>> Welcome to this IBM Watson Health Client Conversation. Here, we are probing the dynamics of the relationship between IBM and its key clients. We're looking back and we're also exploring the present situation. And we're going to talk about the future state of healthcare as well. My name is Dave Vellante from theCUBE and with me are Ryad Rondo who's the Associate director of Data Management at Veristat and Tim Watson, IBM Watson Health. Welcome gents. Tim, any relation? >> (chuckles) If I had a nickel for every time I was asked that question I'd be a wealthy man. >> Well, relationships and trust. I mean, they're pretty fundamental to any partnership and the pandemic certainly has tested us, and we've had to rely on those personal and professional relationships to get us through COVID. So let me start Ryad by asking you, how did the partnership with IBM support you last year? >> Last year as you know was particular year for our industry. So the relationship with our provider was key of the success of any studies we had last year with the new world we had. So we were working very close with IBM Clinical, and I think collaboration was key for successful (indistinct). >> So Tim, I wonder if you could talk about some of the things that you've done with Ryad and his team, maybe some of the things that you accomplished in 2020 anything that stands out. And then maybe take it from there and query Ryad on some of the more important topics that are top of mind for you. >> Yeah, absolutely. I think in 2020, we all know it was a challenging year but IBM actually put together a really good program to support our clients as as it relates to COVID-19 trials. And Veristat did a great job of taking advantage of that with a number of their clients that offered a free promotion for 18 months of a subscription to support individual sponsors in their efforts and trying to find a vaccine that supports the whole world out there. So I think we put together a program that Veristat and their clients were able to take advantage of as it relates to COVID. But in addition to that the platform supported their efforts to maintain the clinical trials that were ongoing. And that was actually probably even bigger challenge for the Veristat team. >> Yeah, so maybe do a little mock session here. Tim you're used to role-playing so let's do a little role-playing. So we're in 2021 you guys are sitting down, unfortunately you're not face-to-face, but imagine you were and Ryad, talk about the objectives that you have in 2021, as you think about your relationship with Watson Health and Tim I'd love for you to respond in real time as to how you're going to help Ryad. Ryad kick it off, what are you trying to get done in 2021? What's the priority? >> Let me take a step back from 2020 and I go to 2021. I think one of the biggest challenge we have in 2021 with studies we had, is the extreme rapid startup of several projects we had. So we needed to start, design and push studies live in the record time. We were able to design a study in a week, another study in two weeks from the protocol to the goal of the study. And all that was with the collaboration of IBM, of course. And 2020 actually brought a change of the approach the client have to the study. So now they are more willing to use more electronic solutions than before. 2020 forced our client and the industry in general to look at the solutions offered electronically by the ADC provider by IBM Clinical. So right now in 2021, we will be leveraging those solutions, I'm thinking about monitoring module, I'm thinking about ePRO, I'm thinking about eConsent which is coming soon and I'm thinking about visualization as well. So these solutions provided by the system are now more acceptable than before and we will be used in 2021. Visualization is in the top list of these solutions eConsent comes with it as well. >> Alright so Tim, how are you going to help? How's Watson Health going to be a great partner in 2021 and beyond? >> Well, I think IBM is continuing to focus on what do these solutions mean going forward and how can we extend the functionality of our platform out there? So with the release of eConsent that's something that I believe Veristat can take advantage of. And the near term is just a matter of getting the Veristat team educated on our eConsent functionality to be able to offer that out to their clients. And visualization is another area that we've had a number of discussions with Veristat on over the past 12 months and leveraging the tool set that we are able to bring to the table with smart reports and how that can provide additional value and then finding that balance where we can get them off the ground quickly maybe with some pre-packaged reports but also educating their team so that they're able to take that tool set and be able to extend that functionality to their clients. >> So Ryad what's the situation like? I wonder if you could think pre pandemic, post pandemic. A lot of clients that I talked to, they would talk the digital game, but in reality it's not that simple. You know things are done a certain way and then I've often called it the forced march to become digital. And that's kind of what happened to us. And so I'm curious as to your sense as to what the climate was like pre and post? How much if at all, I have to believe that everybody's digital strategies were compressed, but was it months? Was it years? And it was sort of overnight we had to make the changes. So it was like a Petri dish. You really didn't have time to plan, you just did. So by how much was that digital transformation compressed and what were the learnings and how do you see taking that forward? >> We historically would go to clients with solutions and you know human nature resists to change. So when we go offering electronic solutions before the pandemic, we always had to define, to use a lot of argument actually to explain to the client that this is the way to go. This is the time to do use more electronic solutions. With the pandemic, the fear forced the client to use these solutions. And they realized that it's working. They realize that we can do it. We can do it very well. Even for complex study, solutions are available and can be used. We also was forced somehow to shorten our timeline to find best way to push studies live in as short as possible timelines without jeopardizing the quality, finding solutions. Splitter is one of the solutions IBM can offer so this is one of the solution we used. The release of the ECRS done later in the edit. IBM offered the capability to do that without jeopardizing the quality. >> So Tim, maybe you could chime in here. I mean, that's really important point. We had sort of no choice but to rush into digital and electronic last year how do you help clients maintain that quality? Maybe you guys could talk amongst yourselves as to the kinds of things you did to maintain that both, when things were going crazy and they somewhat still are. And then how do you preserve that going forward maybe turn the dial maybe a little bit based on your learnings. >> I think one of the advantages that our platform brings to the table is the flexibility. And that flexibility is what Veristat was able to take advantage of in different situations, in different parts of the platform. So whether that was the ability to design trials very quickly and be very flexible with the rollout of that trial to address specific timelines or just the different areas of the platform like ePRO to be able to extend things out to their clients as well so that patients are entering data into the clinical trial so that they're not having to go visit sites necessarily out there. So there's a lot of things that we have within the platform that our clients are able to take advantage of that really came into full focus in the year of 2020. >> Does that resonate with you Ryad? Do you trust what Tim just said? Does it give you a good feeling based on your experience? How confident are you that IBM can deliver on that objective? >> Yeah, actually the pressure we received from the industry in general, in the last year and still this year is to always shorten with high quality deliverables. So we were able to use the flexibility IBM system offers to achieve that goal. Splitting release performing a complex MSU successfully. So all these features and the flexibility we have with the status and flexibility we have with the user roles all these features and flexibilities was key performing that high quality MSU complex updates and in the record time. >> I wonder if you could each talk about sort of personally and bring it professional if you like, but how have you changed as a result of the pandemic and how has it helped you position for what's coming ahead? Ryad maybe you you could start. >> One of the things I'd like to say about what happened last year is that, it has never been easier for me to explain what I do. Historically, when I asked what do they exactly? I had to spend hours explaining what I do. Now I tell them, do you know what's the phase three phase two we are all waiting for the vaccine? That's what we do. So that's I think the number one success of the year for me. Honestly, it's just proud to work in an industry like that. Proud to work in a company like Veristat who cares about the quality who cares about providing the safety of the patient using the best system in the market working with IBM Clinical in this case. We're working to achieve that goal. I think 2020 gave me that just another level of proud maybe, if I may say. Partnership with client, partnership with IBM offered free for COVID studies for an 18-month program. So all of these just confirm that we are, I am personally in the right place, right company, having the right partnership to help humanity actually get better. >> Thank you for that, that's great. And Tim, you too you're obviously part of that, but I wonder if you could comment. >> Well, I'd like to kind of echo just what Ryad had said that professionally I feel we play a very small part. The Veristat team, the Sponsors team they do all the hard work, trying to find new medications, new vaccines to bring to life. But it means a lot to play a small part in that process to offer a technology that helps them do that quicker. And if we can get those drugs and vaccines to market quicker then that's going to have a very positive impact on the world as a whole. So it's a very exciting time to be in this industry. >> Undoubtedly. Ryad what can IBM do to help you near-term, mid-term and long-term? What are some of the most important things that Tim and his company can help with? >> Yeah, as Tim mentioned, we will have eConsent coming soon. I'm sure IBM will have other electronic solution coming soon so partnership, support and training. So education between our two entities between Veristat and IBM to use this new feature now became key for the success of any study. So I expect partnership support on an education from them. We've been successfully doing that and hoping that we'll continue in this case. >> Tim, any comments on that? >> Well, we have a great relationship with Veristat and we try to have that same kind of relationship with all of our clients. We meet regularly with governance meetings. That's a great time to share new information, to revisit old questions that may still be out there. And so, we're going to continue to offer the additional training options to our clients to allow them to leverage that platform so that they can then cater to their clients, the sponsors that are contracting with them for their clinical trials. >> So Ryad, Tim did say lower the price. That's a good sign. What about that though? What about value for investment? How Ryad would you grade IBM's track record in that regard? If you had to put a grade on it, you know, A, B, C, D, E, F. >> I would put a good grade, actually. I think it's the right balance. You know, a client expect always to pay less, but we are the experts, we are doing the job. And we have to guide them, make the right decision. We tell them why they should pick that or that system. And what are they getting for the price they're paying for. Right now we didn't have much trouble selling IBM and there is something common I think so, is to revise the price to be more specific for study, I think will help the client actually. Will help selling the products. >> So if you had to put a letter grade on it what would you give them? >> A grade? (chuckles) >> A grade, come on A, B? >> An A. >> An A, you'd give them an A? >> Yes. Solid A, 4.0 that's great, Tim you got a-- >> A minus to just leave some space for improvement. (Tim chuckles) >> Okay A minus just because, hold the carrot out there right? That's good, it's okay. Tim, how do you feel about that? You don't mind having a little extra incentive, right? >> No, absolutely not. It's always great to work with the Veristat team and we have I think a great relationship and there are certainly opportunities that we can hopefully work together. And If the price needs to be addressed then we can address it and win the business. >> Tim, anything I missed? Anything that you feel like there's a gap there that you want to cover that I didn't touch on? >> No, I think we're good. >> Great, awesome. Well, great conversation guys. I really appreciate it and thanks for the good work that you guys are doing on behalf of everybody who's living through this. It's a critical time and it's amazing how your industry has responded so thank you for that. And thank you for spending some time with us. You're watching Client Conversations with IBM Watson Health.

>>Welcome to this IBM Watson health client conversation here. We're probing the dynamics of the relationship between IBM and its clients. And we're looking back, we're exploring the present situation and discussing the future state of healthcare. My name is Dave Volante from the cube and with me are Alex Dillard. Who's a senior director data analysis at blue choice, blue choice health plan, and Darryl decode, who is IBM with IBM Watson health. Of course. Welcome gentlemen. Good to see you. Thanks for coming on. >>Hey, >>So, you know, you think about lasting relationships. They're the foundation to any partnership and this past year, and it's tested all of us. We've had to rely on both personal and professional relationships to get us through the pandemic. So Alex, let me start with you. How has the partnership with IBM supported you in 2020? >>Well, uh, I've just a piece of a larger puzzle. Uh, the relationship that Darrell and I have had is confined to IBM Watson health, but blue cross blue shield, South Carolina, which food choice is a wholly owned subsidiary of has had a standing relationship with IBM on the it side. Uh, we are a mainframe shop, uh, about 70% of our it infrastructure is on a mainframe. And, uh, that puts us as a segment one client for IBM, we're in the top 300 of all of their clients in the Americans. And more specifically we're the fourth largest, um, uh, Linux on Z shop in the world. So, uh, we've got a lot of diversification at blue cross blue shield of South Carolina and the mainframe and the vastness of that. It infrastructure reflects that, uh, diversification. We are more than just a crossing the shield. Uh, that's typically what people think of is insurance when they think of crossing shield, but we also have a division that does a lot of subcontract work for government programs, uh, track air, which is the military healthcare, uh, claims processing and Medicare claims processing. >>We were a subcontractor of other folks that use our back office, it infrastructure to, to run their claims through. So that's, that's the larger, um, aspect of our relationship that, that blue cross blue shield of South Carolina house with IBM, uh, as it relates to Watson health, we have been a client since 1994 and obviously that predates the IBM proper. Uh, we were a client of med stat and then Truven, who then, uh, was bought by IBM. So we have used the products from Watson health throughout our system to support provider profiling, uh, count group reporting, um, and ad hoc analysis and to some extent to, uh, support our value-based products with, uh, ACO and PCMH, >>Uh, products. >>Awesome. Thank you for that. So Daryl is very long-term relationship. Obviously, if people forget sometimes that, uh, how IBM has modernized the Z Alex talked about, uh, Linux on the mainframe. That's pretty cool. I wonder if you could talk about specifically the things that, that you've done with Alex in his, in his, in his team, you know, thinking back last year, what