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Data + AI Summit North America 2021
May 27, 2021, Online, San Francisco, CA, USA
Data + AI Summit North America 2021
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About the talk

Join our Healthcare and Life Sciences Forum to participate in keynotes and panel discussions with thought leaders from some of the biggest global organizations. Hear first hand how they are unlocking the power of data + AI to accelerate R&D and improve patient outcomes.

 Agenda

Welcome Address: Michael Sanky, Global Industry Leader, Healthcare & Life Sciences, Databricks

 Keynote: Carolyn Magill, CEO, Aetion

 Panel Discussion:

• Carolyn Magill, CEO, Aetion

• Deepak Sadagopan, Population Health Informatics, Providence St. Joseph

• Dr. John S. Scott, Physician Informaticist, Veteran’s Affairs

• Slawek Kierner, SVP, Chief Data and Analytics Officer, Humana

About speakers

Michael Sanky
Global Industry Lead at Databricks
Carolyn Magill
CEO at AetionInc
Deepak Sadagopan
Senior Vice President at Providence St. Joseph Health
John S. Scott
Physician Informaticist at U.S. Department of Veterans Affairs
Slawek Kierner
Senior Vice President at Humana

Carolyn is the CEO of Aetion, the digital health company delivering the platform that turns real-world data into the regulatory-grade evidence needed to inform health care’s most critical decisions: which treatments work best, for whom, when, and how much we should pay for them. Before Aetion, Carolyn held leadership roles at three companies central to the shift from volume to value in health care. As CEO of Remedy Partners, she led the premier company for bundled payments software and services. As Executive Vice President of Payer Strategy and Operations at Evolent Health, she led the team responsible for establishing value-based contracts on behalf of health systems and provider-led health plans. During her four year tenure, Evolent progressed from start-up through IPO to become a major force in health systems embracing population health. For the preceding eight years, Carolyn served in leadership positions in the Medicare and Medicaid businesses of UnitedHealth Group. Her roles included Chief Operating Officer of its Community and State plan in New Jersey, and the national Vice President of Medicare Special Needs Plans, supporting people with multiple chronic illnesses and limited incomes. Carolyn has an undergraduate degree from Harvard University and an MBA in health care management from the Wharton School of Business at the University of Pennsylvania. She serves on the board of the Center for Health Policy Development, and of Parity.org, an organization that seeks to

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Value-driven, high-impact healthcare executive, offering over 22 years of senior leadership experience with top Fortune-rated corporations and aggressive startup environments. Deeply committed to the cause of developing economically sustainable healthcare delivery models that enable equity in access to high quality healthcare. Operational expertise in the development and management of value-based payment models. Recognized health informatics and quality analytics expert with a successful track record in launching new products with breakthrough financial performance. Works with Provider and Payer organizations to implement data-driven population health and care management programs. Domain expert in clinical & revenue cycle workflows, clinical & financial analytics and HIE. Six Sigma Green Belt with strong statistics and health data science background. Proven leader with experience in management of geographically dispersed teams. Deep experience in the management of business relationships and contractual arrangements with customers and strategic partners.

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Doctor Scott is a board certified clinical informatics specialist and pediatric cardiologist with many years of experience with military and VA health information systems. He retired from military service in January 2020, spent a few months as an independent contractor, and joined the Veterans Health Administration (VHA) in April. As a physician informaticist and the Acting Director of the Data Management and Analytics section in VHA's central office, he is helping to advance VA's data management strategy to optimize services for Veterans and enhance VA collaboration with Military Health and other health care partners.

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Slawomir (Slawek) Kierner is an innovator, strategist and results-driven analytics executive with proven track record in FMCG and Technology, and now fascinated by the opportunity of infusing AI into healthcare. Passionate team player, certified coach and successful organization leader in complex, virtual and dynamic teams, focused on learning, change, speed and constantly breaking growth records. Self- motivated by his passion for making this world a better place through consumer empathy, data-science driven innovation, in both fast-paced growth and turnaround environments. Speaker and evangelist at executive-level forums on leading innovation in cloud technology, advanced analytics, data visualization, ML, and real-time user, consumer and market signals like NPS, remote monitoring and cognitive observational data. Internationally mobile and experienced in understanding consumers and leading organizations across cultures from Seattle and Boston, to Europe, Africa, India and China.

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Everyone thank you for joining our Healthcare and Life Sciences industry Forum at the data and AI Summit. By Michael Ortega from the industry marketing team of David bricks and I'll be your host today. We have an amazing group of Industry leaders here to share their perspectives on how data and I are changing the way we develop new Therapeutics deliver care and drive better patient outcomes. Without further Ado, I'd like to hit it off to suffer speaker. Michael Sankey Hi everyone. My name is Mike Sankey and I am the global industry lead for helping Life Sciences at

databricks, some of you know, as well and some of you are new, we are the data and AI companies with more than 5,000, customers globally, including many, across helping Life Sciences, as well. Talk about in just a minute. the founders of data bricks created the open-source project, Apache spark and databricks also is behind other popular open-source projects, including Delta and mlflow What's most exciting for us in helping Life Sciences? The date of Rex, is how we get to work across the healthcare ecosystem, and be in the co-pilot

seat. With all of you as we transform the industry with data and AI. Many of you are from companies that already work with us, in some capacity, and many more are hopefully, starting the journey. Today, we work with nine of the top 10 Global pharmaceutical manufacturer, four of the top six Health insurers, in the United States, and government agencies globally, like the NHS in the UK. The healthcare ecosystem is becoming more interconnected and every stakeholder in healthcare is working with new types of data in meaningful ways. Providers are

taking on Risk, Takers are driving clinical quality measures pharmacies are personalizing, patient engagement, and messaging, social data, government agencies globally are getting involved in telemedicine, testing and contact, tracing in the Life Sciences industry. Now is access the whole genome sequencing data to make personalized medicine a reality. All of these initiatives, require a modern data and AI platforms to succeed. I want to highlight a few of the lasting Trends from the ongoing pandemic, as we're now dealing with covid-19 in 2021. People may not necessarily

think of it through the lens of real-world data and real-world evidence but vaccine Effectiveness, and safety post clinical trials are just that and impacting all of us in massive weight everyday. We're reading and learning more about vaccine Effectiveness. For example, Effectiveness relative to the duration of anybody's as we now have real-world data, beyond the duration of the original trials. Everyday. We're reading about vaccine safety. For example, with regard to blood clots. Now that these vaccines have been administered to tens of millions of patients, which are more representative

of society-at-large, than the initial clinical trial population. At the pandemic has impacted clinical trial enrollment and site visits manufacturers are focusing additional efforts on real-world evidence. Ranging from studies, that are included in regulatory submissions as supportive evidence to external control arms, which are control Kotor. It's outside of the traditional, clinical trial setting. The benefits of such approaches include more robust data that often are more representative of society which has a positive impacts on inclusion and Health Equity,

accelerated drug development, timeline for life-saving medication. And post-approval and I'm going data mechanism to support the safety advocacy, and the value of these interventions in the real world which are critical to all stakeholders in our ecosystem, including payers providers and governments data. And analytics platforms are essential to ensure the quality of real-world evidence generation. The second big Trend as we think about the impact of covid-19 in 2021, centres around the ongoing displacement of care outside of traditional

