How AI is Easing Clinician Burnout with Matt Troup, Clinical Director at Abridge

[00:00:00] Hey everyone, Saul Marquez here. Welcome back to the podcast. In this interview, I host Matt Troup,

[00:00:06] the clinical director for A Bridge. We actually started off recording the episode virtually and then

[00:00:14] finished, but then I ran into Matt at HIMS and we recorded again. So it was great because we got

[00:00:20] to pick up some insights and updates from HIMS at the show floor in 2024 Orlando. So I think

[00:00:27] you'll enjoy it. It's a concise episode with some really interesting updates from Matt. So I hope you

[00:00:33] enjoy it and thanks for tuning in. Hey everybody, welcome back to the Outcomes Rocket. I'm so pumped

[00:00:42] to be with you guys again and today I have a guest. You guys probably have heard his voice.

[00:00:48] We've had him on the podcast actually as a guest and the host. His name is Matt Troup. He is

[00:00:54] director of a clinical success at A Bridge. Matt started his career as a physician assistant in

[00:01:01] inpatient neurology and neuro oncology at North Shore University Health System in Evanston, Illinois.

[00:01:07] He then worked for 12 years as a physician assistant in hospital medicine at Ascension

[00:01:12] in Chicago before joining The Bridge. Matt was the medical director of clinical products at

[00:01:18] Memora Health. He's got a deep expertise in clinical operations, product development,

[00:01:23] and clinician burnout. Matt, thanks for being with us today.

[00:01:26] Yeah, it's a pleasure to be back. I'm so pumped to be back in this chair now on the other side

[00:01:32] of things and you interviewing me. So this is wonderful.

[00:01:34] Yeah man, it's always fun and it's a small world and the impact you guys are doing

[00:01:39] is incredible. So we'll definitely be touching on A Bridge but man, we're going to be together

[00:01:44] at HIMS. I'm excited for what's to come in 2024. For the people that don't know you as well,

[00:01:50] help them understand what got you into the healthcare game.

[00:01:53] Yeah, great question. So like most who have entered into the medical fields, growing up just had this

[00:02:00] strong empathetic nature, wanted to help people wherever I could and then when you mix that with

[00:02:06] a love of science and physiology, you naturally go into a career in medicine.

[00:02:11] And my path was to go to, to become a PA right after college, went to grad school and then

[00:02:17] ended up in neuro-oncology like you mentioned. And got my first experience with what it really

[00:02:22] means to spend time with a patient, to listen to their needs, what's going on in their life,

[00:02:28] especially at really strong inflection points where they're getting significant diagnoses or

[00:02:34] news that they just didn't expect to hear in their life and get to be on that journey

[00:02:39] with them and be an empathetic clinician in their life. And then I after that went to

[00:02:46] hospital medicine where I got to see a really incredible intersection of all kinds of different

[00:02:50] humans dealing with a variety of issues coming through the hospital, leaving the hospital,

[00:02:55] sometimes staying in the hospital and sometimes not leaving the hospital. And the kind of

[00:03:00] intersection there of really where in the hospital setting where healthcare and efficiencies

[00:03:06] and optimization really need to happen quite strongly otherwise, clinicians start to get

[00:03:12] overburdened and burnt out. And then that happened with me when COVID hit working the

[00:03:16] hours that I had to work and undergoing, but once in a lifetime pandemic and being on the front

[00:03:21] lines of that started to see my own personal mental health start to suffer a bit because of it.

[00:03:26] And then at the same time started to develop this love of technology and where technology

[00:03:31] can intersect with healthcare and start to change some of the

[00:03:36] current processes we have in place to really focus on what the clinician needs to have

[00:03:42] positive well-being and serve their patients well. And so that led to joining a healthcare startup

[00:03:48] for about a year and a half, getting to work on the patient engagement, a patient interaction

[00:03:53] workflows, and then more recently joining a bridge and a bridge being the opportunity

[00:03:59] to really affect what I believe is the most significant problem facing clinicians right

[00:04:03] now, which is burden and increase the task load. And that's where I'm now.

