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It's Tuesday news day and here is what we have on tap.


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Welcome to this week in Health IT News, where we look at as many stories as we can in 20 minutes or less that are gonna impact health. It. It's Tuesday Newsday, and here's what we have on tap. Livongo and Health Catalyst went public and we look at a C N B C, uh, news story around that. Uh, grocery bills can predict diabetes rates by neighborhood m i t technology review.

Looking forward to that one. Uh, let's see, I, I've got about 10 stores here. Tennessee creates e h r. . Task force to address health it needs, uh, and many others. We'll see how many we can get to in 20 minutes. My name is Bill Russell. We're covering healthcare, c i o, and creator of this week in health. It a set of podcasts and videos dedicated to developing the next generation of health IT leaders.

I. I've had an executive coach for about two decades now, uh, and it's been invaluable to have someone in my corner. Um, I started this service about two years ago for health, uh, through health lyrics, and, uh, it's been fantastic. I've coached, uh, health system CEOs, CIOs, uh, startup CEOs, um, service providers who are looking to make their mark in healthcare.

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Send me feedback and questions, guest recommendations. You name it. Bill it this week in health And subscribe to our newsletter, uh, or our daily or other things that we have on our website. So let's get to the news. Livongo shares surge, uh, in market debut as digital health space heats up. Christina Farr, C N B C News.

Uh, let's see. Livongo Health shares surge as as much as 62% in their stock market debut on Thursday, the latest sign that public investors are buying into digital health trend the company provides well, diabetes services. . Uh, to large employers, a space that's attracting big dollars in the quest to ultimately provide better coverage and bring down costs.

The i p O has been touted by the industry as a potential benchmark for other startups that sell disease management services to large companies and health systems. Uh, Livongo was joined by Health Catalyst, a, a distributor of data analysis tools to hospitals, which also hit the market on Thursday and gained as much as 56%.

Livongo raised over 350 million in their offering while Health Catalyst brought in 180 million backed by, uh, Microsoft and venture investors. Livongo is part of an emerging group of companies using technology tools like coaching to Bid. To and a bit to improve health outcomes. The company connects to, uh, smartwatch.

Uh, they're open, they connect to Apple, Fitbit, uh, to deliver nudges, uh, provide, um, uh, feedback and to, uh, remind people to take, uh, or to eat certain things or do certain things. Uh, so coaching, nudges, those kinds of things. Uh, let's see. Raquel said in 2018, digital space raised $8.1 billion. So, uh, that's. Uh, good for the space.

Uh, after its debut, Livongo is worth about 3.6 billion. The company price shares at 28, uh, and then immediately rose to close to 40, uh, which is I think where it's at. Uh, well, I'm recording this a little early, so it's, where it's at right now is right around 40. So, uh, the company said revenue, uh, more than doubled.

Uh, to 68.4 million from, uh, a year earlier while it's lost, widened to 33.4 million from 16.9 million in 2017. So, what, you know, you didn't tune into the show for a stock pick, so I'm gonna avoid that part of the analysis. Uh, these are two companies with very different strategies and they're telling you very different things.

The fact that they're raising money in this space, I guess, generally tells you that . Um, there's a, uh, market rock that rock health information would tell you that, um, you know, the, uh, the Livongo, uh, solution is really around, uh, chronic conditions and digital tools around the chronic conditions. Um, they're open, they plug into a wide range of other digital tools, which, uh, become a part of their ecosystem.

Uh, the thing that Livongo brings is deep healthcare knowledge and experience. So instead of going to Apple, who has, um, really understands the digital tool set and the digital, uh, space, IoT and those kind of things, uh, Livongo sort of piggybacks on some of those things as well as their own . Tool set. Uh, but they allow those companies to, uh, play at a little deeper level within the, uh, healthcare space and specifically around those chronic conditions.

Uh, Livongo has expanded from diabetes. They're now looking at hypertension and some other things as well. Um, you know, I, I think this is a, uh, you know, they talked about it being a bellwether and it probably is. It's gonna . Um, it's gonna tell us if there is a market for these kinds of digital tools, because once you go public, there's no hiding.

