Outcomes Rocket Podcast_Bruce Brandes: Audio automatically transcribed by Sonix

Outcomes Rocket Podcast_Bruce Brandes: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.

Saul Marquez:
Hey, everybody! Saul Marquez with the Outcomes Rocket. I want to welcome you back to another episode of our podcast. I've got, no stranger to the podcast, you guys all know Bruce Brandes, he's joining us today. He's the president of care.ai. He's got over 30 years of experience in executive management, and entrepreneurial thought leadership to build growth-stage technology-based businesses in the healthcare industry. Bruce's experiences range as a strategist, operator, entrepreneur, investor, fundraiser, and marketer to advance the transformational promise of digital health. Whenever I think digital health, I think Bruce Brandes. I'm so excited that he's here to speak with us today. So Bruce, thanks for being with us.

Bruce Brandes:
Saul, as always, thank you for having me. You've been a good friend for a long time, and I'm just so impressed with how well you've evolved the transformational promise of the podcasting format. Just such a great job, so thank you for having me.

Saul Marquez:
Of course, Bruce, it's a pleasure to have you here, and thank you for that. For those that don't know, Bruce has a really rich history in a lot of different awesome companies like Livongo, Teladoc. He was at AVEA, you know, was a leader at AirStrip and really began his career at IBM, but certainly at the forefront of digital health. So, Bruce, as you think about some of the areas where care.ai is really answering some of the biggest problems, what would you say those are?

Bruce Brandes:
Yeah, I mean, well, certainly, hospitals and health systems don't have a lack of problems to deal with and issues and opportunities. But I think above all of the noise of things people are facing, I think there are two existential challenges that are drawing everyone's attention. One is recognizing that increasingly what we ask of our caregivers is becoming humanly impossible. And unfortunately, the technology that we've brought to bear to try to help them has actually made their lives harder, not easier, and look no further than the EMR, causing a lot of additional burnout as well as, with the best of intentions, a lot of individual point solutions that by themselves have utility but collectively are further fragmenting an already very fragmented provider experience, and so, therefore, we're losing our best caregivers. And then secondly, even if you had all the labor and caregivers that you needed, the underlying cost of our current acute and post-acute care models, are just fiscally unsustainable. And so what we're really focused on is recognizing the fact that to solve those existential challenges, you can't just tinker around the edges and make a little tweak here or there, you really have to take a step back and reimagine how do we deliver care and where can we bring technology that's been transformative and proven in other industries to address these existential challenges so that the healthcare of the future looks very different, but by the same token, never compromises quality and safety, and regulatory compliance in an era where we can't continue to accomplish those things in the same way that we have in the past.

Saul Marquez:
You know, thank you, Bruce. Those two topics of the labor and cost seem to be at the forefront of most conversations today with healthcare leaders. Sometimes when you're so deep into it, it's hard to imagine something different. You go back to what you're used to. We got to look at other industries, and you and I had a good chat, I think it was last week, around this. Talk to us about some of the inspiration and the solutions that care.ai is bringing to market.

Bruce Brandes:
First of all, I should give you a little bit of background on our founder, Chakri Toleti, because it's an interesting one to get to this path in his career. He's actually a filmmaker by training, and his first job out of film school was as a Disney Imagineer working on the motion capture team to take human movement and create animated characters, so Mulan and a lot of the beloved characters of Disney films in the 90s reflect his work. And so that, married with the fact that he is on the advisory board of a publicly traded company called Luminar, which builds the advanced sensors and AI that power many of the self-driving cars in the world, and through that lens, being technical and creative and understanding how this ambient intelligence technology has been transformative in the transportation industry, that really inspired him to start care.ai, apart from being deep and well entrenched in understanding the problems of healthcare through two earlier ventures that he had, plus all the personal experiences that we all endure and understanding that healthcare is really broken. And so the idea was, if you can, back to the transportation industry, if you can keep with autonomous driving vehicles, keep the driver and society safe from somebody whizzing around at 80 miles an hour on a winding road in the rain while they're watching a YouTube video on their phone, certainly, we can take that same technology and put it into a hospital room and reimagine how care gets delivered in a safer way. And so that was a big part of the inspiration because while we're not there with autonomous driving cars yet, if you think about where we are as an industry, autonomous driving cars have automatic braking and lane change assist, and dynamic rerouting that allow us, when we start extrapolating out this at scale, when you start reimagining not basic features like a backup camera, which is what we're good at in healthcare. And what I mean by that is a backup camera in a car is ubiquitously available now, and it's a nice incremental improvement where you don't get into as many fender benders in the parking lot, so it's better, but by itself, is not transforming anything. We, in healthcare, and transportation and other industries are facing the opportunity for transformational change. And so, what does transformational change look like in transportation? It's challenging the status quo of legacy costs and inefficiencies that we've just accepted for a very long time, like what we pay for car insurance and traffic and road construction and first responder deployments, and taking a step back and reimagining a world where, you know, autonomous driving cars that are leveraging ambient intelligence, all of a sudden maybe that world, maybe those things are no longer taking such hold over us. And so, how do we apply that same technology to many of the entrenched? You talked about falling back on what we've always done, how do we make sure that we're not just looking at a lens of standing up a whole series of new backup cameras, but taking a step back and reimagining a lot of the inherent challenges that we have with a new lens of what's possible with this type of technology and challenging some of the inefficiencies and costs that we've just incurred for a very long time? So that's one example of many others, including if you've ever been to an Amazon Go store or a FedEx distribution center that are smartly using sensors and AI in new ways to drive new efficiencies and possibilities.

Saul Marquez:
Yeah, Bruce, so inspiring, and thank you. And from the founder of the company to the inspirations that you guys take through different verticals, using ambient technology, it is fascinating to think about what the future can look like inside of a hospital, inside of a sniff, inside of a nursing home, or in our own home. So talk to us a little bit about how you guys are thinking about the solution, maybe the segments of value that you're offering to care providers. It's always good to unpack that, to really kind of bring it to life.

Bruce Brandes:
First of all, looking at this from the perspective of bringing ambient intelligence to healthcare to create a smart care facility, and to enable and empower smart care teams which look different than the traditional hospitals and traditional care teams, so how do we think about what that looks like? But by the same token, with this broader vision, how do we start with very specific use cases where the ROI is very compelling in solving some of the most immediate needs that an organization has? And actually, one of the ways that our company grew so quickly was, fortuitously, one of the silver linings that came out of COVID, we were building this smart care facility platform, and then COVID happened, and it became obvious that the first use case was smart entry screening and digitizing the physical front door to keep people safe during COVID. And we had a very unique window of opportunity where in the first 90 days coming out of COVID, we stood up 1500 care locations without ever physically visiting any of them.

Saul Marquez:
1800.

Bruce Brandes:
Right, it had forced us to be innovative ...

Saul Marquez:
That's awesome.

Bruce Brandes:
That you normally wouldn't, and also gave us opportunity to grow in ways that we ordinarily wouldn't and earn trust from these clients. And so when COVID started to stabilize, it became a logical conversation to say, hey, where else do we go with this platform? And there are really two pillars that we found people have gravitated to. One is around ambient monitoring and using these sensors that are in the room to be able to address a variety of use cases, most notably falls prevention and, not falls detection, but falls prevention. There's a significant difference. Pressure injury avoidance, high hand hygiene compliance, rounding compliance, staff duress, the list goes on and on with other capabilities that these same sensors can address by ambiently looking and listening 24/7. And then the second pillar is really around virtual inpatient care, which obviously works hand in glove with the ambient monitoring. So virtual nursing, most notably, is what people are talking about. And interestingly, today, you could ask 100 nursing leaders, what are you doing about virtual nursing, and how do you think of it? And you get 250 different answers, and that just goes to show that a lot of people are talking about it, but not a lot of people have figured out how to do it. And for us, looking at virtual nursing as a good starting point, we recognize that there's a tremendous amount of utility out of the gate to get it right, if you get it right. But if you're looking at this as just another point solution or just another backup camera and standing up virtual nursing is cameras in a room, or worse yet, iPads on a stick that you wheel in, if that's all you're looking at, you're missing the transformational opportunity, the transformational change of looking at wrapping it with ambient monitoring and further with AI, where you can really reimagine the underlying models of care and the way in which the business is run of healthcare, all the clinical and operational workflows. And so that's a common starting point, is virtual nursing, but the key is to look at it more broadly and understand what's possible with the ambient monitoring capabilities and AI to really turbocharge the transformation that this opportunity represents.

Saul Marquez:
That's great and super exciting. And a lot of people might be wondering who's on the other side of the cameras because the solution gets to a certain point, but at the end of the day, it still requires people, right, to help, oftentimes licensed clinicians. So talk to us about that side of the fence.

Bruce Brandes:
First of all, the whole reason for doing this is to help offload the bedside nurse and all the bedside caregivers with a lot of the tasks that are not what they went to nursing school for or not what they went to medical school for, and not allowing them to do the things that they're passionate about that frankly, only human beings can do, you know, to hold someone's hand, to show compassion, to physically examine them. And so, what we're really trying to do is offload that as much as possible with technology, whether it be technology with a human being on the other side, or technology that is leveraging AI to help enable the right resources wherever they may be as when the time is right. And so generally, on the other side, really depends on what the use case is, specifically around virtual nursing, it's a licensed senior nursing professional. And generally, what we tell people is, this is all about building trust with the bedside nurses and extending the careers of your seniormost nurses who are just burned out or physically unable to continue to practice at the bedside to give them the opportunity to take on certain tasks that you don't physically have to be at the bedside to do. The most common ones everyone talks about is admit discharge, medication reconciliation, patient education. But that's who's on the other side of this is, whether it's a senior member of the care team who's already trusted by the bedside care team because they're known, and we intentionally don't want to be in the staffing business because our belief is every health system actually has enough caregivers, they just don't want to continue to work for you because it's too hard, so how do we make it so that the job becomes more fulfilling for what they really want to be doing? And so that's a big part of our focus, is helping to just extend the care teams and have virtual and smart care teams that are working together. And it really doesn't matter who's physically at the bedside, what's being done ambiently, and who's on the other end of the camera, they're working in concert, in service of providing the best possible care at the right time to those patients that they serve.

Saul Marquez:
Thanks for that, Bruce. It's good to understand the strategy and the approach. Where do you see healthcare ten years from now?

Bruce Brandes:
I'll make a couple of comments because ten years is a really long time.

Saul Marquez:
If we go with five?

Bruce Brandes:
Let's just say impossible future. I certainly, apart from what we do, I hope for a world where incentives are aligned for providers to be compensated for keeping people healthy, not for perpetuating a sickness.

Saul Marquez:
Amen to that.