were your accomplishments that you really stand out? >>Yeah, so, so one thing that jumps to mind is, uh, given the long standing relationship, I relied heavily on Alex to help us work through a multi-year renewal. And it was, it was a, um, a good adventure for us. We, we were able to laugh along the way. We certainly had some, some phone calls that, that were a little bit challenging, but the great thing about it was that the relationship that Alex and I had, he really views it as a partnership. And that was just so encouraging and uplifting. So to me, from my perspective, that was absolutely, uh, one of the highlights of my year and working through even through the pandemic and all that, we figured it out. >>So you guys, when you get together, go ahead, please. >>That's what I had as well. Um, you know, the, the unique thing about the Watson health contract is because it involves data. Uh, we take the stance that it's an it contract, so I'm on the business side. So I've got to just, as Daryl has to navigate it with me, we've got to navigate a large of your it bureaucracy. Um, and, uh, it, it was challenging. Um, you know, the business people kind of smooth the tracks and then you get the lawyers involved in, it just goes haywire. So, um, we were able to navigate that. Um, uh, so yeah, so it was a big accomplishment. So Alex, it's not real sexy to talk about, but we got it done >>Well. So Alex you're, you're in sales, so you're, you're used to role playing. So imagine you're, you're, you're sitting down, uh, sorry, Darryl. You're used to, role-playing out. Imagine you're sitting down with Alex and you're thinking about 20, 21 planning, so, you know, take it away. W what do you, what would you ask, what would you talk about or share with us? >>Yeah, yeah, absolutely. So, so I, I know that, you know, one of the key objectives is, uh, continued to ingest, engage with your members and you have key business strategies. I know you recently migrated over to a new PBM, and so there, there's some complexities that come with that. Um, but just, you know, Alex, if you don't mind, why don't you share a little bit about kind of your, your perspective on what 2020 would hold for you in your organization? Well, I think that due to the pandemic, we are, I personally kick the, can down the road on a couple of things, particularly >>Having a strategic roadmap discussion, um, you know, uh, I was going to get into this later, but I enjoy doing things face-to-face rather than, uh, over the phone or, or virtually. And so, uh, I guess I was a little too optimistic about maybe being able to get together late 2020 to have that strategic roadmap discussion. Um, I think, uh, given what has developed with, um, the pandemic and vaccines and stuff, I may, I may be able to get everybody on the same page later this year, hopefully. Uh, but certainly we want to have a strategic roadmap discussion. Um, we license, uh, Watson Hills, uh, cat group insights, uh, tool, which we use for employer group reporting. And we are currently in the beginning stages of rolling that out to our external clients, whether it's agents, brokers, um, those types of folks. And then it vanished we as our core product that we use for analysis, and that product is transitioning to what is called health insights. And so from an analytical standpoint, my staff and the staff of our cluster areas will need to sort of move to health insights since that's where it's going, uh, from an analytic standpoint. So we're going to work on that as well. Um, and then some more detailed things around database rebuilds and stuff like that. Those are all sort of on the roadmap for 2021. >>Yeah. So, you know, you talk about strategic planning and you think about the way planning used to be. I mean, sometimes you take a longer term horizon, maybe that's five years, you know, technology cycles, you know, even though they go very fast, but you see major technology shifts, they're like go through these seven year cycles, you see that in financial world. And then with the, with the pandemic, we're talking about seven day cycles, you know, how do I support people work from home? Do I open the store or not? You know, it's a day-to-day type of thing. So I wonder if you could each talk about personally and professionally w how, how is 2020, you know, changed you and maybe position you for, for what's ahead, maybe Alex, you could start, >>Well, you know, I'm an analyst, so I always fall back to the numbers. What are the numbers show us, um, you know, people can have four perceptions, but, uh, the numbers give us a reality. So the reality is that a year ago, pre pandemic, uh, just 13% of blue cross blue shield employees were working from home a hundred percent, uh fast-forward to today. And that number is now 87%. So think about, uh, just the lift from a it infrastructure to support that we almost, all of those people are using Citrix to get in to our network. Uh, we're using a remote desktop. So you've got this pipeline that probably had to go from, you know, this small, to huge, to get all this bandwidth, all this data and everything. So you've got that huge lift. Um, and then it affects different areas, um, differently. Uh, I don't have any first-line staff, any staff that are member facing, so I didn't really have to navigate, you know, how do these people talk to our member? >>How does staff talk to our members on the phone when they're at home, as opposed to in the office, and, you know, is there background noise, things like that. So I've got analysts, uh, they're just crunching numbers. Um, but my, my, my personal, uh, feeling was I like doing managing by walking around, you know, stopping and talking to other, working on. So that went away and I like face-to-face meetings, as I've mentioned, and that went away. So it was really a culture change for me personally, it was a culture change for our organization. Uh, and, and now we're having conversations with executive management that, you know, if you've got staff who have been doing a good job and they remain productive, you know, give me a reason they got to come back in, which is just, as you told me that I'm going to be the case a year ago, I would have been, you know, flabbergasted, but that's where we are right now. >>And so on a personal standpoint, you know, I went home for a little while and then came back. And so my wife also works for blue cross blue shield of South Carolina. Um, so, you know, she set up in the dining room working, uh, I have my own book in our living room working, and then we've got a great side, you know, the school is not in session, you know, in person. So he's doing virtual learning. So combine all those things, and you've got all kinds of crazy things that could happen. Uh, and then you've got staff who are in the same situation. Um, so it was a lot to handle. And the longer it goes on the novelty of working from home wears off, and you kind of realize, you know, I can't go do this. I can't go out to eat. I can't do all types of things that I used to do. And so that affects your mental health. So as, as a leader, um, of my small area, and then our executives really had to become more, uh, uh, in, in people's faces. So we've got, we've done a lot more video, uh, messages, a lot more emails. Um, I have been tasked with being very deliberate about checking on how everything is going at their house. Are they getting what they need? Um, you know, how are they feeling? Are they getting up and exercising, all those things that you took for granted, uh, beforehand. >>Yeah. So Daryl, anything you'd add to that in terms of specifically in terms of how you might, how you might change the way in which you interact with your clients generally, uh, an Alex specifically, Alex likes, face to face, you know, we can't wait. All right. >>Yeah, yeah. It's funny. We never quite got to do it Alex, but we were talking about doing a virtual happy hour at one point too, to just celebrate the success. Um, but for me, you know, typically I would travel and visit Alex face-to-face on maybe a monthly basis. And so it it's been really hard for me. I didn't realize how, how much I enjoyed that in-person interaction. And so that, that was something that I I've been, you know, working through and finding ways to, to still interact with people. And I'm certainly making, making the best of, of the video phone calls and, you know, that sort of thing. So, uh, just work working to maintain those relationships. >>I wonder if I could ask you when, when, when this thing, when we're through the pandemic, what do you expect the work from home percentage? I think I heard 13% prior to the pandemic, 87% today. What do you think is going to be post pandemic? >>That is a good question. Um, it, it may go back to maybe 60% at home. I think, I think there will be a simple majority, uh, working from home. Um, that's, that's from our planning, uh, space planning standpoint. That's, that's what we are, uh, what we're expecting, um, if, if production stays, um, at acceptable levels, um, >>Do you feel like productivity was negatively impacted positive? It will be impacted or it's kind of weird. >>Yeah. All the metrics that we track show that it was, it was sustained and in some areas even better. Uh, and if you really think about, um, sort of your typical day when you work from home, I found, uh, that I was logged on an hour earlier. That's probably what's happening with other staff as well is they're, they're motivated to get up and, and get online, uh, earlier. >>Yeah. Mostly tech leaders that I talk to share that sentiment, that the productivity is actually improved. So Darryl, I presume you see the same thing in your observation space. Yeah. >>Yeah. I, I do. And, and I have other clients too, and, and, and they are definitely looking at ways to continue to work remotely. I know that for a lot of people who are in the office all the time, uh, having a little bit more flexibility when you work from home can be a good thing. And, and like you said, you, you have to make sure that the productivity is still there and the productivity is up. Um, but I, I could see that the trend continuing absolutely >>I'd love for you to, to look at Darryl and say, and tell him what the kinds of things that IBM can do to help you both today, immediately 20, 21, and in the future and a Darryl, how, how your, how you'll respond. >>Well, I'll tell you that. Um, so in 2020, what, what changed most dramatically for us as a health plan? Uh, and, and I, it echoes what we see across the country is the gigantic shift in telehealth. Um, you know, if, if, again, if you look at the numbers, uh, our telehealth visits per thousand, so that's the number of visits per thousand members in a given month, went up 1472%. And so, you know, the common response to that is, well, you know, your visits overall probably, you know, were flat because, uh, you know, they just weren't happening in that. And that's not necessarily true for us. So if you look at visits overall, they written down four and a half percent. Um, so there was a shift, but it, it was not a big enough shift to account for, uh, visits overall sustaining the level that they were pre pandemic. >>Um, so as we look into 2021, uh, we will be investigating how we can maintain, uh, the, uh, the accessibility of our healthcare providers via telehealth. Um, you know, one of the projects that we started in 2020, uh, was based upon the choosing wisely campaign. So if you're not familiar with choosing wisely, it's a very well thought out process. It involves many, many provider specialties and its sole target is to reduce low value care. Uh, so we took it upon ourselves to Institute sort of a mirror of that plan or that program at, at blue cross here in South Carolina. And so as we moved to 2021, obviously those low value services just because of the pandemic were reduced, uh, and some of the high-value care was reduced as well. And so what we are going to try to do is bring back habit, bring back that high value care, but not bring back that low value care and so low value care or things like vitamin D testing. Uh, it can be other things like, um, uh, CT for head headaches, um, imaging for low abdominal pain, things like that. So, uh, we want to focus on low, uh, eliminating what value care, bringing back high value care, >>Okay, Dale, you're up? How are you going to help Alex achieve that? So, so good news is, is that we've got the analytic warehouse and the database where all of the data is captured. And so we we've got the treasure trove of information and data. And so what we'll do is we'll come alongside Alex and his team will do the analytics, we'll provide the analytic methods measures, and we'll also help him uncover where perhaps those individuals may be, who had postponed care, um, because of the pandemic. And so we can put together strategies to help make sure that they get the care that they need. Uh, I also a hundred percent agree that tele-health hopefully is something that will continue because I do think that that is a good way and efficient way to get care for people. Um, and, you know, as a, as, as a way to, to address some of their needs and, and in, in a safe way too. >>So, um, I, I look forward to working with Alec and his team over this coming year. I think there is, uh, knowing Alex and, and the partnership and his readiness to be a client reference for us. You know, those are all great, um, recognition of how he partners with us. And we really value and appreciate, uh, the relationship that we have with blue cross blue shield, South Carolina and, and blue choice. Excellent. Daryl's right. The, the, the database we use already has some of that low value care measures baked into it. And so throughout 2020, I've worked with our analytic consulting team. Uh, it's under Daryl too, to talk about what's on the product product roadmap for adding to the cadre of live low value care measures inside advantage suite. Uh, so that's something that we'll actively be, um, uh, discussing because certainly, you know, we're, we're obviously not the only client only health plan clients. So there may be other plans that have priorities that very different made very differently than ours. Uh, so we want to give them what we're studying, what we're interested in, so they can just add it in to all their other client feedback, uh, for advantage suites, roadmap. Excellent. >>Look, my last question, Alex is how would you grade IBM, if you had to take a bundle of sort of attributes, you know, uh, delivery, uh, value for service relationship, uh, et cetera, how would you grade the job that IBM is doing? >>I, the thing that I enjoy most about working with IBM and Darryl specifically, is that they're always challenging us to look at different things. Um, things that sometimes we hadn't considered, because obviously it may be an issue for another health plan client or an employer client that they've got. Uh, they tell us, this is what we're seeing. You know, you should look at it. Uh, a lot of times they do some of the foundational work in producing a report to show us what they're seeing in our data that is similar to what is in some of their other clients data. So that's refreshing to be, uh, challenged by IBM to look at things that we may not be, uh, looking at, uh, or maybe missing, because we've got our eye on the ball on something else you >>Care to put a letter grade on that. >>Oh, definitely. Definitely. Thank you. >>Well, Darryl, congratulations, that says a lot and, uh, we have to leave it there and one at a time, but, but Daryl, anything that I didn't ask Alex, that you, you wanted me to, >>So, um, Alex re able to keep your tennis game up during the pandemic? Uh, I, yes, I tried as, as often as my wife would let me good. I would play every time I was asked, but, uh, yeah, so I, I did have to temper it a little bit, although when you spend all day with her and, and my son, you know, she may be a little more, uh, lenient on letting me leave the house. Well, maybe she's >>Yeah. The tribute to the late great comedian Mitch Hedberg, who says, uh, you know, when I, I played tennis, I played against the wall walls. Really good, hard to beat if it's pandemic appropriate. >>Oh, that's good. That's a true statement. And there was a lot of that going on, a lot of that play and playing against the wall. >>Hey, thanks so much, stay safe and really appreciate the time. Thank you. >>Thank you. Thank you. You're >>Really welcome. It was a great conversation and thank you for watching and spending some time with client conversations with IBM Watson health.