Uh, we're gonna know how well they're doing. We're gonna know, uh, what their market penetration is. We're gonna know, uh, what their, uh, profit and loss are. So everything public means public. So we're gonna get to see these things, uh, up close and personal. And, uh, I believe there is a, a real space for this chronic care management, uh, using digital tools and IoT type tools and Livongo's at the forefront.

Let's see how they do. Let's hope they do well. Uh, it would be nice to see, uh, uh, an advancement in that area. Health catalyst data and analytics play among other things. Um, they also have the ability to be a, a, a agnostic platform for a set of APIs, which I think is, quite frankly, is a bigger play. But, uh, that's just my 2 cents and, um, uh, and I, I, I really do think that they have the ability to be that non e h R play.

That gathers data from across, uh, different sources as well as, uh, social determinants, data and some other things which we'll talk about a little later. Um, and then provide a set of APIs and, and to build digital tools on top of that. So, um, you know, these, these two stocks are going to be an indicator for us.

Uh, You know, if nothing else right now, they're an indicator that investors believe in this space. They're investing in this space, and they're putting money into this space. That's good. It's good to have the money. It gives us the ability to innovate. It gives us the ability to try new things and to see where they go.

So, um, I. You know, there's a side note here, and the side note is there's a, there's a bunch of health systems that made Betts here. They made Betts, uh, by either investing early in Livongo and Health Catalyst, uh, or later in, in, in either of those players. Um, and they're, they're some of the big winners this week.

They're, uh, they're going public is an event. Those events, uh, lead to cash, that cash goes directly back into those health systems. So, um, I think you can look that up pretty easily. I did not prefer this episode. . Uh, but I do know some of the players that did invest in Livongo. I know some of the players that did invest in Health Catalyst and, uh, those health systems, uh, just got a windfall.

So that's, uh, pretty exciting. Let's go to our next story. So, grocery bills can predict diabetes rates by neighborhood. This is, uh, m i t technology review. Let's just dig into it. So, uh, better way of studying eating patterns and their health effects is desperately needed. Enter Luca Maria Aiello. . And Nokia Bell Labs in Cambridge, UK and colleagues who have studied diet and, uh, studied diet by mining the data from grocery bills and then compute, uh, then comparing it with the population's health as determined by medical prescriptions issued in that area.

The power of their approach comes in the sheer scale of the work. The grocery bills come from Tesco, Britain's largest grocery chain. This company's database contains every single food item purchased in London, in, uh, in London stores during 2015. Okay? The medical data is publicly available data set that every single prescription written by general practitioners in London during 2016.

The scale and granularity of the analysis is . Unprecedented. It says i l o. Uh, Tesco has 411 shops in London, uh, used by 1.6 million customers with loyalty cards who bought 1.6 billion food items in 2015. The data set includes each item, its weight, the date, and the customer's postcode. So that has their zip code, tells us where they live.

Aiello, uh, and company extracted, extracted the nutrition content for each item. Including to total energy, fats, saturated fats, carbohydrates, and so on. They use this, uh, to work out the average nutrition nutritional intake for 937 neighborhoods in London. This is a pretty fascinating study, uh, and, and really great analysis.

Uh, the medical prescription data is also available, uh, for at the neighborhood level. Lenders were prescribed 1.1 billion medicines in 2016 from which the team inferred the conditions they suffered. The researchers were particularly interested in the prevalence of metabolic syndrome. Conditions, which are characterized by high blood pressure, high cholesterol levels, and high blood sugar levels.

The data revealed the distribution of these conditions across the city. Finally, the team compared the data sets to see how nutrition correlates with metabolic syndrome conditions, and then mapped out the results across the city. Um, you know, the maps are fascinating. Uh, they show as expected that increased consumption of carbohydrates, fat, sugar, and pos, uh, is positively correlated to metabolic syndrome.

While increased fiber intake, uh, negatively correlated, they're going, going to show that, um, that item weight. Which is a proxy for caloric consumption is also positively correlated with metabolic illness. Uh, there's also important difference between London neighborhoods. The wealthy and highly educated residents in the city of London and Chelsea consume more fiber and have greater nutrient diversity.

By contrast, residents of Newham, uh, a relatively deprived neighborhood consume more calories and less diverse nutrients, and they have higher levels of diabetes, but healthy areas are not necessarily well off the residents of Hackney. Which is a deprived, yet highly educated neighborhood in East London.