Bruce Brandes:
So I think that's a foundational element that we should all strive for. And it's actually a really important point, though, because I think we need to be making investments today that serve health systems well, and the reality that we are in fee-for-service for the most part, 94, 95% in fee-for-service. So we need to invest in technologies and solutions that serve us well and have a compelling ROI on fee-for-service but will be the catalyst to enable us to have the data and the delivery mechanisms to be able to more effectively and confidently start taking risk and move more aggressively into a value-based care, and the ability to, you touched on it earlier, to take care of someone not only when they're in the inpatient setting, but in the post-acute setting, whether it's a sniff or assisted living or in their home is going to be really critical to start to look at one neural network that is capturing data wherever someone is in that care journey, and where I get to know that individual layering an AI where I'm really starting to know that person so I can hyper personalize a consumer experience for patients and for people who are not yet patients and ideally create an environment where we're caring for them in the lowest cost, most clinically effective venue, and many times that's not going to be the hospital. But unlike the shopping mall, we can't afford for our hospitals to go out of business, we need them. And so we feel great urgency in what we're doing to help to empower our health systems, to understand how to control their own destiny, and to reimagine their care models so that they can play, take advantage of their incumbency, and their incumbent advantage as so many competitive pressures are coming their way so that in the future, the health system is a health services company that provides high acuity services and everything all the way into the home and as people are just living their lives, but to have a technology stack that, and smart care exists throughout that continuum. And I see a world where the technologies that we're investing in now will serve us very well for where healthcare needs to be in five years.

Saul Marquez:
I want to be part of that world, and I know everybody listening here wants to be part of that world. And so huge kudos goes out to you, Bruce, and your team at care.ai for the work that you're doing to make that world a reality. As we wrap up today's episode, what call to action would you leave to everybody listening?

Bruce Brandes:
First of all, the status quo is no longer acceptable. And I would also challenge you, if you're thinking about more individual point solutions that are backup cameras, that's not going to create the transformative change that every organization needs. I would challenge folks to get out of their comfort zone and don't start thinking about how you're going to solve things with a product or a vendor that you've had for ten years that used to do one thing, and now they can do one more thing and still hamstringing you until, older technologies advance so much you've got to move fast. I think the most important element that I would challenge everyone to look for in a partner, we're in the first inning as it relates to where all this is going, you need to be leaning in with partners that are agile and have the ability to understand and adapt quickly as we continue to iterate as an industry to address these challenges, because no one has it figured out yet, but those who can move fastest will prove to be the winners in the future state of what healthcare looks like and move the fastest without compromising quality and safety and everything else that is near and dear. So, break down the fragmentation, we've got to look more holistically at how we deliver care in new ways and a simpler way.

Saul Marquez:
Yeah. Hey, I'm glad you went there, Bruce, because, you know, there's, this is true for not only health providers, but also the incumbent med device and pharma companies, right? Like partnering with more innovative agile companies like care.ai to take their business to the next level could also be the solution to really scale much faster.

Bruce Brandes:
Again, this is not to disparage any incumbents, but just like the challenges that many health systems face because of their legacy business and the strongholds they need to protect, it's one of the reasons why so many health systems are struggling. So many other established vendors, and suppliers, and partners really aren't going to be able to adapt as quickly as an organization might want. If you, as a health system, want to be able to move quickly, you really have to reassess all of your partnerships and say, is this a catalyst to get us to the future, or are they an anchor that's going to slow us down as we need to go where we need to go? And it's probably a combination of the two, but I think the winners will be those who are most agile, and you're seeing it now happening exponentially in other industries. And incumbents beware, but of all the incumbents, we can't afford to have our health systems not succeed.

Saul Marquez:
Love that. Bruce, as always, thank you. Appreciate everything that you and your team does at care.ai. And by the way, folks, the website is care.ai. We'll leave links to all of the things that we discussed with Bruce and his company care.ai. Bruce, thank you so much, appreciate talking to you.

Bruce Brandes:
A pleasure, as always. Thank you.

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Smart from the Start_Tarun Kapoor: Audio automatically transcribed by Sonix

Smart from the Start_Tarun Kapoor: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.

Smart from the Start Intro/Outro:
Welcome to Smart from the Start, presented by Care.ai, the Smart Care Facility platform company and leader in AI and ambient intelligence for healthcare. Join Steve Lieber, former CEO of HIMSS, as he interviews the brightest minds in the health provider space on truly transformative technologies that are modernizing healthcare.

Steve Lieber:
Hello, and welcome to Smart from the Start. I'm your host, Steve Lieber, and it is my pleasure to bring to you a series of conversations with some of the sharpest minds in health information technology. We'll discuss the smart directions healthcare companies and providers are pursuing to create smart care teams. Today, I'm joined by Dr. Tarun Kapoor. Dr. Kapoor is Senior Vice President and Chief Digital Transformation Officer at Virtua Health. In this role, he oversees Virtua's Digital Transformation Office and orchestrates Virtua's enterprise-wide master plan in support of an intuitive care journey for all consumers. Previously, Dr. Kapoor was the president of Virtua Physicians Partners and the Senior Vice President and Chief Medical Officer for Virtua Medical Group. Prior to joining Virtua, Dr. Kapoor was Regional Director for EmCare's Mid-Atlantic Hospitalist Division. Welcome, Dr. Kapoor.

Tarun Kapoor:
Hi, Steve. Thank you so much for that very kind introduction.

Steve Lieber:
You're quite welcome. And it is a pleasure to be with you today and have a conversation with a physician who has a significant role in leading digital transformation. We've got a couple of intersections there, some disciplines, technology and medicine, and let's start out there. My career goes back to the early days of EHRs, and we had a lot of challenges getting clinicians to buy into what was going on. In that period of time, we may have moved one generation in terms of the clinicians practicing today, I don't know, there's still some of us still around, but kind of take us through, short, sort of the evolution, hopefully, there has been one, around physician opinion and reaction to technology in general.

Tarun Kapoor:
I know that the rub sometimes is, for physicians, or I would say, clinicians in general, including anyone who provides front-level care, whether it be our advanced practitioners, our nurses, etc., to be a little bit skeptical about technology, and their adoption curves within the clinical realm, just like they are anywhere else, right? You got your early adopters, and you have your laggards. I think what sometimes throws the clinical field off on this is, yeah, well, I see the promise of the technology on paper, but then the actuality of what I'm dealing with at 2 a.m. in the, you know, in the middle of the night is something completely different than what's on a PowerPoint slide. And, you know, you see a lot of great PowerPoint slides, a lot of times the execution is a little bit questionable. I'll give an example. And I'm an informaticist, so I, by training, and so I know what it's like to talk to doctors who are skeptical on this. But I remember, once I, it was probably late at night, I was in the hospital meeting somebody, and they say, Hey, look, with our consolidated EMR, you can now see all the previous discharge summaries this patient has ever had for the last 15 years. And on PowerPoint, that's wonderful, but when I'm sitting there trying to admit somebody, and I still have the exact same amount of time to admit them, because I still have 12 other people who are waiting to get admitted, and I realize I don't have time to read 15 years of ... and discharge summaries, I think that's where we hit the nadir of this, where we had all of this consolidated information, but what we didn't have was processed knowledge. And perhaps, what I think folks are on the technology and also in the clinical side are most excited about right now, is that now we are in a place where we can go from that nadir where just volumes of data to say, Hey, can you process this and sum it up for me? And has this person ever had this in the last 15 years? And ask the machine to look at that without me having to read 15 years of medical records? That's what I'm very hopeful for, but it has been a journey and sometimes quite a painful one.

Steve Lieber:
Yeah, I want to get to that because you really have carried us to where we're hoping we're on perhaps the cusp of a next generation. So last generation was about digitizing information. We didn't have it in a digitized form before, we were trying to get off paper, it was all about data collection. I mean, it shouldn't have been, but it was. And now, as you said, something to work with that pulls information out that I need right now that helps me with the next thing I need to do. And so that leads us, obviously, into the two words of the day, artificial intelligence. And so clearly, the intent there is to be able to comb through large amounts of data and information and be able to extract actionable activity out of that. Where are you in terms of virtuous work in this area, and do you have a sense of clinician reaction to this next generation of technology that's being thrown at them?

Tarun Kapoor:
We have some examples here where we think we're making some good progress, where I think it is, there are lots of words thrown out there. One day, I'm hoping I'll be famous for something, and so I put out something called Kapoor's Inverse Law of AI, and that is the number of times a person mentions AI in their presentations, inversely proportional to their understanding of AI. So I will try to keep my usage of AI to a minimum, but what I do find is a lot of times we're we're tossing the word AI and automation back and forth interchangeably, and they're not. Where I think there is an enormous opportunity right now is with automation. And clinicians feel way more comfortable around automation, where the human rights, the rules, and the machine processes within the construct of the rules. Whereas you could say to the, maybe further to the other extreme of AI is that we allow the machine to rewrite the rules as it goes on and learns. I think we're way more uncomfortable with that right now, and as well as we should be, having, letting the machine rewrite the rules. So let's start from a point of comfort, and I think the term you mentioned is absolutely spot-on, fear, right? Because look at how we were trained. We were trained in gladiatorial fashion, that if you did anywhere from 3 to 7 years of, you survived gladiator school, which is known as your residency. At any rate, you're going to see this patient at 2 a.m., and you're going to be 36 hours sleep-deprived, but you're going to still do it the right way because we've beaten it into you to do it the right way. Now, all we're going to say, I have a machine to ... me, don't worry about doing it this old way. I've got a new way, I figured it out on my own, without really any 100% confidence that I know for certain that this thing didn't hallucinate on ..., and it just made up its own rules. So let's work from an automation point of view, and I can give you an example that has had immediate impact. So one of the things that we work on, ejection fraction for the non-clinical listeners, is the amount of blood that your heart squeezes out with each beat, and you want your ejection fraction to be above 35%. Well, when we went to look in our charts, like where is the ejection fraction on all these different patients? It's all over the place, right? Sometimes it's in a discrete field, sometimes it's in progress note. Well, if we wanted to do a chart review on these 6 million progress notes, it would have taken us, Steve, 27 years to pull out all of that information. Our advanced analytics team came out with an algorithm, it read it in a weekend. Now we found all of these opportunities to treat folks who are not getting optimal care, we think, to reach out to them and say, Hey, listen, we think we can do better for you. That's how you get to the heart of the clinician. It's a meaningful, something I can do with the data, not just the data for the sake of the data, something that we came up with that was actionable and that we're having that conversation with those patients now.

Steve Lieber:
When you look at automation, or even you mentioned data analytics and all, where is your philosophy in terms of, go slow, the cost of status quo and incrementalism versus a more aggressive approach in terms of digital transformation? What are you saying to your teams and to your executive suite about how you should proceed?

