never designed for this level of complexity. Danielle, welcome.

SPEAKER_00 2:15

Hi, thank you for having me today.

SPEAKER_01 2:17

Absolutely. I'm excited to chat with you. You have a very impressive, uh, impressive resume that I went just just uh went down there. Tell me, tell me a little bit about the what the the startup of the the startup of the year or the start sorry, startup uh fest student entrepreneur. What what uh what what wouldn't what did that entail?

SPEAKER_00 2:32

Oh I have to tell you, that's a crazy story. So I wasn't going to go in the first place. Like L Logic was a new company. We started in 2025. And the morning of Startup Fest, I bought a ticket, uh, given that we were just a few months old at this point. Went. Um there was one category of a student entrepreneur because I'm currently doing my executive master's, so I'm still a student. Um, so I pitched and we won the one category we pitched for first.

SPEAKER_01 3:01

Oh, that's awesome.

SPEAKER_00 3:02

Yeah, and um we won, we got the prize, and then I was like, okay, so what else? You know? And the final pitch, actually, I was in a car accident getting there.

SPEAKER_01 3:14

Oh my gosh.

SPEAKER_00 3:15

Yeah, and I still showed up and I did my pitch. I was like, guys, I did not prepare for this. I was in an accident, I showed up, and yes, maybe sympathy, but maybe it helped.

SPEAKER_01 3:25

Who knows? Wow, that is wild.

SPEAKER_00 3:27

Yeah, it's a crazy story.

SPEAKER_01 3:29

Well, congrats on that. Uh, sorry about that. I'm glad you're okay. Hopefully, car's okay too.

SPEAKER_00 3:34

It was a little dent. You know, it wasn't the first accident, you know, it happens.

SPEAKER_01 3:38

It happens, it happens, absolutely, absolutely. Well, you know, you you know, as I alluded to, you have a deep background in operations and strategy. Uh, now you've moved into the AI space. Was there was there anything you saw, like some sort of a moment that that you witnessed in in healthcare that made you realize that you know the technology wasn't being used to its full potential for hospital operations?

SPEAKER_00 4:01

I have to say, um, my family's also in healthcare. My uncle's a doctor, my mom is a nurse. So I've had insider vision in what's happening behind closed doors. And I have many friends now who are nurses and clinicians. But the key moment for me was in 2024, one of my close friends, their parent, went to the ER with significant chest pains after waiting over six hours, over six hours, well over, they sent her home saying it was just heartburn, right? And then within an hour of arriving back home, she died of a heart attack.

SPEAKER_01 4:37

Oh gosh.

SPEAKER_00 4:38

So that was a moment where I'm like, how could an elderly person go to the ER wait for such a long period of time only to be sent home to die?

SPEAKER_01 4:49

That's crazy.

SPEAKER_00 4:50

Yes, that's crazy.

SPEAKER_01 4:51

I've had a lot of heartburn in my life. I wouldn't believe a heart attack would feel the same way. At least I wouldn't think so.

SPEAKER_00 4:57

I hope not.

SPEAKER_01 4:58

Yes.

SPEAKER_00 4:59

So that was the moment for me when I realized there needs to be a system that supports patients, but also clinicians, because there's two sides to this coin. Clinicians can only do so much with limited information, limited support. But also patients are the one ones really at risk. They're risking their lives each time they go to the ER for care if they're not met with the resources needed.

SPEAKER_01 5:25

Wow, that's a crazy story. But yeah, you're right. I mean, it's on both sides for sure. And you, you know, uh, so your company is L Logic AI. Uh it emphasizes more of a human-centric solution. So, in an industry that is kind of often wary of AI, you know, replacing doctors or, you know, what have you, how do you define the line between AI making a decision and AI supporting a human's decision-making process?

SPEAKER_00 5:52

Yes. So at the core of L logic, we are building an intelligence layer that sits with emergent department emergency departments. Our goal is to help clinicians see what matters faster so they can make decisions better under pressure. We are not replacing clinicians, we're removing chaos around them, right? We want to provide them clarity and clarity, they need to trust us. Because what we have realized, emergency departments aren't broken because of people, they're broken because of systems. Yeah, right. Um, they have a coordination problem, and clinicians are operating blind in an environment that requires precision. Think of us as we don't want to add more tech, we want to make existing workflow smarter, right? From intake to triage, patient flow to um discharge. We want to be right there with the clinician, helping them to ensure they get support, but also patients get the care they deserve.