settings. This displacement is moving from ad hoc to a codified set a regulatory and business practices across the globe. In the United States siames, the centers for the center, for Medicare and Medicaid services has been improving hospitals, under its rapidly growing hospital at home initiative. This initiative is designed to give hospitals new Regulatory and reimbursement flexibility to treat patients from inside their homes. Data. And Technology are enabling this program, CMS will collect monitoring data on a daily basis which is meant to attract

a variety of measures including patient volumes unanticipated mortality in escalation rates. The Biden Administration is looking to further cement and support this trend by proposing, 400 billion dollars to give the elderly more Care at home. Rather than in institutions, this represents a substantial portion of the administration's 2.3 trillion, dollar infrastructure package and extends Beyond hospital at home to a wide range of post-acute services. As care becomes more displaced data platforms. Must enable timely collection curation analysis and reporting

to ensure Health Care delivery standards are met. The third big Trend as we think about the impacts of covid-19 in 2021 is around digital engagement. Once again data and Technology are the enablers digital engagement, both manifest itself in displacing, existing health care services for example, Primary Care. Moving from the office to telemedicine and opens the door to an entirely new set of services. Focused on things like wearable devices that offer real-time tracking and personalized disease management. And like our other

big trends digital engagement crosses, the healthcare ecosystem. Biopharma companies have launched digital help businesses focus on drug plus intervention, for example, digital weight loss programs organizations like Humana have created ends and clinical operating model centered around holistic member and patient engagement and providers like Providence. Saint Joseph are focused on meeting patients where they are through digital population, health programs, So what do we need to solve to meet the demands of real or real-world? Evidence

care displacement and digital engagement? Unless you're working for a digital native company or art ahead of the curve, you likely are living with some degree of of tech debt from Legacy system built for data warehousing and other purposes that simply don't serve a world of massive streaming, unstructured data, that are required for many of these use cases. These data silos are hard to integrate data. Engineers data, scientist in business, analysts often code in different languages. And data architecture is rarely have complex machine learning work clothes at the Forefront.

This is where Lake House comes in. Databricks is leading a massive paradigm shift in architecture, combining the best of breed of data warehouses and data Lakes. Data warehouses have been around for decades. They are excellent for structured data with batch processing oriented predominantly towards business intelligence, reporting data, lakes on the other hand have been in our industry for about a decade. They solve the problems of data Variety in velocity enabling semi-structured and unstructured and streaming data to reside in the same place. The problem is that many Lake speaking swamps

often lacking query performance, schema enforcement as a transaction guarantees auditing versioning in fine-grained access controls, Databricks Lakehouse platform combines the low-cost scalability and flexibility of data lakes with a performance, reliability, and governance and quality of data warehouses, Delta underpins all of this. Providing the ability to build these curated data. Lakes, Delta, relies on Apache, spark and utilizes Advanced cashing, an indexing methods to process all types of data at scale and includes capabilities, missing from traditional data

Lakes like skeme enforcement in auditing and versioning and those fine-grained access controls. The lake house supports all workload, engineering bi reporting and machine learning on the same platform. The lake house is based on open-source and Open Standards to make it easy to work with existing tools and avoid proprietary format in for healthcare. The importance of this lake house. Pattern is even more pronounced. Why is that the case only think about the unique challenges of healthcare day. We have an enormous data. Variety is estimated that 80% of medical data

is unstructured and this can take the form of even semi-structured data, like text, to image data for things like digital pathology. We also have this multi-stakeholder world that we talked about a little earlier with providers. For example, dealing with claims data for Richard agreements and payers dealing with clinical data for quality measures. And what this results in is that all of these organizations are now dealing with more types of data, much of that data unstructured an unsupported by traditional data warehouses. We also have tremendous data velocity, so

streaming data is critical for Interventional. Care hours, coming the difference of life and death, in the case of something, like sepsis in the inpatient setting resource. Optimization for things like, predicting ICU bed to man was highlighted during covid-19, the ability to stream data in real-time into the lake house is critical to ensure care delivery. The third area, why this lake house pattern is so important is for data, volume being able to have the ability to process data at scale and there's perhaps, no, greater example of

this. And what, you know, mix data where we've moved from genotyping, which typically represents around. One-tenth of one percent of a person's DNA to hold genome sequencing, which is 100% of a person's DNA. And we're now looking across hundreds of thousands of these whole Gino. And in order to create those Association studies and tied at two phenotypic data and disease expression requires massive, computational power. And that's where this lake house pattern. Really delivers value in areas like drug Discovery,

and the fourth area here, is around data veracity. And the reality is that in health and Life Sciences, democratization of data require Governance clinical reproducibility is really important, things like access controls to make sure that minimum uses satisfied are really important and having the ability to audit the data and do version of the data is critical for quality of care, do all of these buckets, if you will together really highlight the importance of the Lakehouse pattern for health and life sciences.

And with health lake house, ultimately, were able to create this unified analytics platform that can ingest all types of different data, a different Cadence's process that data at scale and then feed reproducible machine learning models. Most importantly, what this creates is business value supporting initiatives, including the ones that we discussed earlier around, real-world evidence, care delivery. And displacement of cares we're seeing today and digital patient engagement date. Of births goal is to make this simple and easy for our customers to that

end. We have created a number of solution accelerators that provide the foundation and the code to put use cases into action, ranging from automating digital. Pathology tumor sizing to parsing hl7 clinical feeds. Please check them out, and we look forward to supporting you on your journey. Thank you for joining us today. Thank you, Michael. That was great. Now, like to pass it over to a keynote for today's session. Carolyn, McGill, take it away Leon, and I'm so pleased to be talking to you this afternoon about real-world evidence

and to highlight, as I do. So the partnership that we have built with beta bricks over the years, My background is primarily in the pair at risk, provider, and data and Technology spaces. I spent the last 20 plus years thinking about how we can more effectively pay for healthcare. So that it matches the impact that it has on our lives just the way other Industries tend to do that. So about half that time I was with United Health Group ride like Medicare Advantage. Special needs plans for people with multiple chronic illnesses and

people with limited incomes and then the last decade I was with a series of high-growth tech startups evolent, Health which is population Health Management Company. Then it was the CEO of Remedy Partners, which is a bundle payments company and now the CEO of 80 on I'll start with sharing a bit about our North Star and it is so simple and yet, none of us yet have this A world in which we now what health treatments work. For whom. And what we should pay for them.

An 80 on, WE pursue that Northstar with our data science driven technology and at the end of the day we care most about making a better decision. And using our platform to do that. We take real-world data which simply means Healthcare data that reflects our everyday interactions with health care when we go to the hospital. When we visit our physicians and with our platform we transform that into evidence regulatory great evidence, If you'll decisions about what drugs to develop

where there are gaps in care where to place a medication on a formulary. We do this for Life Sciences companies for health plans for Edwards providers for regulators. And we do this globally. At the core of what we do is rigorous science owned by our Founders, at Harvard Medical School. One of our, Founders Sebastian's device is now the chairperson of pharmacoepidemiology in front of Economics at Harvard Med, Jeremy Ross, and who was his colleague there is with us full-time?