Tarun Kapoor:
Everyone wants everything to be transformative, and the answer is, that's, by definition, it can't. Not everything can be transformative, and nor should everything be transformative. So if you imagine a two by two where the one axis is degree of impact or transformative capability and then the other axis is feasibility of pulling it off, low feasibility, low transfer, low impact, everyone knows to stay away from that. That's not hard. Highly transformative, highly transfer, highly feasible, everyone knows to go after that. It's the two other boxes where there's a mismatch. And what we say is, it's okay to be evolutionary in some things because that is still progress. But what ends up happening is, as you're continuing to evolve, then you start to realize, wait a minute, we now got to a place that we went from maybe high feasible but low impact to, now it's in the upper corner. So things that were previously evolutionary can turn into transformative things. Not everything is transformative on day one. The best real-world example I can think of, and my team's sick and tired of me talking about this, is Netflix. Netflix was not transformative on day one. It wasn't, right? They mailed DVDs to your home, and there was a delay in getting them. Oh, and then they came out with their streaming service, and if anyone remembers Netflix's streaming service to begin with, it was awful. It was just like every single foreign documentary you never wanted to watch, right? But they kept at it, they kept on it, and then eventually, maybe 4 or 5 cycles into it, they realized, oh, the transformative piece is that we got to write our own content. And then, when Netflix started producing everything themselves and put that onto their platform, that's when the transformation truly happened. Evolution is not a bad thing. However, once in a while, all the circles line up for transformation to occur, and what we look for is we look for three things to line up. We look for, is the technology ready to do this? Is the patient consumer ready for the transformation? And they're excited about it. And then the third one, is the operator ready to do that? And then when all three of those circles line up, that's magic time, and you go as fast as you can, right? That's transformative steroid time. And there are some unique things that are starting to happen right now that we're seeing all three of those things line up. I think the other example that happened during COVID was telemedicine. Technology was ready for decades, but the consumer wasn't ready, and the operator wasn't ready. And then, all lo and behold, they all aligned. Interestingly, some of those circles are starting to disengage now post-COVID, right? And so that's not...

Steve Lieber:
Particularly around telemedicine, specifically.

Tarun Kapoor:
Technology is still ready, but some of our patients are saying, I want to come back in person, right? And some of our patients and some of our doctors, I want to see you in person. So it's not a static thing where it's always happening, it's constantly ebbing and flowing.

Steve Lieber:
Is there, because you said, having all three of those aligned at the same time is magic, which it's, I'll translate that into, doesn't happen all the time.

Tarun Kapoor:
Very rarely.

Steve Lieber:
Is there one of those drivers that maybe when it's ready, and the other two are close, yeah, that's a go time? I mean, do you have a hierarchy there in terms of where you look?

Tarun Kapoor:
Yeah, so I would say our rule of thumb here is if one of the three circles, only one of the three circles is ready, no go. Set, let it sit back, we'll keep watching it. If two out of the three circles are aligned, then you got to think through, okay, what is it going to do to take the third one to get in? So let's say the technology is ready, and the operator is ready, and I think those are two of the harder ones, two hard ones to control, then you got to go out and educate the consumer on how to adopt that. That can be pretty hard to do. But if the consumer is ready and the operator is ready, then that's where I'm going out and looking for startups and some cutting-edge technologies. Hey, hey, listen, we want to do this, and look, this is, alignment has worked out beautifully, but I need you to kind of co-develop with us, is how we think about it. And then the last one, in which I do think is probably, well, very hard, but to some extent controllable, is getting the operator to change. And I think you asked me what is a key takeaway, just a heads up on the takeaway is, it's all about the execution, and it's the adoption from the operator where I spend, my team spends, the vast majority of our time.

Steve Lieber:
We learned that 15, 20 years ago, that you can't just throw technology in and not change the workflow, not pay attention to the way clinicians practice, and perhaps work on changing that workflow. Still the case? I mean, we, is that still a key piece of an adoption and new installation?

Tarun Kapoor:
I would say more so than ever because you still have to deal with the facts of all the other times we got it wrong before, and people still remember. So there's still hesitancy. It's like, Oh, wait a minute, this was supposed to make things better, and now we're coming back the fourth time. This time is different. Well, this time better be different, and we're going to have to work through that. I do think this time is different, but if we've made a lot of mistakes in the past, and I think we have some work to do in terms of building; because the opposite of fear is trust, and I think one of the things you talk about is working at the speed of technology that is going to be completely pegged, though, to the speed of trust. They go hand in hand.

Steve Lieber:
Yeah, that's really key, and that trust, in some of the conversations we've had in this series, that question of an issue of trust has come up, and it's caused me to really think about the past. Because we've, yeah, there are a lot of new people in the field now that weren't there 15 years ago, but there are a lot of us that are, and building that trust, and it's, okay, Did you learn from the first time? We went through something like this, and such is really key. I think that's a great insight. There are, and I like your point about the number of times you mentioned AI is inversely related to how much someone knows about it, but as you're looking for new technologies and all, how are you filtering through that? Because you're right. Right now, I think you can probably look at you go to anybody's trade show in healthcare technology, and AI is on everybody's backdrop, whether it really is or not, it's on the backdrop. How do you filter through that?

Tarun Kapoor:
Tell you, our approach, I can't necessarily say it's right for everyone, is there are times in places for point solutions, right? I have an immediate need, and I need to fix it now, and fine, I'm fine with this point solution helping that. The problem that I think a lot of health systems, health delivery systems are going to run into in the upcoming years is these point solutions start to add up really fast in terms of cost perspective, right? There's, these are all six-digit, sometimes seven-digit point solutions, and we have literally hundreds, if not thousands of use cases. So do the multiplication, and I'm going to tell you right now, if you look at the margins for the majority of health systems in this country, you cannot support this. All of our incremental operating margin, I think the average operating margin across the United States for a not-for-profit health system is around 1%. All of our operating incremental or all of our operating margin between now and the rest of this decade could be all consumed by point solutions' AI, it's just not feasible. So then what we're trying to do is we're trying to find, where are few platforms that we can work off and build and iterate such that each incremental use case is not costing the exact same amount as the last one, right? So I'm actually getting some type of still getting returned, but I'm still starting, getting some gain in efficiency in the cost structure. Not that we're not open to experimenting with point solutions, but we're going to have to continue to do this because there are such enormous constraints from a cost perspective, and we're just not going to be able to continue to crank prices up on the services we deliver. The other piece that is just an unescapable fact is, from a human resources perspective, we are not going to be able to hire our way out of some of these problems. It's mathematically impossible. And so therefore, we're going to have to be a little bit more creative with what we're able to adopt.

Steve Lieber:
Some of the conversations we've had have been around patient monitoring as an example of those point solutions versus platforms. The camera is great, but if all it does is point at the patient in the bed, or whatever, and not anything else in terms of other functionalities built into a platform. You are, you're in a sense, having to buy multiple-point solutions instead of one platform to address a range of activities that go on in the patient's room.

Tarun Kapoor:
Yeah, and I mean, I think that's how we're thinking about it as well is, Okay, great, instead of having a one-to-one sitter with someone in the room now I have maybe a person can watch 12 feeds, right? Okay, but you know what? That's still, now we're at the maximum of that point, right? There's that asymptote we've hit. But if I can tee up and watch, but why only 12 people get to be watched, right? Why can't I watch the whole house? Doesn't everyone deserve to be monitored for a fall? And so that's where we're trying to look for scale stuff. Now, if I start to see something that's worrisome, I don't mind escalating to a human and then to turn on ...

Steve Lieber:
Which kind of is in the purpose of monitoring across scale and then having something give you an alert so that you can send that person to the place where they need to be instead of wandering around, maybe crossing paths at the right time.

Tarun Kapoor:
Gosh, it probably goes back to, I think it was, I forget the brothers who did The Matrix, right? But what was the quote? Never send a human to do a machine's job. But there is plenty of work for us humans to do.

Steve Lieber:
Oh, absolutely, because it works the reverse as well. There are times where you need that sort of additional observation to see, because there can be misinformation crosswires, you know, that sort of, and so there is a time where a machine only can carry it so far.

Tarun Kapoor:
Yes. And I think that's what we're really excited about right now, as we're seeing a few opportunities to be truly transformational right from the get-go on this. Yes, in some cases, we will continue to iterate, but the idea of ambient listening is what I think gives me a lot of hope for what we can do. I mean, the other reality of it is our clinical staff is exhausted. There are already pretty significant signs of burnout amongst clinicians, both from physicians, nurses, etc., before the pandemic. Coming out of the pandemic, we've gone from big problem to flat-out crisis, and it's universal, and it's not just in the United States. So it's not like, hey, again, we're not going to hire our way out of this. We're not going to import our way out of this either. Everyone's struggling with this across the world. So we're going to have to come up with other solutions, and I think going through that triple circle piece, the technology is, well, there is some stuff that's really happening nicely with technology now. Our clinicians are like, we need whatever help we can get, and then I think the patient consumers are, maybe there's a, we don't think our patient consumers are like, wait a minute. No, I'm okay with a set of eyes helping me make sure I'm safe. And I think that is where maybe all three circles aren't perfectly unified yet, but they're starting to converge pretty nicely, and that's where we're making a pretty big bet.

Steve Lieber:
I like that in terms of the label you put on that ambient listening because there are multiple pieces to that you're going to extract from a platform type of solution there to be able to guide clinicians. And as a consumer, explain it to me as to why what it's going to do for me, and it's like, I'm there. Because it really does, it adds to a degree of comfort that even though someone's not here, you're listening, you're looking out for me, you're trying to make sure that the best possible things can happen here.

Tarun Kapoor:
If you think about it, we have these technologies in our homes, and we don't even think about it, right? Whether you have a Nest or an Ecobee or whatever, your smart thermostat, it knows whether you're in the room or not. How does, it knows because that's what the sensor is supposed to tell you, that ambient sensor says this person is in the room. If you have a security system, you have a motion sensor. The motion sensor can tell the difference of whether you're a human or a dog, because that's how it knows not to set itself off if you set it on alarm, but it's pet sensitive. So these things are all around us, and we've entrusted our safety to it in our home settings. Well, a healthcare setting is actually a pretty complex place where we could all benefit from a little extra watching and guiding as well. So I think that's again, where we can get very excited about. I think we have to be mindful and be very thoughtful from some of the other angles that people could be concerned about and no, this is not replacing your bedside nurse. This is augmenting, that's the word ...

Steve Lieber:
Augmenting.

Tarun Kapoor:
We are augmenting the skill set that's around you so that when we do spend time with you, we're not being distracted by an alert call going off here and oh, sorry. I'll be back in five minutes. Another alert goes off, I'll be back in five minutes. When I'm with you, I'm with you. And I think that's what is very helpful for both our patients and as well as our clinicians.

Steve Lieber:
And that's what the clinicians have been asking for, from the first time we started bringing information technology into the bedside is, let me spend time with the patient. Don't put the technology between me and the patient. You touched on it earlier, but let's wrap it up with your key takeaway for CIOs, CMIOs, CNIOs, the people that are bridging the gap between technology and clinical care at one end, the other end, and the middle. What's the key takeaway you've got to leave them with?