[00:04:07] Love it. I love it, Matt. And I appreciate you sharing that. You're doing it in an impactful way

[00:04:13] and a bridge has gotten a lot of attention the last few months with the rise of AI,

[00:04:18] LLMs, and just the ability to do something about it. That's scalable. So talk to us about

[00:04:24] a bridge and where you guys think the biggest value to the healthcare ecosystem lies.

[00:04:30] Yeah. When you start to think about the applications for AI and you start to think

[00:04:35] about some of the most pressing issues facing clinicians right now, I think burden

[00:04:42] and burnout top that list. I think on average we're seeing indicators that 63% of clinicians

[00:04:50] are reporting symptoms of burnout. Most clinicians now are spending two hours of their day

[00:04:56] documenting for every one hour of direct patient care. So it's consuming a lot of our lives. And

[00:05:02] for me personally, when I worked in hospital medicine, I had a 12 hour shift and half of that

[00:05:08] shift was spent in front of a computer. And that might be generous. I might be more than half,

[00:05:13] probably 75% was spent in front of a computer doing documentation, trying to make sure that

[00:05:18] I'm doing everything to justify my ability to see patients and provide care.

[00:05:25] And so now with a bridge, it's starting to think about how do we use generative AI to

[00:05:32] reduce the clinician burden? And through optimizing the ways in which we think about

[00:05:38] clinical documentation, relieve some of that stress from clinicians. We just know that this is

[00:05:44] a significant issue. It's not just for PAs and NPs and MDs and DOs, it's nurses, it's social workers,

[00:05:51] it's most everybody that is interacting with patients in the healthcare system.

[00:05:55] So for us looking at some of the low hanging fruit, if you will, of where we can apply

[00:06:01] generative AI to help to start to offload some of that work from clinicians and allow them

[00:06:06] to better focus on the patients they have in front of them. Yeah, it's a big opportunity.

[00:06:10] Talk to us about some wins. What are you guys seeing out there at early applications, early feedback?

[00:06:17] Yeah, it's honestly unbelievable. When I first got a chance to see what a bridge was doing, I was

[00:06:24] as with anybody thinking about how generative AI can impact healthcare,

[00:06:29] maybe a bit skeptical and maybe reluctant. What's the checkpoints that are in place to

[00:06:34] prevent harm or prevent that we can honestly really trust what's happening when we generate

[00:06:39] notes using AI? The first time I saw what a bridge was doing was just completely blown away.

[00:06:45] And it's that realization, it's like that light bulb moment where you're like, this actually can

[00:06:49] change everything about how I work on a daily basis. So I saw that firsthand but then the

[00:06:56] results that we're seeing speak to that as well. We're seeing two to three hours saved in

[00:07:02] documentation work per day by a lot of the clinicians I use us. We get these love

[00:07:08] stories and anecdotes from providers who are saying that they've made it home in time for dinner

[00:07:12] and the first time in months or years or actually said it saved, they might save their marriage.

[00:07:18] Because what's happening right now in the real world for clinicians is that you have to make a

[00:07:24] choice about when am I going to complete this documentation? Am I going to do it in front

[00:07:30] of the patient and distract from that patient provider interaction and that human connection?

[00:07:36] Am I going to save it till the end of the day and push my work into the evening and start to

[00:07:42] contribute to that pajama time that we all talk about now? Am I going to push it onto the weekends

[00:07:46] and interfere with my daily life that exists outside of being a clinician?

[00:07:51] So we're always having to make those choices and you have to borrow that time from somewhere.

[00:07:57] But what a bridge now is able to do is not to remove that decision from your plate. We can

[00:08:02] actually help you complete the clinical documentation from the conversation that you have with the patient,

[00:08:09] provide that note for you in a matter of seconds for you to review and then move on about your day.

[00:08:14] And with that start to reinstill this passion for the communication that happens between a patient

[00:08:20] and their clinician. I often say that there's really a low learning curve to using a bridge.