That commitment to science is critical because we are taking data and it could be. In addition to claims or electronic medical record, patient-reported outcomes. It could be data from a registry is an example, could be from a wearable device. Maybe I have molecular data. We take those data and we transform it into we call real-world evidence. Another catch phrase that relates to the insights that we'd arrived. And at 8:10 on our platform, you are very committed to understanding where the data comes from to applying the most

robust methodology to transform that data into evidence and to use transparent methods so that others can replicate the studies. So that Skeptics, can you try to poke holes or understand the assumptions that we found in variables? Did we take into account? Someone takes a drug. And I'm day to, they have a hospitalization. Is that hospitalization count against the total cost of care for caring for that individual? Or not. Any impact that that drug had, or the relationship between that dragon, that hospitalization likely depends on the kind of medication. Our

platform is a place where we can make these assumptions very clearly. And then we make them at scale, they have tremendous impact on our understanding about which medications work, best for, which patient populations when and how much we should pay for them. We are a platform that sits on top of these data sources and the data sources, you could think of coming from Optum iqvia Flatiron IBM Watson on Tata. We have one consistent analytic approach that

works across these different data sources and that's critical because one data source in and of itself is likely not sufficient to answer all of our questions. And this is why FDA chose a town as a platform in the context of covid-19, where the stakes arguably have never been higher. In terms of ensuring that we have a reliable methodology to turn those data into evidence in this quote from dr. Amy Abernathy, while she was there speaks to why FDA chose 84 this important work,

And it's not enough to say, we are establishing standards, we are committed to Scientific rigour, fda's using her platform on covid-19 you to ensure that if we are really committed to Global standards for transforming data into evidence, we bring together a community of thought leaders and supporters and Industry sponsors. To buy into this approach this methodology that were using the transparency and replicability that we bring to these kinds of analysis dr. Scott Gottlieb, former FDA commissioner board of directors or investor Community which includes Global biopharma

manufacturers. Health plans here in the United States data, aggregators and others who are very committed to how we use data. Regulators. Of course, and having global relationships, do not just here in the United States, but also in Europe and Asia. And in the partnership, we have with organizations, like databricks, which I'll talk to you in just a moment as well as the data providers themselves. We bundle those data into our platform so that we can create measures that are tailored to that underlying data source that maybe take into account with missing this of one

data source versus another or understanding when the same label for a field doesn't mean the same thing. Across different sources of data. We have no shortage of data today. Each of us here knows that all too well. And yet. Why does the data goes unused? We are spending hundreds of millions of dollars. In clinical trials. Healthcare spend is very difficult to manage especially here in the United States but honestly worldwide, we suffer from these problems. And so with all of these data sources out there and all these analytics platform, how can this still be the case?

And you may notice as you read the newspaper every day, headlines that talk about travesties in healthcare, like the rising cost of drugs that make them unaffordable for various patient population or clinical trials that don't represent settings or populations that exist in the real world people over the age of 65. People with different different racial and ethnic backgrounds. Women of childbearing age kids, under the age of 18, the list goes on. These are populations who aren't necessarily included people with different

combinations of clinical trials, and then if you work for a Pharma company or you work for pay or you might be familiar with drugs coming on the market, And not reaching expectations in terms of what their indicated for. Or we sometimes see that drugs come to Market and then are used off-label because Physicians start recognizing. Hey, this medication would be more appropriate or as appropriate for people who have not just diabetes, but also heart failure. How can I be, why wouldn't we know that during the development or the

approval process? And then you also might be asking, okay? Okay, but why should I care and, is this really relevant to take a second walk down the hall in your medicine cabinet. How many half open pill bottle are in there? And if that's not true for you to go to your mom and dad's house and check out there, how many times do we start a medical treatment and Midway through realized doesn't work for us? And what are the implications with respect to the progression of disease or symptoms that we experienced side effects? We experience that maybe we never even had to

expose our bodies to These are the kinds of things that we Endeavor to address by using real-world evidence more effectively across the Continuum of Designing treatments for healthcare, assessing them, testing them through the trial experience, taking them to Regulators for approval, putting them on the market. giving patients access to drugs via of formulary supporting Physicians and clinicians and understanding when to prescribe which treatment when

We're not the only ones who are on to this. Of the approval that FDA gave. In 2019 half of them included real-world evidence and their submissions. And that number jumped last year to nearly 80% And we have course I partnered with them in that in the context of covid-19 where they chose age guns, platform to assess these data from disparate sources around the country. At one analytic workflow to understand which treatments work best for which patient populations.

When there are many applications for real-world evidence. We often think of it as the Continuum run the low end of the spectrum. We're looking at data from The Real World to just understand who's taking which medication and what's happening to them after they taking medication were using it to do Safety Research. As we get more sophisticated, we use real-world data to inform label expansion to conduct external control arms to measure the total cost of care and let me become even more. Sophisticated were using it to support regulatory approvals,

formulary optimization, value-based care contract and paying for outcomes. I'll give you some case studies in just a moment to bring that to life. And we could not do what we do without databricks. And the value that we get from our partnership with databricks and using like house is multifaceted, scalability perspective. It's reducing overhead and our data ingestion process of eliminating manual tasks for engineers and scientists. It brings us faster performance. And it also

can support on-prem capability to the extent. That that's relevant. So, let me share some case studies to bring home how exactly real-world evidence is having an impact for us and Healthcare today, here's an example, from a drug company, that had a medication supporting patient with multiple myeloma. In this example, they're using an external control arm, a control arm. Created through data, to support the approval. And another example were using rwe to help

us see what's happening with medications? Populations who weren't represented in clinical trials for. You may know that children often don't participate in clinical trials and here's a report based on Research that researchers at McLane hospital did using a chance platform. To assess the impact of different ADHD medications in teens. Very valuable insights about which medications work best. And here's an example of work that we did with Horizon Blue Cross Blue Shield of New Jersey

where they're using their own member data, to inform understanding about which drugs work best for their patient population, when and then this becomes the basis of conversations they have with manufacturers Of drugs in the therapeutic class. That they are trying to bring to their members. Another example is ice her which is a an assessment agency that is helping to assess the value of the impact that medications have on different patient population. They're using ATMs platform both at the time of a drug launch to understand that value. And then

24 months later. Okay? Now that we have more real-world data, what's happening when people take that drug and what does that mean in terms of the value of those medications? And at the end of the day, we want to use all of these insights collectively that we're doing for payers that we're doing for manufacturers of drugs. And use that to inform Public Health policy. So that we ensure people had access to the medications that work best when they need them. And you can see that there is a lot of support

from within the regulator Community. This is from dr. Janet Woodcock to the acting Commissioner of FDA talking about the power of real-world evidence, and how we need to use it, more Ann Arbor for approvals and decision-making, but nothing is more compelling. Been appreciating something like what this picture represents? Which is the first person, receiving the Pfizer vaccine. In the context of covid-19, because at the end of the day, we want to ensure that patients have access. To the medications that work best for

them when they need them. Thank you for your time and thank you today to Bricks for your partnership. Thank you. Carolyn for sharing all the great work at a Tiana's doing in the community and the massive opportunity for real of data to improve health care for us. All I like to know, headed back to Michael Sankey and are steamed group of healthcare and Life Sciences leaders for today's panel discussion. Welcome everyone to our health and Life Sciences industry panel, my name is Mike Sankey and I'm the global lead for health and Life.

