The AI conversation inside health systems has moved from governance and validation to return on investment. The problem is that the ROI case usually gets built on top of work that was never finished. Local validation, ongoing monitoring, and performance across the populations a system actually serves are still underfunded in most organizations, and the bill comes due quietly.
Midori Kondo has worked both sides of this, from clinical pharmacy to enterprise applications leadership, and she is second author on published work in the Journal of Medical Internet Research laying out what each AI pathway actually costs and who gets priced out of the safer ones. In this conversation she makes the case that access and validation are not the soft side of the AI agenda. They are the part of the financial model most systems skipped.
We also get into the newer problem. Patients are adopting consumer AI faster than health systems are deploying enterprise AI, and no CIO approved it.
If you are defending an AI budget, sitting on a governance committee, or trying to explain to a CFO why the cheapest pathway is not the cheapest, this one is for you.
Midori Kondo, Pharm.D., MHA, Vice President of Applications, UCSF Health
Megan Antonelli, CEO, HealthIMPACT Live
00:00:00 Intro: Welcome to Digital Health talks. Each week we meet with healthcare leaders making an immeasurable difference in equity, access and quality. Hear about what tech is worth investing in and what isn't as we focus on the innovations that deliver. Join Megan Antonelli, Ginny Sharp, and Shahid Shah for a weekly no BS deep dive on what's really making an impact in healthcare.
00:00:30 Megan Antonelli: Build it, fine tune it, or buy it and go live by Friday. Those are not three versions of the same product. They are three different bets on how much control you need, how much transparency you can live without, and what you will owe later in validation. Nobody put in the business case. Kondo is the vice president of applications and chief application officer at UCSF health. She came up through clinical pharmacy before she came through it. And she has co-authored and published work on the economics of this exact choice. This is Megan Antonelli, CEO of Health Impact Live. And this is digital health talks. Hi, Midori. How are you today?
00:01:10 Midori Kondo: Good. How are you?
00:01:12 Megan Antonelli: I'm good. Is it, uh. Are you in San Francisco? Are you at the office today or are you traveling?
00:01:18 Midori Kondo: I am, thank you. Megan. I'm in wonderful San Francisco, and we're having, like, crazy warm weather, so it's been beautiful out, so.
00:01:28 Megan Antonelli: Good. Well, it's nice that, you know, fall is finally upon us, but it has been has been so hot. But let's start. We like to ask the first question, which is not your resume, not where you've been, but what the best room you've ever been in. Sometimes, you know, might be a wine room in Tuscany. Might be, you know, I think recently we've had someone say, you know, it was a studio at universal. What what's your best room?
00:01:56 Midori Kondo: Oh, gosh. Megan. My, my, I think my best room has four tires on it. Um, I know it's, it it may sound like a, maybe a, a mobile home or something, but no, it's a Ferrari. Actually, it's a, it's a Ferrari on the track. And, um, and there's, you know, I've got the bug. Um, I've only done it twice in my life, but I highly recommend it. It's a, it's just, you know, it's strategic. It's, it's fast. It's exciting. Um, and it's on the race track.
00:02:29 Megan Antonelli: Well that's amazing. We always, always make the analogy of changing the tires while the car is moving for folks in it and informatics. So I guess that's where you ended up, how you ended up here. But do tell our audience a little bit about your background and, and kind of how you ended up in the role that you're at at UCSF now.