SPEAKER_01 6:52

And I think, you know, obviously not a hot take exactly, but people are a little nervous about AI, and we all know that. But you put it into a healthcare setting where people are already uncomfortable a lot of times. The average person is already uncomfortable in healthcare settings a lot of times, whether it's the insurance process, the doctors themselves, whatever, it you're gonna add an extra layer of worry. But people need to realize it's not about the the AI in the healthcare space, it's more about processes and making things better and making things more efficient. Do you do you do you feel like people don't necessarily realize just how crazy the healthcare world is? Like, you know, I have a sister who's a nurse too, and like so I have some I have some understanding of how insane it is. Do you think people just don't really realize how broken certain aspects are?

SPEAKER_00 7:38

I think they're realizing it now, given the augmented wait time we have, um, people in ARs dying in during wait times. I think now it's more visible to the public. But for clinicians, they're feeling it more, whether it's from burnout, people just not going in that sector anymore, people stop working or changing careers. But um, it's something that the more you deep more, the more you dig into it, the more you realize there's more problems and more problems, or companies put in point solutions that only fix one problem but create three others. And then you realize okay, a lot of hospitals might have long wait times, but this it's not the same problem that's causing the long wait time. So, how do you go in multiple hospitals, fix the issue, but actually find the core of that issue to create a sustainable solution?

SPEAKER_01 8:35

Is there any particular, you know, component of uh healthcare of the operational side that you feel is the most overlooked?

SPEAKER_00 8:45

Yes, having data in real time. Um what we have learned is hospitals have a lot of data, a lot of information, but connectivity is simply just not there. You can go to one hospital today and they can assist you go to another hospital tomorrow. That information does not follow you. So having access to data in real time, patient history, symptoms, prescriptions can save so many lives and help clinicians so much.

SPEAKER_01 9:14

It feels like it feels insane to me. It's 2026, we have so much technology even before AI. It kind of seems crazy that it doesn't that that data isn't readily available. Why why has that been so slow for it? How why has it been so slow for the healthcare industry to adopt technology to help this?

SPEAKER_00 9:33

Well, once again, technology in healthcare is always not as easily ready, right? Because you have regulations, you have a lot of doctors that are used to it a certain type of way, protections. And once again, having data is power, right? So giving access to data to someone else is you giving power to someone else because you having that data, you have a now currency why hospitals want to talk to you and you have that protection. And you want to ensure you're releasing that data to something that is credible, safe, and reliable, right? So hospitals are a little harder to adapt. And given that everything is paper-based before now, having that converted into technical um sheets and documents is not easy. It's not an easy feat. So having those converted is one thing, but having that connectivity in multiple hospitals is another thing.

SPEAKER_01 10:29

Yeah, true. And it's not like a hospital can just be like, all right, we're gonna shut down for a week and get our new technology implemented and stuff. It's not like they can do that. So they gotta figure out ways to implement stuff while they're still running at potentially full capacity.

SPEAKER_00 10:42

Yes.

SPEAKER_01 10:43

Yeah.

SPEAKER_00 10:43

Yes. And hospital strategies are not getting better, right? More and more people are going to the ER. There are more and more sickness, there are more and more needs, there are more and more things happening in the world now that we need hospitals. But if you have a system that can support hospitals better, have a system that can uh that clinicians can rely on, that patients can trust, then it no longer becomes a silo environment, but a connected community that people can go and trust that, okay, I will be seen in the utmost priority of my symptoms and my medical history and get the care I need when I need it most.

SPEAKER_01 11:21

So you're a Canadian company, uh, you guys operate in a single payer system uh that's gonna face unique scaling challenges compared to the US. What do you feel like the rest of the world uh you know, what what can the rest of the world learn from the Canadian approach to integrating AI into public health systems?