[00:08:26] The product is so intuitive and most clinicians can use it right away. I think the learning

[00:08:31] curve is actually starting to understand how to reengage with patients and not have to worry

[00:08:37] about clinical documentation. There was a clinician that said, I don't know what to do with my hands

[00:08:41] anymore because she's always typing when she's in front of her patients. And now you just get

[00:08:46] to focus on the conversation, spend the time counseling patients telling them what to expect

[00:08:51] in the coming days and offload some of that cognitive load of, I know I have a note to

[00:08:58] do. I know I'm going to be working until the night. I know I'm not going to be able to make my

[00:09:03] reservation for dinner because I got documentation building up.

[00:09:06] I think that's great. Not having to make that choice is key. One thing that comes up a lot,

[00:09:11] Matt, is the data. Can you share with us a little bit more about the data set? Is it closed?

[00:09:18] Where's it sourced from? Because that's a thing that comes up a lot.

[00:09:21] Yeah. And this is what I truly love about a bridge and the team that we have is we own

[00:09:26] the entire tech stack. We've been building these models over the years from the ground up.

[00:09:33] We are led by Zachary Lipton, who is a PhD professor from Carnegie Mellon. We have a full

[00:09:40] machine learning team of PhD scientists that are analyzing every aspect of our models. And

[00:09:47] it gives me confidence. It gives me the ability to project confidently and also for

[00:09:52] the clinicians to use it to feel confident in the fact that we control the models. We

[00:09:59] have full verification and auditability of what our models are producing. And in that way, we can

[00:10:07] say with confidence that what we're producing is verifiable. So for instance, when we generate

[00:10:14] a note for a clinician, you can highlight any section of that note and it'll take you directly

[00:10:20] to the transcript for where we polled that part of a conversation. If I'm talking about starting

[00:10:26] a patient on Lycinopril for blood pressure, and I want the patient to check their blood

[00:10:29] pressure once a day every day and report back to me in two weeks, I can verbally say that,

[00:10:34] but in the note it's going to list that out as starting Lycinopril, measure blood pressure.

[00:10:39] But let's say I read that in my notes that's generated by a bridge and I'm like,

[00:10:43] oh, I don't remember talking about that. That's got to be a hallucination.

[00:10:47] I can highlight that portion of the note and I can see verified in the transcript that, oh,

[00:10:52] yeah, I actually did talk about this. And that's had interesting outcomes actually.

[00:10:56] I've heard from a few physicians recently that they'll have these long dialogues. One is a stroke

[00:11:02] neurologist who does these long, strokey vowels and there's a lot of information passing back

[00:11:06] and forth from the clinician and the family to the physician and got back to his office and

[00:11:14] couldn't remember if he had discussed a certain aspect of what was going on with the patient,

[00:11:19] but then saw it in the note and was like, how did this get in here? And then highlighted that

[00:11:23] section of the note and realized that it actually was discussed by a family member

[00:11:27] and just in the chaos sometimes of what happens when we're evaluating patients you don't remember.

[00:11:33] And that's human error that happens when we have very little mental reserve,

[00:11:38] when we're burnt out, when we have a million plates spinning in the air

[00:11:42] and now a bridge is the supplemental tool. I like to say, I think it's a tool that's going to be as

[00:11:48] important as a stethoscope or a reflex hammer at some point that helps you

[00:11:52] ensure that you're doing the best care possible by your patients.

[00:11:56] That's fantastic. Yeah, so many opportunities to use it beyond saving time.

[00:12:02] Just yeah, that's super cool. So what about challenges? What have you found our

[00:12:08] early challenges in adoption and getting things going?

[00:12:12] Yeah, well, clinician adoption is a challenge for I think all anything. Health tech.