Sciences at databricks, I'm thrilled to host. This amazing panel, representing diverse stakeholders across the healthcare ecosystem, will be discussing the opportunity for data and AI through the lens of a few of the lasting trends of this ongoing pandemic. I'd like to thank our panelists for joining us today. We're joined By Carolyn McGill, the Chief Executive Officer of 80 on a healthcare technology company that provides decision grade real-world evidence Solutions. Suave kierner the senior vice president for Enterprise data and analytics at Humana, one of the largest

health services companies in the United States. Epoxide to go behind the senior vice president for value-based care and population Health. Informatics at Providence? Saint Joseph, a large health system with more than 50 hospitals that operates across seven states and dr. John Scott, a physician informaticist at the Department of Veterans Affairs. Working on the va's data, governance and data management strategy and Suave Deepak dr. Scott, welcome. Thank you. To be with you.

We'll start our discussion today, with real-world evidence, or are we given the different Vantage points across the panel? Let's Dive Right In and learn more about the impact of rwa in your industries? Slavic. I know that one of the things you're passionate about is interoperability and data standards such as fire. Can you share how important these are in terms of generating reliable real-world evidence and now Humana? More broadly thinks about rwe from a payer perspective, Thank you, Mike and let me stop it. I'm going to invite of course I know I was doing

to build on that response but clearly from our point of view fire is just one of many very important Avenues to complete health. Records of our members, I got so many new data sources for their energy, from all kinds of devices, Apple watches fitbit's Bluetooth blood glucose meters in a diet apps, all of those are a meeting date on it. Now, even more days are we have no more accurate remodel so we can create and provide more personalized similar to our numbers

morning, more standards Fire based on the Earth. The mother of country is a baker, need them Digimon for opening up new apis. Issue, tracker BJP is between us and providers of healthcare and said, we cannot balance. I would have all your baseball, those of care. And we invest in here at out in the open for all players, in the industry of consideration will accelerate. And the, I do hope for another goodness to come back home from dress. So I like more evidence available to work.

So Deepak one of the things that is why the commission was value-based care and I know that you're on the other side of that from the health system perspective and one of the things that we spoken about before in the context of rwe is the inherent tension between having more data and and yet potentially less control over some of these confounding variables. So I'd love to know how this plays out at Providence, Saint Joseph in term of both, standardizing the data across all the different facilities and then maybe through the lens of value-based care. How you think about the role of rwa.

Yeah. Thank you Mike and and thank you. So I look the role that data plays in our ability to manage the hell out Health outcomes for populations. Cannot, I cannot be overstated. I think it's it. It's a critical Lifeline all of us how we manage populations and I think we are in a time and space where provider organizations are increasingly being held accountable, not only Quality quality outcomes but quality at a particular cost, right? Like in terms of saying that you've got to be able to manage

the hell. Comes to a particular population within a particular cost budget at a particular level of quality that we expect. And that level of that level of accountability would be almost impossible to fulfil, unless we had real-time insights into how our populations were doing across the board. Not Intensive clinical-stage which we have right now with electronic health. Records in health information exchanges. We have some insight into that but I think the evolving part that is still being developed is how do pears and providers communicate with each other in this growing space,

right? Like interest, avocado talked a little bit higher standards. While I'm here to say is it's not only the exchange of clinical information between party and B. It is also the automation that exists behind the scenes in administrative processing is being able to say that you're able to. If you're able to tell your clinicians participating in these programs that they have they have been damned exceeded spending in one case or do you understand do you have underachieved on quality and other other areas being able to provide that visibility

into them real time and also being able to tell them that this intervention that you put in Last month is is not either showing the results or outcomes or is working real time and real-world data is critical for us to be able to measure measure progress. And, and that's really what this is about to ultimately is how, how do we impact the experience of the patients, we care for, and we share responsibility for a between payers and providers and all the other entities contributing to the space. That's a great segue to you. Dr.

Scott. So, how do you think about translating this from a population level down to an individual level in in care delivery cuz you're thinking about this boat that a data management governance level. But also thinking about that the implications of treating patients, Yes. As a Deepak was with speaking. I was thinking about the particulars perspective that I've had it is as a, as a clinician forced to use an EHR. Since I began my career, the burden that the HR creates on the clinician and the challenge of being able to get the clinicians to be able to use

the HR to consistently, enter the data. That's necessary for the kinds of insights specially real-time insights. That Deepak was talking about. So, at the large organization, like the VA, we are, how do we get our clinicians to use the EHR correctly? How do we tell what they did? How do we make it good enough for them to be able to do that? So that we have consistently acquired the data that we can then look at to measure the actual value here whether they followed guidelines and and and follow the care Pathways that we recommend trying to standardize the way the HR work. And make

it worthwhile enough for the clinicians. And at the same time, another current in current in medicine today is personalized care account for variations that are appropriate at the end of visual patient-level. How do you do both of those things? Well, is I think I shoot challenge for us and any other large Healthcare organization. You mentioned that the VA is both a pair and a provider. So we are needing to be able to look at the information we Garner from. Are the use of rehr in our Direct Care System, but also

in order to to promote the VA as a group. As the best choice for veterans, we do need to be able to compare how the quality of the car, inside the VA to the care, the veterans, get outside the VA. And that's that's an additional challenge cuz there's different types of data sets. Carolyn. So you you have a lot of pass perspectives from your work at United managing health plans at Evelyn's serving Health Systems and are easy on what really has established itself as a leader in in real-world evidence. How do you think about

the role that data and I plays and enabling the space around rwe and maybe some of the biggest change is that you've seen a sort of, in the evolution of of rwe over the last few years. And you're right. We've actually seen a fair amount of change over the last three years in particular. So, you know, three years ago, for years ago, we saw some legislation that talked about real-world evidence of the introduced this notion of turning data that reflects our everyday lives and health care in two

insights that are actionable relative to. How well drugs and clinical treatments work for different patient populations. And in different settings three years ago we were explaining to people what rwd stood for what are w e was why it mattered, how it maybe was differentiated from some of our other approaches to analytics. Why do we need rwe? If we have Actuarial science, what do you mean I already have? It is not sufficient. What is truly differentiated about this? And I take back then to to the extent that we were using real-world evidence, it was primarily focused on

safety. We were looking at a medication is an example that had been on the market. And we were looking at the impact that a given drug might have on a patient population after taking that medication and you fast-forward a few years. Now, everybody's talking about real world and real-world evidence. So, even you know here, just represent representatives from the payer and private. Our provider communities, help to underscore that. We're able now at also to just access more data. Then we were historically. And we have better methodology for understanding

data provenance and what to do with it. And we can be much more transparent with how we're identifying confounding variables, and then how we're controlling for them and the implications of what we're controlling for, on the results that we see and that level of transparency is absolutely critical. So now, we're at a place where Regulators are actually making decisions on whether a drug is safe for a new population that wasn't represented in a clinical trial based off of real-world evidence. And that's something we hadn't seen before. And the role of a, I in this is helping