>> Welcome to this IBM Watson Health client conversation. And we're probing the dynamics of the relationship between IBM and it's clients. We're going to look back at some of the challenges of 2020 and look forward to, you know, present year's priorities. We'll also touch on the future state of healthcare. My name is Dave Vellante. I'll be your host and I'm from theCUBE. And with me are Doctor Alex Towbin, who's Associate Chief Clinical Operations and Informatics at Cincinnati ChilDoctoren's Hospital and John Chrisman of course from IBM Watson health. Welcome gentlemen, Good to see you. Thanks for coming on. >> Thanks for having us. >> Yeah, thanks for having me. >> Yeah I know from talking to many clients around the world, of course virtually this past year, 11 months or so that relationships with technology partners they've been critical over during the pandemic to really help folks get through that. Not that we're through it yet but, we're still through the year now, there's I'm talking professionally and personally and Doctor Towbin, I wonder if you could please talk about 2020 and what role the IBM partnership played in helping Cincinnati children's, you know press on in the face of incredible challenges? >> Yeah, I think our story of 2020 really starts before the pandemic and we were fortunate to be able to plan a disaster and do disaster drill scenarios. And so, as we were going through those disaster drill scenarios, we were trying to build a solution that would enable us to be able to work if all of our systems were down and we worked with IBM Watson Health to design that solution to implement it, it involves using other solutions from our primary one. And we performed that disaster drill in the late January, early February timeframe of 2020. And while that drill had nothing to do with COVID it got us thinking about how to deal with a disaster, how to prepare for a disaster. And so we've just completed that and COVID was coming on the horizon. I'm starting to hear about it coming into the U.S for the first time. And we took that very seriously on our department. And so, because we had prepared for this this disaster drill had gone through the entire exercise and we built out different scenarios for what could happen with COVID what would be our worst case scenarios and how we would deal with them. And so we were able to then bring that to quickly down to two options on how our department and our hospital would handle COVID and deal with that within the radiology department and like many other sites that becomes options of working from home or working in a isolated way and an and an office scenario like where I'm sitting now and we planned out both scenarios and eventually made the decision. Our decision at that point was to work in our offices. We're fortunate to have private offices where we can retreat to and something like that. And so then our relationship with IBM was helpful and that we needed to secure more pieces of hardware. And so even though IBM is our PACS vendor and our enterprise imaging vendor, they also help us to secure the high resolution monitors that are needed. And we needed a large influx of those during the pandemic and IBM was able to help us to get those. >> Wow! So yeah you were able to sort of test your organization resilience before the pandemic. I mean, John, that's quite an accomplishment for last year. I'm sure there are many others. I wonder if one of you could pick it up from here and bring your perspectives into it and, you know maybe ask any questions that you would like to ask them. >> Yeah, sure, Doctor Towbin, that's great that we were able to help you with the hardware and procure things. So I'm just curious before the pandemic how many of the radiologists ever got to read from home, was that a luxury back then? And then post pandemic, are you guys going to shift to how many are on-site versus remote? >> Yeah, so we have a couple of scenarios. We've had talk about it both from our PACS perspective as well as from our VNA enterprise imaging perspective from PACS perspective we always designed our solution to be able to work from a home machine. Our machines, people would access that through a hospital-based VPN. So they would log in directly to VPN and then access the PACS that way. And that worked well. And many of our radiologists do that particularly when they're on call works best for our neuroradiologist who are on call a little bit more frequently. And so they do read from home in that scenario. With enterprise imaging and are used to the enterprise viewer and iConnect access. We always wanted that solution to work over the internet. And so it's set up securely through the internet but not through the VPN. And we have radiologists use that as a way to view studies from home, even not from home, so it can be over one of their mobile devices, such as an iPad and could be at least reviewing studies then. We, for the most part for our radiologist in the hospital that's why we made the decision to stay in the hospital. At COVID time, we have such a strong teaching mission in our department in such a commitment to the education of our trainees. We think that hospital being in the hospital is our best way to do that, it's so hard. We find to do it over something like zoom or other sharing screen-sharing technology. So we've stayed in and I think we'll continue to stay in. There will be some of those needs from a call perspective for example, reading from home, and that will continue. >> And then what's your success been with this with the technology and the efficiency of reading from home? Do you feel like you're just as efficient when you're at home versus onsite? >> The technology is okay. The, our challenges when we're reading from the PACS which is the preferred way to do it rather than the enterprise archive, the challenge is we have to use the PACS So we have to be connected through VPN which limits our bandwidth and that makes it a little bit slower to read. And also the dictation software is a little bit slower when we're doing it. So moving study to study that rapid turnover doesn't happen but we have other ways to make, to accelerate the workflow. We cashed studies through the worklist. So they're on the machine, they load a little bit more rapidly and that works pretty well. So not quite as fast, but not terrible. >> We appreciate your partnership. I know it's been going on 10 years. I think you guys have a policy that you have to look at the market again every 10 years. So what do you think of how the market's changed and how we've evolved with the VNA and with the zero footprint viewers? A lot of that wasn't available when you initially signed up with Amicas years ago, so. >> Yeah, we signed up so we've been on this platform and then, you know now the IBM family starting in 2010, so it's now now 11 years that we're, we've been on as this version of the PACS and about eight, seven or eight years from the iConnect platform. And through that, we've seen quite an evolution. We were one of the first Amicas clients to be on version six and one of the largest enterprises. And that went from, we had trouble at the launch of that product. We've worked very closely with Amicas then to merge. And now IBM from the development side, as well as the support side to have really what we think is a great product that works very well for us and drives our entire workflow all the operations of our department. And so we've really relished that relationship with now IBM. And it's been a very good one, and it's allowed us to do the things like having disaster drill planning that we talked about earlier as far as where I see the market I think PACS in particular is on the verge of the 3.0 version as a marketplace. So PACSS 1 one was about building the packs, I think, and and having electronic imaging digital imaging, PACS 2.0 is more of web-based technology, getting it out of those private networks within a radiology department. And so giving a little bit more to the masses and 3.0 is going to be more about incorporating machine learning. I really see that as the way the market's going to go and to where I think we're at the infancy of that part of the market now about how do you bring books in for machine learning algorithms to help to drive workflow or to drive some image interpretation or analysis, as far as enterprise imaging, we're on the cusp of a lot there as well. So we've been really driving deep with enterprise imaging leading nationally enterprise imaging and I have a role in the MSAM Enterprise Imaging Community. And through all of that work we've been trying to tackle works well from enterprise imaging point of view the challenges are outside of radiology, outside of cardiology and the places where we're trying to deal with medical photos, the photographs taken with a smart device or a digital camera of another type, and trying to have workflow that makes sense for providers not in those specialty to that don't have tools like a DICOM modality workloads store these giant million-dollar MRI scanners that do all the work for you, but dealing with off the shelf, consumer electronics. So making sure the workflow works for them, trying to tie reports in trying to standardize the language around it, so how do we tag photos correctly so that we can identify relevancy all of those things we're working through and are not yet standard within our, within the industry. And so we're doing a lot there and trying and seeing the products in the marketplace continuing to evolve around that on the viewer side, there's really been a big emergence as you mentioned about the zero footprint viewers or the enterprise viewer, allowing easy access easy viewing of images throughout the enterprise of all types of imaging through obtained in the enterprise and will eventually incorporate video pathology. The market is also trying to figure out if there can be one type of viewer that does them all that and so that type of universal viewer, a viewer that cardiologists can use the same as a radiologist the same as a dermatologist, same as a pathologist we're all I think a long way away from that. But that's the Marcus trying to figure those two things out. >> Yeah, I agree with you. I agree with your assessment. You talked about the non DICOM areas, and I know you've you've partnered with us, with ImageMover and you've got some mobile device capture taking place. And you're looking to expand that more to the enterprise. Are you also starting to use the XDS registry? That's part of the iConnect enterprise archive, or as well as wrapping things in DICOM, or are you going to stick with just wrapping things in DICOM? >> Yeah, so far we've been very bunched pro DICOM and using that throughout the enterprise. And we've always thought, or maybe we've evolved to think that there is going to be a role for XDS are I think our early concerns with XDS are the lack of other institutions using it. And so, even though it's designed for portability if no one else reads it, it's not portable. If no one else is using that. But as we move more and more into other specialties things like dermatology, ophthalmology, some of the labeling that's needed in those images and the uses, the secondary uses of those images for education, for publication, for dermatology workflow or ophthalmology workflow, needs to get back to that native file and the DICOM wrap may not make sense for them. And so we've been actively talking about switching towards XDS for some of the non DICOM, such as dermatology. We've not yet done that though. >> Given the era children's hospital has the impact on your patient load, then similar to what regular adult hospitals are, or have you guys had a pretty steady number of studies over the last year? >> In relay through the pandemic, we've had, it has been decreased, but children fortunately have not been as severely affected as adults. There is definitely disease in children and we see a fair amount of that. There are some unique things that happen in kids but that fortunately rare. So there's this severe inflammatory response that kids can get and can cause them to get very sick but it is quite rare. Our volumes are, I think I'm not I think our volumes are stable and our advanced imaging things like CT, MRI, nuclear medicine, they're really most decreased in radiography. And we see some weird patterns, inpatient volumes are relatively stable. So our single view chest x-rays, for example, have been stable. ER, visits are way down because people are either wearing masks, isolating or not wanting to come to the ER. So they're not getting sick with things like the flu or or even common colds or pneumonias. And so they're not coming into the ER as much. So our two view x-rays have dropped by like 30%. And so we were looking at this just yesterday. If you follow the graphs for the two we saw a dip of both around March, but essentially the one view chest were a straight line and the two view chest were a straight line and in March dropped 30 to 50% and then stayed at that lower level. Other x-rays are on the, stay at that low level side. >> Thanks, I know in 2021 we've got a big upgrade coming with you guys soon and you're going to stay in our standalone mode. I understand what the PACSS and not integrate deeply to the VNA. And so you'll have a couple more layers of storage there but can you talk about your excitement about going to 8.1 and what you're looking forward to based on your testimony. >> Yeah we're actually in, we're upgrading as we're talking which is interesting, but it's a good time for talking. I'm not doing that part of the work. And so our testing has worked well. I think we're, we are excited. We, you know, we've been on the product as I mentioned for over 10 years now. And for many of those years we were among the first, at each version. Now we're way behind. And we want to get back up to the latest and greatest and we want to stay cutting edge. There've been a lot of reasons why we haven't moved up to that level, but we do. We're very careful in our testing and we needed a version that would work for us. And there were things about previous versions that just didn't and as you mentioned, we're staying in that standalone mode. We very much want to be on the integrated mode in our future because enterprise imaging is so important and understanding how the comparisons fit in with the comparison in dermatology or chest wall deformity clinic, or other areas how those fit into the radiology story is important and it helped me as a radiologist be a better radiologist to see all those other pictures. So I want them there but we have to have the workflow, right. And so that's the part that we're still working towards and making sure that that fits so we will get there. It'll probably be in the next year or two to get to that immigrating mode. >> As you, look at the number of vendors you have I think you guys prefer to have less vendor partners than than more I know in the cardiology area you guys do some cardiology work. What has been the history or any, any look to the future of that related to enterprise imaging? Do you look to incorporate more of that into a singular solution? >> Cardiology is entirely part of our enterprise imaging solution. We all the cardiology amendments go to our vendor neutral archive on the iConnect platform. All of them are viewed across the enterprise using our enterprise viewer. They have their unique specialty viewer which is, you know, fine. I'm a believer that specialty, different specialties, deserve to have their specialty viewers to do theirs specialty reads. And at this point I don't think the universal viewer works or makes sense until we have that. And so all the cardiology images are there. They're all of our historical cardiology images are migrated and part of our enterprise solution. So they're part of the entire reference the challenge is they're just not all in PACSS. And so that's where, you know, an example, great example, why we need to get to this to the integrated mode to be able to see those. And the reason we didn't do that is the cardiology archive is so large to add a storage to the PACS archive. Didn't make sense if we knew we were going to be in an integrated mode eventually, and we didn't want to double our PACS storage and then get rid of it a couple of years later. >> So once you're on a new version of merge PACS and you're beyond this, what are your other goals in 2021? Are you looking to bring AI in? Are you using anybody else's AI currently? >> Yeah, we do have AI clinical it's phone age, so it's not not a ton of things but we've been using it clinically, fully integrated, it launches. When I open a study, when I opened a bone age study impacts it launches we have a bone age calculator as well that we've been using for almost two decades now. And so that we have to use that still but launching that automatically includes the patient's sex and birth date, which are keys for determining bone age, and all that information is there automatically. But at the same time, the images are sent to the machine learning algorithm. And in the background the machine determines a bone age that in the background it sends it straight to our dictation system and it's there when we opened the study. And so if I agree with that I signed the report and we're done. If I disagree, I copy it from my calculator and put it in until it takes just a couple of clicks. We are working on expanding. We've done a lot of research in artificial intelligence and the department. And so we've been things are sort of in the middle of translation of moving it from the research pure research realm to the clinical realm, something we're actively working on trying to get them in. Others are a little bit more difficult. >> That's the question on that John, Doctor, when you talk about injecting, you know machine intelligence into the equation. >> Yeah. >> What, how do you sort of value that? Does that give you automation? Does it improve your quality? Does it speed the outcome and maybe it's all of those but how do you sort of evaluate the impact to your organisation? >> I there's a lot of ways you can do it. And you touched on one of my favorite one of my favorite talking points, in a lot of what we've been doing and early machine learning is around image interpretation helping me as a radiologist to see a finding. Unfortunately, most of the things are fairly simple tasks that it's asking us to do. Like, is there a broken bone? Yes or no, I'm not trying to sound self-congratulatory or anything, but I'm really good at finding broken bones. I get, I've been doing it for a long time and, and radio, you know so machines doing that, they're going to perform as well as I can perform, you know, and that's the goal. Maybe they'll perform a little bit better maybe a little bit worse but we're talking tiny increments there they're really to me, not much value of that it's not something I would want. I don't value that at a time where I think machine learning can have real value around more on some of the things that you mentioned. So can it make me more efficient? Can it do the things that are so annoying that and they'd take, they're so tedious that they make me unhappy. A lot of little measurements for example are like that an example. So in a patient with cancer, we measure a little tumors everywhere and that's really important for their care, but it's tedious and so if a machine could do that in an automated way and I checked it that, you know, patient when because he or she can get that good quality care and I have a, you know, a workflow efficiency game. So that one's important. Another one that would be important is if the machine can see things I can't see. So I'm really good at finding fractures. I'm not really good at understanding what all the pixels mean and, you know in that same patient with cancer, oh what do all the pixels mean in that tumor? I know it's a tumor. I can see the tumor, I can say it's a tumor but sometimes those pixels have a lot of information in them and may give us prognosis, you know, say that this patient may, maybe this patient will do well with this specific type of chemotherapy or a specific or has a better prognosis with one with one drug compared to another. Those are things that we can't usually pick out. You know, it's beyond the level of that are I can perceive that one is really the cutting edge of machine learning. We're not there yet and then the other thing are things that, you know just the behind the scenes stuff that I don't necessarily need to be doing, or, you know so it's the non interpretive artificial intelligence. >> Dave: Right. >> And that's what I've been also trying to push. So an example of when the algorithms that we've been developing here we check airways. And this is a little bit historical in our department, but we want to make sure we're not missing a severe airway infection. That can be deadly, it's incredibly rare. Vaccines have made it go away completely but we still check airways. And so what happens is the technologist takes the x-ray. They come in to ask us if it's okay, we are interrupted from what we're doing. We open up the study, say yes or no. Okay, not okay, if it's not okay they go back, take another study. Then come back to us again and say, is it okay or not? And we repeat this a couple of times it takes them time that they don't need to spend and takes us time. And so we have, we've built an algorithm where the machine can check that and their machine is as good or a little bit worse than us, but give can give that feedback. >> Dave: Got it. >> The challenge is getting that feedback to the technologist quickly. And so that's, that's I think part for us to work on stuff. >> Thank you for that. So, John, we've probably got three or four minutes left. I'll let you bring it home and appreciate that Doctor Towbin >> I think one of the biggest impacts probably I knew this last year with the pandemic, Doctor Towbin is this, I know you're a big foodie. So having been to some good restaurants and dinners with the hot nurse in a house how's the pandemic affected you personally. And some of the things you like to do outside of work. >> Everything is shut down. And everything has changed. I have not left the house since March besides come to work and my family hasn't either. And so we're hardcore quarantining and staying you know, staying out and keeping it home. So we've not gone out to dinner or done much else. >> So its DoorDash and Uber Eats or just learned to cook at home. >> It's all cooking at home. We're fortunate, my wife loves to cook. My kids love to cook. I enjoy cooking, but I don't have the time as often. So we've done a lot of different are on our own experimenting. Maybe when the silver lining one of the things I've really relished about all this is all this time I get to spend with my family. And that closeness that we've been able to achieve because of being confined in our house the whole time. And so I've played get to play video games with my kids every night. We'd been on a big Fortnite Keck lately since it's been down making. So we've been playing that every night since we've watched movies a lot. And so as a family, we've, I it's something I'll look back fondly even though it's been a very difficult time but it's been an enjoyable time. >> I agree, I've enjoyed more family time this year as well, but final question is in 2021, beyond the PACS upgrade what are the top other two projects that you want to accomplish with us this year? And how can we help you? >> I think our big one is are the big projects are unexpanded enterprise imaging. And so we want to continue rolling out to other areas that will include eventually incorporating scopes, all the images from the operating room. We need to be able to get into pathology. I think the pathology is really going to be a long game. Unfortunately, I've been saying that already for 10 years and it's still probably another 10 years ago but we need to go. We can start with the gross pathology images all the pictures that we take for tumor boards and get those in before we start talking about whole slide scanning and getting in more of the more of the photographs in the institution. So we have a route ambulatory but we need inpatient and ER. >> All right one last question. What can IBM do to be a better partner for you guys? >> I think it's keep listening keep listening and keep innovating. And don't be afraid to be that innovative partner sort of thinking as the small company that startup, rather than the giant bohemoth that can sometimes happen with large companies, it's harder. It is fear to turn quickly, but being a nimble company and making quick decisions, quick innovations. >> Great, quick question. How would you grade IBM, your a tough grader? >> It depends on what I am a tough grader but it depends on what, you know as the overall corporate partnership? >> Yeah the relationship. >> I'd say it's A minus. >> Its pretty good. >> I think, I mean, I, we get a lot of love from IBM. I'm talking specifically in the imaging space. I not, maybe not, I don't know as much on the hardware side but we, yeah, we have a really good relationship. We feel like we're listened to and we're valued. >> All right, well guys, thanks so much. >> So even if it's not an A plus- >> Go ahead. >> I think there's some more to, you know, from the to keep innovating side there's little things that we just let you know we've been asking for that we don't always get but understand the company has to make business decisions not decisions on what's best for me. >> Of course got to hold that carrot out too. Well thanks guys, really appreciate your time. Great conversation. >> Yeah, thank you. >> All right and thank you for spending some time with us. You're watching client conversations with IBM Watson Health.

