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Welcome to this Weekend Health. It's Tuesday News Day where we look at the news, which will impact health it today. . We are gonna take a look at, uh, a digital transformation article that was written by Jeffrey Moore, the author of Crossing the Chasm. And it really sets a, a great framework for discussion around digital transformation.

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It helps me to prepare for the show, and this is a service of Drex to Ford, a frequent contributor of the show. Alright, our first story, digital transformation behind the scenes. Jeffrey Moore, author of Crossing the Chasm. If you're not following this guy on LinkedIn, I, I highly recommend it. What he does is he gives us frameworks for how to think about things.

And in this article he talks about digital transformation. It's not specific to healthcare, it's more broadly for many industries. But what he does is he starts with a graphic and he lays out the industrial product era on the left side and the digital services era on the right side. So in the, to just give you an idea of some of the back and forth here.

So, industrial product era, demand exceeds supply, digital services, era supply, exceeds demand, industrial focus on supply chain. Digital focus on the customer. Industrial Six Sigma quality programs, digital user experience. User design, if you will. Uh, user-centered design. Industrial era. Internet changes everything.

Digital era, cloud and mobile change everything. Industrial B two B enables B two C. Digital B two C enables B two B. last one. Uh, although there's others. Last one system of record in the industrial era gives way to, in the digital era, systems of engagement. And then he goes on, there's a couple more here.

the first thing he notes is that no matter what happens, we're building off of the industrial area. We're not getting rid of those things. Like you wouldn't stop focusing on your Six Sigma program or your lean program. Uh, you wouldn't stop focusing on supply chain. You're just starting to invest a little more heavily in things that are going to be customer focused, things that are going to take the friction out of the interactions with the consumer.

So even as we're talking to bringing this practical down to healthcare, even as we're talking to our EHR providers, they respond to us. We tell them this is what's important to us, and they respond to it. As we start to move away from the system of record. And really focusing in on the system of record and start to focus in on the system of engagement.

We should be informing our EHR providers that we want more tools that look like X, Y, and Z, which form our basis for engaging the population. 'cause at the end of the day, until we figure out a way to engage people in between the times they're sitting in front of a doctor or they're in our acute care facility, we're not gonna be able to impact the health of the communities that we serve.

So that . That is one of the ways, and, and actually all these other industries, they're trying to figure out how to increase the number of touchpoints between the time you're say, in a car dealership and the next time you're in a car dealership, they want you to become a Tesla person or they want you to become a.

Mercedes person because you're interacting with them often because they're updated. They're actually starting to create their, their cars, even as ways of engagement. There's more tools on that screen, and they're trying to figure out how to get you hooked into their overall service experience. And that's the same thing that's available to healthcare.

Uh, so some of the things he, he goes through a list of things and, and it's not a complete list, but a partial list, . Of some things that are distinct to the digital era. And so he goes, the first thing is it's born in the cloud, not in the data center, right? If you're gonna be in a system of engagement, if you're gonna be creating things that are gonna touch a lot of consumers, you need to be in a place that's, UBI has ubiquitous access.

It's born in the cloud, it's born on the cloud infrastructure. It's born on cloud economics, so it's born in the cloud. Second thing, customer system of engagement, not standard systems of record. So we need to be thinking in those terms. Third thing, focus on convenience and ease of use, not security and reliability.

He goes on to say, not that you would not worry about security and reliability, but he's making the point that we need to move fast. And sometimes when you move fast, you make . Mistakes on the reliability and security side in, in deference to the need to move fast, because if you don't, you might become irrelevant, uh, in your markets.

He, uh, makes that point. So focus on convenience of the your user. He then goes on to talk about consumer apps, not ISVs and SaaS applications, right? These are applications that are built and designed around the consumer, engage the consumer. Find out what they're looking to, how they're looking to engage your system, and then provide them those tools.

Incident response, not technical support. This is an interesting point that he makes. That we're not always gonna know what situation and where. As we start to go into this consumer facing app kind of thing, we're going to end up in a situation where we're not gonna be able to anticipate all the scenarios that are gonna be coming at us.

And so we end up with more of an incident response, which we're all very used to now with C-O-V-I-D and the wildfires and other things. It's that same kind of response model that we are moving towards instead of a tech support, uh, help desk kind of model. Second to last, empower the people, not empower the system.