Tarun Kapoor:
Our team, we use a formula that we're not exactly sure where it came from, someone stole it from someone, who may have stolen it from one of your old colleagues, Halle Wolf. And that is the formula, NT plus OO equals COO. New technology plus old organization equals cost the old organization. This is not about the NT, this is all about the OO, and the willingness and the courage to change the OO. And our team, what we say and think it's a phrase that we embrace, it's about cold-blooded execution. Everyone's going to have these tools available to them, the price points on these tools will continue to drop as they democratize, but it's those folks who are able to operationalize them with just absolute precision and focus and energy and urgency that are going to see the day through. I think for the first time in healthcare delivery, like it or not, there's going to be winners and losers. That has never happened before. In the private world, that happens every day. I think it is a brave new world, but I do feel comforted that those who are willing to be bold, but most importantly, boldly execute, are going to have a tremendous advantage.

Steve Lieber:
Excellent. Tarun, it's great to see you and chat with you. I sure do appreciate you being with us today.

Tarun Kapoor:
Steve, many, many, many thanks to you and the team for the opportunity to share some ideas.

Steve Lieber:
Great, thank you. And to our listeners, thank you for joining us. I hope this series helps you make healthcare smarter and move with the speed of tech. Be well.

Smart from the Start Intro/Outro:
Thanks for listening to Smart from the Start. For best practices in AI and ambient intelligence, and ways your organization can help lead the era of smart hospitals, visit us at SmartHospital.ai, and for information on the leading Smart Care Facility platform, visit Care.ai.

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Smart from the Start_Sara Vaezy: Audio automatically transcribed by Sonix

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Intro:
Welcome to Smart from the Start, presented by Care.ai, the Smart Care Facility platform company and leader in AI and ambient intelligence for healthcare. Join Steve Lieber, former CEO of HIMSS, as he interviews the brightest minds in the health provider space on truly transformative technologies that are modernizing healthcare.

Steve Lieber:
Hello, and welcome to Smart from the Start. I'm your host, Steve Lieber, and it is my pleasure to bring to you a series of conversations with some of the sharpest minds in health information technology. We'll discuss the smart directions healthcare companies and providers are pursuing to create smart care teams. Today, I'm joined by Sara Vaezy, executive vice president and chief strategy and digital officer for Providence. Sarah is responsible for system strategy and digital innovation for this integrated delivery network, which includes 52 hospitals and over 1000 clinics serving over 5 million unique patients. She brings deep experience to the organization in both digital and enterprise strategy development and lead systems strategy. The ongoing development and evolution of Providence's integrated strategic and financial plan. Her framework for building and maintaining deep organizational relationships with stakeholders across the industry has resulted in partnerships with over 150 health system, digital and innovation teams, venture capital organizations, industry analysts and influencers, and digital health organizations. Welcome, Sara.

Sara Vaezy:
Thank you so much for having me, Steve. I'm looking forward to the conversation.

Steve Lieber:
I am as well. You're well known across the healthcare digital world, and so the opportunity to spend some time with you today is quite a treat. So let's start out talking a little bit about your environment in Providence. Providence has a reputation for challenging its own establishment and its incumbency. So there are two sides to that. One, you can run into some resistance to change, and then, there's also benefits from it. Let's start out with the internal environment and what you encountered in the way of challenges, resistance and how you overcame that.

Sara Vaezy:
So I've been with Providence for seven and a half years, and the nature of the challenges, and the internal environment has actually changed quite a bit over that time period. Seven and a half years ago, when I joined the Digital Innovation Group, it was a much less mature market from an innovation standpoint, from a digital standpoint, and as such, the organization itself was a lot less mature, and there were, the environment was much more around like science projects and interesting things that we could do in digital and things that maybe wouldn't really pay off for several years and were fairly, I would say, expensive things to even develop, and I know we'll get to this in a little bit, but mostly in point solution land. Then, and the nature of those challenges was a lot of butting heads with our IT colleagues around, like how do you build in a sustainable architecture that's really focused on uptime and maintaining the EMR and sort of those core functions versus keeping innovation going? That was the nature of the sort of challenges at that stage. And then, as we progressed, and we honed our thesis around why we do digital and not just innovation, but digital innovation specifically, and in service to driving sustainable growth for the system, for our patients to get more patients and consumers within our system and retain them and serve them in the most effective way, those conversations changed into, okay, now you've got two different teams building and maintaining enterprise software. And so there was natural tension there because the interdependencies between the team grew and were, we were building everything on top of our core EMR platform and things like, Oh, we've got an upgrade coming up, and therefore you can't do innovation. It was just like constant clashing. Now we get to the COVID period, and I would say maybe most relevant is the sort of downward I don't, I wouldn't call it post-COVID quite yet, but this, like the tail end of COVID when the health system environment, internally for us, but also every single health system out there just economic the bottom fell out. And that actually became an opportunity for us from an IS and technology standpoint to stack hands and to really divide up like, what are we all respectively here for? And those, that, those historical challenges went away out of necessity. But what emerged in its place is a focus on needing to just double down on the core, on care delivery, and our recovery efforts, and that becomes very difficult to compete for attention with clinical and operational needs that are like very much keeping the lights on. And it's a hard kind of argument to make from my perspective, even, I'm like, I'm not asking for us to not go hire nurses or to ensure that our caregivers are safe and happy or that we are serving patients in our hospitals. And so that's the natural tension that has emerged, and over the course of the last 18 to 24 months or so. And now we're emerging out of that and beginning as an organization to lift our heads up and say, what do we need to do that's further out and knit together our enterprise strategy with our digital strategy? And so the internal environments becoming more responsive and receptive to that. But those challenges still remain where we're, we've got a massive workforce challenge ahead of us. It's actually, one of our executives in our workforce team reminds us, this is about as good as it's ever going to be in the future because it's actually going to get tougher and tougher. And so how we function in that environment, that's where those internal challenges are emerging. And it's the way that we've handled all of these situations and in particularly over the course of the last year, is constant engagement, constant kind of reminders about what we do, why we're here, why sustainable growth is important, how it works in service to and compliments all of these other things in the organization that are competing for attention and they should, and why they all build like a mutually reinforcing story together and just doing it over and over. So that's been our evolution from an internal environment standpoint, it's still very tough. And, but for, I would say it's tough, not for silly reasons. We've got a lot going on in healthcare, in health systems, and we're working on structural changes that are going to be meaningful into the future.

Steve Lieber:
Yeah, you touched on something as you went through that timeline that was a new sort of thought to me in terms of the pandemic changing the way we looked at change and, maybe out of necessity, that we were faced with a lot of our workforce not being in the same place, we are all the time, patients not being in the institution and having to reach them. And so is that really a message there that we did change the way we looked at change because of the environmental necessity of having to work differently?

Sara Vaezy:
Absolutely. And that was most obvious at the very beginning of COVID when there was this massive, we didn't really know what was going on, and everybody had to stack hands, and we had to shut clinics down and stop doing certain services because folks were so worried about exposure. And so everybody had to work together to, in that more virtual environment, figure out how do we serve, how do we do things that would have taken a year and do it in 3 to 5 days? Like, we stood up our first home monitoring program in under a week, and that's like unheard of now. And so the way we think about change and our risk tolerance and the pace at which we embraced change was completely transformed. Now, in some ways, like the inertia from the past took back over, and so we've, in some ways, gone back to how we take that very thoughtful and like methodical approach. And we are very concerned about dotting all the I's and crossing all the T's from a risk integrity perspective, risk, we call it risk and integrity services, so like risk compliance, all that stuff. But when in the beginning, like it was just, it was a bit of a free-for-all, but it was also just a different way of working where it was like everyone swarmed the problems together. And so that definitely happened, but both things, one thing I think we took for granted was that momentum would continue, and it doesn't because people get tired, and it's really hard to work that way over the fullness of time. And you, and I don't even know if it's, I don't even think it's healthy, right? You get into a hero mentality as opposed to a, we got to build systems that allow for us to do this over the fullness of time, and we didn't have the bandwidth to be able to do that.

Steve Lieber:
You talk about being methodical and dotting I's, crossing T's, and that sort of thing, but from the outside, Providence has a reputation of being on the forward edge of things. The impression I have of the organization is, it's not a plodding organization. There's an aggressive mentality, and especially in your area, that drives strategy in the organization. Fair assessment?

Sara Vaezy:
I think it's a fair assessment, though there are places from a clinical in the clinical domains where we are very, I don't know if I would use the word plodding, but we definitely take our time because there is a much there's more at stake.

Steve Lieber:
Sure.

Sara Vaezy:
When we're talking about, for instance, like a lot of the work that I do around ensuring folks have a really great experience booking their appointments or getting access to their, all of their digital sort of solutions. And we have this concept of identity-driven engagement around a centralized platform, those things aren't life or death. We don't want to have bad experiences, right? But we also they're not life or death versus the clinical domain. So it depends on the part of the organization. But we are, we're very aggressive on certain things because we, that's a necessity unto itself. For instance, in the, anything that's in the consumer space, we're out there in the market with folks that are much more nimble, have much more capital, have much more, in some cases, connection to patients and consumers because of, because they might be a payer. So they've got the head element working for them. So we have to be, and so we really view all of these things in a, I would say, a relatively sophisticated way. What's the opportunity cost of not being aggressive? And in some cases, it's pretty high.

Steve Lieber:
Pretty high, yeah. You mentioned the Digital Innovation Group earlier, and you've architected evolution of that group, according to my notes, commercialized three incubated technologies into independent companies. Talk to us a little bit about that journey and how that works, both in terms of building those technologies and creating new companies, but also integrating that into Providence own systems and operations, which I assume is equally an objective of what we're trying to do here, not just create new solutions for other people.

Sara Vaezy:
It is equally an objective, and it's the harder part. So we have, yeah.

Steve Lieber:
And we're going to follow that up with, Okay, let's talk about the tension between innovation and operations, but let's start out with the group and how you got there, and then you can follow on into that area, or I'll ask the question again.

Sara Vaezy:
Sure. From an innovation standpoint, all, so this is less about the operationalization side of things. It's, especially when we come, we talk about the consumer-facing sides of an organization, it's absolutely essential to build differentiated experiences. Otherwise, we won't be able to maintain any sort of competitive advantage over these digital-first disruptors and companies that are coming into our space. And it's not like one company is going to deal a death blow, it's more chipping away little by little at our relationships with our patients and our consumers and the economics all up. So we build in that innovation context because we know that differentiation is so important. But we can't, we're not a technology company, we're a healthcare organization, we're a health company. And so we had to figure out a way throughout the evolution of our group to go from building cool technology to actually doing something. And that's why we started commercializing and launching these new companies, because we can still build the company, but then we can raise external capital and release these companies out into the market so that they can compete with that capital. They can serve other health systems, which we have this broader sort of objective to help others transform as well. It's not just about keeping it within Providence because we're just one among many. And in order to have a full transformation, we really need others to come along for the ride, if you will. And then we can redeploy our internal resources against the next set of problems. And so that's the way we think about why we do innovation. We get really deep on understanding our own problems as well as the problems of other health systems, and then we solve for them. We do extensive build-buy analysis, and then once we build with this sort of market-oriented, is there a market out there, and does it make sense for us to, do we have some sort of advantage in terms of how we're building? And often, the answer is no. But sometimes the answer is, look, we're a customer of, we're going to be a customer, we know that we have a sandbox, we've got the internal expertise, we've got the, from a clinical and operational standpoint, and we bring in this technology orientation. So we have this very unique vantage point relative to others simply by just because of this little, this interesting intersection of all these services.