us to identify patterns to sift through large amounts of data. You know, three years ago when we were talking about real-world data, we were thinking of claims electronic medical record. Now you put on top of that patient-reported outcomes data from wearable. Isis genomics data. Not clear data. No, these are the kinds of things that just protecting petabytes, right? There's a lot of data and without the advancements that we seen an AI, we just wouldn't be able to sift through that and any systematic way. And now we're at a place where we can generate hypotheses to understand better

what's happening with different populations and then we can test it and we can test it with methodology like ours that is less black box. Then a, I often is but you have to start somewhere and I say that's where it's at. The biggest impact. Yeah, I love the perspective of an important things for them to be able, to be way more personalized. Including that. Of course, I have too much. Choice will be putting VM don't say anything when we have more evidence, so we can

employ all those two are sanitizing, and they're out to destroy Isis with, hopefully Can field down to what actually works for, by particular case, I need them to better outcomes. Because the thing is, we talked about things, like personalized medicine and absolutely look, less give solutions that work on behalf of the patient. And then think about them holistically, right? As a former Health Plan leader. You're also trying to manage the medical loss ratio. And you're trying to understand how to deploy a limited resources, across a very needy population. And so one of the

things that we are passionate about is how do I know what's differentiated? And it's so it's not just about personalizing, it's about figuring out what's different for roubaix versus 50 that is truly driving meaningful differentiation and the outcomes of cost and quality that Deepak was talking about and don't have and how can we do that in a systematic way? So it's it's not necessarily a different approach for each member Who's involved in a Humana. Health plan is an example, but we start to see better. The kind of interventions that actually Meaningful impact

for different groups of patients and members. And I I think I think something you said there Carolyn really spoke to me which is that in one of the things we consistently hear from our Frontline caregivers is that we don't want to see, you don't want to see and treat a Humana patient differently from the United patient, from a Blue Cross patient to do their patients. They, they, they they all up to, to me they want to hear agnostically, right? And that that's one part in the second part is what we're learning as we get deeper into some of the population Health

stuff is that, you know, there are a lot of factors Upstream that, you know, we call social determinants of Health there, another Stein, two factors, that that impact Downstream Healthcare outcomes. And I think the, the, the more we focus on Integrating care delivery to care about the whole person and do that up front and use that. And then be able to be prepared to react and have visibility to real-time information about that population. I think the better off we will be in in achieving our eventual goal of having Health Care system. That is not spending

five times as much as other countries. You know. I like I think we we've placed far too much burden on the back end of healthcare when conditions become serious and the security becomes higher than addressing wellness. And whole pushing whole person care up front. And I feel there's opportunity here for a private-public partnership to be able to frame policies in this area to be able to really create products and services in the space that that can that can really Transform, what we know to be Health Care. Delivery today,

VA has a tremendous opportunity to contribute in that regard because it is a large organization with a health promotion Mission. And it in that mission. It not only has health care for 6.4 million veterans being delivered directly. It has a mission to promote health for Veterans generally. So that the size that the VA is a relationship and beneficiary relationship that it has with its patients. I didn't drive to promote Health, we should be able to put prevention and health promotion in the front of everything that we do and be

able to collect enough information and use it at the CLE. In that mission to be able to make big data inferences on what types of care, actually lead to the best outcome, for the VA, fax Veterans for their entire lives and gets a complete health record on every one of them from the dod when they, when they were younger and active-duty service members and it creates a tremendous opportunity to look at what, what predictors it when they're younger? And active-duty are important to focus on as determinants of later at auction. So

tremendous opportunity with VA right now and if we can sort through the data management, challenges being a big government, bureaucracy makes that a little more difficult. But if we cancel For those, we can contribute significantly to the kinds of things that you're talkin about you though. It's interesting dr. Scott like there's a there's a one region in our system especially who's working with the Department of Defense actually in an interesting way to to provide a play just like you guys. Are we are a combination for plan in the delivery service

delivery system to and one of those plans. And products we offer is actually for family members off of Department of Defense personnel and I think a partnership between the agencies and an rrt Mark, end of every team, has really helped Drive outcomes and lower costs of care for that for that segment of the population and overall improved experience. And, and really thinking about Primary Care transformation has been at the heart of fate of being place, in Primary Care at the front and center of how care deliveries triaged. Do you advise

your, your beneficiaries who are, who are also military beneficiaries to make you sad? Patient portal that they have access to from the military to acquire their entire health record. And, and then share more of that with you because I'm a big proponent of patient-centered health information exchange. And in the end. They both have pioneered patient, portals and, and and notes access. But we do not. We do not always make the most effective education and promotion of the services we create. So I'm,

I'm a big proponent of anyone who is also providing care to service members and Veterans to help them Avail themselves of the patient portals and access that that the Departments are trying to give them. I think it's always going to be more robust means of information sharing. Then we will achieve, despite your work on the fire standard. We were never going to share it be able to share as much between Healthcare systems. As the patient can download from one end and send to the other, we can facilitate that transaction. So it's not too much burden

for the patient. Anyway, but there was a question their most of our members in the US family health plan. As they call it, our tents to be family members of of serving serving professionals and Personnel. Not as much as the military personnel themselves can use the same tools and I'm not aware if they used user portal but with something that I'll look about and get back to you, I'll send you the link to Dr. Scott me to spend another minute. How is that information? Sharing gone between the dod and the VA, I know you're working on initiatives to get more predictive around adverse

behavioral. Vance even Suicide, Prevention, can you share a little bit about that? There's three ways that we share information between Healthcare systems and I think the Odeon VA are doing well at very well, it two of them, but not not the third one. We we, we make viewers available for health information exchange and do the dod and VA have a very comprehensive share. Do our system right now, so that every single bit of electronic information created by both departments Health Care Systems is viewable in an

integrated viewer, to the other department. So we we've, we've got a good view of it that you don't put the burden on the clinician to do something with the information. We we also have a a pretty well operating document transfer system. If you will win a service member separates, the entire health record is, is collated into a set of documents because that's the evidence that the veterans benefits Administration needs and they have a basically interface between the electronic filing cabinets. So we would store the record of gets copied into the vva systems and they have the

entire record as a set of documents that's working. But what isn't so good yet and we're working on is actually sharing data so that it can be used for analytics so that it can contribute to clinical decision support systems in it in a more robust matter. That's where I think we're warm or at up if we say crawl-walk-run stage, we're at crawl, maybe we're starting to walk a bit. There's Walmart thread. I want to pull in a little bit on the rwe topic and that's around the nature of Representative, patient, populations and and Caroline. You

mention this in the context of rwd vs. Clinical trials in the opportunity to have these more inclusive. Patient populations in rwd. Can you expand on that a little bit? And then I'd like to hear from the others? How you think about the patient? Populations, respectively of Providence, Saint Joseph Humana, the VA in terms of Representative Nelson, and serve the opportunity there for r w. A r c t because we don't see them as sort of every cereal if you will, we see them as supplemental to one another and then often times it's just not feasible to represent every setting every