>> Welcome to this IBM Watson Health "Client Conversation." We're probing the dynamics of the relationships between IBM and its clients. And we're going to look back, we're going to explore the present situation and we're going to discuss the future state of healthcare. My name is Dave Vellante from theCUBE and with me are Dr. David Huelsman, who is a radiologist at TriHealth, which is a provider of healthcare in hospitals and John Kritzman who is with of course IBM Watson Health. Gentlemen welcome. Thanks so much for coming on. >> Thank you. >> Yeah, thanks for having us. >> Doctor let me say you're welcome. Let me start with you. As an analyst and a TV host in the tech industry, we often focus so much on the shiny new toy, the new widget, the new software. But when I talk to practitioners, almost to a person, they tell me that the relationship and trust are probably the most important elements of their success, in terms of a vendor relationship. And over the last year, we've relied on both personal and professional relationships to get us through some of the most challenging times any of us have ever seen. So, Dr. Huelsman, let me ask you, and thinking about the challenges you faced in 2020, what does partnership mean to you and how would you describe the relationship with IBM? >> Well, it is exactly the reason why when we started our journey on this enterprise imaging project at TriHealth, that we very early on made the decision We only wanted one vendor. We didn't want to do it piecemeal, like say get a vendor neutral archive from one organization, and the radiology viewer from another. We wanted to partner with the chosen vendor and develop that long-term relationship, where we learn from each other and we mutually benefit each other, in sort of not just have a transactional relationship, but that we share the same values. We share the same vision. And that's what stood out to us is Watson Health imagings vision, mirrored TriHealth's in what we were trying to achieve with our enterprise imaging project. >> You know, let me follow up with that if I could. A lot of times you hear the phrase, "Single throat to choke" and it's kind of a pejorative, right? It's a really negative term. And the way you just described that Dr. Huelsman is you were looking for a partnership. Yeah, sure. Maybe it was more manageable and maybe it was a sort of Singletree, but it was really about the partnership, going forward in a shared vision and really shared ownership of the outcome. Is that a fair characterization? >> Yeah, how about more positive is "One hand to shake." >> Wow, yeah, I love it. (chuckles) One hand to shake. I'm going to steal that line. That's good. I like it. Keep it positive. Okay, John, when you think about the past 12 months and I know you have history with TriHealth, and more recently have rejoined the account, but how would you kind of characterize that relationship and particularly anything you can add about the challenges of the 2020? What stands out to you? >> Yeah, I think going back to your one hand to shake or one vendor to hug all that's not allowed during COVID, but we're excited to be back working with you, I am in particular. And at the beginning of this sales process and RFP when you guys were looking for that vendor partner, we did talk to you about the journey, the journey with AI that we already had mature products on the vendor neutral archive side and all the product pieces that you were looking for. And I know you've recently went live over the last year and you've been working through, crawling through and learning to walk and starting to run, hopefully. And at some point we'll get to the end of the marathon, where you'll have all the AI pieces that you're looking for. But this journey has been eyeopening for all of us, from using consultants in the beginning, to developing different team members to help make you successful. So I think I've been tracking this from the outside looking in, and I'm happy to be back, more working direct with you this year to help ensure your longterm success. >> Yeah, that's great John. You have some history there. I'm going to probe that a little bit. So doctor, you talked about this enterprise imaging project. I presume that's part of, that's one of the vectors of this journey that you're on. What are you trying to accomplish in the sort of near term and midterm in 2021? John mentioned AI, is there a data element to this? Are there other, maybe more important pressing things? What are your main goals for 2021? >> Sure. Well, where we are, where we've started, the first step was getting all of our imaging stored consistently in the same place and in the same way. We had like many health system, as you grow, you acquire facilities, you acquire physician practices and they all have their own small packs system, different ways of storing the data. And so it becomes very unwieldy to be a large organization and try to provide a consistent manner of your physicians interacting with the data, with the imaging in the same way. And so it was a very large dissatisfier in our EMR to, oh if you wanted to see cardiovascular imaging, it's this tab. If you wanted to see radiology, it was this tab. If you wanted to see that, oh you got to go to the media tab. And so our big goal is, okay, let's get the enterprise archive. And so the Watson enterprise archive is to get all of our imaging stored in the same place, in the same way. And so that then our referring physicians and now with our patients as well, that you can view all the imaging, access it the same way and have the same tools. And so that's the initial step. And we're not even complete with that first step, that's where COVID and sort of diverting resources, but it's there, it's that foundation, it's there. And so currently we have the radiology, cardiology, orthopedics and just recently OB-GYN, all of those departments have their images stored on our Watson Enterprise Archive. So the ultimate goal was then any imaging, including not just what you typically think of radiology, but endoscopy and arthroscopy and those sort of images, or wound care images, in that any image, any picture in our organization will be stored on the archive. So that then when we have everything on that archive, it's easier to access consistently with the same tools. But it's also one of the large pieces of partnering with with Watson Health Imaging, is the whole cognitive solutions and AI piece. Is that, well now we're storing all the data in a consistent manner, you can access it in a consistent manner, well then we hope to analyze it in a consistent manner and to use machine learning, and the various protocols and algorithms that Watson Health Imaging develops, to employ those and to provide better care. >> Excellent, thank you for that. John, I wonder if you could add to that? I mean, you've probably heard this story before from other clients, as well as TriHealth, I call it EMR chaos. What can you add to this conversation? I'm particularly interested in what IBM Watson Health brings to the table. >> Sure, we've continued to work with TriHealth. And like we said earlier, you do have to walk before you can run. So a lot of this solution being put in place, was getting that archive stood up and getting all the images transferred out of the legacy systems. And I think that we're nearly done with that process. Doing some find audits, able to turn off some of the legacy systems. So the data is there for the easier to do modalities first, the radiology, the cardiology, the OB, as Dr. Huelsman mentioned and the ortho. And now it's really getting to the exciting point of really optimizing everything and then starting to bring in other ologies from the health system, trying to get everything in that single EMR view. So there was a lot of activity going on last year with optimizing the system, trying to fine tune hanging protocols, make the workflow for everybody, so that the systems are efficient. And I think we will continue on that road this year. We'll continue down further with other pieces of the solution that were not implemented yet. So there's some deeper image sharing pieces that are available. There are some pieces with mobile device image capture and video capture that can be deployed. So we look forward to working in 2021 on some of those areas, as well as the increased AI solutions. >> So Dr. Huelsman I wonder if you could double click on that. I mean if you're talking to IBM, what are the priorities that you have? What do you, what do you really need from Watson Health to get there? >> So I spoke with Daniel early last week, and sort of described it as now we have the foundation, we sort of have the skeleton and now it's time to put meat on the bones. And so what we're excited about is the upcoming patient synopsis would be the first piece of AI cognitive solutions that Watson Health Imaging provides. And it's sort of that partnership of we're not expecting it to be perfect, but is it better than we have today? There is no perfect solution, but does it improve our current workflow? And so we'll be very interested of when we go live with patients synopsis of does this help? Is this better than what we have today? And the focus then becomes partnering with Watson Health Imaging is how do we make it better for ourselves? How do we make it better for you? I think we're a large health organization and typically we're not an academic or heavy research institution, but we take care of a lot of patients. And if we can work together, I think we'll find solutions. It's really that triple aim of how to provide better care, at cheaper costs, with a better experience. And that's what we're all after. And what's your version of patient, the current version of patients synopsis, and okay does it work for us? Well, even if it does, how do we make it better? Or if it doesn't, how do we make it work? And I think if we work together, make it work for TriHealth, you can make it work at all your community-based health organizations. >> Yeah. So, John that brings me to, Dr. Huelsman mentioned a couple of things in terms of the outcomes. Lower costs, better patient experience, et cetera. I mean, generally for clients, how do you measure success? And then specifically with regard to TriHealth, what's that like? What's that part of the partnership? >> Yes, specifically with TriHealth, the measure of success will be when Dr. Huelsman is able to call and be a super reference for us, and have these tools working to his satisfaction. And when he's been able to give us great input from the customer side, to help improve the science side of it. So today he's able to launch his epic EMR in context and he has to dig through the data, looking for those valuable nuggets and with using natural language processing, when he has patients synopsis, that will all be done for him. He'll be able to pull up the study, a CT of the head for instance and he'll be able to get those nuggets of information using natural language processing that Watson services and get the valuable insights without spending five or 10 minutes interrogating the EMR. So we look forward to those benefits for him, from the data analytics side, but then we also look forward to in the future, delivering other AI for the imaging side, to help him find the slices of interest and the defects that are in that particular study. So whether that's with our partner AI solutions or as we bring care advisers to market. So we look forward to his input on those also. >> Can you comment on that Dr. Huelsman? I would imagine that you would be really looking forward to that vision that John just laid out, as well as other practitioners in your organization. Maybe you could talk about that, is that sort of within your reach? What can you tell us? >> Well, absolutely. That was sort of the shared vision and relationship that we hope for and sort of have that shared outlook is we have all this data, how do we analyze it to improve, provide better care cheaper? And there's no way to do that without you harnessing technology. And IBM has been on the cutting edge of technology for my lifetime. And so it's very exciting to have a partnership with WHI and IBM. There's a history, there's a depth. And so how do we work together to advance, because we want the same things. What impressed me was sure, radiology and AI has been in the news and been hyped and some think over-hyped, and what have you. Everyone's after that Holy grail. But it's that sense of you have the engineers that you talk to, but there is an understanding that don't design the system for the engineers, design it for the end user. Design it for the radiologist. Talk to the end user, because it can be the greatest tool in the world, but I can tell you as a radiologist, if it interrupts my workflow, if it interrupts my search pattern for looking at images, it doesn't help me and radiologists won't use it. And so just having a great algorithm won't help. It is how do you present it to the end user? How do I access it? How can I easily toggle on and off, or do I have to minimize and maximize, and log into a different system. We talked earlier is one throat to choke, or one vendor to hug, we only want one interface. Radiologists and users just want to look at their... They have the radiology viewer, they have their PACS, we look at it all day and you don't want to minimize that and bring up something else, you want to keep interacting with what you're used to. And the mouse buttons do the same thing, it's a mouse click away. And that's what the people at Watson Health Imaging that we've interacted with, they get it. They understand that's what a radiologist would want. They want to continue interacting with their PACS, not with a third vendor or another program or something else. >> I love that. That ton of outside in thinking, starting with the radiologist, back to the engineer, not the reverse. I think that's something that IBM, and I've been watching IBM for a long time, it's something that IBM has brought to the table with its deep industry expertise. I maybe have some other questions, but John I wanted to give you an opportunity. Is there anything that you would like to ask Dr. Huelsman that maybe I haven't touched on yet? >> Yeah. Being back on your account this year, what do you see as a success? What would you count as a success at the end of 2021, if we can deliver this year for you? >> The success would be say, at the end of the year, we've got the heavy hitters, all stored on the archive. Do we pick up all the little, we've got the low hanging fruit, now can we go after the line placement imaging and the arthroscopy and dioscomy, and all those smaller volume in pickups, that we truly get all of our imaging stored on that archive. And then the even larger piece is then do we start using the data on the archive with some cognitive solution? I would love to successfully implement, whether it's patient synopsis or one of the care advisors, that we start using sort of the analytics, the machine learning, some AI component that we successfully implement and maybe share good ideas with you. And sure we intend to go live with patient synopsis next month. I would love it by the end of the year, if the version that we're using patients synopsis and we find it helpful. And the version we use is better than what we went live with next month, because of feedback that we're able to give you. >> Great we looked forward to working with you on that. I guess, personally, with the pandemic in 2020, what have you become, I guess in 2020 that maybe you weren't a year ago before the pandemic, just out of curiosity? >> I'm not sure if we're anything different. A mantra that we've used in the department of radiology at TriHealth for a decade, "Improved service become more adaptable." And we're a service industry, so of course we want to improve service, but be adaptable, become more adaptable. And COVID certainly emphasize that need to be adaptable, to be flexible and the better tools we have. It was great early in the COVID when we had the shutdowns, we found ourselves, we have way more radiologists than we had studies that needed interpreted. So we were flexible all often and be home more. Well, the referring physicians don't know like, well is Dr. Huelsman working today? We don't expect them to look up our schedules. If I get a page that, Hey, can you take a look at this? It was great that at that time I didn't have a home workstation, but I had iConnect access. Before there was no way for me to access the images without getting on a VPN and logging on, it takes 10, 15 minutes before I'm able. Instead I could answer the phone, and I'm not going to say, "Oh, I'm sorry, I'm not at the hospital day, call this number someone else will help you." I have my iPad, go to ica.trihealth.com logged on, I'm looking at the images two minutes later. And so the ease of use, the flexibility, it helped us become adaptable. And I anticipate with we're upgrading the radiology viewer and the iConnect access next month as well, to try to educate our referring physicians, of sort of the image sharing capabilities within that next version of our viewer. Because telehealth has become like everywhere else. It's become much more important at TriHealth during this pandemic. And I think it will be a very big satisfier for both referring physicians and patients, that those image sharing capabilities, to be able to look at the same image, see the annotation that either the radiologist or the referring physician, oncologist, whoever is wanting to share images with the patient and the patient's family, to have multiple parties on at the same time. It will be very good. >> With the new tools that you have for working from home with your full workstation, are you as efficient reading at home? >> Yes. >> And having full access to the PACS as in-house? >> Absolutely. >> That's great to hear. Have you been able to take advantage of using any of the collaboration tools within iConnect, to collaborate with a referring physician, where he can see your pointer and you can see his, or is that something we need to get working? >> Hopefully if you ask me that a year from now, the answer will be yes. >> So does that exit a radiologist? Does that help a radiologist communicate with a referring physician? Or do you feel that that's going to be a- >> Absolutely. We still have our old school physicians that we love who come to the reading room, who come to the department of radiology and go over studies together. But it's dwindling, it's becoming fewer and fewer as certain individuals retire. And it's just different. But the more direct interaction we can have with referring physicians, the better information they can give us. And the more we're interacting directly, the better we are. And so I get it, they're busy, they don't want to, they may not be at the hospital. They're seeing patients at an outpatient clinic and a