[00:12:19] Even the most savvy of us have, we're ingrained in our workflows,

[00:12:23] and I think clinicians start to feel a little bit of pride about their workflows. And certainly

[00:12:27] when you start to think about EHR templates, the templates that we build to try to optimize

[00:12:32] our workflows. But we can also get to ingrains and be resistant to change, especially if the

[00:12:38] technology you might have used in the past has failed you before. It hasn't lived up to the

[00:12:45] billing or what you've heard from individuals. So for me, and in the role that I'm in at a bridge,

[00:12:51] along with the team that I work with, our whole focus is how do we get clinicians to adopt

[00:12:56] this and use it? Because personally, I believe so much in the product. We've seen such success

[00:13:01] with the product, but if no one uses it, it doesn't have the impact. We know that this can impact

[00:13:07] clinician burden, reduce cognitive load, and provide satisfaction. And it can really impact

[00:13:14] every part of the quintuple aim. But if clinicians don't use it, that impact isn't

[00:13:19] realized. So it's the trust. I think when I just did an onboarding session today with a

[00:13:24] group of physicians, and for me, I'm inserting a lot of my own experience with being a clinician,

[00:13:31] using a bridge, how I think about generative AI and have turned the corner to very much

[00:13:37] trust what we're doing. But it's getting that buy-in from the clinicians we talk to

[00:13:41] from the top down that where people might have been skeptical about generative AI,

[00:13:48] we now have a verifiable, auditable platform with a bridge that can allow you to use it

[00:13:55] and not have the concern about what's happening. I think that's the key. And then I think it's

[00:13:59] also just, yeah, at every intersection that I have with clinicians that are using a bridge is

[00:14:05] developing trust, listening, understanding where their pain points are, and then working

[00:14:10] closely with our team to optimize it as quickly as possible. And that's the benefit

[00:14:15] of also owning all of our technology is we have the ability to optimize in real time.

[00:14:21] That's great. Now, thank you for those insights, Matt. And no question,

[00:14:26] gen AI, large language models making a huge difference. What is it that, where do you see

[00:14:32] this going? Where do you see things five years from now?

[00:14:36] Yeah, that's a great question. Love dreaming about the future. I think that's one of my

[00:14:41] favorite things is, and I probably get ahead of myself when I think about the

[00:14:44] intersection of tech and healthcare is like, oh, this is cool. But think about what this could be

[00:14:48] in five years or 10 years or where this goes from here. First off, I think we continue to refine

[00:14:54] these types of ambient AI technologies as they are now always focusing on how you even better

[00:15:01] help clinicians with documentation burden. And understanding, I think the research that

[00:15:06] we're doing right now at a bridge is understanding what this truly unlocks for

[00:15:10] clinicians when you reduce that cognitive load of having to do notes and clinical documentation

[00:15:17] all hours of the day. So what does that unlock in terms of patient outcomes,

[00:15:22] clinician outcomes, like I said, all parts of that quintuple aim,

[00:15:27] and really better understanding the impact that this has at scale? So I think that's

[00:15:31] primary and we'll start to see that in the next months and years for certainly.

[00:15:36] Beyond that though, you start to think about AI and our access to all the data that happens

[00:15:42] within a conversation. And it's not just about clinical documentation, which is key,

[00:15:46] but there's also things that we can extract from that conversation to help with coding. We can

[00:15:51] use insights from conversation to help make suggestions to clinicians about maybe some

[00:15:55] clinical decision support, right? As I'm engaging with a patient, again, optimizing

[00:16:02] the output of that conversation to help suggest things that I might not have thought about.

[00:16:07] I think there's also an opportunity here to use generative AI and conversation to extract

[00:16:13] biomarkers like our clinicians who are talking in some way, right?

[00:16:17] Depression.

[00:16:18] More at risk of depression or burnout. Our patients more at risk for something based

[00:16:23] on how they're talking. I don't think there's any question that at the start of a 12-hour

[00:16:28] shift and at the end of a 12-hour shift in somewhere in between probably I talk differently to patients.

[00:16:34] When there's very little mental reserve left, you're more apt to make mistakes. You're probably,

[00:16:41] you have less patience for your patients, right? You have less ability to empathize

[00:16:47] with your patient. We want to restore all of that and give back to clinicians, but I also

[00:16:52] think there's a future in which we're like, we're better able to analyze that and use that

[00:16:56] data to even promote better wellness within not only clinicians, but patients as well.