SPEAKER_00 11:41

Well, there's a lot of things we can learn. In Canada, we have our system might be lacking resources, but we do not lack community here. That's something I have learned and something I really applaud Canada about. With a logic, I think if the world look at it at a way as um time-saved, decision-improved, or outcome influenced, that would change the way we view healthcare. If, for example, in America, healthcare is viewed as a business and patients they didn't go to the ER, they really think, do I want to have this medical bill? Can I afford to go to the ER? If we can change that perspective of, okay, I'm gonna have, instead of thinking I'm gonna have a really long wait time plus this really augmented medical bill, okay, I'm gonna go there and get the care I need at the fastest possible way with the resources I actually do need, that would be a better way to look at it. Not as, okay, how much do I have to pay, but what support can I actually get?

SPEAKER_01 12:44

Mm-hmm. Yeah, you're not kidding about the it was a whole topic for a whole nother day, but uh yeah, it is definitely a business down here, uh, no doubt about that. Um, you know, one of the things I think that that hospitals kind of have to operate as a react in a reactive mode. You know, they respond to a crisis, you know, as it happens, but it's really hard to be predictive uh in that environment. You know, how can Ellogic help uh a hospital CEO move toward that predictive model? And what is that what have you seen that shift do for maybe the mental health of the frontline staff?

SPEAKER_00 13:24

Yes, so I have to say building a company like L Logic to be more proactive than reactive, you have to be very disciplined, right? You have to figure out how to balance being um accurate, um, what factors you to consider into being more proactive, and what can you do to make sure you can maintain a level of trust and credibility? How we do that is to take in the hospital by their geographical area. Each hospital are located in, for example, I'm in Quebec in Montreal. It's very French, right? So if I was to go into a hospital here, I would think about okay, it's a French environment. So our primary language should be French for the hospital systems. We have other secondary languages, but primarily should be French. Okay, well, we have winters, so we have snow. So in a winter, we're gonna have winter storms, we're gonna have um ice storms, we're gonna have snow. So whenever the weather is augmenting a certain type of way, we update with that. So we can now say, okay, there's Halloween coming up, so it's more likely we're gonna have more people based on past patterns on Halloween. There's been augmented people in the ER. So we need more resources, we need more staff in the ER, we need this doctor. We can now predict what's happening in the ER. But also a key of our software that is a pros and cons, I would say some people like it, some people don't, is that we can also um notify you when a doctor has been overstretched, when they've been on schedule for way too long, and it's time for them now to take breaks because breaks is important, meaning a doctor's high stress, high pressure. So we have that little ping on our schedule, like, okay, this doctor worked two double shifts now. Having them work another shift will not be the best decision.

SPEAKER_01 15:21

Yeah, they need to go home and sleep. Yes.

SPEAKER_00 15:23

So we have that feature that not all of our customers would like, but it's a good option out there so you can make sure you're making the right decisions to help mitigate certain risk, certain incidents in the ER to make sure everyone there is optimal and no longer now we just think about okay, how can we react to this? We're like, okay, we're fully now prepared or fully staffed or fully equipped for what's to come.

SPEAKER_01 15:48

Do you you know, do you find that doctors and nurses in in Canada have the same burnout issues that we see here in the States?

SPEAKER_00 15:56

100%. Um, a lot of people now in healthcare, we have the shortage shortages. We have people looking for different careers, we have people saying that it's not a good environment to be in right now. The wait times here are crazy. Uh it's it's not the best environment right now. Yes.

SPEAKER_01 16:18

Yeah, it feels like obviously COVID had a lot to do with that, um, of the burnout. I know that a lot of people down here had a lot of burnout and there was a lot of issues with that uh coming from from COVID. Did you do you feel like that was a big a big part of it? Is it is there are there other factors at play?

SPEAKER_00 16:33

Uh I think COVID really showed us the system we had and why we need to improve and why it would not work going forward. COVID was really a stress test for our health system and emergency systems, and really showed the cracks and opened them wider in COVID. Right. And from then on, which is now, it's continuing is continuing to widen that gap to show us what really matters and remind us that healthcare is about people and it's about people being there for people. It's not about the bottom line all the time, it's about the impact you make in someone's life and that going to the ER, people are looking for care and human-centered technologies. Not that they don't want the best results or the best medicine, but they sometimes, like sometimes I'm gonna speak about my grandmother a little bit. She sometimes would probably go to the doctor to have someone to talk to, right? Because you can. Does that mean like you don't need a system like this that can say, okay, she's a repetitive offender? But but to have that system where you have that bandwidth now to say hi to an elderly lady, wouldn't wouldn't that be nice again to bring that back?