00:02:47 Midori Kondo: Great. Thank you. Um, so I am actually a pharmacist by training and, um, and so I got my PharmD from Creighton University and did a residency and fellowship at University of Washington, as well as a Masters of Health Administration. I really love clinical practice and, you know, throughout my career, um, had various administrative responsibilities and in acute care, um, as well as for ltachs and building out clinical programs for, for really sick patients that were always sort of told they were nursing home patients, but they're on dialysis and they really need some really good clinical programs to get them back on their feet and through that journey. Um, I had an opportunity to do some corporate clinical programs for kindred healthcare. And they put me on their technology team that was looking at EMRs. And, and so this was sort of, I'm not going to, you know, gray hair sort of back in the day. Um, and so we were all looking at EMRs and kindred actually was on from nineteen seventies was on an EMR called Pro Touch. And they're like, look, we're at end of life, if you can imagine, for an EMR. Um, in that time period. And we need to select a new one. So this was before ONC sort of said we had to do this. And so I got the technology bug. And I really, really like to sort of understand the workflows and the requirements and like to say that was an early informaticist before, um, there was a term and so really just got involved, um, with that, with doing technical technology evaluations, eventually joined Healthlink, which purchased IBM, worked for IBM, then, um, really traveled around, did a lot of system selections, ended up at Cedars-Sinai as one of my customers. Um, worked with Darren Dorkin there, um, as his executive director for epic as well as his, his, um, director for technology. Loved that. Um, got the bug for doing emerging technology. Um, I had sort of the, the special projects. That's what we called them back then before the accelerator. And, um, really just got into machine learning and sort of the AI stuff back then at Cedars moved into, um, eventually a role, um, with, with building software, um, sold software applications, started to do a lot of product design for emerging tech, moved back into operations, brought up the community cancer Institute in Fresno, California, and really started to, to get back into operations and how we bring technology into the space for cancer care. Went to Seattle Cancer Care Alliance as their chief application officer and then now at UCSF.
00:05:34 Megan Antonelli: Amazing. So I didn't know you were at Cedars, uh, with Darren. That's great. You know, and I think over that time and you mentioned in terms of the, the work that you've done, I think what strikes me about your career, both obviously starting as a clinician, but you've also done research and coauthored papers and stay very active in speaking and educating in the community. Um, and I know you wrote a paper twenty twenty four ish. So like pretty soon after chat and all that became kind of, you know, just mainstream coming online. Um, that was really about, you know, the pathways that health systems can take with those, you know, and now here we are a couple years later, there's been a lot of talk about it and a lot of, you know, use and, and where things have gone, how are you seeing in terms of, you know, the choices that organizations are making with respect to using and adopting AI? And I think one of your passions around kind of serving vulnerable populations and, you know, ensuring equity. What are you seeing across the landscape in terms of what's driving those decisions?
00:06:43 Midori Kondo: Well, um, I think a lot of the sort of general economic decisions that are happening around what we pick and choose to. It's sort of morphed, um, sort of over time. And I think that, uh, it's one of those things where, you know, we've, we've really focused our efforts around, uh, how we collect data, how we are actually serving the populations. Uh, we don't often sort of use the data that we need to, but we certainly have had a lot of work in collecting it. And, and now with AI, we have an opportunity to really, um, sort of transform that data and have that at your fingertips as you're actually treating the patient making decisions. And I do see that, you know, what seemed like a conceptual, you know, can I, can I capture this attribute to really sort of identify these populations to I can do this now at scale, as long as we're collecting the information. Um, this is where I can, I start to see sort of the technology coming forward to provide the value that we can actually provide. And I do think that, um, that's when a passion of mine is to really have equitable care. And I do think that with the advancements in technology and, and what we can actually do with it, um, responsibly, that we can actually have a better chance of, of covering what patients needs are and at the time that you need it. Um, sometimes we surface that stuff later. So I'm, I've been very passionate in this space and in that value proposition of how we can use our tools for good. And, um, and, and really, although some of the economics and some of the pieces that, um, Radha, my partner in crime, he actually, I should give him a lot of credit, um, really had the vision around sort of educating people around what this actually really means. Um, you know, we've been on this journey and talked about sort of these different use cases as you know, what, what is that sort of, um, sort of cost to benefit analysis that you need to actually have. And I think that, um, I think that's probably the driving reason why, you know, we really wanted to write the paper and then obviously how we transform that and utilize that information in health care systems.