Steve Lieber:
What you're talking about, you have the problem, you're experiencing the problem, and you're also coming up with the solution for it.

Sara Vaezy:
Exactly. And the problem is they're all wrapped up together. The operational problems, the technology platform problems, and the operational problems, they're all together. And so we are, we live it every day, and therefore, we're best positioned to solve for it. So we've done this three cycles, each with a different model. Our first instance was a company called Zell's, which was an EIR, entrepreneur-in-residence-driven model where we had a great team of formerly mobile entrepreneurs come in and build an enterprise solution for driving digital prescriptions. That company is run by a gentleman named Mike McSherry, who is awesome, and we are still partners with them. The second time we did it, we actually had built a platform for women's health personalization that was acquired by Wildflower Health, which is a women's health platform, and they're moving more and more into risk-based maternity care. And then the third cycle was a company called Dex Care that we did, that we built, and it's led by Derek Street and Sean O'Connor, again, two entrepreneurs. They were in the sort of surgical education, and they worked intuitive surgical kind of space. And then they came in and brought this thinking to platforms as a service for driving, essentially load balancing and access optimization. So in each of these instances, very different. In the Dex Care case, like we founded a lot of that, we built it internally and then brought Derek and Sean in to do that work. And, but the similarities were we had an MVP internally, and then we scaled it across our organization. Then we commercialized to other health systems had or brought in external leaders to be able to continue to lead these things, not just converting internal operators into leaders of startups, and then, we raised external venture capital. So we have three points of external validation. So that's how we thought about our model. And then, in each case, we redeployed resources to the next set of problems. We've got a list of 99 problems and ever-growing and continuously being refreshed. Then the question you asked around operationalization.

Steve Lieber:
Yeah.

Sara Vaezy:
That's a really tough one. And in particular with our, that we're now on our fourth cycle of building a company. We've been emphasizing that quite a bit. Who is our internal buyer? What problems are they trying to solve that they are willing to pay for is something that we are much more, much more focused on this time around. And then what are the capabilities that we need that will allow us to catch that technology to make it scale successfully? So that's what we're really focused on this time around, and we're getting really dialed in on it.

Steve Lieber:
Cool. I want to pivot a little bit and talk about platforms and point solutions, we came up in the conversation a little while ago, come back to it now. So over the last 20 years, we've seen a couple of cycles back in the early part of the millennium, very focused on EHR platforms. All of us were really driving that, digitizing healthcare, and that's the way we figured out how to do it. Then came along an era of applications. Everybody had a solution for a single problem point solution type of approach. So talk a little bit about where you see where we are today, advantages and disadvantages. From my perspective, you solve one problem with point solution. Usually, problems are not isolated. There are other activities related to that function. And if you just have a technology that addresses a piece, now you've got dozens related to the same care process, to use that term. So talk a little bit about your experience platforms versus point solutions where you see us going.

Sara Vaezy:
I think we're swinging back in the direction of more platforms. That's the short answer and the reason for that being, as you described, right? Point solutions, one, there are other kind of related problems. It creates, if we only live in application land, it creates a huge amount of integration challenges for IT, and then there's the question of like, how do these things interact with one another in order to actually drive outcomes? In many cases, from an information data transfer perspective, like they live in silos. And so these sort of the, they don't talk to one another, they don't really work collaboratively in service to some sort of outcome, whether it be for a patient or a consumer. And so we're swinging back, I think, in the direction of platforms, and that's been one of our theses when it comes to build, is that there was a huge amount of emphasis as you articulated, around the EMR during the meaningful use era. That's fine, but those have very specific kind of things that they're good for and it's very oriented around like the clinical transaction as opposed to a more longitudinal or continuum of view.

Steve Lieber:
And more of the collection of data versus doing something with it.

Sara Vaezy:
That's exactly right. Exactly. They're not workflow tools. And when it comes to consumer, like if we think about the consumer lens, it's certainly not a consumer experience, commercial grade experience. It is a very clunky sort of lots of menus with dropdowns and all kinds of stuff like that. And our thesis has been like there, the EMR has its place, but the platforms, but the systems on top are really important in order to bring up the platforms to the level of consumer expectation or clinician expectation around how they actually manage their workflow. And so I think we're swinging in that direction and it's the right thing to do, but -I don't really, when we talk about point solutions and people bash point solutions, they have their place. And if we are able to create an environment, a technical environment where we can actually like, for instance, again on the consumer side, have a single sign-on protocol to knit things together, point solutions can actually be really powerful and they will, we get like that best-of-breed approach to solving a very specific problem, but within the context of an ecosystem that's connected around an identity of an individual. So that's like the kinds of things, I think we're, now the puzzle pieces are coming together more, and so that instead of being focused just on like data infrastructure, which is what the EMR did, or getting these isolated little things done, we're knitting, we're connecting the dots and orchestrating experiences, and that's what modern-day platforms are more for.

Steve Lieber:
So if I'm hearing you correctly, there's an evolution here. We needed what we did 20 years ago to get to the point where we are today and for the things that we can do in the future. Again, key variables here are, you use term knitting together, so interoperability, they got to talk to one another. And certainly, we've got to be focused on ease of use at the clinician point of connection to our systems as well, because I'm still hearing that, although not like in the beginning, we still got some clinical resistance in terms of changing workflow, introducing new tools and all. And we really do need to listen to that and make sure we're not creating more clicks and taking away from care, so to speak.

Sara Vaezy:
Absolutely. There's no reason for us to make the clinicians' life harder, just like we don't want to make the consumer or patient's life harder. Like one of the things we remind folks is, it's really great, it's really important to have a 1 to 2-click scheduling experience. For every other additional click, you're losing folks throughout the process, right? When you're adding friction, you're losing, you're adding effort, and you're losing people along the way, and clinicians, same thing. We, one of the things that we've noticed actually is that we brought a bunch of folks online during the height of COVID because folks had to engage in telehealth and other types of things, but then we created this, there was an unintended consequence around like driving a huge volume of in-basket messages to providers because folks got trained up on like, how do I use these things? And we're now putting in place some platforms to actually support a message being sent, in some cases is a defect because that means that the person could have gotten, perhaps could have gotten their task completed with, if they had been able to find the information they needed or been able to complete the task but they couldn't. And so how about we navigate them through that and prevent a message from being generated in the first place? So we've got, we've done some work there and noticed already upwards of 20% reduction in administrative messages. So it's a really important thing to keep in mind.

Steve Lieber:
Yeah, that's a great takeaway in terms of recognizing that a decrease in messages is actually an improvement because the idea is self-service. You get your answer, you get your information, you transact your activity, versus I can get started, I can get to a point, then I have to send a message. That's a great metric. I really do like that. Okay, wrapping up here, our listeners are all kinds of digital health leaders, CIOs, CMIOs, CNIOs, and others. A takeaway for them. You've been through a lot here in just the last seven and a half years, plus a longer career period here. Take away a message.

Sara Vaezy:
To go back to our previous theme, the sense of urgency is something that it's not a technical thing to take away, but it is a, the sense of urgency around bringing together clinical, operational, and technology to meaningfully, especially solve consumer problems is something that can't be ignored and it can't be relegated exclusively to an infrastructure layer around the electronic medical record. It's not going to serve their needs because customers expect differently, and especially in this new era, our customer expectations are often set by retail and tech. They're so pervasive. That's what governs how we, what we want from everywhere else in our lives. And so it's not like, I'm not trying to be a technocrat. What I'm trying to say is that's the reality is that...

Steve Lieber:
You've got to respect your customer and what their expectations are.

Sara Vaezy:
Yeah, exactly. And so we need to lean in with urgency around understanding that it's not just about infrastructure and like putting all your data somewhere. It has to be usable and it has to make sense for driving a specific experience that people expect. So lean into it, don't expect your EMR to do everything.

Steve Lieber:
Yeah, and I'd add to that, clinicians are customers too, and thinking about them and their expectations of convenience as well as the patient. In a sense, they are the same set of expectations.

Sara Vaezy:
For sure, they are people too.

Steve Lieber:
They are. So this has been a great conversation. I really do appreciate your time today. It's been a fantastic few minutes here of visiting with you.

Sara Vaezy:
Thank you so much for having me. I really enjoyed it.

Steve Lieber:
Excellent. Thank you again. And to our listeners, thank you for joining us. I hope this series helps you make healthcare smarter and move at the speed of tech. Be well.

Intro:
Thanks for listening to Smart from the Start. For best practices in AI, in ambient intelligence, and ways your organization can help lead the era of smart hospitals, visit us at SmartHospital.ai, and for information on the leading Smart Care Facility platform, visit Care.ai.

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Smart from the Start_Alan Smith: Audio automatically transcribed by Sonix

Smart from the Start_Alan Smith: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.

Intro/Outro:
Welcome to Smart From the Start, presented by Care.ai, the Smart Care Facility platform company and leader in AI and ambient intelligence for healthcare. Join Steve Lieber, former CEO of HIMSS, as he interviews the brightest minds in the health provider space on truly transformative technologies that are modernizing healthcare.

Steve Lieber:
Hello, and welcome to Smart from the Start. I'm your host, Steve Lieber, and it's my pleasure to bring to you a series of conversations with some of the sharpest minds in health information technology. We'll discuss the smart directions healthcare companies and providers are pursuing to create smart care teams. Today, I'm joined by Alan Smith, a Senior Vice President and CIO for Lifepoint Health. Al leads the organization's information technology services and cybersecurity functions across a more than $9 billion organization, which includes more than 60 acute care hospital campuses, 22 behavioral health hospitals, more than 2000 employed MDs, and more than 30 freestanding inpatient rehab facilities. In his role, he is responsible for implementing information technologies that support Lifepoint's mission and drive the company's innovation, operational performance, and financial excellence. Previously, Al has served as SVP and CIO for RCCH Healthcare Partners and Capella Healthcare, both now part of Lifepoint Health, as well as other leadership positions at Vanguard Health Systems, Cerner Corporation, and vice president of clinical applications for Carolina's Healthcare System. Welcome, Al.

Alan Smith:
Thanks for having me. I'm looking forward to it.

Steve Lieber:
Likewise, coming from Lifepoint and also having worked in facilities that became part of Lifepoint, you're living with, I expect, putting together legacy systems of different brands in terms of, let's just start out with the EHR platforms. Are you moving towards standardization, or, no, this is the hand we've been dealt, and we're working with each one of them with the different varieties that you have. How's that working?