[00:17:01] That's great. Love the vision. Not only saving time with notes, but RevCycle, biomarkers,

[00:17:08] sky's the limit here. Just getting this execution up front is critical. Matt, this has been fantastic.

[00:17:14] I always love connecting with you. What closing thought would you leave our listeners with

[00:17:19] as we wrap today? Where's the best place they could get in touch with you and the abridged

[00:17:22] team? Yeah, awesome. We'll be at Hymns next week. Please come

[00:17:26] and find me if you're there. I'm always excited to chat with folks about technology,

[00:17:32] where they're at with implementing new technologies, and I'm always happy to talk more about a bridge.

[00:17:37] I think the lasting thought here, especially for clinicians who are listening or those folks who

[00:17:42] are trying to figure out best practices to instill around solving for a provider. Burn-on is not

[00:17:49] solely dependent on resiliency. You can't just tell an individual just to work harder or find ways

[00:17:57] to... It's not an individual problem, it's a systemic problem. There are things in place that

[00:18:04] are causing a significant burnout that technology has the opportunity to mitigate.

[00:18:11] I think what we see right now with generative AI applications for clinical documentation,

[00:18:18] exactly what a bridge is doing, is the right technology at the right time. The ability to provide

[00:18:25] a tool that can offload that burden and really allow clinicians to focus again on that human

[00:18:31] connection. For me, this is full circle. I mentioned at the beginning of this call that

[00:18:35] I got into healthcare to be an empathetic voice and provide human connection to patients,

[00:18:42] and then put them on the best course for health. When I'm burdened, when I'm burnt out

[00:18:47] and I don't have mental reserve, I start to sacrifice that. And clinicians across the

[00:18:52] country can tell the same story. So for right now, what we need to focus on is giving clinicians

[00:18:58] back that ability to be a clinician once again and remove a lot of this burden and

[00:19:03] documentation and paperwork off their plates. Amazing, Matt. Look, I'm all in on that.

[00:19:10] Excited to see you and the team at HIMS as well. And man, for everybody listening,

[00:19:14] make sure you check out the show notes for the best ways to get in touch with Matt.

[00:19:18] I'll get those from you and plug them in there. All right. And that is it for the virtual interview.

[00:19:24] And here we go. Transition to HIMS 2024 in Orlando. Enjoy.

[00:19:31] Hey, everybody, welcome back to the Outcomes Rockets here at HIMS 2024.

[00:19:37] Last week, I recorded a podcast with Matt Troupe. And Matt, so great to see you.

[00:19:44] We had to do a podcast on the spot. So thank you for doing this.

[00:19:47] Yeah, I saw it. Good to meet you live and in person. This is such a treat for me.

[00:19:51] The best. It's a treat for me too. What insight has risen to the top that sticks out for you?

[00:19:57] And then let's put it in the context of new things that you guys have going on.

[00:20:02] Burnout is a hot topic right now. I think you're hearing about it everywhere at HIMS.

[00:20:06] We know it's a significant issue nationwide right now for clinicians,

[00:20:10] for nurses, for really any clinical staff in a hospital system right now.

[00:20:15] And what we need to do is understand where can we actually make real impact?

[00:20:19] And what we're finding at a bridge is that the use of generative AI can really unlock

[00:20:26] opportunities that we haven't really seen in the past before.

[00:20:29] It's so interesting to me. We had a client just yesterday, a partner of ours,

[00:20:33] go live with our bridge product. And on day one, the wellness officer at our partner posted on

[00:20:41] LinkedIn about the success she's already seen, the feedback she's already gotten,

[00:20:45] the love story she's hearing from her clinicians that this is already changing

[00:20:49] the way that they practice on day one. So the impact is there. Now what we have to unlock,

[00:20:54] and what we're hearing a lot about at HIMS is how do you scale that impact?

[00:20:58] And what does it mean to take a product from an individual and scale it across an entire health

[00:21:05] system? And at a bridge, that's what we're focused on. Personally, that's what I'm focused on.