population in a clinical trial. And so that's why we want to stop. Does trials with data, and they're all kinds of examples of this. So often times people, over the age of 65 people with different combinations of chronic illnesses, women of childbearing age people under the age of 18 are explicitly excluded from trials. So it's not until a medication is on the market that were actually able to see what's happening for those populations. And then we have other examples. Like with covid-19 is an example where we were running these clinical trials but we were not getting

diverse populations and rolled and we needed to see what was actually happening was African. Americans has been example, Asian Americans, who aren't necessarily adequately represented. And so we look to data to help us fill in those gaps and a much more systematic way. And this speaks to why FDA is an example chose to use our platform in the fight against covid-19 and specifically wanted to look at data sources from different parts of Country to get a better sense. And looking at open claims is an example from a hospital setting as much as they were looking

at electronic medical records and then trying to understand which data are truly giving us incremental information. That drives a different decision or tells us something meaningful about what's happening with those populations. And how can we ensure that we are applying methodology in a consistent enough way that our analytics can be replicated? And there aren't any secrets about how we analyze those data to come up with those conclusions. Any thoughts from the others in terms of how you think about? Representing. I would say I'd agree on the

d challenge in implementing. I would. Also what I would also add is that a r c t and the RCT mode of gathering data and evidence while it's been time-tested and you know it's like the ultimate manifestation of the scientific process that we've all grown to go into, you know, you no respect is is all so time-consuming and it's also involves a certain level of funding as a prerequisite to be able to do that in there. Also leaves out. Unfortunately, many of the other opportunities, like, for

interventions that you're not able to put to the same rigor, because we don't have funding to do that, like, you know, things like I would even taking taking a another completely different example, you know, out of the out of the power products or the, or the medication, Context, simple things like, you know, you change how you are redirecting. The use of emergency departments for a segment of the population and you're trying intervention, a horse's intervention be, there's no way you're going to get you. No funding to run an RCT for something like that or you're going to

have that. You're even if you do the the results of such an RC is going to take far too long for you to to be able to do to make a determination on whether such interventions are effective. I think the rwe pathway of actually making care delivery. In determining the efficacy of one care delivery intervention versus the other can can offer a viable alternative pathway for us to actually get be more effective in the implementation of value-based Care at the speaking from the, from the world that I live in day today, at least

And I know what is the same time? Of course, allowing for more Innovation and and in fact, The Innovation cycle is that what's stopping us? A reminder varsity? Because it does take a long time to wait for the timer called cancer and then if you also based calculation of Health outcomes on my claims, you know, but this process of creating my own sometimes even mom's. So i w e counseling to Placer by but also thinking about getting indicators, which I could check think a very important for our industry. Especially now when we are looking at the social of England,

And then go with said, types of how can be measured with indicators that are coming here in a bit faster and as long as we believe in yourself, healthy fruit, on your people, to call Health, we can measure with her but you actually did switch to know that a diet and eating more healthy or evidence to continue playing the grass insert and intervention, or on all the way for the health outcomes of ferocity. It seems to me when you're using rwe in the in the context that you're discussing it with Carol and it's you,

you really got to be careful about what confounders, there might be a. No, for example, I were working with our are cancer tracking system in and then providing better data back end for them. And some of the things we talked to them, about our treatment for cancer and trying to compare the effectiveness of that of those who had that treatment. And those, who didn't, I think it's important. Perhaps the men to measure how engaged are the page consider that as a as a potential confounders you know maybe the patients who are signing up for the new treatment are simply

more engaged in their care and general until we've got to get the new field for me but you're not in your head. I imagine that. That's a real trip to being able to use the r w in this context. And that we're making and then that leaves two skepticism and we saw things in the context of covid is an example with retractions and very respected medical journals after having printed studies real-world data studies that we're not conducted in a reliable way. And so there are examples out there that we have to ensure that we are very committed to addressing with a

level of scientific rigor. That makes the results credible. The more transparent, we are about the assumptions that we make them more confident. People will have, especially stakeholders with different views and aligning on the inside that you drive and say. Yes this is, this is actually reliable. It's something that John that we can all agree on. If I talked with Mike in the prep for the panel when we think about the VA, it's it was a huge population. You think that is being processed chicken of the uws but it's it's got certain skews. It's Its first while they were all in that

military service so that's not the entire crop. A good cross-section of the country but then the ones that have their care in the VA, that's just 6.4 million out of the 24 million veterans that that are alive. So which ones are getting care. In the VA there, people who had conditions that were related to their military service, first of all, and then the VA was their first choice, do it. How representative is that of the American population? You have to consider all those potential skewing factors even at a big population like like the VA population

are we can get data from Fitbit but it's the same thing will who's wearing a Fitbit? Absolutely being sure that we're using data that are fit for purpose of the question that we're trying to adjust is critical the RCT in the rwe are supplementary to each other, and I think, I think probably we think of these as essential components of self, our evaluation process going forward. Not one, not one complete in an elf. It's also And using lake has Mike's favorite topic there in women's that we need for this evening

to be possible. Great gray, close to the rwa topic. Theme around displacement of care. And by displacement of care, what we mean is are moving outside of traditional facility settings. And this is happening in the context of virtual care and telemedicine, which will address in a little more detail on our next beam around digital engagement. It's also happening in the context of acute hospital care being delivered at home with CMS hospital at home initiative as an example. And and that doesn't even take into account the rising Trend in Post. Acute home

care, and and Home Services, like home infusion, which are merging and and the Biden Administration. Earmarked for hundred billion dollars in its 2.3 trillion, dollar infrastructure plan around increasing Care at home. I'm so swaback. Maybe you can kick us off here again. You man has been investing heavily in home base, care, most recently, in acquiring all of Kindred. Can you tell us a little more about what you man has vision is for at home care and the role that data in a i play in achieving it. A sure thing might I'm going to be up for

that all super excited and there and probably will come and go through all of this expansion of accompanying anaerobic conditions, that are now joining us and for basic training hiring to clean, your health care services company and allied with no by conditions before. And that is certainly a response to a growing Trend and their increased demands from from, from the market, for the car could be delivered at home receiver in taking care of home and 5 * 7. L, i s s

a Spanish omelette with bacon and see if the home setting. So so it's not the only one who has, they can see the whole set of its member and then I will be by there. So course a very valuable lesson of all of us together and provide with quality care of telephone and Outreach. And when necessary. And, of course, they taking the center of us. Can you evolve Kadabra to acquire process them there and use way more different than before? And also, you know, they're for making the server and economical mother

work week. We want to play way.more machine, learning and prediction to know, which type of Health do. I remember something at home in the night time? When was the writer moment for an Eastern context of ensuring, that this experience for a person, your simplify, your personalized, and the Indian res to Better Health outcomes at lower cost. Detoxing when we've talked in the past we've touched on some similar themes and I know you have a concept around ubiquitous care now, which is

really about meeting the patient when and where they need it. Can you expand on that a little bit and tell us what providence Saint Joseph is doing in terms of programs to deliver on ubiquitous care? I think one of the things said dawned on us especially for, you know, over the past year has he been grappling with covid and and how it impacted our different communities? One of the things we'd worked on even prior to covid that it was has been heavily, focused. Heavy Focus area for us is expanding our digital footprint and capabilities and