00:09:02 Megan Antonelli: Yeah. I mean, it's been such an amazing couple of years to kind of watch the adoption and the assessment and, you know, and yes, the hesitancy. But I think the, the promise of being able to do things that we couldn't do before. I mean, I just remember, you know, when we would talk about social determinants of health and how important it was to have the data so that physicians and clinicians could make decisions. And now, and the barriers to that was the time of collecting it, the time of cleaning it, the time of reviewing it. And now I feel like when I look at these tools, that's going to be easier, right? That being said, it still costs money. I mean, in your in the paper, you talked about sort of the the constraint around infrastructure. And you know where that some of the tech has gotten so fast, but there's still a lot of cost to it. Let's talk about that a little bit in terms of what you're seeing and, and how people are assessing, you know, the costs of, of these tools as they're adopting them.
00:10:04 Midori Kondo: Yeah, it's a, it's a great question. And, and, you know, the, the value proposition, we've been sort of toying, toying with for quite some time. And in fact, um, you know, the cost of these tools and, and that ROI analysis, um, really is driven by what value we're seeing. And so I, I gave this talk one time and I, and I called it, um, you know, ROI e I e I o because there's just so many pieces and parts to this. And, and so, um, the cost is real. Um, you know, it's, there's, we haven't talked about really opportunity cost, but there's a ton of opportunity costs, not just sort of real costs in this. And then there's a value that doesn't have necessarily a dollar figure attached to it. And so we're in sort of this really nebulous world for, for part of it. Um, the responsible sort of use of AI is, is really where I can sort of highlight and, and really say that this, that term is used a lot. But, you know, that sort of has to cover a little bit around not just sort of workforce, but it has to cover sort of this, this cost factor that we, we don't talk about. And so, um, I'm going to even just sort of set that aside a little bit, um, because, you know, we know that there's water, there's, you know, energy, there's other things right around sort of consumption. Um, but then sort of getting down to some of the real costs that we can measure, there's a lot that has to do with like, you know, we talk about tokens, we talk about cloud compute, we talk about all of the stuff that it takes. Even the models that we're utilizing in the AI solutions consume different amounts of, um, of tokens and, and, and so the costs can go up really, really high. If you're not really thinking about do I need AI? And we haven't even talked about that, that there are certain cases that we really don't. We talked about just a, you know, a few minutes ago around where we can utilize in service. If you think about the mapping and the, all the stuff we used to do and all the time that we spent when all of it's in a note and you can really extract out that information. Like that's really, really valuable. Like there's a trade off right around sort of human sort of time versus sort of the cost that you're paying for. And I'm going to say the whole word artificial intelligence because, you know, I like to say that every once in a while for people to really understand what it means. Because when you say AI, it's sort of like, you know, can you turn the channel on the remote? Like it's, it's becoming sort of, um, used so often that it actually doesn't mean anything. But like when we get into some of these conversations, I like to say the whole word. Um, because it reminds us around when do we need that versus when is a suitable report fine? Or when is there something actually in your workflow that's surfaced? Fine. When do we actually use it? When can we and should we use it? And I think that that's directly related to some of the costs that we're doing. Um, yeah. The other piece is that everybody's really excited. We're on this wave. Like there's so much AI around us. See, I said it. Um, but really the cost to connect and people don't see that. So like, we know there's licensing, we know there's utilization costs, but there's also the cost to connect. There's all these things in the platform around connectivity. And so we're paying for APIs. We're paying, you know, um, inter-system bills for like that connectivity and sort of whether you're connecting in or pulling data out. There's, you know, for how many different APIs that you actually have in epic, there's, there's this cost to connect and there's different sort of cloud compute that you need. Those basic infrastructure pieces are not often in the price tag in the ROI. We're looking specifically purely at licensing, but we're not looking at that total cost of ownership. And then there's the opportunity cost because we like to do pilots right now. So not only are we doing a lot of connectivity on something that we don't know, we're going to scale, we're actually taking human capital and we're applying it to these projects and not doing other things. And so there is an opportunity cost around other projects too. So all of these different facets are some things that we're starting to look at at UCSF to see how responsible we can be around all of these different pieces.