radiologist isn't even there, that's where that technology piece. This is how we live. We're an instantaneous society. We live through our phone and so great it's like a FaceTime capability. If you want to maintain those personal relationships, we're learning we can't rely on the orthopedist or whomever, whatever referring physician to stop by our reading room, our department. We need to make ourselves available to them and make it convenient. >> That market that you working in Cincinnati, we have a luxury of having quite a few customers with our iConnect solutions. There's been some talk between the multiple parties, of potentially being able to look across the other sites and using that common tool, but being able to query the other archives. Is that something that you'd in favor of supporting and think would add value so that the clinicians can see the longitudinal record? >> Yes And we already have that ability of we can view care everywhere in our EMR. So we don't have the images right away, but we can see other reports. Again, it's not convenient. It's not a click away, but it's two, three, four clicks away. But if I see, if it's one of my search patterns of I just worked the overnight shift last week and then you get something through the ER and there's no comparisons, and it's an abnormal chest CT. Well, I look in Care Everywhere. Oh, they had a chest CT at a different place in the city a year ago, and I can see the report. And so then at that time I can request, and it can take an hour or so, but look back and the images will be accessible to me. But so how do we improve on that? Is to make the images, that I don't have to wait an hour for the images. If we have image sharing among your organizations that can be much quicker, would be a big win. >> As you read in your new environment, do you swivel your chair and still read out of any other specialty systems, for any types of studies today? >> No, and that was a huge win. We used to have a separate viewing system for mammography and we were caught like there were dedicated viewing stations. And so even though we're a system, the radiologist working at this hospital, had to read the mammograms taken at that hospital. And one at the other hospital could only read the ones taken at that hospital. And you couldn't share the workload if it was heavy at one site and light at the other. Well, now it's all viewed through the radiology viewer if you merge PACS, in not just general radiology, but impressed. It has been so much better world that the workflow is so much better, that we can share the work list and be much more efficient. >> Do you feel that in your, your new world, that you're able to have less cherry picking between the group, I guess? Do you feel like there's less infighting or that the exams are being split up evenly through the work list? Or are you guys using some sort of assignment? >> No. And I'm curious with our next version of PACS, the next version of merge packs of 008. I forget which particular >> John: 008. >> It's 008, yeah. I know there's the feature of a smart work list to distribute the exams. Currently, we just have one. It's better than what we have before. It's one large list. We've subdivided, teased out some things that not all of the radiologist read of like MSK and cardiac and it makes it more convenient. But currently it is the radiologist choose what study they're going to open next. To me how I personally attack the list is I don't look at the list. Some radiologists can spend more time choosing what they're going to read next than they do reading. (chuckles) And so if you don't even look, and so the feature I love is just I don't want to take my eyes off my main viewer. And I don't want to swivel my chair. I don't want to turn my head to look at the list, I want everything right in front of me. And so currently the way you can use it is I never look at the list. I just use the keyboard shortcuts of, okay, well I'm done with that study. I mark it, there's one button I click on my mouse that marks it dictated, closes it and brings up the next study on the list. >> Hey guys, I got to jump in. We're running up against the clock, but John if you've got any final thoughts or Dr. Huelsman, please. >> Sure. Dr. Huelsman, I guess any homework for me? What are the top two or three things I can help you with in 2021 to be successful? >> Keep us informed of what you're working on, of what's available now. What's coming next, and how soon is it available? And you let us see those things? And we'll give you a feedback of hey, this is great. And we'll try to identify things, if you haven't thought of them, hey, this would be very helpful. >> Gents, great conversation. Gosh we could go on for another 45 minutes. And John you really have a great knowledge of the industry. And Dr. Huelsman, thanks so much for coming on. Appreciate it. >> Thank you. >> You're welcome >> And thanks for spending some time with us. You're watching "Client Conversations" with IBM Watson Health.

>>Welcome to this IBM Watson health client conversation here. We're probing the dynamics of the relationship between IBM and its clients. And we're looking back, we're going to explore the present. We're going to discuss the future state of healthcare. My name is Dave Volante from the Cuban with me are Robert Stell horn. Who's associate director, H E O R at sukha, otherwise known as pharmaceuticals, America and Rena Felton. Who's with of course, IBM Watson health. Welcome folks. Great to have you. Hi, so like strong relationships, as we know, they're the foundation of any partnership. And of course over the past year, we've had to rely on both personal and professional relationships to get us through some of the most challenging times, if not the most challenging times of our lives. So let me start with you, Robert, how has the partnership with IBM helped you in 2020? >>I think it was just a continuation of the excellent relationship we have with Rena and IBM. Um, starting in March, we had really a shift to an all remote, uh, workplace environment. And I think that constant communication with Rina and IBM helped that situation because she kept us up to date with, uh, additional products and offerings. And basically we came up with some additional solutions towards the end of the year. So we're gonna watch >>Pick it up from here. Let's go, let's go a little bit deeper and maybe you can talk about some of the things that you've done with Robert and his team and, and maybe some of the accomplishments that you're most proud of in 2020. >>No, absolutely. And I have to kind of echo what you first said about the foundation and our partnerships being the foundation, um, of our past present and future. So I do want to take the opportunity to thank Rob again for joining us today. It is, um, I know, you know, with his kids home and remote learning, um, it's a lot, uh, to, to ask in addition to, you know, your day to day work. So, so thank you, Rob. Um, I guess the question that I have for you is what would be the greatest accomplishment, um, that Watseka and IBM Watson had in 2020? >>I would say it was the addition of the linked claims EMR data, the LDCD product that we were able to license in-house, uh, thanks to your attention and to show the advantages and the strengths of that data. We are able to license that in to our, uh, set up assets we have internally. And what that's gonna allow us to do is really find out more information about the patients. Uh, we're existing users of the Mark IBM, uh, market scan data. Um, this is going to allow us to tie into those same patients and find out more about them. Um, in particular, uh, a lot of our products are in the mental health space and a lot about standing questions we have are why are the patients getting different products? And with the notes are available in that link data. We're going to now be able to tap into more information about what is happening with the patient. >>Okay. Can I ask a question on that? Um, if you guys don't mind, I mean, you know, when you, when you hear about, you know, uh, EMR, uh, in the early days, it was a lot about meaningful use and getting paid. It sounds like you guys are taking it much deeper and as a, as a, you know, as an individual, right, you're, you're really happy to hear that this information is now going to be used to really improve, uh, healthcare is, do I have that right? Is that, you know, kind of the nature of where you guys are headed? >>Well, I think ultimately it's the, the, the, the main goal is to help the patients and provide the products that can really, um, help them in their daily lives. So, um, really with this data, now, we're going to be able to tap into more of the why, um, exist in claims data. We cannot really get that information, why VC information, about what diagnoses they incurred during their treatment history. And we also can see, uh, different prescriptions that are given to them, but now we're going to be able to tie that together and get more understanding to really see more focused treatment pattern for them. >>So, Reno, w w you sit down with Rob, do you have like a, sort of a planning session for 2021? Why don't you sort of bring us up to, uh, to what your thinking is there and how you guys are working together this year? >>Yeah, no, absolutely. Um, actually, before we get to that, I wanted to kind of add onto what Rob was saying as well. It's interesting given, you know, the pandemic in 2020 and what the LCD data is going to do, um, to really be able to look back. And as Rob mentioned, looking specifically at mental health, the ability to look back and start looking at the patients and what it's really done to our community and what it's really done to our country, um, and looking at patients, you know, looking back at, at sort of their, their patient journey and where we are today. Um, but Rob and I talk all the time, we talk all the time, we probably talk three or four times a day sometimes. So I would say, um, we, we text, uh, we do talk and have a lot of our strategic, um, sessions, uh, our outlook for 2021 and what the data strategy is for Otsuka. Um, in addition, additional data assets to acquire from IBM, as well as how can we sort of leverage brander IBM, um, assets like our red hat, our OpenShift, our cloud-based solutions. So, you know, Rob and I are constantly talking and we are, um, looking for new ways to bring in new solutions into Otsuka. Um, and you know, yeah, we, we, we talk a lot. What do you think, Rob? >>I think we have an excellent partnership. Uh, basically, um, I think their relationship there is excellent. Um, we have excellent communication and, you know, I find when there's situations where I may be a bind Reno's is able to help out instantly. Um, so it's, it's really a two way street and it's an excellent partnership. >>I wonder if I could double click on that. I mean, relative to maybe some of your, I mean, I'm sure you have lots of relationships with lots of different companies, but, but what makes it excellent specifically with regard to IBM? Is there, is there anything unique Rob, that stands out to you? >>It would be the follow-up, um, really, it's not just about, uh, delivering the data and say, okay, here you have your, your product work with it in basically the, the, the vendor disappears, it's the constant followup to make sure that it's being used in any way they can help and provide more information to really extract the full value out of it. >>So I'm gonna forget to ask you guys, maybe each of you, you know, both personally and professionally, I feel like, you know, 20, 20 never ended it just sort of blended in, uh, and, and, but some things have changed. We all talk about, geez, what's going to be permanent. How have you each been affected? Um, how has it helped you position for, for what's coming in in the years ahead, maybe Reena, you could start and then pick it up with, with Rob. >>Oh man. Um, you know, 2020 was definitely challenging and I think it was really challenging given the circumstances and in my position where I'm very much used to meeting with our customers and having lunch and really just kind of walking down the hallways and bumping into familiar faces and really seeing, you know, how we can provide value with our solutions. And so, you know, that was all stripped in 2020. Uh, so it's been, it's been quite challenging. I will say, working with Rob, working with some of my other customers, um, I've had, uh, I've had to learn the resilience and to be a little bit more relentless with phone calls and follow ups and, and being more agile in my communications with the customers and what their needs are, and be flexible with calendars because there's again, remote learning and, and, um, and the like, so I think, you know, positioned for 2021 really well. Um, I am excited to hopefully get back out there and start visiting our customers. But if not, I certainly learned a lot and just, um, the follow-up and again, the relentless phone calls and calling and checking up on our customers, even if it's just to say, hi, see how everyone's doing a mental check sometimes. So I think that's, that's become, um, you know, what 2020 was, and, and hopefully, you know, what, 2021 will be better and, uh, kind of continue on that, that relentless path. >>What do you think, Rob? Hi, how are you doing? >>I would echo a lot of Rina's thoughts and the fact of, yeah, definitely miss the in-person interaction. In fact, I will say that I remember the last time I was physically in the office that Scott, it was to meet with Rina. So I distinctively remember that they remember the date was March, I believe, March 9th. So it just shows how this year as has been sort of a blur, but at the same time, you remember certain milestones. And I think it's because of that relationship, um, we've developed with IBM that I can remember those distinctive milestones and events that took place. >>So Rob, I probably should have asked you upfront, maybe tell us a little bit about Alaska, uh, maybe, maybe give us the sort of quick soundbite on where you guys are mostly focused. Sure. >>Oh, it's guys, uh, a Japanese pharmaceutical company. The focus is in mental health and nephrology, really the two main business areas. Um, my role at guys to do the internal research and data analytics within the health economics and outcomes research group. Um, currently we are transitioned to a, uh, name, which is global value and real world evidence. Um, fact that transition is already happened. Um, so we're going to have more of a global presence going forward. Um, but my role is really to, uh, do the internal research across all the brands within the company. >>So, so Rena, I wonder this, thank you for that, Robert. I wonder if you could think, thinking about what you know about Scott and your relationship with Robin, your knowledge of, of the industry. Uh, there's so much that IBM can bring to the table. Rob was talking about data earlier, talking about EMR, you were talking about, you know, red hat and cloud and this big portfolio you have. So I wonder if you could sort of start a conversation for our audience just around how you guys see all those assets that you have and all the knowledge, all that data. How do you see the partnership evolving in the future to affect, uh, the industry and the, in the future of healthcare? >>Well, I would love to see, um, the entire, uh, uh, platform, um, shift to, to the IBM cloud, um, and certainly, you know, leverage the cloud pack and analytics that, that we have to offer, um, baby steps most definitely. Um, but I do think that there is, uh, the opportunity to really move, um, and transform the business into something a lot more than, than what it is. >>Rob has the pandemic effected sort of how you think about, um, you know, remote services and cloud services and the, like, were you already on the path headed there? Did accelerate things, have you, you know, have you not had time because things have been so busy or maybe you could comment? >>Yeah, I think it's really a combination. And so I think you hit on a, a fair point there, just the time, uh, aspect. Um, it's definitely been a challenge and your, um, I have two children and remote learning has definitely been a challenge from that perspective. So time has definitely been, uh, on the short side. Um, I do see that there are going to in the future be more and more users of the data. So I think that shift to a potential cloud environment is where things are headed. >>So we, I have a bunch more questions, but I want to step back for a second and see if there's anything that you'd like to ask Rob before I go onto my next section. Okay. So I wonder if you could think about, um, maybe both of you, the, the, when you think back on, on 2020 and all the, you know, what's transpired, what, what transitions did you guys have to make? Uh, maybe as a team together IBM and Alaska. Um, and, and, and what do you see as sort of permanent or semi-permanent is work from home? We're gonna going to continue at a higher rate, uh, are there new practice? I mean, I know just today I made an online appointment it's for a remote visit with my doctor, which never could have happened before the pandemic. Right. But are there things specific to your business and your relationship that you see as a transition that could be permanent or semi-permanent? >>Well, I, I think it's there, there's definitely a shift that's happened that will is here to stay, but I don't know if it's full, it's going to be a combination in the future. I think that in-person interactions, especially what Rena mentioned about having that face-to-face interaction is still going to be one things are in the right place and safe they're going to happen again. But I think the ability to show that work can happen in a virtual or a full remote workplace, that's going to just allow that to continue and really give the flex of people. The flexibility I know for myself, flexibility is key. Like I mentioned, with two small children, um, that, that, that becomes such a valuable addition to your work, your life and your work life in general, that I think that's here to stay. >>Okay. Um, so let me ask you this, uh, w one of the themes of this event is relentless re-invention. So what I'm hearing from you Rob, is that it kind of a hybrid model going forward, if you will, uh, maybe the option to work from home, but that face to face interaction, especially when you're creating things like you are in the pharmaceutical business and the deep R and D that collaborative aspect, you know, you, it's harder when you're, when, when, when you're remote. Um, but maybe you could talk about, you know, some of those key areas that you're, you're going to be focused on in 2021 and, and really where you would look for IBM to help. >>I think in 2021, the team I'm part of it, part of is, is growing. So I think there's going to be additional demand for internal