Name: Brainstorm Health 2022 - From Challenge Comes Change: The Future Of Data AI, And Health
Uploaded: 2022-05-11
Duration: 14 min 11 s
Description: Lynn O’Connor Vos, Board Director, Former CEO, Modular Medical Hilary Kerner, IBM Watson Health Moderator: Michal Lev-Ram, FORTUNE

Lynn O’Connor Vos, Board Director, Former CEO, Modular Medical
Hilary Kerner, IBM Watson Health
Moderator: Michal Lev-Ram, FORTUNE


Brainstorm Health 2022 - From Challenge Comes Change: The Future Of Data AI, And Health

Conferences

Lynn O’Connor Vos, Board Director, Former CEO, Modular Medical
Hilary Kerner, IBM Watson Health
Moderator:  Michal Lev-Ram, FORTUNE


Brainstorm Health 2022 - The Future Of Data AI, And Health


Brainstorm Health 2022 - From Challenge Comes Change: The Future Of Data AI, And Health


Hi everyone. All right. We are moving along the pandemic supercharged the amount of data being thrust across science, medicine and healthcare. But the delusion of data needs to be harnessed correctly and that is no small task. Yes, there are challenges but there's also massive opportunity. Um This is a moment where increasingly capable resilient systems can be developed, ones that work together and deliver better experiences whether for the patient, the administrators or clinician. So how can the industry successfully move from data collection, the data inside to taking action And what exactly does that look like? Let's talk with two people who have quite a lot of experience in this area. Hilary Kerner is chief marketing officer of IBM Watson Health and Lynn O'Connor vous is board director and former ceo of modular medical mhm George. All right, thank you. Thank you both for joining us. Um So I know you have very different backgrounds, different perspectives and hoping to tap into all of those today. Um I wanted to just start really high level. Just alluded to the deluge of data but you know the from point A to point B collecting all that data to actually harnessing it in actionable ways that lead to better outcomes? That's quite a long journey. So just very high level where where are we at? How would you assess? What's going? Right? What's not going right. Um When it comes to big data and everything that we are collecting today and feel free to talk about specific applications or keep it high level. Can we start with you? So I would say in health care, the idea of data insight to action is not a new thought. It's something that we've been talking about for years. You know, obviously the emergence of technologies like AI um has helped with adoption interestingly. I think we saw Covid was really an accelerant for adoption of of analytics. It's hard as how valuable data is. Um and we saw a lot of organizations uh look at Covid as a catalyst for transformation. When we talked about some of that transformation already today. Okay, Lynn Sure. So my background is, you know, heavy uh many many years and healthcare communications and pharmaceutical marketing and then and then a number of years in non profit. And I would say that when you look at what Covid did to the industry, both the pharmaceutical industry and the nonprofit industry, um it really opened their eyes to the need for information and bringing that information to the doctor or that individual so we can get action. And so I would say that I would agree with you. Years ago we were enthusiastic about a Watson application in breast cancer. And we're an early mover there. And what we realized then is it was great. The promise of a I was fantastic. But how do you actually assemble the data in a way that it was actionable. And so I'm I'm really excited about this period. Post Covid we're not really post Covid but during Covid um where many more people are focused on action. And that means that we'll have to use tools to bring data to that point of care to make sure that patients get what they need. So um it's interesting because on the one hand we're collecting more data than ever uh partly due to an acceleration from Covid and everything we saw happen over the last couple of years. And um you two you two also have some interesting takes on some of the data collection that stopped and clinical trials that had to stop. So talk a little bit about that and what you saw on the earlier side of Covid, what you're seeing today. Um Clinical trials is an incredibly interesting uh space. So we you know, we saw not surprisingly during covid um some barriers to that, one of which was, you know, typically, you know, you need to run a clinical trial, you recruit patients into a site and if you can't be face to face, you know, how do you replicate that? Um We we did see uh the data collection pick back up with decentralization um and an added benefit of decentralized in clinical trials as you get more diversity in the data that you do collect because you're not drawing from the population around a particular site We actually saw in 2020 uh customers who use our clinical trial management solution. They noted that data um from patients self reporting outcomes actually tripled. So they ended up with more of it because they were reporting outcomes from home. And the technology enabled them to do that. And when you say decentralized clinical trials, you don't mean Blockchain. Right? We'll get to that later. Okay. You just mean actual different areas. You can do it from anywhere different place. So my experience during I was privileged to be the ceo of MD. A muscular dystrophy association during Covid. Um And that's obviously those neuro muscular diseases are rare diseases. And at the very moment when Covid hit was probably the best best time in the industry where many, many more compound are coming out. Finally there's the mission to cure that disease. Um And what we found um was that again the clinical trial situation became very different as you said. Um nobody can get to the clinical center. Um And interestingly enough when you think about doing research and A. L. S. Why are we asking those people to go to the center anyway? It's very challenging. Um So what what M. D. A. Did which was again as has put the the industry in a very good position to do more research As we had 50 care centers around the country. And we put a real world evidence database together. So we have the largest real world evidence database in neuro muscular that gave us the ability to have the data available um for industry as well as researchers. What we've also discovered is you need to have a I tools so you can actually make this a more efficient way to get data out of the system manually is far too expensive. But what I will say is that was a great example where you know, years had gone by. No one had really organized data. We were clinical trials for being done the old fashioned way covid hits and all of a sudden there was a 911 call. We've got to get organized and a lot of