00:14:33 Megan Antonelli: Yeah. It is. I mean, it's definitely a situation where you're kind of peeling the onion and every layer has additional cost to it, right? And, you know, I don't know if that's so different from any other new technology, but it feels that way. And part of that is because I think because adoption is, is sort of faster because people like it. You're seeing them. Those costs escalate rather quickly. And I think your point around, you know, are we using it when we need it is really important. And I think some of the discussion I've also heard, because there's this, you know, when we get to kind of the, the trust versus the value conversation, the trust conversation of particularly with clinicians where there's this, you know, is it being, am I using this? And then it's training to replace me or so that I can do more. Right. So that I can, you know, just fit more work into the day. And I hear, you know, often, you know, that's not the point. It's the point is to, you know, kind of reduce burnout, reduce the burden, you know. But the reality is it will be people, you know. People will be expected to do more. But what do you do with that time saved? And to your point, that there is even the opportunity cost of implementing these systems, redesigning the workflows for these systems, that's currently taking time as we ramp up. So you've got this. I mean, you know, sort of on both sides, a balancing act that you're trying to do. Um, and then the value part of that is what is the value of the output, right. Um, and I think to some degree is that, is that people hours. Is it live saved? You know, where do we have that?
00:16:17 Break: You're listening to digital health talks. When we return, we'll continue our discussion on how technology is revolutionizing healthcare delivery. Stay with us to hear more insights on creating sustainable, patient centered digital health solutions.
00:16:36 Megan Antonelli: Where are you seeing the value in in the systems that you're implementing? What are you looking at as the, as the real thing that's kind of moving the needle needle on value.
00:16:48 Midori Kondo: Sure. Um, it's a great question. Um, I think I'll probably say the first thing that everybody says to you and that's ambient. Um, right. So, you know, you're alluding to and some of your examples, um, and smartly so that, you know, we have seen, um, satisfaction, we've seen people being like, whoa, hey, look, I can actually go home on time. Um, we're starting to actually look to see if we can provide value in pre charting. Um, you know, because that's, you know, we, we, we don't think we've maximized in saving time for clinicians. And we think that we can, we can really sort of move that needle a little bit more. And now we're starting to look at sort of the nursing workflows and sort of the other clinicians. And, um, there's a small pilot that's going on right now. Um, because we're, you know, we're UCSF, we like to test out things. So we've got a couple of different things happening right now around the nursing documentation. And we're doing evaluation with, um, with epic around chart with art for nursing. Um, we think that the value is going to be there, but we're still, there's still some bumpiness in the road for, for clinicians or for non-physician clinicians. Um, part of this is obviously content. Part of this is that we got to teach them how to, um, sort of talk out loud to get sort of the voice to text. Um, but we also haven't figured out exactly what digital solution is actually the best solution for them. And what I mean by that is like, they're still devices, like what device do they use? Like, you know, where should they actually be getting the value around? Um, is, is it right there? Do they say everything head to toe to the patient. Do they? You know, what should they actually be engaged with around sort of talking into this voice to text versus sort of engaging with the patient? And so we're all sort of trying to figure that out a little bit right now.
00:18:47 Megan Antonelli: I know I imagine a day where, you know, we've always been, you know, saying, oh, well, I wish my doctor, I wish my doctor would turn around and talk to me. And now we're going to be like, you know, he just would not stop talking everything, you know, he said absolutely everything out loud, you know.
00:19:02 Midori Kondo: And right. And they're like, wait, he said something about my elbow. What's wrong with my elbow? You know? So, you know, it's.
00:19:09 Megan Antonelli: It is interesting. And I mean, I've heard even I mean, in talking about the nurse implementations, it changes the practice of, of their care and it changes how they care. And now in the case of nurses, I've heard it's been very positive. I mean, generally the out, you know, the feeling of I now understand more because they said more, you know, but it is it's an absolute change of, of the practice of care, you know?