research, uh, uh, capabilities for analysis done within the company. So I think I'm going to be looking to Rena to, uh, see what new data offerings are available and all what new products are going to be available. But beyond that, um, I think it's the potential that, you know, there's so much, uh, projects, um, that are going to be coming to the table. We may need to outsource some of that projects and IBM could be potentially be a partner there to do some of the analysis on to help out there. >>Anything you'd add. >>Uh, no, I think that, that sounds good. >>How would you grade IBM and your relationship with IBM Rob? >>Well, I have to be nice to Rina cause she's been very nice to me. I would say an a, an a plus >>My kids, I got kids in college. Several, they get A's, I'm happy. Oh, that's good. You know, you should be proud. So, congratulations. Um, anything else Reno, you give you, I'll give you a last word here before we wrap, >>You know, 2020 was, was a challenging. And, you know, we talked a little bit about, you know, what time in 2020, you know, Rob and I have always had a really good relationship. I think 2020, we got closer, um, with just both professionally and really diving in to key business challenges that they have, and really working with him to understand what the customer needs are and how we can help, not only from, you know, an HR perspective, but also how can we help Otsuka, um, as a company in, in totality. So, you know, we've been able to do that, but personally, I would say that I really appreciated the relationship. I mean, we can go from talking about work to talking about children, to talking about family, um, all in the same five minute conversation or 10 minute conversation, sometimes our conversation. So, you know, thank you, Rob 2020 was definitely super challenging. >>I know for you on so many levels. Um, but I have to say you've been really great at just showing up every time picked up the phone, asked questions. If I needed something I can call you, I knew you were going to pick up, I had an offering and be like, do you have 10 minutes? Can I share this with you? And you would pick up the phone, no problem, and entertain a call or set up a call with all your internal colleagues. And I, I appreciate that so much. And, you know, I appreciate our relationship. I appreciate the business and I, I do hope that we can continue on in 2021, we will continue on in 2021. Uh, but, um, but yeah, I thank you so much. >>Rain has been extremely helpful. I don't want to thank you for all the help. Um, just to add to that one point there, you know, we have, uh, also another product, which I forgot to mention that we licensed in from IBM, it's the treatment pathways, um, tool, which is an online tool. Um, and we have users throughout the globe. So there's been times where I've needed a new user added very quickly for someone in the home office in Japan. And Rena has been extremely helpful in getting things done quickly and very proactively. >>Well, guys, it's really clear that the depth of your relationship I'm interested that you actually got closer in 2020. Uh, the fact that you communicate, you know, several times a day is I think Testament to that relationship. Uh, I'm really pleased to hear what you're doing and the potential with the EMR data for patient outcomes. Uh, as I say in the early days, I used to hear all about how well you have to do that to get paid. And it's really great to see a partnership that's, that's really focused on, on, on patient health and, and changing our lives. So, and mental health is such an important area that for so many years was so misunderstood and the, and the data that we now have, and of course, IBM's heritage and data is key. Uh, the relationship and the follow-up and also the flexibility is, is something I think we all learned in 2020, we have to, we've kind of redefined, you know, resilience in our organizations and, uh, glad to see you guys are growing. Congratulations on the relationship. And thanks so much for spending some time with me. >>Thank you. Thank you, Dave. Thank you, Raina >>For watching this client conversation with IBM Watson health.

>>Welcome to this exclusive discussion. IBM, the next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond. My name is Dave Volante from the Cuban today, we're going to take a deep dive into some of the most important trends impacting the life sciences industry in the next 60 minutes. Yeah, of course. We're going to hear how IBM is utilizing Watson and some really important in life impacting ways, but we'll also bring in real world perspectives from industry and the independent analyst view to better understand how technology and data are changing the nature of precision medicine. Now, the pandemic has created a new reality for everyone, but especially for life sciences companies, one where digital transformation is no longer an option, but a necessity. Now the upside is the events of the past 22 months have presented an accelerated opportunity for innovation technology and real world data are coming together and being applied to support life science, industry trends and improve drug discovery, clinical development, and treatment commercialization throughout the product life cycle cycle. Now I'd like to introduce our esteemed panel. Let me first introduce Lorraine Marshawn, who is general manager of life sciences at IBM Watson health. Lorraine leads the organization dedicated to improving clinical development research, showing greater treatment value in getting treatments to patients faster with differentiated solutions. Welcome Lorraine. Great to see you. >>Dr. Namita LeMay is the research vice-president of IDC, where she leads the life sciences R and D strategy and technology program, which provides research based advisory and consulting services as well as market analysis. The loan to meta thanks for joining us today. And our third panelist is Greg Cunningham. Who's the director of the RWE center of excellence at Eli Lilly and company. Welcome, Greg, you guys are doing some great work. Thanks for being here. Thanks >>Dave. >>Now today's panelists are very passionate about their work. If you'd like to ask them a question, please add it to the chat box located near the bottom of your screen, and we'll do our best to answer them all at the end of the panel. Let's get started. Okay, Greg, and then Lorraine and meta feel free to chime in after one of the game-changers that you're seeing, which are advancing precision medicine. And how do you see this evolving in 2022 and into the next decade? >>I'll give my answer from a life science research perspective. The game changer I see in advancing precision medicine is moving from doing research using kind of a single gene mutation or kind of a single to look at to doing this research using combinations of genes and the potential that this brings is to bring better drug targets forward, but also get the best product to a patient faster. Um, I can give, uh, an example how I see it playing out in the last decade. Non-oncology real-world evidence. We've seen an evolution in precision medicine as we've built out the patient record. Um, as we've done that, uh, the marketplace has evolved rapidly, uh, with, particularly for electronic medical record data and genomic data. And we were pretty happy to get our hands on electronic medical record data in the early days. And then later the genetic test results were combined with this data and we could do research looking at a single mutation leading to better patient outcomes. But I think where we're going to evolve in 2022 and beyond is with genetic testing, growing and oncology, providing us more data about that patient. More genes to look at, uh, researchers can look at groups of genes to analyze, to look at that complex combination of gene mutations. And I think it'll open the door for things like using artificial intelligence to help researchers plow through the complex number of permutations. When you think about all those genes you can look at in combination, right? Lorraine yes. Data and machine intelligence coming together, anything you would add. >>Yeah. Thank you very much. Well, I think that Greg's response really sets us up nicely, particularly when we think about the ability to utilize real-world data in the farm industry across a number of use cases from discovery to development to commercial, and, you know, in particular, I think with real world data and the comments that Greg just made about clinical EMR data linked with genetic or genomic data, a real area of interest in one that, uh, Watson health in particular is focused on the idea of being able to create a data exchange so that we can bring together claims clinical EMR data, genomics data, increasingly wearables and data directly from patients in order to create a digital health record that we like to call an intelligent patient health record that basically gives us the digital equivalent of a real life patient. And these can be used in use cases in randomized controlled clinical trials for synthetic control arms or natural history. They can be used in order to track patients' response to drugs and look at outcomes after they've been on various therapies as, as Greg is speaking to. And so I think that, you know, the promise of data and technology, the AI that we can apply on that is really helping us advance, getting therapies to market faster, with better information, lower sample sizes, and just a much more efficient way to do drug development and to track and monitor outcomes in patients. >>Great. Thank you for that now to meta, when I joined IDC many, many years ago, I really didn't know much about the industry that I was covering, but it's great to see you as a former practitioner now bringing in your views. What do you see as the big game-changers? >>So, um, I would, I would agree with what both Lorraine and Greg said. Um, but one thing that I'd just like to call out is that, you know, everyone's talking about big data, the volume of data is growing. It's growing exponentially actually about, I think 30% of data that exists today is healthcare data. And it's growing at a rate of 36%. That's huge, but then it's not just about the big, it's also about the broad, I think, um, you know, I think great points that, uh, Lorraine and Greg brought out that it's, it's not just specifically genomic data, it's multi omic data. And it's also about things like medical history, social determinants of health, behavioral data. Um, and why, because when you're talking about precision medicine and we know that we moved away from the, the terminology of personalized to position, because you want to talk about disease stratification and you can, it's really about convergence. >>Um, if you look at a recent JAMA paper in 2021, only 1% of EHS actually included genomic data. So you really need to have that ability to look at data holistically and IDC prediction is seeing that investments in AI to fuel in silico, silicone drug discovery will double by 20, 24, but how are you actually going to integrate all the different types of data? Just look at, for example, diabetes, you're on type two diabetes, 40 to 70% of it is genetically inherited and you have over 500 different, uh, genetic low side, which could be involved in playing into causing diabetes. So the earlier strategy, when you are looking at, you know, genetic risk scoring was really single trait. Now it's transitioning to multi rate. And when you say multi trade, you really need to get that integrated view that converging for you to, to be able to drive a precision medicine strategy. So to me, it's a very interesting contrast on one side, you're really trying to make it specific and focused towards an individual. And on the other side, you really have to go wider and bigger as well. >>Uh, great. I mean, the technology is enabling that convergence and the conditions are almost mandating it. Let's talk about some more about data that the data exchange and building an intelligent health record, as it relates to precision medicine, how will the interoperability of real-world data, you know, create that more cohesive picture for the, for the patient maybe Greg, you want to start, or anybody else wants to chime in? >>I think, um, the, the exciting thing from, from my perspective is the potential to gain access to data. You may be weren't aware of an exchange in implies that, uh, some kind of cataloging, so I can see, uh, maybe things that might, I just had no idea and, uh, bringing my own data and maybe linking data. These are concepts that I think are starting to take off in our field, but it, it really opens up those avenues to when you, you were talking about data, the robustness and richness volume isn't, uh, the only thing is Namita said, I think really getting to a rich high-quality data and, and an exchange offers a far bigger, uh, range for all of us to, to use, to get our work done. >>Yeah. And I think, um, just to chime, chime into that, uh, response from Greg, you know, what we hear increasingly, and it's pretty pervasive across the industry right now, because this ability to create an exchange or the intelligent, uh, patient health record, these are new ideas, you know, they're still rather nascent and it always is the operating model. Uh, that, that is the, uh, the difficult challenge here. And certainly that is the case. So we do have data in various silos. Uh, they're in patient claims, they're in electronic medical records, they might be in labs, images, genetic files on your smartphone. And so one of the challenges with this interoperability is being able to tap into these various sources of data, trying to identify quality data, as Greg has said, and the meta is underscoring as well. Uh, we've gotta be able to get to the depth of data that's really meaningful to us, but then we have to have technology that allows us to pull this data together. >>First of all, it has to be de-identified because of security and patient related needs. And then we've gotta be able to link it so that you can create that likeness in terms of the record, it has to be what we call cleaned or curated so that you get the noise and all the missing this out of it, that's a big step. And then it needs to be enriched, which means that the various components that are going to be meaningful, you know, again, are brought together so that you can create that cohort of patients, that individual patient record that now is useful in so many instances across farm, again, from development, all the way through commercial. So the idea of this exchange is to enable that exact process that I just described to have a, a place, a platform where various entities can bring their data in order to have it linked and integrated and cleaned and enriched so that they get something that is a package like a data package that they can actually use. >>And it's easy to plug into their, into their studies or into their use cases. And I think a really important component of this is that it's gotta be a place where various third parties can feel comfortable bringing their data together in order to match it with other third parties. That is a, a real value, uh, that the industry is increasingly saying would be important to them is, is the ability to bring in those third-party data sets and be able to link them and create these, these various data products. So that's really the idea of the data exchange is that you can benefit from accessing data, as Greg mentioned in catalogs that maybe are across these various silos so that you can do the kind of work that you need. And that we take a lot of the hard work out of it. I like to give an example. >>We spoke with one of our clients at one of the large pharma companies. And, uh, I think he expressed it very well. He said, what I'd like to do is have like a complete dataset of lupus. Lupus is an autoimmune condition. And I've just like to have like the quintessential lupus dataset that I can use to run any number of use cases across it. You know, whether it's looking at my phase one trial, whether it's selecting patients and enriching for later stage trials, whether it's understanding patient responses to different therapies as I designed my studies. And so, you know, this idea of adding in therapeutic area indication, specific data sets and being able to create that for the industry in the meta mentioned, being able to do that, for example, in diabetes, that's how pharma clients need to have their needs met is through taking the hard workout, bringing the data together, having it very therapeutically enriched so that they can use it very easily. >>Thank you for that detail and the meta. I mean, you can't do this with humans at scale in technology of all the things that Lorraine was talking about, the enrichment, the provenance, the quality, and of course, it's got to be governed. You've got to protect the privacy privacy humans just can't do all that at massive scale. Can it really tech that's where technology comes in? Doesn't it and automation. >>Absolutely. >>I, couldn't more, I think the biggest, you know, whether you talk about precision medicine or you talk about decentralized trials, I think there's been a lot of hype around these terms, but what is really important to remember is technology is the game changer and bringing all that data together is really going to be the key enabler. So multimodal data integration, looking at things like security or federated learning, or also when you're talking about leveraging AI, you're not talking about things like bias or other aspects around that are, are critical components that need to be addressed. I think the industry is, uh, it's partly, still trying to figure out the right use cases. So it's one part is getting together the data, but also getting together the right data. Um, I think data interoperability is going to be the absolute game changer for enabling this. Uh, but yes, um, absolutely. I can, I can really couldn't agree more with what Lorraine just said, that it's bringing all those different aspects of data together to really drive that precision medicine strategy. >>Excellent. Hey Greg, let's talk about protocols decentralized clinical trials. You know, they're not new to life silences, but, but the adoption of DCTs is of course sped up due to the pandemic we've had to make trade-offs obviously, and the risk is clearly worth it, but you're going to continue to be a primary approach as we enter 2022. What are the opportunities that you see to improve? How DCTs are designed and executed? >>I see a couple opportunities to improve in this area. The first is, uh, back to technology. The infrastructure around clinical trials has, has evolved over the years. Uh, but now you're talking about moving away from kind of site focus to the patient focus. Uh, so with that, you have to build out a new set of tools that would help. So for example, one would be novel trial, recruitment, and