those trials continued, which is really great. We're seeing demand for data and clinical trials um being used in different ways, you know, to create synthetic control arms. What? So taking a step back um I feel like I I hear the words insight driven and and patient driven a lot when it comes to big data systems. Um what does that actually mean? And how much is that really taken into account in developing some of these in terms of IBM Watson health, what can you share? Um for us? Uh We've seen the best insights come from combining different types of data. So um I'll give you an example from Covid. We um we were working with 19 different states with their Medicaid agencies to assess the risk of hospitalization for their populations if they were exposed covid and it, you know, not surprisingly you uncover a whole host of risk factors that are not necessarily clinical, so they're not going to show up in a medical claim or in a thr their social determinant data um when you are able to combine those different data sources, you know, from different systems that is where the true insights come from. Mhm. And what about you? Maybe? So you've worked on a on a few really big ambitious projects. So maybe that yeah, I'm a board member of um optimize our X. And that's a that's a company that we invested in WPP seven years ago with the idea that why aren't we being more efficient in using the E. H. R. As the point of care where we can actually impact hp HCP engagement and pull through messaging to patients that are meaningful at that moment. Um Again, calling out to covid this was a system that was set up but that was mostly financial messaging that was being delivered to patients. And what we've done now is through ai we can actually um dip into several different databases. Um have looked into a five year longitudinal data on a patient and deliver the right message to the doctor at the moment that that patient is in there and that's driving early adoption in in oncology and in certain rare diseases. It's also improving outcomes. So again to me having spent so many years in communications if we can start to actually use tools like this where we actually have a point of care strategy and we're not wasting a lot of time. We're not wasting products, we're actually getting the patient the right information that they need immediately and the right drug and that that to me is the future of how we're going to use ai in a system. But you have to have the channel, that's the real that's the obstacle and a lot of cases you don't actually have the system to be able to get to someone. Um Can you talk a little bit more about that? Because I think um obviously there's still a lot of hurdles and there's a privacy piece to to figure out here. But what what are the biggest hurdles to again taking it from point a point b the data collection to actually leading to better outcomes. I would just start by saying you really have to understand the patient and you actually really have to understand the doctor as well. And so the the obstacle has always been that you don't have a real connect between doctor and patient. And if we can bring the right insights and the right data and all of the the the information about this patient's history that will trigger for the HCP. Oh I think I have to act now on this because they haven't had the ability to kind of take all of that information of visits in the past and five years of history to say maybe this patient has early onset Ls maybe I should act on that. Maybe this patient needs X. And so that's that's this combination of what you just said behavioral insights are important as well. But actual medical insights are important. You bring that together and you have a channel and you might actually make a meaningful difference in that patient's life. It's very complicated. That's why it's been so difficult for the healthcare industry to to do some of this. But I think we're moving, someone said earlier, it's my favorite phrase we're moving from a nice to have to a must have and I think we're actually going to must have he is was what we're going to do in terms of how we're going to communicate to patients and doctors. That's exactly right. I mean you need to reassemble the information around the individual. I mean at any given time, you know, you are a citizen of a government, you are a member of a health plan, you are an employee of an employer, you're a patient with a doctor and all of those different systems need to be able to you know serve you and in order for them to optimize that. You know, you've got to have the full picture and we're not there yet to be able to bring in the social determinants and all of that into one location. Yes. But I think that that will be the future. There's I'm sorry I'm sure all sorts of issues with that um evolution. But I'm curious to hear a bit of of your perspective also on, you know, IBM Watson health has, has gone through different evolutions and you're entering a whole new territory pretty soon and being your own independent company. So um what have you learned along the way and and you know, just from the perspective of what hurdles remain, what still needs to happen to drive more adoption and how, if at all, do you think this new reality for IBM Watson health will, you know, help that? Um it's been a really interesting journey um I would say our our time at IBM has been incredibly valuable in teaching us the value and the importance of open standards, interoperability technologies like Blockchain that are going to optimize for data privacy or patient consent, I mean these, these are all technologies that are so fundamentally important to the work that we're doing and to optimizing, you know, the, the empowerment of the patient, um I think we're really excited about our future um and spinning off, I think being a standalone enterprise, we're going to have the ability to focus um on our, our clients which, you know, span a whole host of industries and ultimately, you know, drive real progress for patients the goal and Lynn um real quick, you're not spinning off from IBM but um but what are you excited about as you look towards the future and your board positions and anything else you've got on the horizon. Yeah, I just think we're at the tipping point here where we're going to transform patient care through better communication at at the point at the points that matter. Um I think that um the digital health conversation this morning and I'm I'm passionate about digital health. I think a lot of these new startups, a lot of the companies that I'm working with are really stepping in and bringing really exciting solutions, but hopefully we can bring together to make a big change for patients. Great, Well, Liz Hillary, thank you so much, Lynn Hilary, apologies. Thank you so much for being here and talking to us. Thank you. Thank you.