barely being able to able to provide folk are virtually. You know, and what reverse experiencing before the covid-19 is shoes off last year, where is that? The adoption of digital cameras actually very minimal. And and there was hardly any any object and there was a period in the middle of last year when it went from 0 to about four thousand percent or something crazy like that where where childcare really skyrocketed, right. The other area where you've been

focused on this Home and Community Care, where you have a pretty large Home and Community Care Division that takes care of patients at home at home, visit at home, different levels of a cutie. We have a hospital at home program and, and and Post Acute Care, which is an Uber to sniff sensitive notification, nursing facilities and things like that. One of the things that we have experienced, we've seen firsthand in Racine and data to is that, you know, I think over 70% of the time or something like that in a, in a recent study, with patients are given a preference of whether they want to be

treated on an ongoing basis and an extended incubation environment or rather go home or even for that matter. Choose a more intimate of treatment pathway was his two less aggressive treatment Parkway. They always when they are informed and empowered, and I use the word empowered to be able to make that choice. They actually choose the less aggressive and the end the morgue. Home pathway and partly. We feel it's our calling to listen to our patients and really deliver care where they need it, where they feel more comfortable, and that affords, a better healing path way to

chew chew their conditions. And from that perspective, what we've been looking at is this combination of a care delivery model that is equivalent, no matter where you deliver care, whether it's wherever the patient is bringing care to the patient. Rather than the so nervous system that we've created over the past in a multiple Decay Decades of having the patient navigate, the complexity of the health system to find their way to you and it's a huge I know you were frozen Trim in a thief.

So yeah, I was just saying that, you know, like they eat the whole notion of bringing care to the patient rather than not not waiting for the patient took her to find their way to you. And so as we deconstruct our health system, as we know it and reconstructed, again, that's the experience that we wanted to design. The round is really, how does the patient now and not in a way that is simple intuitive and are able to get care of grandma and where they need it. So,

I know digital digital engagement, we're going to talk on about separately, but there's a, there's a tie in to that conversation. About the displaced Karen, the way, the traditional care, we relied heavily on the electronic health-record, do, you know? And the clinician using electronic health record to provide the data that we then used to measure the outcomes within the displaced air is harder to do that. And I think they're becomes more of a Reliance on the kind of data that comes from the devices that you can. If you're going to

have to buy says that are involved in home care the mechanism by which that information is communicated to the healthcare system so it can be used as part of our analytics. That's where the overlap with with with digital engagement. I think you exist. We, we have to do that for whatever. The patient wants to send us the mechanisms by which we connect a patient at home in their devices. To a data transmission that that we can validate an aggregate at the at the Healthcare System. I think that that applies then to whatever Partnerships exist for the people who want to do the home care and

monitor those devices were going to, we're not going to get those people to use rehr but we can probably get all that device dated a flow through the same day to connect connections, to get it into our, our analytics platforms, at least that's that's how we're beginning to think about that in the VA, looking at the same mechanism where we put it together. I can't speak from experience is so big. This is not an area of but I've studied of just how the VA is partnering to perform home care. But I I know that will be a challenge for us

as well. Garland, how do you think the displacement of care sort of building on? On some of these comments opens the door to additional data types of them can be used as part of the submission packages and how should, you know, whether it's a pharmaceutical industry, generating evidence, or Regulators, considering the evidence. Think about, you know, these new emerging data types, driven by the, the different nature of the interactions influencing the ways in which we look at patient

populations and how he even Define patient cohorts and really positive ways. Because previously we're relying on data from claims that were created for billing purposes or from electronic medical records that were created for the purpose of delivering share and those aren't necessarily reflective of whether I can walk up my stairs or whether I'm making it to the pharmacy to pick up my Medication. And these are the kinds of things are just how I'm, you know, engaging in activities of daily living. These are the kinds of things that really are saying, whether my quality of life is

where I need it to be, you know, relative to my own career goals. And so, by having these additional settings, we're able to get a better picture of the trip is that we need to capture data in the settings and we need to do it. And a consistent way. Your back when I was managing health plans for UnitedHealth Group. Many years ago, we really struggled with the data that was gathered in people's homes because there were inconsistencies and access to the internet is an example access to ways to transmit that data to us and was the absence of that data.

Reflective of a few know, of the capture not working correctly, or the fact that that wasn't existent in someone's life. But you know, they're all these questions. I think we've come a long way. The other challenge that we have today is around linking data. So how can we take the data that's reflected in. My home is an example and combine that with what happened to me last year when I was at Providence, in an inpatient setting. And how do I then combine that with the medications that I'm taking, please start looking at people more holistically based on what they're experiencing with

Health Care, regardless of that setting. And some of the other tokenization, we've made a lot of progress in that regard as well, so we're able to do that much more effectively now than maybe we were historically. Weather. That's why I'm interested. What happening in many ways? It is we have been to two segments. Different needs to be. We have family members that are attacking tonight and a home. That's got back on budget to eventual car and seen excuse Vigo

crap about another funny. Funny visits are being called me and was going for the ladies grade and I am at the Home Speakers gets here soon. Become unable to do so with, not stand there and screams and then maybe some overtime places to signal is being generated and you know and then hoping for And you better not Advanced Technologies, but might start believing with internet connectivity and I will need to be there for them as well, which included getting up and then it would seem so many suffering from food, insecurity, because of Transportation challenges. I need the right now with

vaccinations I've seen some that do ink transfer working, just how to change through telephones and and Ferb is delivering used to identify a security and vaccinations. We will make you more than five thousand phone calls I need and maybe don't have access to technology. How to conduct a clinical trial? We had to go into a setting and and be care in person, be monitored in person. And, you know, this technology and and practice has been around for a long time that we hadn't really adopted it as an industry until covid necessitated because so many of us were Homebound

and so I would expect to see more of that. So that the testing and that the clinical trials happening and he's more and you know, very setting Think the other experience other thing that the experience of last year has taught us has this notion of agility and in health care Delivery Systems that have you never thought of it that way. I'm in route. We think of healthcare Delivery Systems at the as these monolithic structures that is centered around these buildings of primary care in acute care services. But it was like when it came time for an

emergency and we were Ranch out of hospital beds and critical care beds. We were able to be extremely Innovative, to be able to create those beds in a football, stadium more like another types of areas where, where, you know, the hospital, the traditional Notions of a hospital doesn't exist, but we were able to move components of what represented care needed to be delivered at that point in time without incurring. The fixed cost of actually creating a building and there's something we take away from that experience, add, you know, like and we've implemented several Innovations and Spotify

system where we create like this mobile primary Caravans, where we, you know, we actually take mobile Healthcare to, you know, places of employers, or things like that, or so that our communities where they're able to get there in a primary care. Check up wellness check, you know, things like that. Or, you know, mental health check-ups, you know, like, you know about mammograms things like that. That happened on a remote setting that is not anchored to a fixed facility but it's also meeting the community where they are, you know? And, and I think in a way she acts like that

project, the delivery of care to Woods where the patient is in their Community involving Lexus, fixed cost structure as we've known to embrace the health system off today, I think is going to take us in a direction where you're able to ultimately. See that goal that we all share of bending the cost curve of healthcare but creating a more responsive Health System. For our community and populations. We're going to have to adapt the EHR to serve those care settings. You know, the way in which the flu