00:19:34 Midori Kondo: Absolutely. And I'm excited for them because a lot of times, you know, our our poor nurse nurses, they don't get technologies rolled out for them. You know, they're like, I've got to wait or wait a second. I've got a, I've got a type like, but everybody else has something else. But what about me? And so I, it's exciting to see nurses very excited. Um, you know, they're moving up the priority list and I'm happy for them. Um, of course we're seeing the same sort of benefits around, um, you know, you know, we're working on prior authorizations, you know, we've got a lot around technology that we've got planned coming in. We've, we've implemented something like twenty AI models that are inside epic. Um, are we seeing some value? Yes, we're seeing some, um, um, you hit upon something that I do want to cover. We have adoption problems. And I think that, um, part of this I, I think is just really the education for people. Um, part of this is like your rollout strategy and like, how fast do you go? Um, you know, I think that every organization is trying to figure out their adoption right now and like with which tools, um, we're trying to be very deliberate. We have our, our interim, um, chief AI officer. Um, she's, she's been great to work with and partner with. She's really sort of, she's a physician. Um, and she's, you know, they're looking at sort of, okay, we've got all these tools. What does that mean for the full workflow? So, you know, we're trying not to also break people's workflows. So we're being a little more careful around our rollout strategy. But, um, I was on a call today and one of my, one of my directors said, Midori, I have to say the p word. Is it okay? And I was like, oh, if you have to say it. So he said pilot, because it's not my favorite word. I like phases and phase gates, and we've got criteria so far as we can move forward. Um, but like we, you know, the reality is, is that we've got so much new technology that we are still doing some pilots and we're trying to like figure out what we can scale so that we can actually phase gate them versus sort of going into a pilot mode. But, but again, there's so many tools out there you don't want to break workflows.
00:21:51 Megan Antonelli: No. And I've also been hearing, you know, and you've got new tech kind of being introduced by various places in the organization. How are you managing that? I mean, is there is that sort of where the governance comes in? You know, are you discovering I mean, I'm reading, you know, sort of again, I feel like for a while I didn't hear as much about shadow it, but now it's a lot in, in the, um, you know, discussion and discourse. Are you seeing your clinicians kind of using stuff that's not authorized and kind of introducing that into the system?
00:22:23 Midori Kondo: I'm smiling, Megan, because like, you know, governance, it's, it's very interesting. Um, It's one of the topics that we talk about a lot that nobody's sort of like, oh my God, like we've had so many governance conversations, but, um, yes, um, we are, so we're, we're, we're looking at this, um, sort of where do we, where can we manage the, at the lowest common denominator so we can move fast? So as an example, you know, just like everybody else, we're looking at risk, different risk evaluation. Is this contained within an application. Is this an epic epic model or is this something that's a third party model? Is this our own self development? Because we also have a lot of self development. We've been using AI for quite a long time. So we've always had sort of that pressure around sort of shadow it or people researchers, you know, we've got our, what's different about us is that our, our school is professional school. So it's pharmacist dentistry, nursing physicians, and we have a lot of informaticists that are not just sort of under the IT umbrella, but like there are people that are like, they're board certified as physicians and they've, you know, they dabble in informatics because they love, they like to build these AI models and like and solve problems. Um, we want to actually have that innovation and like that spirit here. Like that's, that's what's lovely about being at UCSF. But we also have to think about being very practical in what we actually put in our environment so that we are being responsible about like, how many agents do we have in there? And really sort of considering agent registries and, and really thinking about, um, what do we need to sort of be okay with a proof of concept in a place outside of the system, but when is it ready in that phase gate to actually integrate and have this sort of something that we evaluate for wide scale rollout, all of these different pieces, um, is going into sort of this new model that we're building actually now. And that's how do we sort of measure these different things. Um, but I think our general principle is that we want to manage at the lowest common denominator. We want to do all the right things, but we want to make sure that we also are nimble enough to innovate.