screening, you know, how do you, how do you find patients and how do you screen them to see if are they, are they really a fit for, for this protocol? Another example, uh, very important documents that we have to get is, uh, you know, the e-consent that someone's says, yes, I'm, well, I understand this study and I'm willing to do it, have to do that in a more remote way than, than we've done in the past. >>Um, the exciting area, I think, is the use of, uh, eco, uh, E-Pro where we capture data from the patient using apps, devices, sensors. And I think all of these capabilities will bring a new way of, of getting data faster, uh, in, in this kind of model. But the exciting thing from, uh, our perspective at Lily is it's going to bring more data about the patient from the patient, not just from the healthcare provider side, it's going to bring real data from these apps, devices and sensors. The second thing I think is using real-world data to identify patients, to also improve protocols. We run scenarios today, looking at what's the impact. If you change a cut point on a, a lab or a biomarker to see how that would affect, uh, potential enrollment of patients. So it, it definitely the real-world data can be used to, to make decisions, you know, how you improve these protocols. >>But the thing that we've been at the challenge we've been after that this probably offers the biggest is using real-world data to identify patients as we move away from large academic centers that we've used for years as our sites. Um, you can maybe get more patients who are from the rural areas of our countries or not near these large, uh, uh, academic centers. And we think it'll bring a little more diversity to the population, uh, who who's, uh, eligible, but also we have their data, so we can see if they really fit the criteria and the probability they are a fit for the trial is much higher than >>Right. Lorraine. I mean, your clients must be really pushing you to help them improve DCTs what are you seeing in the field? >>Yes, in fact, we just attended the inaugural meeting of the de-central trials research Alliance in, uh, in Boston about two weeks ago where, uh, all of the industry came together, pharma companies, uh, consulting vendors, just everyone who's been in this industry working to help define de-central trials and, um, think through what its potential is. Think through various models in order to enable it, because again, a nascent concept that I think COVID has spurred into action. Um, but it is important to take a look at the definition of DCT. I think there are those entities that describe it as accessing data directly from the patient. I think that is a component of it, but I think it's much broader than that. To me, it's about really looking at workflows and processes of bringing data in from various remote locations and enabling the whole ecosystem to work much more effectively along the data continuum. >>So a DCT is all around being able to make a site more effective, whether it's being able to administer a tele visit or the way that they're getting data into the electronic data captures. So I think we have to take a look at the, the workflows and the operating models for enabling de-central trials and a lot of what we're doing with our own technology. Greg mentioned the idea of electronic consent of being able to do electronic patient reported outcomes, other collection of data directly from the patient wearables tele-health. So these are all data acquisition, methodologies, and technologies that, that we are enabling in order to get the best of the data into the electronic data capture system. So edit can be put together and processed and submitted to the FDA for regulatory use for clinical trial type submission. So we're working on that. I think the other thing that's happening is the ability to be much more flexible and be able to have more cloud-based storage allows you to be much more inter-operable to allow API APIs in order to bring in the various types of data. >>So we're really looking at technology that can make us much more fluid and flexible and accommodating to all the ways that people live and work and manage their health, because we have to reflect that in the way we collect those data types. So that's a lot of what we're, what we're focused on. And in talking with our clients, we spend also a lot of time trying to understand along the, let's say de-central clinical trials continuum, you know, w where are they? And I know Namita is going to talk a little bit about research that they've done in terms of that adoption curve, but because COVID sort of forced us into being able to collect data in more remote fashion in order to allow some of these clinical trials to continue during COVID when a lot of them had to stop. What we want to make sure is that we understand and can codify some of those best practices and that we can help our clients enable that because the worst thing that would happen would be to have made some of that progress in that direction. >>But then when COVID is over to go back to the old ways of doing things and not bring some of those best practices forward, and we actually hear from some of our clients in the pharma industry, that they worry about that as well, because we don't yet have a system for operationalizing a de-central trial. And so we really have to think about the protocol it's designed, the indication, the types of patients, what makes sense to decentralize, what makes sense to still continue to collect data in a more traditional fashion. So we're spending a lot of time advising and consulting with our patients, as well as, I mean, with our clients, as well as CRS, um, on what the best model is in terms of their, their portfolio of studies. And I think that's a really important aspect of trying to accelerate the adoption is making sure that what we're doing is fit for purpose, just because you can use technology doesn't mean you should, it really still does require human beings to think about the problem and solve them in a very practical way. >>Great, thank you for that. Lorraine. I want to pick up on some things that Lorraine was just saying. And then back to what Greg was saying about, uh, uh, DCTs becoming more patient centric, you had a prediction or IDC, did I presume your fingerprints were on it? Uh, that by 20 25, 70 5% of trials will be patient-centric decentralized clinical trials, 90% will be hybrid. So maybe you could help us understand that relationship and what types of innovations are going to be needed to support that evolution of DCT. >>Thanks, Dave. Yeah. Um, you know, sorry, I, I certainly believe that, uh, you know, uh, Lorraine was pointing out of bringing up a very important point. It's about being able to continue what you have learned in over the past two years, I feel this, you know, it was not really a digital revolution. It was an attitude. The revolution that this industry underwent, um, technology existed just as clinical trials exist as drugs exist, but there was a proof of concept that technology works that this model is working. So I think that what, for example, telehealth, um, did for, for healthcare, you know, transition from, from care, anywhere care, anytime, anywhere, and even becoming predictive. That's what the decentralized clinical trials model is doing for clinical trials today. Great points again, that you have to really look at where it's being applied. You just can't randomly apply it across clinical trials. >>And this is where the industry is maturing the complexity. Um, you know, some people think decentralized trials are very simple. You just go and implement these centralized clinical trials, but it's not that simple as it it's being able to define, which are the right technologies for that specific, um, therapeutic area for that specific phase of the study. It's being also a very important point is bringing in the patient's voice into the process. Hey, I had my first telehealth visit sometime last year and I was absolutely thrilled about it. I said, no time wasted. I mean, everything's done in half an hour, but not all patients want that. Some want to consider going back and you, again, need to customize your de-centralized trials model to, to the, to the type of patient population, the demographics that you're dealing with. So there are multiple factors. Um, also stepping back, you know, Lorraine mentioned they're consulting with, uh, with their clients, advising them. >>And I think a lot of, um, a lot of companies are still evolving in their maturity in DCTs though. There's a lot of boys about it. Not everyone is very mature in it. So it's, I think it, one thing everyone's kind of agreeing with is yes, we want to do it, but it's really about how do we go about it? How do we make this a flexible and scalable modern model? How do we integrate the patient's voice into the process? What are the KPIs that we define the key performance indicators that we define? Do we have a playbook to implement this model to make it a scalable model? And, you know, finally, I think what organizations really need to look at is kind of developing a de-centralized mature maturity scoring model, so that I assess where I am today and use that playbook to define, how am I going to move down the line to me reach the next level of maturity. Those were some of my thoughts. Right? >>Excellent. And now remember you, if you have any questions, use the chat box below to submit those questions. We have some questions coming in from the audience. >>At one point to that, I think one common thread between the earlier discussion around precision medicine and around decentralized trials really is data interoperability. It is going to be a big game changer to, to enable both of these pieces. Sorry. Thanks, Dave. >>Yeah. Thank you. Yeah. So again, put your questions in the chat box. I'm actually going to go to one of the questions from the audience. I get some other questions as well, but when you think about all the new data types that are coming in from social media, omics wearables. So the question is with greater access to these new types of data, what trends are you seeing from pharma device as far as developing capabilities to effectively manage and analyze these novel data types? Is there anything that you guys are seeing, um, that you can share in terms of best practice or advice >>I'll offer up? One thing, I think the interoperability isn't quite there today. So, so what's that mean you can take some of those data sources. You mentioned, uh, some Omix data with, uh, some health claims data and it's the, we spend too much time and in our space putting data to gather the behind the scenes, I think the stat is 80% of the time is assembling the data 20% analyzing. And we've had conversations here at Lilly about how do we get to 80% of the time is doing analysis. And it really requires us to think, take a step back and think about when you create a, uh, a health record, you really have to be, have the same plugins so that, you know, data can be put together very easily, like Lorraine mentioned earlier. And that comes back to investing in as an industry and standards so that, you know, you have some of data standard, we all can agree upon. And then those plugs get a lot easier and we can spend our time figuring out how to make, uh, people's lives better with healthcare analysis versus putting data together, which is not a lot of fun behind the scenes. >>Other thoughts on, um, on, on how to take advantage of sort of novel data coming from things like devices in the nose that you guys are seeing. >>I could jump in there on your end. Did you want to go ahead? Okay. So, uh, I mean, I think there's huge value that's being seen, uh, in leveraging those multiple data types. I think one area you're seeing is the growth of prescription digital therapeutics and, um, using those to support, uh, you know, things like behavioral health issues and a lot of other critical conditions it's really taking you again, it is interlinking real-world data cause it's really taking you to the patient's home. Um, and it's, it's, there's a lot of patients in the city out here cause you can really monitor the patient real-time um, without the patient having coming, you know, coming and doing a site visit once in say four weeks or six weeks. So, um, I, and, uh, for example, uh, suicidal behavior and just to take an example, if you can predict well in advance, based on those behavioral parameters, that this is likely to trigger that, uh, the value of it is enormous. Um, again, I think, uh, Greg made a valid point about the industry still trying to deal with resolving the data interoperability issue. And there are so many players that are coming in the industry right now. There are really few that have the maturity and the capability to address these challenges and provide intelligence solutions. >>Yeah. Maybe I'll just, uh, go ahead and, uh, and chime into Nikita's last comment there. I think that's what we're seeing as well. And it's very common, you know, from an innovation standpoint that you have, uh, a nascent industry or a nascent innovation sort of situation that we have right now where it's very fragmented. You have a lot of small players, you have some larger entrenched players that have the capability, um, to help to solve the interoperability challenge, the standards challenge. I mean, I think IBM Watson health is certainly one of the entities that has that ability and is taking a stand in the industry, uh, in order to, to help lead in that way. Others are too. And, uh, but with, with all of the small companies that are trying to find interesting and creative ways to gather that data, it does create a very fragmented, uh, type of environment and ecosystem that we're in. >>And I think as we mature, as we do come forward with the KPIs, the operating models, um, because you know, the devil's in the detail in terms of the operating models, it's really exciting to talk these trends and think about the future state. But as Greg pointed out, if you're spending 80% of your time just under the hood, you know, trying to get the engine, all the spark plugs to line up, um, that's, that's just hard grunt work that has to be done. So I think that's where we need to be focused. And I think bringing all the data in from these disparate tools, you know, that's fine, we need, uh, a platform or the API APIs that can enable that. But I think as we, as we progress, we'll see more consolidation, uh, more standards coming into play, solving the interoperability types of challenges. >>And, um, so I think that's where we should, we should focus on what it's going to take and in three years to really codify this and make it, so it's a, it's a well hum humming machine. And, you know, I do know having also been in pharma that, uh, there's a very pilot oriented approach to this thing, which I think is really healthy. I think large pharma companies tend to place a lot of bets with different programs on different tools and technologies, to some extent to see what's gonna stick and, you know, kind of with an innovation mindset. And I think that's good. I think that's kind of part of the process of figuring out what is going to work and, and helping us when we get to that point of consolidating our model and the technologies going forward. So I think all of the efforts today are definitely driving us to something that feels much more codified in the next three to five years. >>Excellent. We have another question from the audience it's sort of related to the theme of this discussion, given the FDA's recent guidance on using claims and electronic health records, data to support regulatory decision-making what advancements do you think we can expect with regards to regulatory use of real-world data in the coming years? It's kind of a two-parter so maybe you guys can collaborate on this one. What role that, and then what role do you think industry plays in influencing innovation within the regulatory space? >>All right. Well, it looks like you've stumped the panel there. Uh, Dave, >>It's okay to take some time to think about it, right? You want me to repeat it? You guys, >>I, you know, I I'm sure that the group is going to chime into this. I, so the FDA has issued a guidance. Um, it's just, it's, it's exactly that the FDA issues guidances and says that, you know, it's aware and supportive of the fact that we need to be using real-world data. We need to create the interoperability, the standards, the ways to make sure that we can include it in regulatory submissions and the like, um, and, and I sort of think about it akin to the critical path initiative, probably, I don't know, 10 or 12 years ago in pharma, uh, when the FDA also embrace this idea of the critical path and being able to allow more in silico modeling of clinical trial, design and development. And it really took the industry a good 10 years, um, you know, before they were able to actually adopt and apply and take that sort of guidance or openness from the FDA and actually apply it in a way that started to influence the way clinical trials were designed or the in silico modeling. >>So I think the second part of the question is really important because while I think the FDA is saying, yes, we recognize it's important. Uh, we want to be able to encourage and support it. You know, when you look for example, at synthetic control arms, right? The use of real-world data in regulatory submissions over the last five or six years, all of the use cases have been in oncology. I think there've been about maybe somewhere between eight to 10 submissions. And I think only one actually was a successful submission, uh, in all those situations, the real-world data arm of that oncology trial that synthetic control arm was actually rejected by the FDA because of lack of completeness or, you know, equalness in terms of the data. So the FDA is not going to tell us how to do this. So I think the second part of the question, which is what's the role of industry, it's absolutely on industry in order to figure out exactly what we're talking about, how do we figure out the interoperability, how do we apply the standards? >>How do we ensure good quality data? How do we enrich it and create the cohort that is going to be equivalent to the patient in the real world, uh, in the end that would otherwise be in the clinical trial and how do we create something that the FDA can agree with? And we'll certainly we'll want to work with the FDA in order to figure out this model. And I think companies are already doing that, but I think that the onus is going to be on industry in order to figure out how you actually operationalize this and make it real. >>Excellent. Thank you. Um, question on what's the most common misconception that clinical research stakeholders with sites or participants, et cetera might have about DCTs? >>Um, I could jump in there. Right. So, sure. So, um, I think in