[00:21:09] Because to see all that downstream impact, you really have to get clinicians using it

[00:21:14] all the time, reduce the burden of entry, the barrier to entry, and the burden to use a

[00:21:19] product as low as possible. And once you decrease that friction,

[00:21:23] let the clinicians just have a tool built for them.

[00:21:26] I love it. And so ultimately, it's about using it. And so what have been your findings early on?

[00:21:33] What are best practices to help with that?

[00:21:38] Yeah, it's honestly convincing a clinician just to try it. As a clinician myself,

[00:21:43] I've been at times reluctant to try new technology. You never quite know, is this going

[00:21:48] to be worth it? Am I willing to give this a try and change my current workflows I've been

[00:21:54] using for years, my normal routine to see if technology can really improve how I worked?

[00:22:00] And so if we can get clinicians to just try this type of technology

[00:22:04] and see that immediate impact, then we can continue that flywheel of,

[00:22:08] I can start to use this in every patient. And if I use this on every patient,

[00:22:12] I start to decrease the time spent documenting. If I decrease the time spent documenting,

[00:22:17] my mental reserve increases and my cognitive load decreases and I get home for dinner and time.

[00:22:22] We have clinicians say now they can think about practicing

[00:22:26] more years than they thought about before because this technology exists. So

[00:22:32] it's getting them to try it for that first time and then helping them understand the impact

[00:22:37] that this has that they start to use it over and over again. That's great, Matt. What are some of

[00:22:42] the common questions that you guys get from clinicians about the technology, whether it's

[00:22:50] security or just top things that come up? Yeah, it's a good question. All of us have probably

[00:22:56] tried generative AI products. We understand that there's limitations and there's always been a

[00:23:01] concern about hallucinations or exactly what's going on in the background when we use these

[00:23:06] products. What we've designed and what I think was a game changer for me when I first used a

[00:23:12] bridge was our ability to see linked evidence for where all the documentation comes from

[00:23:17] in the note. So when a note's generated, like a bridge, you can highlight any section of that note

[00:23:22] and it takes you into the transcripts to exactly where that information was pulled out from

[00:23:28] and also where they're in the audio recording it was pulled out from as well.

[00:23:32] So if I'm a clinician for the first time and I'm skeptical about just how much I can trust

[00:23:37] generative AI, a bridge is changing the narrative here with a technology that is fully auditable.

[00:23:45] You can fully verify exactly where that information is coming from and we can change the minds of how

[00:23:51] much we can start to trust this technology. And again, so like what I said before, once you do

[00:23:56] that and you make that mental switch, you can start to understand how this can impact

[00:24:01] your life really. Yeah, and I really like this idea of a clear box that you can reference

[00:24:10] and validate. And it's easy, right? It's easy to validate.

[00:24:16] Yeah, it's easy to validate. And not only that is at a bridge feedback is oxygen for us. We take

[00:24:23] every piece of feedback to heart. It informs every piece of part of the roadmap that we do.

[00:24:30] And so we're always improving. And today is it's very good tomorrow it'll be better.

[00:24:37] By next Monday, it's going to be even better. Because that feedback loop is so critical to

[00:24:42] earning the trust of clinicians that we're in this together. As a clinician, I use this and I want

[00:24:48] to continue to see it get better for my own use and the patients that I work with. And for

[00:24:54] the partners that we work with, the same story applies. I love that, Matt. And folks,

[00:24:59] let's think about that. What Matt just said, feedback is oxygen. Are you thinking about

[00:25:05] that for your business, your practice? I think that's a very healthy way to look at it for sure.