Enjoyed healthier eating habits and do not suffer from diabetes as much as new ham's, residents says IO and company. Uh, the, the team goes on to predict the levels of high blood pressure, high cholesterol, high blood sugar in the neighborhoods, merely by looking at the local calorie and nutrient consumption.

Indeed, they say the classifier can identify unhealthy areas with a 91% accuracy. Uh, Y this is interesting work, you know, and each one of these stories with sort of a, so what, um, you know, this is a great use of technology, great use of data, great, uh, analysis. Uh, here's my question. I, I'm gonna end instead of ending with a, so what I'm gonna throw a question back at the innovators in the community that are listening to this, um, I think about this and I'm, I'm thinking about another innovation that happened.

You know, what's the equivalent in health . To the rear window breaking light, you know, that third light that we put in the window, um, you know, allow me to go a little bit on this for a second. Uh, in 1974, psychologist, uh, John Esky PhD tested a small, inexpensive gadget. He took this other, he took this light, put it at the bottom of the, uh, rear view window, and he equipped 343 San Francisco taxis with that third braking light, which is so common today.

We know exactly what, uh, what it's referring to. Um, and then they rotated the drivers. They didn't give 'em the option. They did it for about 10 months. And what they found is that 60.6% fewer rear end collisions, uh, than the controlled group. Additionally, drivers in those taxis with the third braking light, uh, were struck in the rear by other vehicles were injured, 61.1% less.

Um, we know that distracted driving killed more than 3,300 people and injured 421,000 in 2012, according to the US figures, a third braking light provided an extra signal of four distracted drivers. Studies confirm that it reduced automobile accidents. So how much did it, you know, the, the, uh, national Highway Safety uh, administration, uh, took that study and, uh, expanded it and found that, uh, it reduced rear collisions by 4.3%, uh, which, uh, doesn't sound like a lot, but it, it, it equated to 60,000 fewer injuries, 600 million less than property damage a year.

Uh, and so forth and so on. You know, I usually do answer the question of, so what? But this time I'm asking the question. I see clearly how this, this food data, how this mining of grocery data, uh, can be used for surveillance. But I. What I'd like to see is the data and a set of digital tools that operates as like the third breaking light.

You know, somehow it's uh, it is able to help those communities to live healthier lives. So it's the combination of the medical data that prescription data. Uh, the food data that we take in and any other data, you know, whole Person Care requires a whole person profile. That whole person profile, while has some risk associated with it, uh, with regard to privacy, uh, has a significant amount of benefit if used correctly.

Um, I don't know what the solution is. I'm not offering a solution. I, I don't, uh, I don't have a startup in the back of my head that says, Hey, here's where this all goes. But I see the combination of that data, the combination of digital tools, uh, going in a direction that could be really beneficial. And I use the third breaking light as sort of an example of sort of a passive kind of thing that sort of, uh, reminds us, hey, oh yeah, I'm trying to live healthy.

Oh yeah, I. Um, you know, this, this kind of, uh, activity is, uh, not going to lead, uh, where I want it to lead. So I leave you with that challenge. Do with it what you can, and please let me know what you're, what you're thinking as you sort of move, uh, move down the, uh, that path. I would, uh, I would jump all over this kind of, uh, research.

I think it's, uh, invaluable and . The whole person profile is the only way we're gonna be able to, to deliver care, whole person profile, behavioral change, uh, nudges. Um, this is the only way we're gonna be able to deliver real health change, uh, in our communities. Uh, third story, uh, Tennessee creates e h r task force.

I think this is worth looking at. It's, uh, very interesting. So, Tennessee Senator. . Todd Gardenhire Garden Shire Gardens Shire was recently appointed to the chairman of the state's E H R Task Force. To help provide increased clinical efficiency, cut costs, and reduce, uh, instances of potential fraud stemming from abuse of the State's Medicaid program.

The task force was, uh, partly born out of frustration for high rates of provider dissatisfaction with the E H R technology. Uh, let's see what he says, uh, when electronic health records was first introduced by the Obama administration 10 years ago. . They were promised to streamline the health records process for doctors and patients by keeping all of the patients' health records in one place.