Right? So you're not, you're not focused as much on how do we empower our health system? You're focused on how do we empower our ? You can start with the clinicians and the care providers, but also how are you gonna empower the, uh, consumers and the, uh, patients that we serve. And then finally, agile, not itil.

And I know a lot of people think that's just a buzzword that Agile is just a buzzword. Really look into, I'm not gonna have time in this show to really go into it. Look into it. It is important. It's not, and it's not that it o goes away, but agile methodologies, thinking, thinking in a way that is about speed and, uh, movement and constant iteration and working code is the best.

Uh, metric for, are you going to deliver? I still am running into people that are waiting to see code at the end of a project and I say, no, no, stop right there. You should be seeing code all along the way. In fact, you should be seeing code within the first two weeks that you kick off any software development project, even if it's just the log a working login screen so you can look at it.

And you can respond to it and say, no, that's not gonna work for us. We need dual factor authentication, or we need to be integrated. If you're looking at code, it's the best way anyway. Agile is not only in that way in software development way, but also in, uh, response to system outages and those kind of things.

Agile is just a better method than a lot of the things we have traditionally done with Waterfall. So he goes on to say, Hey. This is just a framework for conversation. It's just what I think. What do you think? And I'm gonna put that same thing out to you. I'm gonna give you my so what, but what I wanna hear from you is what do you think?

I'll probably post this article out on LinkedIn, start a discussion around it. But, uh. , but generally my So what on this is systems of engagement. So systems of record, we're used to those. Our EHR is fundamentally a system of record. Now we're moving to systems of engagement. This is gonna be built on APIs and mobile applications and some web applications, but more and more it's gonna be mobile applications.

That's how we need to be . Thinking, but that's gonna give ways to systems of intelligence. And for systems of intelligence, what we're gonna need is clean data that we can train computers, that we can train systems. And we need to be, start thinking about that clean data. Do we have clean enough data to train the, the computers, quite frankly, the technology to start to recognize patterns and those kind of things.

So that's the first story. That's my So what I'd love to hear your so what on this? It's, uh, Jeffrey Morris . The, uh, author, it's out on LinkedIn, digital Transformation behind the scenes. Loved it. I loved it. Hope you, hope you like it as well. Let's see, next article. Alright, as you can hear, I have a lot of construction going on behind me still, so you're gonna keep hearing that.

Uh, our next article is Ohio State. Wexner has partnered with One Medical, and I found this to be interesting. I think this is a, this is one of those things, . That we are gonna see over and over again in this digital era, and that is partnerships in, in pursuit of moving faster. It's not that Ohio State doesn't have the resources to build out the capabilities that one medical brings into their market, it would just take them multiple years to do it.

Right, so they partner with One Medical. If you're not familiar with One Medical, they have a, let's just call it a clinic platform so they can roll out clinics that are high that have a very digital, uh, frictionless experience. For the, uh, consumer, sort of, you make the appointment, you walk in, it recognizes you're there, you go straight through to the room.

Again, you're looking at large screen tea, large screen monitors that they're walking you through things. They have a very, let's say, 21st century kind of experience built around their, uh, clinic, uh, visit. And so what Ohio State did is, I'll just read, this is actually a. A press release from Ohio State, so it's gonna be a little fluffy, but, uh, the partnership will provide central Ohio residents acro access to one medical's modernized primary care model, which supports seamless access to Ohio State's network of highly ranked specialists, ambulatory facilities, and hospitals.

One medical's membership based model combined 24 by seven on demand access to telehealth services, paired with convenient in-person care, in addition to direct. . To consumer membership, more than 7,000 employers have sponsored memberships on behalf of their workforce. Together the two organizations will aim to achieve greater clinical integration and deliver exceptional value to consumers and employers.

And then it has a quote from their CEO about transforming the health system. Actually, this is worth reading. Let me, as an academic health center, we are focused on transforming from a health system to a comprehensive health platform to provide innovative care. And I. Delivers unparalleled experiences for all those who look to us for care across Ohio and nationally.

So think about that. There's two. Some people might say there's two buzzwords in there, but I don't think they're buzzwords. I think it, what it frames up is how Ohio State is thinking about their health system. They're looking at it as a health platform, which means that they have to facilitate a transaction that is frictionless.