SPEAKER_01 17:47

Yeah, yeah, I like that. I like that. Yeah, and I so so you mentioned before that that you know moving from hospital to hospital, not a lot of communication there, but it can even be in the same hospital, right? Where pharmacy doesn't talk to radiology, doesn't talk to nursing. Uh the they it feels a lot of times that they're kind of all in their little bubbles or their own little silos. Do you feel like AI can act as that sort of connective tissue to bring these bring these departments together?

SPEAKER_00 18:17

100%. Um, it's crazy to think that you can be in the same hospital and go from the ER to the ICU and they ask you the same triage questions.

SPEAKER_01 18:25

Yeah, they ask you all the same stuff, and you're like, I just did this.

SPEAKER_00 18:28

Yes. What's your name? It's the work injury along as well. So honestly, that's exactly what we see. It's not between just hospitals, it's within them. You know, you have all these highly specialized departments and people within and systems doing great work. They're operating in silos, though. So because the systems don't naturally connect with them, enter the hospitals, and I think that's where AI can play a really important role, not as another system, but as a connective tissue, as you said. And the way I think about it with L Logic is how do I create a layer that sits across those workflows and brings the right information to the right person at the right time? Because the issue isn't that people aren't communicating, is that systems aren't designed to support real-time coordination. So if you solve that, you don't just improve efficiency, you actually improve how care is delivered.

SPEAKER_01 19:26

Yeah, and and again, you know, we talked about the burnout and stuff like that. I mean, all these things can help, you know, doctors feel more confident and less stressed, and nurses to feel less stressed, patients to feel like they're getting better care. You know, there's no there's no downside to to this ecosystem being uh, you know, sort of self-sustaining.

SPEAKER_00 19:50

100%. And if you look at it that way, um, being self-sustaining, then you have to think about it as okay, how do we do that in a way that um, as you said, there will be no no downside because that is the goal, right? Um, the opportunity here is huge in terms of reducing burnout, improving confidence, but only if it's done thoughtfully. Because if you introduce technology that adds complexity or disrupts workflows, it can actually have the opposite effect, right? So for us, the focus is really reducing the cognitive load, not adding to it. And when it's done right, you can see that shift. Clinicians feel more supported and decisions feel clearer, patients feel that difference in the quality of care they receive, but it has to be designed around a human, not the technology.

SPEAKER_01 20:49

Yeah, like you said, it has to make things easier. They don't have time to like learn some robust, complicated system. It has to kind of has to be somewhat plug and play, right?

SPEAKER_00 20:57

Exactly.

SPEAKER_01 21:00

So, you know, a lot of tech startups out there, they move fast, they have the ability or or at least the uh the uh flexibility, I should say, to maybe move fast and break things, but it's kind of hard to do that in a hospital setting. Is is do you find it's difficult to balance that need for rapid innovation with that extreme kind of do no harm caution required in healthcare?

SPEAKER_00 21:25

Well, I put it this way: what is speed without clarity, right? Um, you have to see where you're going for you to go somewhere most of the time. And honestly, healthcare forces you to rethink the whole move fast and break thing mindset. Because here, if something breaks, it actually matters, right?

SPEAKER_01 21:48

Right.

SPEAKER_00 21:48

And for us, it's not about moving slower, it's about moving deliberately, intentionally. And we spend a lot of time making sure we build things. Things that fit naturally into existing workforce workflows. Because the last thing you want to do is to introduce friction in a high pressure environment. The way we balance this is by starting very focused, solving a specific problem and high impact problems, and then scaling from there once we know how it works safely and effectively. And so still it's innovation, but it's disciplined innovation, I would say.

SPEAKER_01 22:32

Disciplined innovation. Yes. I like that. I like that. How how far are we from? Yeah, I'm gonna have you put your uh put your your Nostradamus cap on and tell me like, you know, AI is moving fast, obviously. How far are we from where just so many aspects of the of the the the process are automated or or or helped dramatically by AI?