Alan Smith:
Yeah, so definitely, as you said, legacy of a company that has been the product of 3 or 4 mergers over time, and everybody had a little different way that they were dealing with things. So the short answer is, we have just about every EMR that's out there and multiple versions. So we have a lot of disparity, a lot of diversity. That's a challenge. And I will say, we are selectively moving to consistent ones, but not wholesale across everything we might have. So, for instance, on our post-acute care side, we are in the process of implementing a standard EHR across all of our behavioral health and ... On the acute care side, it's a little bit case by case, either because we're being forced because EMR is end of life or the business case can be made. I can bend the cost curve, or there are reasons we do that, but there has to be a business case behind replacing them, so I'm going to live in a world of disparate EMRs for a long time, a long time. I won't get to one anytime soon.

Steve Lieber:
Yeah, well, and as you say, the business case has got to be there. The resources aren't there for us just to rip and replace without that being a key driver. And in your intro, it talks about focus on innovation, operational performance, and financial excellence, so obviously, those are three pillars that you're balancing all the time.

Alan Smith:
Absolutely, absolutely, and I think there's some natural tension there a little bit to be innovative. Can you spend the money? Do you want to spend the money? Do you want to be a fast follower? Do you really want to be cutting-edge? And, you know, I think that's probably a good tension to have—and checks and balances, if you will, a little bit, and depending on what we're working on and how we're doing financially, sometimes it might weigh one way or the other. So that's a good thing, but it has made us be, think, when we think innovation, we try to find partners who are EMR agnostic. I think one of the challenges we have is our EMR vendors, some of them are innovating very quickly. Other ones are not innovating very quickly. And so there's a little bit of a natural tension there of if I've got a more innovative EMR I'm working with, do we go with something that's the same across the enterprise? Because now I'm solving for something that's maybe with an EMR that doesn't have a lot of functionality. So do we go consistent, or do we vary a little bit to take advantages of the EMR that maybe are a little bit more innovative? So that's an ongoing discussion some people will argue for. Well, I just need consistency across the board. But well, if I'm in an epic market, maybe I don't need that because they can do something or a Cerner market, etc. So I think it's forced us to look at EMR agnostic, but I think it's also forced us to not always look for one size fits all. And sometimes, when it makes sense, we vary off that because of the capabilities of the systems that we're working in a local market. The other thing is a little different about us is our acute care hospitals are spread out across 60 hospitals in 20-plus states. So we don't have a lot of regional density where you get like, you know, what's the likelihood that a patient's going to go from somewhere in western Washington to South Carolina? Not a whole lot. So that hurts some of the business case, on why a lot of people say, hey, I got to have one patient record within a geography. We do have some of that, but we're a little bit spread out where some of that dilutes from our operational perspective, whether it's sharing staff, sharing patients, etc., so it makes the business case maybe a little bit harder for us.

Steve Lieber:
So as you're looking at sort of moving beyond the EHR, we kind of been through that a little bit with data analytics. We looked at solutions there. Now we're starting to talk about artificial intelligence and ambient monitoring and that sort of thing. What are you seeing in terms of the solutions out there, especially in a diverse environment like you've got? What's the status of the market right now and some of those newer directions?

Alan Smith:
Yeah, I think if I look at ambient listening in particular, there's a couple of folks that we are piloting. I think part of the challenge is there's so much coming at us. I could spend all my time just looking at new products that claim they can do X, and they're the greatest thing since sliced bread, right? And we talk about, with our innovation committee, how do we fast triage. Because you can spend a lot of time triaging. Every vendor is going to tell you their best side. Half of them are true, half of them aren't. And so how do you do some of that? And then when you make a decision, how do you just say, look, I'm sitting in this space. If I've got a couple of partners, I'm going to pilot, I'm putting the other ones to the side. So we talk about fast triage. We think of yes, no, and not now, and there's a lot of stuff that's sort of not now. I'm busy right now. Let us partner with a couple people. We've got pilots going. If those don't pan out, we'll be back to the table. And if they do, do we really need a third partner? What's the difference between the first two? Unless it's cost or significant functionality, at some point, you've got to kind of cull the herd and get it down just to a couple partners, because you just can't handle everything that might be out there. So that's a couple of ways we look at it. I'd say both in the ambient listening, sort of the virtual assistant, and then also in the, what I would call, when I talk ambient listening, also in sort of like the tele sitting virtual nursing, those types, more of the camera-based AI type things. Again, there are vendors popping up left, right, center, wverybody can figure it out better than the last one. At some point, you got to pick a couple do pilots and then figure out if you're going to scale it or not. Yeah, so lots to do there.

Steve Lieber:
So in that area in particular, ambient monitoring, ambient listening, and all, I see a lot of point solutions. I also see some platforms out there. Are you looking more in the platform that has multiple functionality, or are you working on specific use cases and looking more at a point solution approach?

Alan Smith:
Platforms, clearly platforms. That's one of the big concerns I have is death by a thousand integrations, death by a thousand vendors. At some point, it gets unwieldy, so our preference is platforms, clearly. I don't want to go with the best tele-sitting if they can't support my virtual nursing because I want one set of devices. I want one set, I want one vendor, I want one contract, etcetera, etcetera. So our hope is really to drive the platforms and to minimize that. We're doing that on analytics too, right? I mean, you can think of analytics that can be death by a thousand extracts. So push platforms and then kind of say, why can't you use this? If we can develop it and we can use that platform or that platform can be extended, any of those partners, we'd prefer to do that and maybe even co-develop than we would to have use case-specific partners.

Steve Lieber:
So as you look at perhaps the analytics area, are there lessons learned, just because that one's maybe a half a generation older than we are in ambient and artificial intelligence, you know, in terms of coming out of it, I think clearly one of them you've just articulated there is platform. No, you didn't even hesitate on that question. Any other sort of lessons learned from the analytics area, just because, let's say, we've been farther down that path of installed, used driving different practices in terms of care paths, for example, or whatever? Any takeaways as you start moving into the AI area from your past experiences that you've learned?

Alan Smith:
Well, I think you hit on one. One was the platform. I think initially, we definitely had use case-specific analytics, and everybody could pitch something, and eventually, you had to collapse to some things. I think for us, we are not typically a development shop. We'll co-develop with people, and we'll partner with you, we'll help ideate, etc., but we're looking for people that can deliver a full solution, not just tech, but come with the people to build it, process technology, etc. And when I say platform, those are the types of things we've kind of looked at, getting internal resources to build analytics or getting internal resources to do tele-sitting. It's probably not going to happen, at least not out of the gate. We want to outsource some of those things and leverage others' best thinking, best practices, and other skill sets as well. So those are a couple of things I think we learned through the analytics piece. Having said that, I think the analytics is getting a whole another boost now with AI and ChatGPT and LMS, etc. So there's almost like a resurgence a little bit on analytics. And can we do a lot more predictive and a lot less retrospective? So it's kind of like we had foundational analytics, and now I see AI kind of pushing us forward into what I would call more predictive and more assistive real-time analytics. So I think we're almost going through a second round on that side as well, so it's been interesting.

Steve Lieber:
Yeah, totally agree with you. Because, certainly, in the past, your analytics applications would give you information that then required someone to study, analyze further, and draw conclusions.

Alan Smith:
Right.

Steve Lieber:
Now we've got applications that are kind of coming in on top of that and doing those steps that carry our thinking a little bit further before it ever gets to us to look at.

Alan Smith:
Kind of looking down the road, right, skating to where the puck is going to be, not where it is. And we're seeing a lot of use cases and a lot of interest from our operators in that, right? Don't just tell me things about labor management. Tell me what my forecast, for me, what my demand is going to be, and how many nurses I need two days from now based on OR cases and discharges and ER throughput this time of year, etc., etc., etc. So it's getting a lot more complicated, but to me, it's a lot more fun, because we're starting to answer some really cool questions, not just sort of, well, what happened yesterday?

Steve Lieber:
Well, yeah, and it does. It allows us because of, just like the original concepts behind EHRs, that it allowed us to collect a lot of data and be able to retrieve it. Now, we're able to analyze a lot of data and work with it. And it really does kind of carry us further into a more exciting place and start to anticipate directions that patients might go or whatever. And so, I think you're right. It's sort of a rebirth of the analytics area as we add this new machine learning piece on top of it. It's very exciting.

Alan Smith:
It's kind of, like we're finally getting to the payoff for all the work we all did through MU-one, MU-two, slogging through data and codifying and all this stuff that we all took a lot of grief for, and we're finally getting to the oh, I get it. That's why we did this.

Steve Lieber:
That's why we did well. And we talked about it at the time. You know, you got to get out of paper, you got to digitize it so that, and here we are, we're now at doing that. That's a good, good point. In my notes, I've got a reference here to Lifepoint Forward, an incubator area in the organization. Talk a little bit about what that is and what you're up to.

Alan Smith:
Yeah, that's interesting. So Lifepoint Forward is really our innovation platform, if you will, and in that, we really do three different things. We build, we do have an incubator, and I'll come back to that; we buy, we make strategic investments in partner, especially if they want to co-develop; and then we do the traditional partner, right? The traditional contract, we're going to ride you for everything across the enterprise. So there are sort of like build, there's co-invest or invest where we might actually get warrants or put equity in, and then there's sort of the traditional partnership. Probably the most interesting or unique of those is the 25M-health. So that's a partnership with a company called 25 Madison and Lifepoint, and we basically each put money in and create an incubator. They actually sit on the second floor right here below me, so I get to talk to them quite often. And the thought here was, Lifepoint is big enough, and we have enough issues that if we have an issue and they can use us, they can find things that either we keep to ourselves and we keep the IP but it's good for us, it's efficient, it's creating efficiencies for us and in workflow, etc., or they may build something, and we may spin that out as a commercial enterprise at some point. One of the interesting parts about us is, because we run so many different EMRs, we like to say, if you can make it here, you can make it anywhere, because I get lots of vendors come in and go, well, you know, here's how I interface with Epic. I'm like, great, what does that do for Meditech magic? Nothing. Paragon? Doesn't do anything. It's harder to make it here and to work scale here because of all the diversity or disparity, but at the same time, if you can do it here, you pretty much have hit just about everything you're going to hit in the marketplace. There might be some, but you've hit an awful lot of it. So it's been an interesting partnership with them where they go out into our hospitals, they work with frontline clinicians, and they're looking for incubation, new ideas that they can build software that, again, we either keep the IP because it's something we want to keep or something it'll be commercialized later. So that's been really interesting that I have not had the chance to do that in my career. We're not a development shop, so now there's people on the second floor who are development. So if we've got a big idea now, we can potentially do it. So that's been really interesting. And then the whole equity thing, you know, we've got a number of partners where we've made strategic investments, and health is one Loyal Health is another, and there's other Bio Intelligence. There's others. One of the discussions we have when we entertain a new vendor partner is what's your capitalization structure? Are you looking for capital? And some of those things? I'm not on the investment committee, but that's been kind of interesting to learn about those things as well. And in the past, until about three years ago, that just wasn't part of the conversation for us. That's been fun as well, yeah.