00:24:42 Megan Antonelli: Yeah, yeah. I mean, I think it's like this fine balance between innovation, you know, death by pilot and actual implementation of valuable tools that, you know, provide value to the patient and the physicians and nurses and the organization. Right. I mean, and it's sort of going back to the checklists of, you know, figuring out what, what really does provide value. And all the while, you know, the patients aren't waiting for us. They're using consumer AI, they're, you know, looking at their labs and, and visit summaries and hopefully able to use it for insurance processes and all of that. I mean, is that in terms of the larger reality of, of kind of how the patients are changing. Are you seeing that? And is that also impacting your decisions on what to kind of move forward with and how to change the delivery?
00:25:35 Midori Kondo: Um, it's this just came up the other day. Um, we have like, we have some pretty savvy patients these days. And, um, and so patients coming in, like they practically come in with their own care plan. Um, and so I, you know, I, I actually feel for our providers because that's a, that's a whole new reality. Um, and so we, you know, we're just talking about how we need to start to engage a lot more of our patient and family advisory councils and start to be a little bit more sort of directive on how we do that. Um, I think most organizations are starting to look at that. Um, how do we have sort of patient humans in the loop? Um, and really sort of engage them sort of differently around how we actually think about our technology. Um, I'm not sure we have a full solution. And if somebody does, like, let's talk. Um, but we are starting to talk about the internet of things. So like, you know, I've got a, my aura ring on like, what do we do with, with patients with their, with their own patient provided data? Um, like how much do we take in? Do we allow for that? You know, patients can, can show physicians. Um, my, with my mom and her cardiologist, I actually create a, do a little EKG, um, and sort of send that to the doctor periodically and say, we'll talk about it next appointment. So like, I'm even that patient, am I? And as a caregiver for my mom. So, um, like I'm excited about where we're going next. I think that, um, we're trying to get ahead of what's actually available within our own ecosystem. We're realizing that we're probably a little behind in sort of thinking about how we bring in sort of the patient data, but that's on the horizon and it's on our radar.
00:27:23 Megan Antonelli: Yeah. No, and it is interesting as we think about it. I mean, we have a bunch of conversations last week around that and kind of designing the experience for that. And again, it goes back to, you know, before there was just no way that we could process the data to help, you know, to, to add that to the medical record. And now it's there. But to your point, before there's a cost associated with that, you know, and it will cost money to assess their data. You know, certainly some who have eighteen different devices like myself write data there. It's more than I can process before I get out of bed in the morning. So, you know. Totally. So, you know, between the rings and the scales and everything else that we have this connected world. But, you know, if it can't connect to the medical record, um, where do we go with that? But, um, you know, the, and what is, you know, kind of the, the level to which everyone is, is accessed. And we've talked about this in terms of, you know, rural communities and what's happening. You know, what what people are able to access and what is the level of care. You know, that's just kind of a that we're able to give people now more cheaply or less expensively, uh, as a baseline, you know, and I think there's a lot of opportunity in that.
00:28:39 Midori Kondo: Yeah. And I mean, we're thinking about along those lines as well. You know, we're a huge referral center. And so, you know, um, you know, I, I feel very fortunate and lucky to be part of the UCSF culture because we, we don't want to leave a patient behind. So we're like, we're starting to think about how we partner differently with Fqs and like, what's our catchment area and the patients that are referred to us and how can we really impact that experience? So that's nice to be with an organization that, despite some of the challenges that we know is coming economically, we're still have that as part of a mission and vision for our organization. And so that's I feel lucky that way.