They have to facilitate a transaction where the data moves around the system. They're actually creating a platform where the user experience becomes central to how things function and how things operate. They're starting to design, first of all, around a a platform. and around experiences. So I think that's, uh, important.

My so what on this, quite frankly, is there's gonna be times where you need to move faster and you just partner. It's not that Ohio State does not have the resources to do this. They're a world class academic medical center, and they have the financials to support it. They have the university that has the technical

Actually, we might as well just say it for the next five years on this show. I'm gonna be telling you that consolidation's, uh, a major theme and it, it will be until we, we get, uh, to the St. Elmo's Fire of Scale. Economies of scale is what we're always searching for. If you're not familiar with St. Elmo's Fire, it's a, I actually don't really know it.

From the Agency for Healthcare Research and Quality. What's my so what on this? My so what on this is, it's gonna be a little bit of a curve ball in that I think there's an opportunity here. I don't think that providers that is independent, uh, physician practices are partnering with health systems because they want to, I think they have to.

I think they have to get access to patients through contracts. I think that's one aspect of it, but I think the other is just firmly on, on our doorstep, which is the cost of the technology aspects and the sophistication of the technology aspects, uh, of being in healthcare has gotten to be too excessive for the independent physician.

Think about the security. The security budget alone is challenging the EHR customization. . Is significant and let alone the EEHR implementation. Itself, any kind of digital tools that are gonna be required as well as access to, uh, AI and some new capabilities, uh, they're gonna find themselves just from a sheer budget standpoint, falling behind on a daily basis.

And I, so I don't say that to be negative. I say that to say I think there's a business opportunity here. Anytime you hear something like that and you go, oh, they're falling behind. They don't wanna do something, but they have to do something. If somebody can come in here with a technology platform that gives them access to advanced analytics, a, a high functioning EHR, that's customizable to the, uh, physician practice, ways to engage their consumers to, to create, again, I keep saying this, you know, reduce the friction of the transactions and, and, and

And I think more of them would stay independent. So there is an opportunity, there's an opportunity for, for some enterprising organization or group to come in there and say, we're gonna create a platform specifically for independent physicians and independent physician practices. That's my So what on that, curious what you think on that, uh, GoodRx files to go public.

Boasting a track record of profitability. . All right. So I like GoodRx. Our family uses GoodRx. I think it's, uh, if you don't know what it is, transparency for finding the, uh, lowest cost on prescriptions in, uh, in your local market. I think it's a good thing. I, I don't understand why it's not something that's just.

Provided when the physician writes the script. To be honest with you, when a physician writes a script, it should, it should have the, the, the script right there. And it should have not the close. You chose this pharmacy, that's where we're gonna fill it. It should say, here are the three places you can get this filled and here are the prices.

I think that should be standard. And actually there are some health systems that do that. That's not an original idea with me. Uh, I know that we're seeing that more and more. Uh, I think it was, uh, St. Luke's outta Bethlehem had it, and I'm sure a couple of others do. Anyway, the other aspect of this is that the I-P-R-I-P-O market in healthcare is pretty hot right now.

So past 12 months you saw the vango Freesia Health Catalyst Change Healthcare A one Medical GoHealth Progeny, Amwell. Any others are missing? I can't, but there's a lot of them, right? So there's a lot going on in this space. The thing that makes GoodRx distinct, is it odd, but they have, the revenues are up and their profit is up.

Well, I, to be honest with you, I think it's gonna be a lackluster IPO and the reason is because, uh, I think it's 'cause of that profit. I wish they were reinvesting that profit and what's next outside of their transparency into . Medications. I'd like to see some other tools be coming along and what's in the pipeline.

And quite frankly, profits are not, for whatever reason, are not really valued in today's IPO market. More of what's valued is your investment in the future and and being ahead of the game, so there's an op opportunity there. But speaking of success stories, . We have, Livongo is going to co-create a new digital and clinical care experience across behavioral health continuum with Magellan Health.

This story is just downright fascinating to me, and I shouldn't say story. This is a press release. I'm pulling this straight from the Magellan Health website. So here it is. Magellan Health, one of the nation's leaders in behavioral health today announced a strategic relationship with Livongo. The leading applied health signals company, empowering people with chronic conditions to live better and healthier lives, making Livongo for behavioral health available to Magellan Health customers and their members as a digital entry point to a wide range of Magellan Health and Livongo Solutions and Services.