terms of misconceptions, um, I think the communist misconceptions that sites are going away forever, which I do not think is really happening today. Then the second, second part of it is that, um, I think also the perspective that patients are potentially neglected because they're moving away. So we'll pay when I, when I, what I mean by that neglected, perhaps it was not the appropriate term, but the fact that, uh, will patients will, will, will patient engagement continue, will retention be strong since the patients are not interacting in person with the investigator quite as much. Um, so site retention and patient retention or engagement from both perspectives, I think remains a concern. Um, but actually if you look at, uh, look at, uh, assessments that have been done, I think patients are more than happy. >>Majority of the patients have been really happy about, about the new model. And in fact, sites are, seem to increase, have increased investments in technology by 50% to support this kind of a model. So, and the last thing is that, you know, decentralized trials is a great model and it can be applied to every possible clinical trial. And in another couple of weeks, the whole industry will be implementing only decentralized trials. I think we are far away from that. It's just not something that you would implement across every trial. And we discussed that already. So you have to find the right use cases for that. So I think those were some of the key misconceptions I'd say in the industry right now. Yeah. >>Yeah. And I would add that the misconception I hear the most about is, uh, the, the similar to what Namita said about the sites and healthcare professionals, not being involved to the level that they are today. Uh, when I mentioned earlier in our conversation about being excited about capturing more data, uh, from the patient that was always in context of, in addition to, you know, healthcare professional opinion, because I think both of them bring that enrichment and a broader perspective of that patient experience, whatever disease they're faced with. So I, I think some people think is just an all internet trial with just someone, uh, putting out there their own perspective. And, and it's, it's a combination of both to, to deliver a robust data set. >>Yeah. Maybe I'll just comment on, it reminds me of probably 10 or 15 years ago, maybe even more when, um, really remote monitoring was enabled, right? So you didn't have to have the study coordinator traveled to the investigative site in order to check the temperature of the freezer and make sure that patient records were being completed appropriately because they could have a remote visit and they could, they could send the data in a via electronic data and do the monitoring visit, you know, in real time, just the way we're having this kind of communication here. And there was just so much fear that you were going to replace or supplant the personal relationship between the sites between the study coordinators that you were going to, you know, have to supplant the role of the monitor, which was always a very important role in clinical trials. >>And I think people that really want to do embrace the technology and the advantages that it provided quickly saw that what it allowed was the monitor to do higher value work, you know, instead of going in and checking the temperature on a freezer, when they did have their visit, they were able to sit and have a quality discussion for example, about how patient recruitment was going or what was coming up in terms of the consent. And so it created a much more high touch, high quality type of interaction between the monitor and the investigative site. And I think we should be looking for the same advantages from DCT. We shouldn't fear it. We shouldn't think that it's going to supplant the site or the investigator or the relationship. It's our job to figure out where the technology fits and clinical sciences always got to be high touch combined with high-tech, but the high touch has to lead. And so getting that balance right? And so that's going to happen here as well. We will figure out other high value work, meaningful work for the site staff to do while they let the technology take care of the lower quality work, if you will, or the lower value work, >>That's not an, or it's an, and, and you're talking about the higher value work. And it, it leads me to something that Greg said earlier about the 80, 20, 80% is assembly. 20% is actually doing the analysis and that's not unique to, to, to life sciences, but, but sort of question is it's an organizational question in terms of how we think about data and how we approach data in the future. So Bamyan historically big data in life sciences in any industry really is required highly centralized and specialized teams to do things that the rain was talking about, the enrichment, the provenance, the data quality, the governance, the PR highly hyper specialized teams to do that. And they serve different constituencies. You know, not necessarily with that, with, with context, they're just kind of data people. Um, so they have responsibility for doing all those things. Greg, for instance, within literally, are you seeing a move to, to, to democratize data access? We've talked about data interoperability, part of that state of sharing, um, that kind of breaks that centralized hold, or is that just too far in the future? It's too risky in this industry? >>Uh, it's actually happening now. Uh, it's a great point. We, we try to classify what people can do. And, uh, the example would be you give someone who's less analytically qualified, uh, give them a dashboard, let them interact with the data, let them better understand, uh, what, what we're seeing out in the real world. Uh, there's a middle user, someone who you could give them, they can do some analysis with the tool. And the nice thing with that is you have some guardrails around that and you keep them in their lane, but it allows them to do some of their work without having to go ask those centralized experts that, that you mentioned their precious resources. And that's the third group is those, uh, highly analytical folks that can, can really deliver, uh, just value beyond. But when they're doing all those other things, uh, it really hinders them from doing what we've been talking about is the high value stuff. So we've, we've kind of split into those. We look at people using data in one of those three lanes and it, and it has helped I think, uh, us better not try to make a one fit solution for, for how we deliver data and analytic tools for people. Right. >>Okay. I mean, DCT hot topic with the, the, the audience here. Another question, um, what capabilities do sponsors and CRS need to develop in-house to pivot toward DCT? >>Should I jump in here? Yeah, I mean, um, I think, you know, when, when we speak about DCTs and when I speak with, uh, folks around in the industry, I, it takes me back to the days of risk-based monitoring. When it was first being implemented, it was a huge organizational change from the conventional monitoring models to centralize monitoring and risk-based monitoring, it needs a mental reset. It needs as Lorraine had pointed out a little while ago, restructuring workflows, re redefining processes. And I think that is one big piece. That is, I think the first piece, when, you know, when you're implementing a new model, I think organizational change management is a big piece of it because you are disturbing existing structures, existing methods. So getting that buy-in across the organization towards the new model, seeing what the value add in it. And where do you personally fit into that story? >>How do your workflows change, or how was your role impacted? I think without that this industry will struggle. So I see organizations, I think, first trying to work on that piece to build that in. And then of course, I also want to step back for the second to the, uh, to the point that you brought out about data democratization. And I think Greg Greg gave an excellent point, uh, input about how it's happening in the industry. But I would also say that the data democratization really empowerment of, of, of the stakeholders also includes the sites, the investigators. So what is the level of access to data that you know, that they have now, and is it, uh, as well as patients? So see increasingly more and more companies trying to provide access to patients finally, it's their data. So why shouldn't they have some insights to it, right. So access to patients and, uh, you know, the 80, 20 part of it. Uh, yes, he's absolutely right that, uh, we want to see that flip from, uh, 20%, um, you know, focusing on, on actually integrating the data 80% of analytics, but the real future will be coming in when actually the 20 and 18 has gone. And you actually have analysts the insights out on a silver platter. That's kind of wishful thinking, some of the industries is getting there in small pieces, but yeah, then that's just why I should, why we share >>Great points. >>And I think that we're, we're there in terms that like, I really appreciate the point around democratizing the data and giving the patient access ownership and control over their own data. I mean, you know, we see the health portals that are now available for patients to view their own records, images, and labs, and claims and EMR. We have blockchain technology, which is really critical here in terms of the patient, being able to pull all of their own data together, you know, in the blockchain and immutable record that they can own and control if they want to use that to transact clinical trial types of opportunities based on their data, they can, or other real world scenarios. But if they want to just manage their own data because they're traveling and if they're in a risky health situation, they've got their own record of their health, their health history, uh, which can avoid, you know, medical errors occurring. So, you know, even going beyond life sciences, I think this idea of democratizing data is just good for health. It's just good for people. And we definitely have the technology that can make it a reality. Now >>You're here. We have just about 10 minutes left and now of course, now all the questions are rolling in like crazy from the crowd. Would it be curious to know if there would be any comments from the panel on cost comparison analysis between traditional clinical trials in DCTs and how could the outcome effect the implementation of DCTs any sort of high-level framework you can share? >>I would say these are still early days to, to drive that analysis because I think many companies are, um, are still in the early stages of implementation. They've done a couple of trials. The other part of it that's important to keep in mind is, um, is for organizations it's, they're at a stage of, uh, of being on the learning curve. So when you're, you're calculating the cost efficiencies, if ideally you should have had two stakeholders involved, you could have potentially 20 stakeholders involved because everyone's trying to learn the process and see how it's going to be implemented. So, um, I don't think, and the third part of it, I think is organizations are still defining their KPIs. How do you measure it? What do you measure? So, um, and even still plugging in the pieces of technology that they need to fit in, who are they partnering with? >>What are the pieces of technology they're implementing? So I don't think there is a clear cut as answered at this stage. I think as you scale this model, the efficiencies will be seen. It's like any new technology or any new solution that's implemented in the first stages. It's always a little more complex and in fact sometimes costs extra. But as, as you start scaling it, as you establish your workflows, as you streamline it, the cost efficiencies will start becoming evident. That's why the industry is moving there. And I think that's how it turned out on the long run. >>Yeah. Just make it maybe out a comment. If you don't mind, the clinical trials are, have traditionally been costed are budgeted is on a per patient basis. And so, you know, based on the difficulty of the therapeutic area to recruit a rare oncology or neuromuscular disease, there's an average that it costs in order to find that patient and then execute the various procedures throughout the clinical trial on that patient. And so the difficulty of reaching the patient and then the complexity of the trial has led to what we might call a per patient stipend, which is just the metric that we use to sort of figure out what the average cost of a trial will be. So I think to point, we're going to have to see where the ability to adjust workflows, get to patients faster, collect data more easily in order to make the burden on the site, less onerous. I think once we start to see that work eases up because of technology, then I think we'll start to see those cost equations change. But I think right now the system isn't designed in order to really measure the economic benefit of de-central models. And I think we're going to have to sort of figure out what that looks like as we go along and since it's patient oriented right now, we'll have to say, well, you know, how does that work, ease up? And to those costs actually come down and then >>Just scale, it's going to be more, more clear as the media was saying, next question from the audiences, it's kind of a best fit question. You all have touched on this, but let me just ask it is what examples in which, in which phases suit DCT in its current form, be it fully DCT or hybrid models, none of our horses for courses question. >>Well, I think it's kind of, uh, it's, it's it's has its efficiencies, obviously on the later phases, then the absolute early phase trials, those are not the ideal models for DCTs I would say so. And again, the logic is also the fact that, you know, when you're, you're going into the later phase trials, the volume of number of patients is increasing considerably to the point that Lorraine brought up about access to the patients about patient selection. The fact, I think what one should look at is really the advantages that it brings in, in terms of, you know, patient access in terms of patient diversity, which is a big piece that, um, the cities are enabling. So, um, if you, if, if you, if you look at the spectrum of, of these advantages and, and just to step back for a moment, if you, if you're looking at costs, like you're looking at things like remote site monitoring, um, is, is a big, big plus, right? >>I mean, uh, site monitoring alone accounts for around a third of the trial costs. So there are so many pieces that fall in together. The challenge actually that comes when you're in defining DCTs and there are, as Rick pointed out multiple definitions of DCTs that are existing, uh, you know, in the industry right now, whether you're talking of what Detroit is doing, or you're talking about acro or Citi or others. But the point is it's a continuum, it's a continuum of different pieces that have been woven together. And so how do you decide which pieces you're plugging in and how does that impact the total cost or the solution that you're implementing? >>Great, thank you. Last question we have in the audience, excuse me. What changes have you seen? Are there others that you can share from the FDA EU APAC, regulators and supporting DCTs precision medicine for approval processes, anything you guys would highlight that we should be aware of? >>Um, I could quickly just add that. I think, um, I'm just publishing a report on de-centralized clinical trials should be published shortly, uh, perspective on that. But I would say that right now, um, there, there was a, in the FDA agenda, there was a plan for a decentralized clinical trials guidance, as far as I'm aware, one has not yet been published. There have been significant guidances that have been published both by email and by, uh, the FDA that, um, you know, around the implementation of clinical trials during the COVID pandemic, which incorporate various technology pieces, which support the DCD model. Um, but I, and again, I think one of the reasons why it's not easy to publish a well-defined guidance on that is because there are so many moving pieces in it. I think it's the Danish, uh, regulatory agency, which has per se published a guidance and revised it as well on decentralized clinical trials. >>Right. Okay. Uh, we're pretty much out of time, but I, I wonder Lorraine, if you could give us some, some final thoughts and bring us home things that we should be watching or how you see the future. >>Well, I think first of all, let me, let me thank the panel. Uh, we really appreciate Greg from Lily and the meta from IDC bringing their perspectives to this conversation. And, uh, I hope that the audience has enjoyed the, uh, the discussion that we've had around the future state of real world data as, as well as DCT. And I think, you know, some of the themes that we've talked about, number one, I think we have a vision and I think we have the right strategies in terms of the future promise of real-world data in any number of different applications. We certainly have talked about the promise of DCT to be more efficient, to get us closer to the patient. I think that what we have to focus on is how we come together as an industry to really work through these very vexing operational issues, because those are always the things that hang us up and whether it's clinical research or whether it's later stage, uh, applications of data. >>We, the healthcare system is still very fragmented, particularly in the us. Um, it's still very, state-based, uh, you know, different states can have different kinds of, uh, of, of cultures and geographic, uh, delineations. And so I think that, you know, figuring out a way that we can sort of harmonize and bring all of the data together, bring some of the models together. I think that's what you need to look to us to do both industry consulting organizations, such as IBM Watson health. And we are, you know, through DTRA and, and other, uh, consortia and different bodies. I think we're all identifying what the challenges are in terms of making this a reality and working systematically on those. >>It's always a pleasure to work with such great panelists. Thank you, Lorraine Marshawn, Dr. Namita LeMay, and Greg Cunningham really appreciate your participation today and your insights. The next three years of life sciences, innovation, precision medicine, advanced clinical data management and beyond has been brought to you by IBM in the cube. You're a global leader in high tech coverage. And while this discussion has concluded, the conversation continues. So please take a moment to answer a few questions about today's panel on behalf of the entire IBM life sciences team and the cube decks for your time and your feedback. And we'll see you next time.