[00:25:11] Matt, ease of use integration into existing environments. I understand you guys have this

[00:25:17] thing called the bridge inside. You want to unpack that for us? Yeah, thanks, all. This is an

[00:25:21] exciting opportunity for us at HIMS 2024 is our debut of a bridge inside. If you swing by the

[00:25:27] booth while you were here, you got to see a demo of what that looks like. And for us,

[00:25:30] what that means is we are fully embedded now within the Epic ecosystem. So for me, when I practice in

[00:25:37] the hospital, I practice and has Epic, I use an app about Hikku. It's Epic's mobile app. And now a

[00:25:44] bridge can be directly embedded within Hikku. And so as I'm going to see my patients in the clinic

[00:25:49] around in the hospital, I can open up Hikku, I can select a bridge, and I can record directly

[00:25:54] within Epic's Hikku app. And then as soon as I'm done recording within 30 seconds, that note generates

[00:26:00] right within Epic. And it's there for me to review. It's been honestly a game changer for me as a user

[00:26:07] of Epic for 15 years to think how this changes my workflow. Also for those who have used a bridge

[00:26:14] before, now to think about how this even further streamlines their workflow, that in the place

[00:26:22] that they operate every day within Epic now exists this incredibly powerful tool right at their fingertips

[00:26:31] and they never have to leave that ecosystem. It's been fun to demo. We had a huge group yesterday,

[00:26:37] I was incredibly excited about what this means for streamlined clinician workflows.

[00:26:41] And back to what I said earlier for adoption at scale, the key thing here is reducing that

[00:26:46] barrier of entry and reducing friction as far as possible because the impact is there. You just

[00:26:52] got to use it. Totally, I love that. Hey, and a quick question on the input mechanism.

[00:27:00] What are they speaking into? What are clinicians speaking into? Yeah, great question.

[00:27:05] So right now within a bridge inside a bridge is directly in Hikku. So for your mobile phone,

[00:27:11] you can record directly through your mobile phone. So for me, my phone goes everywhere with me

[00:27:15] when I'm on the nonpatients or seeing them in the clinic. So just pull out my phone, open Hikku,

[00:27:20] press record and it all lives within that ecosystem. We can also record directly within a web browser

[00:27:27] or within soon to be Epic itself. So you don't need any additional recording tools?

[00:27:34] No, not at present. We have a standalone app as well for those that don't have Epic or

[00:27:40] for those that are not quite to a bridge inside of Epic quite yet, but it's mobile based right now.

[00:27:45] It's also going to be via our web web recording and also can be embedded within the EHR.

[00:27:50] Outstanding, definitely exciting. I'll have to stop by the booth to get a demo. I'd love to

[00:27:55] see that. And Matt, as we close our chat today, what call to action would you leave to all

[00:28:01] of our viewers and our listeners? And what's the best place they could reach out?

[00:28:06] Yeah, it's some bias here. I am a clinician myself and when I think about technology and I

[00:28:12] evaluate what's going on in him's, I'm always thinking about the end user and the end user

[00:28:18] in most cases is a clinician and the patient and that patient clinician interaction

[00:28:23] is what we need to preserve so that we can rebuild that human connection that

[00:28:29] so many clinicians want to have with their patients and so many patients that enter

[00:28:32] into a clinic just really want to have with the person that's providing them care.

[00:28:37] And so we need to protect that and use tools and use generative AI and use other technology

[00:28:43] to reestablish that connection, reestablish empathy between a patient and their provider

[00:28:50] and protect that connection. I'd also say that immediate impact and measuring impact is going

[00:28:57] to be more important than it ever. I think last year we heard a lot about hype in generative AI

[00:29:02] and now people are asking what is the data that reflects the impact that we're talking about?

[00:29:07] So at a bridge, we are doing extinuous research. We have case studies and research

[00:29:13] opportunities in the pipeline right now that are very exciting and that's going to be the key

[00:29:18] that gets people on board to understand that generative AI is here. It has impact

[00:29:23] and clinicians are ready for a tool that gives them some of their autonomy back.

[00:29:28] Love it, Matt. Appreciate that call to action. I appreciate the perspective

[00:29:33] and for everybody listening and viewing thanks for tuning in here. We're at Hymns 2024. In the

[00:29:39] show notes you'll find ways to get in touch with Matt and the ABRIDGE team to learn more about

[00:29:44] the amazing work they're doing to make clinicians' lives better and work more enjoyable.

[00:29:49] Matt, thanks for being with us.

[00:29:50] Awesome, Saul. I appreciate it.