In a portable form, Senator Gardenhire said in a statement to the Chatted Newgen. However, the EHRs have fallen short of their promise and to have resulted in more headaches. For many doctors and healthcare professionals, garden Shire continued. I look forward to leading this task force as we work to identify ways EHRs.

Can help more efficiently utilize in Tennessee hospitals? The first thing I would say to Mr. Gardenhire, the Honorable Senator Gardenhire, is, um, it wasn't the Obama administration, it was the Bush administration. It's sort of a combination. No one really ran away from this whole idea of digitizing the medical record.

Uh, the Bush administration really, uh, ca was the catalyst for starting it. The Obama administration came in and looked at it and said, . Yeah, we've digitized every other industry in, in the world. Let's continue doing this. And this is what we're finding. This is a nonpartisan issue. Uh, this is an issue where we have agreement, and the agreement is that healthcare needs to be digitized.

Uh, we just need to do a better job of it. So thus, the task force is born. Um, let's see, what does he say? So rather than saving time and money, the cost of the E H R continuing to grow. . Despite the $36 billion spent, uh, by the federal government on EHRs, and technology is often implemented in hospitals with detrimental bugs that can fall on the hospital to incur the cost of fixing, uh, explained officials, uh, officials that are part of the task force.

According to an article published by Kaiser Health News, I assume this is the Death by a Thousand Clicks article, have, uh, EHRs have also opened the door for fraud and abuse, some of which . Is costing Medicaid and state administered Medicaid programs. They added, uh, fraud and fraud and abuse are not, uh, a direct result of digitizing anything.

Uh, fraud and abuse are a direct result of people, people using that technology. Uh, people with either nefarious, uh, intent or, uh, ignorance, one of the two. But, uh, digitizing it didn't, uh, make it any more or less prone, uh, to being, uh, open to fraud is, I think what you're going to find. Uh, people are the ones who commit fraud.

Uh, that's number one. Uh, number two, um, . Yes, absolutely. This stuff has been implemented in hospitals, uh, across the country. There have been some, uh, horrific stories, uh, of how these have been implemented. They're very complex, uh, implementations and some have gone well, and some have gone very poorly. That is a true statement.

Uh, the task force will collaborate with national healthcare experts to review E H R use in Tennessee on a national lever level. Senators, uh, John Tester and Marsha Blackburn. Uh, in the story we covered, uh, a couple weeks back are working to implement E H R Task Force Charge with providing third party oversight to monitor the VA's multi-billion dollar Cerner E H R implementation.

The senators introduced the VA E H R Advisory Committee Act. In April to help VA maintain transparency and stay on task as it deploys the e r system at facilities across the country to boost care quality for more than 9 million veterans. The new E H R uh, system is too important to Veterans Healthcare for the VA to get it wrong.

So tester ranking Mender member of the Senate Veteran Affair Committee, our bill will create another layer of accountability and oversight. Uh, of the process to make sure the VA rolls out, uh, rollout does right by the 9 million veterans who will rely on the system. Okay, so what I've commented in, in the middle of this, but, so what, you know, this is, this is actually a tough one.

Um, is this necessary oversight? Uh, I, I'm gonna fall , I fall squarely on the maybe category. Maybe it is. Uh, I'm not, I'm not opposed to it being set up and I'm sort of curious to see where it goes. Um, uh, you know, I would hate to see one of these started in each state. I'd like to see where Tennessee goes.

Uh, let's, let's see how, let's have some oversight. Let's see where it goes. Let's see what values derived. And let's see, sort of what they come up with. Uh, you know, anyone who's been in the industry for a, for a while, anyone who's done one of these implementations, uh, can, uh, can probably give you an indication of what you're gonna hear and what you're gonna see.

Uh, but it would be interesting to see what they, uh, what they come together with. Um, you know, another, so what I'd hate to be the C I O for the va, actually, I'd love to be the c i O for the VA because I think it would be a wonderful way to invest your life. With that being say, said the, uh, do you need double oversight on the VA for their implementation of the E H R?

Um, No, I don't think so. I mean, the, you know, I've never known an E H R implementation where the user satisfaction rate is above a B minus on the day it goes live, and usually it hovers around a C or, uh, even a D level, uh, that day you go live is the lowest customer satisfaction you're gonna have. Uh, you know, that's the bad news.