00:29:19 Megan Antonelli: Yeah. That's great. Well, we'll close with. We also on on our show have a segment called Five Good Things. And so it was actually born out of the pandemic where we went to Hims and we were like, we had to talk about good things. What were the good things that came out of this? Give us the silver lining. Sometimes we in healthcare can kind of point out the challenges and what's hard. Um, but in terms of when you look at the technology landscape and how it's impacting care delivery right now, what, what are you most excited about? What do you think is the, you know, the brightest star in terms of, um, you know, where technology and care delivery are, are improving?
00:29:58 Midori Kondo: Um, so wow. Five good things.
00:30:00 Megan Antonelli: Um, well, you can just give me one. We then put it all to five, but if you have five we'll take them.
00:30:06 Midori Kondo: I will see how I do. Um I feel like it might be jeopardy so we'll see. Um I will tell you that the one thing that I feel um, really, really grateful for being in technology as long as I have is that we're finally getting to see the value of, of digital, like digitizing things and, um, and really having more information at our fingertips that we can use. And so I'm very excited and I'm going to say the artificial intelligence around the promise of it. You had mentioned that and I think the promise of it, but also what we're starting to see being delivered. And so getting into sort of now that digital, this digital age where things are at your fingertips, you can see the information where you don't actually have, um, clinicians sort of banging on keyboards and people are closer and interacting with the patients. I love that dream. That's the dream that I signed up for years ago that we're now finally being able, we have the compute, we do have the intelligence to be able to do this and make it real so that we can, you know, basically be very mobile and portable and do all the things we need to do for patient care. That to me is incredibly exciting and it really keeps me going. With all the, you know, all the challenges in healthcare today. This is what I signed up for, is to deliver that promise. And so I'm very excited about that.
00:31:33 Megan Antonelli: Yeah, absolutely. I mean, I think that that's for all the work and all the incredible challenges of kind of the implementation of EHRs and getting them. And you were clearly right there at the forefront of it. And to think that now, because the compute power, because things have caught up, that we're going to see that economic promise that that actually delivers on equity and access, which is, you know, without compromising quality. Right? All the, the triple quadruple aims of, of all of it to kind of get there. Well, it's so good to talk to you. Um, I love the work that you're doing and I always love your perspective on it in terms of, for our audience, how they can follow your work, keep the conversation going. What's the best way? Um. LinkedIn or.
00:32:19 Midori Kondo: Yeah. Connect with me on LinkedIn. Um, would love to hear your thoughts. And, um, if you want to sort of chat sometime around these topics, you know, I was going to rattle off a few more things for you just because I was trying to like be, you know, me and my competitor.
00:32:34 Megan Antonelli: You're an overachiever. I know.
00:32:36 Midori Kondo: So it's like the democratizing of knowledge, giving time back to humans. Maybe proactive care have the opportunity for proactive care. And then I already talked about mobile and then also sort of getting out of like banging on a keyboard. So. How about that? I, I, you.
00:32:55 Megan Antonelli: Knocked it out of the park. Give give you a Ferrari.
00:33:00 Midori Kondo: Yes. I want a Ferrari. That would be great.
00:33:03 Megan Antonelli: Oh, maybe someday. Maybe someday. Um, but yeah, no, I mean, and that that actually almost covers. I mean, it is, it's kind of the access, the quality, the safety and, you know, and ultimately, the experience for both the clinicians and the patients coming together and having technology be the enabler, not the, you know, the bottleneck or the problem, right?
00:33:24 Midori Kondo: I mean, how long have you heard that? Like we're like the age of cpoe? Like it was like, oh, we're ruining their lives. It's like, oh my God, can we please give back to these people now? So yes.
00:33:36 Megan Antonelli: So I do, I do think we're here. I agree with you one hundred percent. And it's exciting to see and thank you for all your work and of course, for your time today. It's a pleasure. And if this conversation got you thinking, that is the whole point, share it with someone who needs to hear it. Subscribe to Digital Health Talks. Follow us on YouTube at Health Impact Live. This is Megan Antonelli of Health Impact Live, and this is digital health talks. Let's keep fixing health care one conversation at a time.
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