Alright, so there you have it. Again, this is one of those partnerships, the, the partnerships are about moving fast. And here's what I read into this. I don't know anything, I'm not on the inside of this, but Magellan Health probably had a problem. They had a digital problem. They didn't have a way to engage their consumers.

They didn't have a way to grow based on a digital platform. So they stepped back and said, how do we get there? Or Livongo approached them and said, look, you're about to get your lunch handed to you by a handful of really good competitors that have digital capabilities. They were digital first. And behavioral health second, eh, that's, that's a little harsh, but they had behavioral health capabilities, but they thought about it first from a digital standpoint.

And, uh, there's a handful of those companies out there. We've even had multiple of them on the show to highlight the digital nature of behavioral health and how it works together. So LivOn in, in steps, Livongo and says, look. . We know how to engage chronic patients. We know how to engage patients, we know how to engage health systems, and we can create, we can be your digital front door and we can help you to, I'm sure Magellan could have hired people.

I'm sure they could have built it out over three years. You don't have three years. So at some point they have to step back and go, partner, we're gonna partner with Livongo. We're gonna go from being. In last place in this whole, you know, spectrum of behavioral health companies that are digital to leapfrogging and potentially, uh, taking a lead just by, uh, partnering with the right provider so that I don't wanna do two.

So whats about partnership? So how about this as a, so what, which is behavioral health is a significant deal if you don't have a, a behavioral health partner that is digital first. Uh, be looking at that. Try to figure that out. That is something that your health system's gonna be looking for probably in the next 12 months to, to bring that to bear.

All right. There's a, I don't usually do these kinds of stories and I really haven't vetted it. It makes me a little scared to go into it 'cause somebody's going to, uh, somebody is going to vet it and come back to me. But I wanted to, uh, cover it because it was really well written and done. But it's a, uh, PhD candidate out of, um, Australia.

Okay. Luke Oakton, Rainer, I. Radiologist, PhD candidate out of out of Australia, as we said. And what he did is he goes into this whole aspect out, and I know why I wanna share this, I wanna share this, because he lays an awful lot of responsibility for AI not being adopted in health systems at the feet of the CIOs.

So that's the first reason I wanna go in that. The second reason I wanna go in that to this is because we need to be following reimbursement very closely because it will dictate where technology goes, especially in this AI and machine learning space. Alright, so he starts with, it's widely known that the medical AI community that has, that it has a troubled marketplace for AI developers.

Okay. Medical AI community troubled for AI developers. Uh, majority of companies have developed useful AI models, but they've been unable to sell them. This has led many predictions that we're going to see a crash amongst medical AI startups, and I've heard that same thing, an AI winter, if you will. Uh, to be clear, this has never been a problem of technology.

I agree. I think we have a lot of really good . AI solutions that are out there, but on the clinical side, it takes a long while to get these things in place because they have to be proved out. They have to be, they have to be vetted, just like any other clinical process that we're going to be embedding.

Deep learning works, and there are lots of ways that it can be applied. Usefully in medicine, it was an alignment problem. The people who procure medical technology, the CIOs are motivated by business needs not, but not by how useful the model is. So he lays this entire thing at the CIO's feet. Actually, as I'm reading this again.

You should just read system because I'm, I don't think the CIOs are really selecting an AI platform for clinical decision making and that kind of stuff, and thrusting it on the system. I think it's the system that's making that decision and when the system makes that decision, he's making the case that the business needs trump the efficacy of the, of the clinical results.

And I would also make the case on this that the clinical results. Are far from vetted at this point, and so we are at the early stages of some of these getting funding and being vetted. Alright, so he goes, the strongest business incentive is money, earning more and spending less and providing AA models can help, can help here, can help here.

Obviously whenever there's an incentive, it drives behavior. and, and that's really true for health systems. He actually shares a story. And again, I haven't looked at this story in detail, but somebody, one of my listeners who's, uh, smarter than me who's looked at this, I'm talking to you, David sma. He, he goes on to tell this story and, and it's around radiology.

So reimbursement is how medicine incentives actually. Help people. A central payer, whether a government or insurance company decides what medical management is cost effective to improve health. When a test or treatment is reimbursed, then healthcare providers get paid and use it. All of a sudden, CIOs are really, systems are really excited.