Steve Lieber:
So as you work in what is Incubator Lab, so to speak, what's it like to move that into operations? What are some of the things you have to go through, you need to go through, in order to bring it to life?

Alan Smith:
Yeah. I mean, I think first and foremost, right? It's got to be something that our front-line clinicians or operators are interested in, obviously. So they spend a lot of their time with front-line clinicians in particular, saying, what are your pain points? We start there. This isn't usually "Hey, Al had a great idea." That's not usually where this comes from. I'm more on the back side going, okay, how are we going to operationalize this? And we thought of this. How are we going to get the data out? Do we have to put data back in and doing some of those things? So we're part of that process. But it is not an IT-driven process at all. It's what's going to move the needle in terms of operators, and then IT's kind of the back side saying, okay, how can we operationalize it, and where does the data have to be, does it be secure etc., etc., etc. So it starts clearly with them, because if they're not going to buy in, then it's kind of a waste of time. So that's really what drives it. I think it's interesting because the post-acute, and we've got a sister company who does LTACs, so their needs aren't always the same. So are we going to focus acute, post-acute, where are we? There's only so many calories, but we're always looking at those types of things as well. So it's an interesting process. It works relatively well, but we've spent a lot of time with them, and you know, there's also trust there too, right? So they come to us quickly, especially if they're going to innovate. If they hear something, they'll pull us in relatively early to kind of give it a sanity check. How are we going to make this work? There's a lot of great ideas, but if can't do it and if can't inter-operate with my EMR, they start to fall flat. So we're pretty early, but we are not the driver of it.

Steve Lieber:
So what's the mood in the workforce today? Where are we in terms of how people are dealing with technology, dealing with change? Because this usually, if not almost always, impacts workflow and changes workflow as well. Talk a little bit about the personal side of this.

Alan Smith:
Yeah. Where are we with workforce? I mean, coming out of COVID, no big shock, we're like everybody else, a lot of burned-out folks. That was a rough, rough road to hoe, so a lot of turnover. We're starting to see that come down. I think people are open to change, but they're cautious, and they feel like the last couple of years were pretty rough on them. So there's always this little bit of like, how much change can people take? I think a lot of that comes back to leadership, and that's at our local facilities. Can they get people excited about change? Can they sell the case for change or not? Not every CEO is change-friendly, if you will. Not every CNO is change-friendly. You've got to have those leaders. But I think people are realizing we've got to operate differently, and we've got to change the way we do it and are open to it. But I think there's still this balance where people are still pretty burnt out, if you will, or tired from COVID. And now there's a lot of financial pressures, and that's causing a lot of, I think, natural tension there, but I think people are open to it. But it is a challenge to balance all that. It's easy to sit in the ivory tower and say, we're just going to innovate all this stuff. Great in the front lines, like, wait a minute, hold on. So that's why again, we start with engaging clinicians on the front side. If a facility and a group of nurses are willing, there's no point in going on this. We need to find somebody else to go with.

Steve Lieber:
Yeah. Do you find at times that because you've got those champions, you'll roll it out in one place and not another, even if the platforms are the same or whatever? I mean, is there a judgment call you make where you kind of look at the environment and say, okay, I think it's going to fly here, but let's wait because we've got to be able to show them more? We need results before we tackle that group.

Alan Smith:
Absolutely. The reality of it, I mean, for instance, if you've got a facility, you just turned over their CNO and the new ones, and there's probably not the right time to bring something in, they're still trying to get their sea legs underneath, so there's absolutely certain markets where we're focused on. We've not gone to like, you know HCA, and some people kind of innovate. There's 2 or 3 hospitals that they say those are innovation centers. We've not done that yet. That's an open dialogue right now. Is that a better way to do it, or do you just, can any one of our hospitals handle that, or do we need to spread the load? And I don't know that we have the right answer for that now. Sometimes, it depends on what the innovation is too, and where you're going.

Steve Lieber:
Sure, that makes all the sense in the world. You know, our listeners are folks like you, CIOs, CMIOs, CNIOs, other information technology and digital health leaders. What's your takeaway? What's the message you've got to share with your colleagues that you're doing, you've learned that you'd like to share?

Alan Smith:
I'll throw out two things, if that's okay. One is, be humble. I don't know everything, no way, and none of us do, especially at the HSC. Be humble. We don't know everything. We need to engage our clinicians. We also need to take good lessons, learn from outside our industry. We aren't the leaders in innovation in many cases, so we need to be humble and try to learn from others and make that the tent, if you will, big, get lots of good ideas from lots of people. The second thing I'll say is just keep pushing forward. We talked about fast triage, but fast fail. Innovation, you're going to fail some. I mean, we've incubated some things that we had to just terminate. It wasn't going to work. We piloted, it didn't work, make the call, move on, let's go to the next thing. I think sometimes that's really hard when, especially if it was your idea or you're part of it, it's like, this is going to work, it makes sense. But at some point, you've got to cut bait, move on, go to the next thing. So I look at it as we collectively win, we collectively fail, and with innovation, you're going to fail some. You're not going to throw a perfect game, you're not going to hit every ball. So just keep moving forward, and as long as you're making incremental progress, that's good. Keep doing that. Change is difficult. You're going to have some failures, regroup, learn from them, keep moving forward, and don't stop pushing on it.

Steve Lieber:
Yeah. And you mentioned earlier trust and creating that safe environment where it's okay to fail. If that's the way it plays out, nobody's going to get punished for that, but it's like, find the answer right or wrong quickly and then, as you say, move on, but creating that trusting environment where everybody's comfortable and believes that's the way it actually will happen.

Alan Smith:
Yeah, I think the other part of that is, have clear KPIs going in, right? How are you going to measure success or failure, right?

Steve Lieber:
What does it look like?

Alan Smith:
If you don't have good KPIs, everything looks good, right? And I say that sometimes we get a little too granular, and we push the financial KPIs. We go, you got to get it directionally correct. You got to get it correct. Sometimes, we can go too long nitpicking those down to everything. Sometimes, just get it close, come back, get the real data and come back and then make a call after the fact, but you got to measure it.

Steve Lieber:
Absolutely. Yeah, if you don't know what you're trying to accomplish, you don't know what to measure, and you don't know whether you've made it there or not, great insight. Now, this has been a great conversation. I really do appreciate your time today.

Alan Smith:
Hey, thanks. This was great. This was fun. It's fun to kind of think about some of the things we're doing and take the time out to talk about them a little bit, so I appreciate your asking me.

Steve Lieber:
Excellent, thank you. And to our listeners, thank you for joining us. I hope this series helps you make healthcare smarter and move at the speed of tech. Be well!

Intro/Outro:
Thanks for listening to Smart from the Start. For best practices in AI and ambient intelligence, and ways your organization can help lead the era of smart hospitals, visit us at SmartHospital.ai, and for information on the leading Smart Care Facility platform, visit Care.ai.

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Smart from the Start_ Karen Murphy: Audio automatically transcribed by Sonix

Smart from the Start_ Karen Murphy: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.

Intro/Outro:
Welcome to Smart from the Start, presented by Care.ai, the Smart Care Facility platform company and leader in AI and ambient intelligence for healthcare. Join Steve Lieber, former CEO of HIMSS, as he interviews the brightest minds in the health provider space on truly transformative technologies that are modernizing healthcare.

Steve Lieber:
Hello, and welcome to Smart from the Start. I'm your host, Steve Lieber, and it's my pleasure to bring to you a series of conversations with some of the sharpest minds in health information technology. We'll discuss the smart directions healthcare companies and providers are pursuing to create smart care teams. Today, I'm joined by Karen Murphy. At Geisinger, Karen is an Executive Vice President and serves as Chief Innovation and Digital Transformation Officer, as well as founding director of the Steele Institute for Healthcare Innovation. In these roles, she's developed Geisinger's Digital Transformation Office, which includes Geisinger's AI lab. She's also the architect of the Intelligent Automation Hub, designed to optimize operations and produce significant cost savings. Prior to Geisinger, Karen served as Pennsylvania's Secretary of Health, and she also served as president and CEO of Moses Taylor Health System. Welcome, Karen.

Karen Murphy:
Thanks, Dave. Thanks for having me. Thrilled to be here today.

Steve Lieber:
You know, I've been really thrilled as well and really looking forward to getting your perspective on a number of issues. But where I'd like to start out first is two areas that, identified during your intro, the AI lab and the Intelligent Automation Hub. Tell us a little bit about how those came about, what sort of objectives they have, and maybe a couple of examples of what you're focused on.

Karen Murphy:
Sure, Steve. So the Steel Institute was started five years ago this past July, so we got our five-year birthday, and the goal of the Steel Institute was really to produce transformation innovation that had quantifiable outcomes and solved problems. That's a tall order, to be able, I always say this job is the hardest job I ever had in my career, and I had some tough ones, but the reason this job was difficult is because the healthcare delivery system is very complex, and it's easy to create a bunch of shiny new nickels that you say is innovation, but to move the needle on quality or cost in a meaningful way is really different. So I start out by saying that is, as we built this innovation center, we were always going to solve problems. We were always going to do it in a fundamentally different way, and we were always going to have quantifiable outcome. So about five years ago, AI really started to healthcare, and some companies were coming in offering us to work with them. And I say we started with six of us in a row to evaluate companies, understand what they were offering. We started out with a couple of pilot programs. One turned out to be one that is still active today, and that was ..., a startup Israeli company who worked with us to develop an algal marker that identified patients who are at higher risk for colon cancer. So very successful, we've saved lives through that, but that started our evolution into AI. We started an AI lab within Geisinger. We have our own team that does two things, assesses AI opportunity and then also develops AI applications. We're doing one of our own risk profile. So risk stratification what patients are going to be admitted to the hospital or frequent ED visits, that's one example. We have another program going on for lung nodules to be sure that we're picking up the ... and have follow-through. So we really are all in. Flash forward to last, this week we had our AI committee, and there were 61 people at the meeting, 61 people on the committee, where we have some really high-level discussions about AI, where it could be helpful, where are the gaps, and then, of course, now with Gen AI, if you don't say ChatGPT five times a day, you're really not innovative. So we've developed the way to test in a safe way, generative AI within the organization, put together a governance structure, and I think we'll be talking about generative AI, really increasing the conversation in the very short term.

Steve Lieber:
Yeah, your examples are really striking in that you're very focused on clinical issues in terms of your examples anyway. And I'm going to contrast that with something that came out of ... in August, where Judy announced that their focus is on, let me look at my notes here, in baskets, clinical notes explaining medical bills, notes, summaries, coding, billing, more back office sort of things. Can you give us some insights in terms of where you're going, where they're going, where AI is going?