SPEAKER_00 23:00

Not that far, I would say. I would say given how we are right now, keep in mind where we started with AI. I know AI is a new thing for everyone, but AI has has been around for a decade. It's just now been so publicized and everywhere. It just penetrated with everywhere out at once, right?

SPEAKER_01 23:16

It did.

SPEAKER_00 23:17

So it's the the future of AI is the momentum of what we are right now, right? AI is definitely moving fast, but in healthcare, adoption moves a bit at a different pace than in technology itself. So I would say we're already seeing meaningful impact today in specific areas. Things like triage support, patient flows, documentations, where AI can reduce a lot of the operational burden. But in terms of fully automated systems, we're still a few years out, I would say. And honestly, I don't think that's the goal. I think the shift is augmentation, right? That's where the real goal is, where AI is handling the complexity in the background. So clinicians are able to focus on the actual care of the patients. So it's less about replacing the process and more about making every step of it faster, clearer, and more coordinated.

SPEAKER_01 24:14

That makes a lot of sense. Makes a lot of sense. When I talk to my parents about AI, because they're just confused and terrified by it, I always try to try to say it's a tool. Don't think of it as a replacement, don't think of it as like, you know, robots taking over. Think about it as a as a tool to make life, your life more efficient in a lot of ways.

SPEAKER_00 24:33

100%.

SPEAKER_01 24:34

Yeah. Yeah, I agree with that for sure. So tell me, so LAI, so so how do you how does that get integrated into a hospital? What you know, obviously there's a lot of steps here. Give me the give me the cliffs notes version of how someone would get started.

SPEAKER_00 24:47

Right. So first I hope they're interested, you know. Um, but how someone gets started with AL Logic is either we reach out to them or they reach out to us, they can reach out on our website or just you know, just spam us. That's okay too. But in reality, um, we approach it in a very phased and lightweight way, because once again, we do not want to create additional load. Um, so first we integrate with the hospital's existing systems, like their EMRs, EHS systems. So we're not replacing anything, we are laying on top of already what's there. Um, then we typically start with a very focused use case. So, like intake or patient flow. What is your core problem? So teams can see value quickly without having to overall everything, right? And then from there, it's really about gradual adoption. So clinicians get started using in their day-to-day workflows, we gather feedback and then we refine and then we expand. The core of our system is that we help clinicians. So we have a lot of feedback sessions, we have a lot of sessions where they give us their input or something they would like to see in a feature, or it'd be great if we had this. We take all those comments back to our drawing board and see how best we can implement them on a bigger scale. So we end up feels feeling less like a big tech rollout and more like a natural extension of how they already work.

SPEAKER_01 26:18

That's really cool. And I think that goes back to what we were talking about. Like you, that's a good way to put it, the big tech rollout. It's like you can't just shut the hospital down to do this. You have to, you have to to to implement it in real time while you're still working. So that's that's really cool. That's that's that's very cool. I I'd like to end with with this as you because you're a founder and CEO. You know, you I'm sure you you look at leadership a lot or you think about leadership. What is the most significant lesson that you've learned from your journey so far about leading a team through the high pressure environment of health tech?

SPEAKER_00 26:52

Wow, that is a great question to end with. Was not expecting that turn. Um, I have to say I'm a second founder, but this is my first tech company in a health tech um environment. Um, I think the biggest lesson has to be that clarity matters more than speed. In a high pressure environment like health tech, there's always urgency. Things are moving fast, expectations are sky high. But if your team isn't clear on what you're building and why, that pressure just turns into noise, right? So I really learned to focus on keeping everyone aligned around the mission and what we're making to ensure that we're solving the right problems and not just moving quickly, because then when the team has clarity, they can operate with confidence, even in uncertainty.

SPEAKER_01 27:46

That's great. And two companies, two foundings already. You you've done a lot with your life in a short amount of time.

SPEAKER_00 27:54

I mean, life was meant for a living, right?

SPEAKER_01 27:56

Yes, hey, I agree. Good for you. I love it. That's great. All right. Well, Danielle Crisp, thank you so much for joining me. The company is L Logic AI. Check it out for sure. Danielle, really appreciate your time. Thanks so much.

SPEAKER_00 28:08

Thank you for having me.