Works in a hospital and who does watt in terms of who does what bit of data entry has to be flexible enough to too. Still. Can air that takes place in those new dude about a fixed monolithic structure. I think that's the next big thing is that the electronic health records? Let me know off today tend to be done to be large things, right? That that that's on the operating system of garden Health Systems. I think we it's time for us to a really interesting fact on what an electronic health record really is and how that that that needs to apply to this emerging models of care that we

are seeing and how do we leverage technologies that are cloud-centric that are in intimately tied to the agility. That is represented by the cloud and not digestible client-server architecture. Like we like you've seen over the past few decades the VA can can enable a clinician to use a mobile device and enter information? It's it's the workflow it's so they can work clothes on this person. Does this the screening set of vital signs of limitation goes over

there that that's inherently tied to the fixed facility mentality and adapting. The workflow is as much as as having a mobile entry device information. Attitude, it's a huge challenge. I mean, cuz it's it's hard enough to get the clinicians to use the thing correctly. When you do have them all in a in a fixed facility in combination. Actually, it's the combination of technology and that workflow that your afternoons, dr. Scott primarily, because Anythink of electronic health records. Today it is is if these are entities that are implemented within the walls of Health System,

they are implemented. So when you when you say that let's say you implement a care in the mission model Lycamobile health plan or something like that that is co-owned between one Health System in another partner in the community or something of that sort, right? It doesn't naturally lend itself to the same model that they even if they had their mobile device to actually Implement that enter data architecture, doesn't naturally lend itself to work and support across organization type partnership. Whereas a, an organization that is centered or negatively, a technology that is built on a

cloud natively built-in at out an application. Don't like that, you know, take Google Docs as an example, right? I mean, if you want, it share, it created like for this panel, my created a Google doc, and shared it with all of us. And then we were able to access it view it, edited things like that to be able to do that. With an electronic health record is like getting a root canal right now. It's all the policy that make sure the thing is, you know what, I legal document at the same time as, as

serving the date of needs at, that's it has to be flexible and and I'm, I'm probably in two of the most inflexible organizations. I wasn't DOD, I'm in VA now, incredibly inflexible because we're not only or not only have a covered entities were help. We're federal health records manager at Federal records manager, I completely agree. I think it's a combination of everything. It's the whole ecosystem that we've created around a fixed Healthcare. Liberty model that there needs to be needs to be a broader. We think of that

technology can eat a translator between with Mona leaves and and the human and open-source Technologies this week, we will bring you a more natural language processing through analyzing. I will have records from reacts to practice up as a change from Marine to work so we can get into people's phones at mr. I can kind of see approval process right now. We can synthesize with dogs so that they don't need to stand know. I was eating with thousands of pages of documents

for some of our members, but it can have How do I set up an? Because you're my dream car equity and the responsibility to make sure that all of his decisions are properly monitor them time and I have so something can talk without maybe New Year's or do we need to be put into an to replace the smaller lips that you think I get talked about? Got nnss rapidly accelerating the cycles of of sort of how quickly we've moved in terms of care, displacement, and digital engagement.

So I was planning on on sort of separating out digital engagement, but it came up so, nicely organically in the, in the conversation around Karen gate, displacement of care. I think we, we tackled a lot of it. So maybe that the clothes out the panel today, I'd love to sort of have 60 seconds from each of you sharing what excites you most, as you look out over the next year, as technology continues to advance and enable new Solutions Carol and maybe we'll start with you. You know, when we touch down a

lot of the themes related to the things that we are most excited about over the next year. You know, one of them honestly is more conversations. Like the one that we're having here today where we have health systems connecting with pears, connecting with the farm at Community connecting with position to be able to How we can advance the ways in which we look to data and how we align on the evidence that we get, you know, to drive better decisions you, we talked about things, like the displacement of care, and some of these other

Trends, they're here to stay. So less of all, I'm in terms of are looking to data to drive these decisions. Doing that in a systematic way. And it does feel like we are finally at a place where the methodology and the technology can keep Pace with these kinds of ideas. Dr. Scott what excites me most about the for the potential for the next five and ten years is is the revolution that is at hand with the patient being in control of their own data, right? And the

the legislation in the 21st century, cures act, and then when Cena rules and requirements of every Healthcare System to make an entire set of electronic information, available to the patient. What's the changes in culture and plus the technology that exists enable the patient to be the aggregator and the communicator of their information that with a with a patient control, digital space personal health record that is empowered to get information from any care provider and then aggregate that. So getting from our last generation sorts of tether personal health

records, to to ones that really are. What I'm talking about. I think is, is the opportunity. And if we fully seized that opportunity, it solves a lot of the problems we've been talking about because the patient in a bad creates the record, that's the complete record cluster, patient-generated A2, plus devices that are connected to cloud-based. And then they send it with the standard you're working on two to their Health Care system when they're going to have a health care. Visit, that's the opportunity but there's a

Challenges to that as well. The internet connectivity and some type of more sophisticated to push the buttons and do that aggregation and benefit from the data display that that sort of is the Achilles heel to what I'm talking about. But otherwise it is it helps a great deal and it and and enables care to truly be personalized when it's delivered that way. So that's what I'm most excited about. Sonic. Rights of Migrant. We talked about this for a for a while I already. So we find just finished

investment into our machine Learning Place from which we could flow in the eye and hand signals and data, the next year at a time for us to remember Sunday, when we talked about this way from the investment in to Homosassa grief, I will just made. And also interrupt our ability to lose coming to coming to action. I know all of this has been a perfect storm. Where will be able to provide way more actionable? Simple. As soon as I stir in the one that turned into Skype outcomes, Membership cost. Yeah,

I'm up. Gosh, I am most excited about the potential for transformation in our Healthcare System overall to make it more responsive to our patients and, and empowering our caregivers to really practice in a weight of medicine, you know, without being burdened by the administrative burdens, that the recent environmental changes have come to place on their shoulders. And and so that they have more time to invest in patient care. And I think the conversation said we're having today and more conversations, like this, that

need to happen across the industry and the the all the stuff that you're talking about the interoperability work, the ability to use technology more. So that information that is supplied to a caregiver the tasks, the administrative tasks that they perform at their end, our kind of absorbed by technology itself behind I need focus more on care delivery and the deer. The information they consume as meaningful and is, is curated through the use of advanced technology. I feel that's the calling of Our Generation as health

information, technologist, 10. And I think there has never been a place or time where I think there's a Confluence of technology and Readiness to embrace it. That that places us in a position to make that difference. So I'm hoping we can rise to the challenge. Read. Well, thank you all for spending your time, sharing your thoughts, extremely thought-provoking. I'm optimistic about the future here and I know that I'm excited and date of birth is excited to continue to partner with each of you on this journey. So thanks again and and thank you to our audience for tuning in.

Okay, thank you. And that concludes our entry for him. Thank you all for tuning in and make sure to stop by the solution, theater for interactive demos on the most popular data, and machine learning, use cases, and Industry, enjoy the rest of summit.

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