Pay some money to a company and get much more money back for using a product. Does it work? Well, it, it turns out it does work. This is his example. I've spoken about mammography CAD before an old form of AI intended to assist in detecting breast cancer. This became popular in the two thousands when CMS decided to reimburse CAD aided mammography test.

A provider would get about $10 more if they used CAD than if they did a standard reading. Within a decade, almost every screening mammogram in America is read with CAD assistance. But you say maybe it, they just used it because it was amazing. Nope. It didn't work. Again, these are his words and I, I would love one of my listeners to, uh, help me with the story.

In fact, nobody else uses it. I've never found an exact number, but CAD use outside of the USA is particularly non-existent. Why? Because it doesn't work. And you don't get paid for it. Just think about that. Medicare has spent hundreds of millions, if not billions on a technology which didn't work driving widespread use.

Financial incentives are powerful and dangerous things, so financial incentives are a big deal. . Absolutely. So in the context of this, he talks about the company that's getting this a thousand dollars per patient reimbursement v AI with a product called Contact, C-O-N-T-A, capital CT contacts. Uh, ct. So what they do is, let's see, vis AI claims by reducing the time specialist to review the CT scan of possible blockages, they prevent long delays during which time more and more brain cells are dying from lack of blood.

They have published few papers on the topic here and here, and had provided a fair bit more to CMS to justify this claim. So CMS is ready to support their to reimburse based on this ai. And the way that they got CMS to reimburse it. They had, and again, this has been a while in the making, it's 20 18 40 page document.

I. . These things alone are interesting. He goes on to say, these things alone are interesting, but rely purely on the existing knowledge that delays lead to worse brain injuries. As the saying goes in strokes, time is brain. But vis AI didn't stop there. They actually did the thing I always harp on about.

They showed outcomes improved. Modified Rankin score at discharge, improved NIH stroke score at day five, and improved MRS at day 90. He went on to, to state that once this came out, not everyone was real happy on social media and other things. I, I, again, I shared this story for two reasons. One is it's interesting that he laid the entire thing at the feet of the CIO.

I don't think that is, I think that is a, a miscalculation on his part. But the second is. that if I were ACIO I'd be keeping an eye on reimbursements. Reimbursements are gonna drive what I'm gonna need to have in place, and I'm not sure we're ready for this level of ai. I'm not sure we have the data to support it.

I'm not sure we have the systems to support it. I'm not sure we have the skills and capabilities to support it. And if the, if they start reimbursing it, our systems are gonna be knocking on our door saying, Hey, we, we need to participate in this. This is a thousand bucks per patient. Let's get in front of this.

So anyway, thought I'd put, that's my so what on that is, uh, get ready for some of this stuff. And I think your EHR provider will help in some way, uh, but in other ways you're gonna have to, uh, figure out what gaps are gonna exist and fill those gaps. Let's see. Uh, here's a quick one. Multiple workers fired at George after George Floyd's medical records improperly accessed.

And I just, I share that to say not all attacks are external and we have to remain vigilant internally, and it's a politically charged environment. There's a lot of incentive. There's a lot of incentive financially too. If you had George Floyd's medical records, you probably sell those to fill in the blank and get that information out there ho.

Hopefully people know by now that every click in the EHR is monitored, but for those who don't, who happen to be listening to the show. Every click in the EHR is monitored. And when I say every click, every click, we know what you're doing in the EHR and we have to, it's just part of what we do. Let's see.

Right? And he goes on to talk about that. We have a lot of frameworks for determining if AI is fair and we all we have to do is look at the laws that are already in place. We can look at the equal, uh, credit Opportunity Act, civil Rights Act, fair Housing Act, equal Employment Opportunity Commission. We can look at those things as frameworks and structures where we get into trouble.

It's when we use things as proxies. I, I'm really summarizing significantly here when we use things as proxies. Let me see if it occurs. Seemingly, it occurs when a seemingly neutral variable like level of home ownership acts as a proxy for a protected variable like race. What makes avoiding disparate impacts so difficult in practice is that is often extremely challenging to truly remove all proxies for a protected class.

And so that's what we're trying to do. See, it's sometimes not even clear what the most fair decision really is. In one study, Google AI researchers the seemingly beneficial approach of giving disadvantaged groups easier access to loans, had the unintended effect of reducing these this group's credit scores.