The good news is it goes up almost immediately because you're, you're, um, Because it's so complex, because there's so many moving parts and there's so many things to get right, and there's new users that you're training and, and you're implementing new workflows, uh, there's a lot of things that are changing when you implement that much change.

If I went into your home and started moving your furniture around the first day, even if I did it perfect, perfect. Feng shui. . You would hate it the first day. Too much change, too much workflow and those kind of things. That's just natural when you implement that much change. It's just natural to have that level of dissatisfaction.

Now, if you still have that level of dissatisfaction six months later, a year later, two years later, uh, then the IT team is not doing their job. Uh, so from a, the C I O for the VA standpoint, . I wouldn't judge 'em on day one. The, the, the basic block in blocking and tackling has to work on day one. You have to be able to, to, uh, to, to, uh, deliver great quality care.

You have to be able to track that care. You have to be able to share the information. You have to be able to move data around. You have to be able to support the workflows. All those things are important on day one. They're not gonna be perfect on day one, but they, they are important to do well on day one.

Um, with that being said, b c-level satisfaction with the system on day one is really probably all you can, can expect. Even if you were doing an e R P in a major manufacturing facility, it's not day one of go live is rarely, uh, you know, a time to do a victory lap. Um, finally, you know, this is, you know, this is just my personal here.

Um, I. We're, we're digging a, a, an ever-growing hole. We have too few vendors in this space. So you have Epic, you have Cerner, you have Meditech, and maybe a handful of others. I mean, every thing I see, it's like 30%, 28%, 20%. So, uh, you have fewer vendors. Anytime you have fewer vendors, you're not gonna be able to innovate fast enough.

You're not gonna be able to, uh, uh, improve the system fast enough, uh, to create a better user experience for those physicians to create, uh, innovative solutions around it. Um, my thing that I would like to see the government sort of press in a little bit on. Um, although I, again, anytime the government's pressing in on, um, all in a free market economy, it gets kind of dangerous.

But I'd like to see them press in a little bit on is opening these systems up. I'm not, I'm not against these, uh, systems that have, uh, these companies that have created these very complex systems that have done great work and employ . Uh, you know, hundreds of thousands of people, uh, they've done great work.

They should make money from their solution. I'm not saying they shouldn't, I'm saying that their system should be open. We should be able to get the data out. We should be able to do, uh, innovative things. On top of that data, we should even be able to plug into that user interface and change that user interface.

Um, because I think , that's one of the problems with these systems is it's take, it's taken them three years to I, they're still not there. They still don't have web interface for a lot of these solutions. It makes no sense. Everything is web-based today. Everything needs to be web-based today. Um, and it shouldn't take, shouldn't take five years to do it.

And if we open up those systems in, in some way, I believe that, uh, U H C innovation move faster, I think you'd see, uh, some of these problems that are discussed here, uh, move a little quicker. Um, and, uh, and actually if I were, if I were at Epic, Cerner, or Meditech, I would be, uh, chomping at the bit to open those up.

I would open 'em up because you know what, Microsoft won the game, uh, a long time ago because they allowed other players to write applications on their, uh, on their solutions. And the minute that those three players understand that they are platforms and not applications, not an E H R application, but a, a healthcare platform.

They're, they're off to the races. They're, they're gonna win the game, but until they do, they can keep trying to, uh, fight to hold onto their space. Uh, I think it's a mistake. I think they could, uh, they could grow immensely if they were to act more like platforms and less like applications. I. I can't believe I've already, uh, three stories in 23 minutes.

Anyway, uh, that's all for this week. Um, to, you know, don't forget to check out our Friday interviews this week. In Health, it influence, uh, so many interviews, so many great insights. Uh, we do this for you. Hope you're enjoying it. Uh, hope you're getting value out of it. Uh, keep the comments coming. Bill it this week in health

Good, bad or indifferent, it all helps. Uh, this shows a production of this week in health it from work. Great. . Content. You can check out the website this week,, uh, or the YouTube channel at this week, Uh, you could click on video to get to that, uh, as well. So thanks for listening. That's all for now.


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