Karen Murphy:
And I would say to you, we're going in the very same direction, because many of those things that you mentioned, they are going to be our early AI projects. I think Gen AI is more appropriate for those types of, and I think those types of use cases, and I think it's going to save us tremendously over time. I mean, let's not get hyped up here, like it's going to take us time to develop, but if the only thing you could do is stand still, and that's not acceptable. So it's tough. I don't say that as a plug-and-play solution, that we're going to be able to answer all of our problems. That's just not the case. But is it another tool, the toolbox, to help us increase the quality of life for providers as well as help us be more efficient?

Steve Lieber:
Yeah, you mentioned just a moment ago standing still is not an option, obviously. So how are you feeling about the pace of change and the pace of innovation, pilots and full scale and scaling up and that sort of thing? How do you feel about that? How do you feel where you folks are situated as it relates to getting in there, identifying the problems, and driving solutions on a scale?

Karen Murphy:
Well, Steve, you can probably imagine I never move fast enough. I mean, that, that's somebody once told me, I was speaking frustratedly about, we're just not moving fast enough. And my friend ... said, if the world moved as fast as you want it to, I can't imagine what an awful place it would be. So I guess that tells you that I like to move fast. I think we're going into, I think we're going into a phase of innovation that everybody realizes that a million pilots are not the way to go. That you can be taking, you can be a mile long and an inch deep, and never really get anything that's meaningful. So, what we have done is we have begun to not only look at the pilot phase, but we design the implementation at the same time as the pilot. So when we're designing the pilot, we're saying, okay, understanding we have to iterate, but here's where we're going to spread it, and here's how we can spread it. And I think we're going to see healthcare, because of all the pressures on healthcare, not only financial workforce, aging population, there are a lot of pressures for us to get it right. So I think you're going to see faster moving industry, and I also think these tools that we're talking about in our toolbox, you brought up intelligent automation, how we started intelligent automation probably about eight months before the pandemic. And what we do is build bots to really do low-level tasks so that we can actually maximize the, maximize our human intelligence wherever possible. So it started out, and we thought that this is a, perfect to your point, back office kind of functions that would really be helpful. I can't even describe how excited everyone has been because, of course, during the pandemic, when we were getting 36,000 calls a day, we didn't have people to answer 36,000 calls. So we built a bot to do that. Testing results of the height of the pandemic, we were reporting 500, 600 results a day. We build about ..., so it saved us millions and millions of dollars. And it wasn't like it saved us millions and millions of dollars, or we would have hired the people. There were no people to hire. It was, we had to do it. So now, post-pandemic, we've set into a strategic plan where we're really trying to give workers relief, our workers relief in every area that we can. So let's take, you can't find four people to work and do the job. Let's identify the tasks that could be automated of those workers that you can't find. Number two, where is the automation then that can raise revenue? So can we do claims review more effectively so we can identify missing pieces that missing information that would ordinarily be then kicked back to the revenue cycle department to be completed? Can we have a bot that's actually going to proofread that claim before it goes? So it goes on and on and on, but it is a technology that is really, it saves time, saves money, and also provides greater efficiency, and sometimes even more quality of work than what a human does.

Steve Lieber:
You mentioned the challenge, both during the pandemic, and I think it continues today in terms of staffing and in really on a couple of levels. Availability is one, but also burnout and just fatigue, and exhaustion. At times, we hear people raise concerns about is, are AI tools going to replace people. And as you sort of indicated, well, the first response is there are so many vacancies, we're not replacing people with this, we're filling gaps. What's the tone of the workforce as these tools are coming in? What are you hearing, sensing, in terms of, particularly clinicians on that side of the House, reaction to the tools?

Karen Murphy:
I think what realistically, and Steve, I'm a registered nurse, I started out my career as an ICU nurse for a decade, so it really laid a foundation for me that allows me to understand what clinical, what everyone, I worked, I always say, in every department, except the Lord, in a hospital, so I can relate to the issues of short standings, short staffing stress, and burnout. If we're going to bring AI tools to the clinical environment for the providers, we have to make sure they make their life easier, not harder. So that's my, you know, if you're going to go in there and you're going to say, hey, this is a great thing, shiny new nickel, but it's going to add another ten minutes onto your day, that's just not. And I think we have to keep, we have to be realistic, and we have to bring the clinicians in, the nurses, the doctors, ... techs. Whoever you're working with has to be a part of the design process, because if you build the design process in a box and you don't consider or really have a good understanding of what the workflow is going to be, it doesn't, it just doesn't work. I'll give you a good example of that, and we talk about AI. Well, a data scientist can build an algorithm that pretty much can produce all the data you want, depending on what the question is. And early on, and this was a great lesson, early on, we developed an algorithm that looked at prediabetes. It looked at the signals for prediabetes. And then, obviously, we looked at pre-diabetic care gaps. And when we went to put it in, great information, first of all, it was 30,000 in the population. Second of all, when we went to put it in the workforce to say, hey, here's your 30,000 patients, every doctor, maybe 1000, here's your thousands of patients that are pre-diabetic and have six care gaps. And the clinicians look just, ... wireless, what do we do with that? Like, well, do you get on the phone and call all 60, do you, or a thousand? My point here is we did not think it through to say, how is this going to go in the clinical work? So we had it since refined. We want to make sure that the information produced by the AI in the clinical area is clinically relevant. And number two, that we can actually get that, we can share that information in a meaningful way and integrate the information in the clinical workflow, and it doesn't put more pressure on the physician, or nurse, or support staff.

Steve Lieber:
Sticking with the nursing area for just a moment, given your background as well as your current roles, certainly, the pandemic drove us into a higher level and quantity of virtual care had to. So what are you seeing today, and what has been the trend? I'm going to make the assumption, maybe there was some drop off in the amount of virtual care from the peak of the pandemic, but it probably is going to plateau and then probably move back up again. A little outlook in terms of your thinking around virtual nursing.

Karen Murphy:
I think virtual nursing will only accelerate, and for two reasons. We talked about the one, Steve, about the shortage of nurses, but it is also protecting the quality of life of those that are at the bedside. And those nurses, if you're working short-staffed, have so much to do that if, and I will say this, inpatient nursing is an early career game. You're not going to find, so the dynamics are changing, and that, it's a lot of work, very hard work seven days a week, 24 hours a day. I think we have to understand it's a very demanding profession, and heretofore, I don't think anybody appreciated that. I think that, other than nursing, I think the second piece is that we're not going to be able to recruit adequate numbers to be at the bedside, but we can recruit nurses who want to be virtually and just do certain tasks that are non-physical that are, you know, that aren't difficult. I'm a nurse. I can do a discharge with the patient right here, and I can use my skills as a nurse, but I don't have to have the physical burden of being at the hospital, at the bedside. And if that's two, I think three, we were at a conference yesterday and they talked about the, I heard about the health system in the Midwest that is taking the nurses off the floor and giving them breaks to be able to go do their virtual nursing. So I think virtual sitting, virtual nursing checks, or changing the care model. I think virtual nursing is only going to go, it's only going to accelerate.

Steve Lieber:
And would it be fair to say that utilizing virtual tools, remote monitoring, and that sort of thing, can take away also some sort of below the highest level of your licensure task so that you do operate at the peak of your licensure?

Karen Murphy:
Yeah, I definitely think about a patient, I mean, if you think of the, patients in the hospital today are really, really sick because we've shifted so much to the outpatient. So patients are sick, they're complicated to take care of, they're time-consuming to do a good job. So yes, I think it allows, and when you're a nurse in the ICU, you're not going to, I mean, you have to be there next to the bed, really holding that patient in your hand, and you're never going to replace that. So what we have to do is take the tasks away from everyone that can be done by, to your point, someone a lower license level or at the same license that doesn't desire to work in the field but will be willing to do other functions. So I'm very excited about the future of virtual nursing and all that will, all the benefits that will come.

Steve Lieber:
Right. In your background, as we mentioned in the introduction, Pennsylvania Secretary of Health, and I think there was a focus that you had, and it probably exists given Geisinger's location in a largely rural area. In terms of helping rural healthcare, in terms of supporting it, and ensuring it's there for patients, what do you see as what we can do for rural healthcare settings?

Karen Murphy:
So thanks for bringing that up, Steve; it is a passion of mine. I spent a great deal of time studying rural health and actually developing, when I was the Secretary of Health, developing a payment model, payment and delivery model, working the federal government with Sam and Mike, because I realized they were so challenged. So as we talk about this technology, these are tools that will help. Rural hospitals are understaffed, and both clinicians and physicians, they are, sometimes it takes them 2.5 hours to get to a place where they can receive care that we can get down the street. They're underfunded, so they cannot reinvest in these digital technologies that we're talking about that could be beneficial for them. How I see AI and really all the tools that we talked about today, virtual care for rural communities, I see there has to be investment on the federal side and the state side to really be able to deliver the tools that we have in urban areas for rural communities. And I think that all of these tools could be beneficial, but we have to find a way to connect them and have the rural communities truly understand what the value is and how we can get the value to them.

Steve Lieber:
Excellent. So to wrap up here as a final note and comment to our listeners, we have folks like you and as well as CNIOs, CMIOs, CIOs that will be listening. What's a practical piece of advice? What's the big takeaway you'd like to share with the audience?

Karen Murphy:
So I think that we didn't realize that the world, and including healthcare, the world was going to experience post-pandemic problem. We thought getting rid of the virus was going to take care of everything. I think it's clear now that we are going to go through a period of challenges that were developed during the pandemic or exacerbated during the pandemic, and are now even more exacerbated. I think what's really important now, Steve, is to build the resilience that you have in yourself. And it's not about, you know, it's not just organizational resilience, it's really, we've got to get out of that mindset. We can slow down a little bit. There's, you can't put every fire out all the time, but try to get back. You are resilient. You, everyone will be lifted. But I think we just have to be a little more patient, and I think we have to be thinking positively of the future, and we will get through this. And I've never been in healthcare for the decades that I've been in healthcare, that it was easy, so I'm not going to say it's going to be easy, but I think we got to turn the temperature down a little bit.

Steve Lieber:
I think that's a great Karen in terms of, yeah, we get all focused, especially those of us in the technology space, in technology and innovation. Let's not forget the people. That's what I'm hearing. Karen, thank you very much. This has been a wonderful conversation. I really appreciate your time today.

Karen Murphy:
Oh, it's my pleasure, Steve. Thanks so much for having me.

Steve Lieber:
You bet. And to our listeners, thank you for joining us. I hope this series helps you make healthcare smarter and move at the speed of tech. Be well.

Intro/Outro:
Thanks for listening to Smart from the Start. For best practices in AI and ambient intelligence, and ways your organization can help lead the era of smart hospitals, visit us at SmartHospital.ai, and for information on the leading Smart Care Facility platform, visit Care.ai.

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