Overall, easier access to loans, actually increase the number of defaults within that group, therefore, therefore, lowering their collective scores over time. To me, this was just a, it, it was, it, it was interesting. He, and he does go on to say it's really complex, right? Despite all these complexities, however, existing legal standards can provide a good baseline for organizations seeking to combat unfairness in their ai.

But we have to know what the algorithms are. . He goes on to say, first regulated companies must clearly document all the ways they've attempted to minimize, and therefore, to measure disparate impact on their models, they must, in other words, carefully monitor and document all attempts to reduce algorithmic unfairness.

And uh, second thing is regulated organizations must generate clear good faith justifications for using the models they eventually deploy in fair methods existed. If a fair method existed, they would also have also met the same objectives. Liability can ensue. Okay. So, uh, again, this is a, this is actually, it's not a long article, it's just a hefty article in terms of.

Of what it's talking about. Here's my so what on this? We used to have it governance, then we went to data governance, then we went to fill in the blank governance. Uh, I think the next thing we're gonna have is we're gonna have algorithm gov governance. So we're gonna have what we'll call it something else, we'll call it our ai whatever group or our whatever.

What we're gonna be looking at in that group is anywhere we've introduced where computers are making decisions. We're gonna be evaluating, is that decision right wrong? Is that decision fair? Unfair? We're gonna have to create this level of governance where we're looking at the algorithms. So first, that's gonna require us to understand the algorithms and we shouldn't be buying software that we don't understand the algorithms or building software, that we don't understand the algorithms, but we're gonna have to collect that information, bring it before that governance group is gonna have to be able to look at it, because quite frankly, you're gonna have to document it anyway.

At some point you're gonna get an audit. I don't know from who. But you'll get an audit from somebody on your fair practices of using that data in the care of patients. . . So that's gonna be an important metric. So I think that's the So what the, so what is, do you have a, an algorithm, governments, that's an awful name.

You'll come up with a better name. But you get the idea, the group that's gonna be looking at how computers make decisions with how chatbots interact with, with your patients, how we made those decisions. You don't want the technology group making that by themselves. Actually. You don't want the clinicians making those decisions by themselves.

Uh, you, you probably want ethicists. Ethicist, ethics Ethicist. That's right. Ethics. People at the table talking about, uh, you probably want diversity and, uh, representation at, at the table to, to talk about, again, the bias that's readily available or readily transparent. Okay. That's enough of that. The, I think the last story I'm gonna leave you with.

Halamka is moving. He's having some fun, and I don't know, it's just John Mayo's been doing some great work for a while here, but, but this has John's fingerprints on it, so I'll share it with you. Mitre partners with Mayo Clinic Nuance on common data elements. So if you remember the conversation we had a little while back.

With, with Anish Chopra, he talked about the, the fact that we, the Cures Act gives us an opportunity to self govern, to identify the data elements and to bring those standards forward as health systems. And if we don't, what's gonna happen is the government's just gonna keep setting 'em. They're gonna set the floor, they're gonna keep raising the floor unless we do this ourselves.

and he gave the example of the energy sector, which did this on their own. And then the banking sector, which did this on their own. So those two industries that did this on their own. But healthcare has yet to really produce any of these, uh, data standards that, that have gotten traction across multiple health systems.

In walks this. This partnership, which I think is a huge step in this direction. The McLean, Virginia based nonprofit organization announced a partnership with Mayo Clinic to conduct research and development on common data elements for oncology, cardiology, and c Ovid 19. The collaborative research will further the development of platforms for intelligent automation, including M Code and M card, common data standards for oncology and cardiology to improve quality and coordination of patient care.

If some of this stuff is of interest to you, I, I think there's an opportunity to expand. The, the data sets use across the industry, and as we do, that will become the defacto standard and eventually the, the standard for the use of data sets across oncology, cardiology, and c Ovid 19, which as would just be a huge benefit for combating this pandemic and addressing some of the extremely challenging conditions that, uh, present themselves in oncology and cardiology.

So, uh, I think that's enough for today. I have another 15 stories, so you'll have to come back next Tuesday and, uh, keep checking back on the, on the LinkedIn feed. I'll drop a story a day, get this discussion started and just see what you guys think. That's all for this week. Don't forget to sign up for clip notes at this week.

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