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January 24, 2022: Charles Boicey from Clearsense joins Bill for the news today. Truveta and LexisNexis Risk Solutions partner to advance health equity and health research quality. Traditional research rarely has access to social determinants of health or mortality data since 65% of people die outside the hospital. ONC publishes TEFCA details and FHIR roadmap. Trilliant Health discuss the data behind Z codes for social determinants of health. German Bionic releases new wearable AI robotic suits that boost human strength - taking human augmentation to new levels. And Bill and Charles put on their CIO and CTO hats respectively to discuss the clinical and IT labor shortage plus how do we create a platform and mindset of bringing the data and integration points together and setting it up so that the entrepreneurial community can innovate with us?

Key Points:

00:00:00 - Intro

00:07:40 - It's been challenging for medical research to include participants representative of the diversity of our country

00:10:10 - Mortality data is notoriously hit and miss

00:15:50 - HIN should collaborate with stakeholders across the continuum of care, to electronically exchange digital health information, even when a stakeholder may be a business competitor

Clearsense -



📍 Today on This Week in Health IT.

We have the data sets that we need, but they're all over the damn place and they gotta be brought to a single environment, because the last thing you want your data scientists to be doing is knocking on the doors of 60 subject matter experts to get that particular dataset. And it's a pain in the butt because I got to go to the lab person. I got to go to the pathology person. The EMR person. I get the data that I'm looking for. I'm working and things are going well. And now I discover I need a different data element and now you're back to the well. So having everything in one place is absolutely essential to making all this work.

📍 📍 It's Newsday. My name is bill Russell. I'm a former CIO for a 16 hospital system and creator of This Week in Health IT. 📍 A channel dedicated to keeping health IT staff current and engaged. Special thanks to CrowdStrike, Proofpoint, Clearsense, MEDITECH and Cedars-Sinai Accelerator, who are our Newsday show sponsors for investing in our mission to develop the next generation of health leaders.

All right. It's day. And today we have Charles Boicey CTO for Clearsense online. Charles, welcome back to the show.

Thanks Bill. Glad to be here.

Today we're going to talk about the news, but some people aren't familiar with you. So I want to go back and forth a little bit about Clearsense. Some of the work you're doing right now, you're doing a lot of different things. Let's start with Clearsense. What does Clearsense do? What's your role at Clearsense?

Sure. So Clearsense came out of a healthcare organization called Optimum Healthcare IT that did primarily implementations optimizations. And about eight years ago, they came up with the idea that, Hey data machine, learning analytics is going to be the next thing in healthcare. They brought me on to help to start the company. And really we are a healthcare data platform from the ground up.

And we really make it possible for products that we've created as well as products that our clients have created to take care of problems now, as well as take care of problems in the future. From just your basic reporting dashboarding, et cetera, to advanced analytics and data science and what we do better than the rest is we're able to grab all of the healthcare organizations, data, assets, both internal and external, both streaming as well as static and put them into one place. So they're accessible by all.

Wow. But that's not all you do. You're also a professor.

Oh, yeah. Now we're talking about me. So yeah, I helped develop the analytics elective program for Stony Brook Medicine. So healthcare applied in informatics and I teach the data visualization in introductory data science, as well as technology and healthcare.

And you also just finished coming back from India. What were you doing over there?

Sure. That was really interesting. And I will tell you that India has done a phenomenal job with testing, vaccination, as well as therapeutics for those that do come down with COVID. I was there working with representatives of the health ministry and whatnot putting together a platform so that they can do federated research. So researchers can be anywhere within India access the combined dataset from of all of the patients in India, for purposes of research and finding therapeutics. And so.

Sometimes people say to me Bill, I don't know how you get all the things done you get done in the day and all the things you're producing and all that other stuff. I feel that way every time I talk to you, because that's just the tip of the iceberg. You also mentioned you're doing some stuff with with the university of Arizona. What are you doing over there?

Sure. So the University of Arizona has a aerospace surgical fellowship. So as we send more folks into space, we're going to we'll get.

The eventuality that things are going to happen. We've been sending absolute specimens of excellence in space. It's going to be the common folks and whatnot, and there's going to be a need for surgical intervention, whether it be robotic or whether we have folks that are actually placing lines and doing procedures.

So the University of Arizona has put together a really nice fellowship program to get them folks ready for that. And I'm just taking care of the streaming data aspects of it, as well as the analytics components.

Data. Data science. So here's what I did for this week's Newsday show. I pulled a bunch of stories that are related to data. I figured since I have you on the show, we might as well just hang out there for a little bit. The first story is the Truveta story. You're familiar with Truveta, new company, a new platform, if you will. Here, let me just read some of this.

It's actually a press release, Truveta and LexisNexis Risk Solutions Partner to advance health equity in health research quality. And it says Truveta. The health system led company with a vision for saving lives with data and the healthcare business of LexisNexis Risk Solutions.

That's hard to say. The leading provider of healthcare optimization data in patient linking technology today announced a strategic partnership that will improve the quality of all health research enabled new insights on health equity in our country. For the first time daily clinical data from over 16% of all clinical care in the US will be linked together across health providers and then integrated with 40% of all Medicare and Medicaid medical insurance claims. 70% of all commercial medical insurance claims, social determinants of health on every American adult and comprehensive mortality data in one data platform for medical research. They start off with health system led. So it's, it's a whole bunch of companies that come together at the JP Morgan conference. I think we heard Bon Secours Mercy. Providence obviously is in it. I think Trinity is in it.

I think I think Northwell's actually in it as well. A bunch of them shared that they were a part of this. So it's a lot of fairly large health systems bringing their data together. They've now partnered with LexusNexis and they're pulling up all this data together. That's the first paragraph I'm going to read some more, but when you hear that aspect of all those things where they're bringing together, is there anything like this today?

Not that I'm aware of. And the really importance of this Bill is from what I understand is that all races, all ethnicities will be represented. So it's really, really important that they get a true population, a true data set within this. And it's not just one particular region, one particular race, one particular ethnic group that it really is a diverse data set that we can actually use to to, to advance research and whatnot.

There are many like this, but they're all regional. This is the first that will be across the US but it's really important that it's absolutely representative of the population.

It seems like it is. I mean, if I don't have the list of health systems in front of me, but just the ones I rattled off. You have New York to Alaska down to Southern California and across to some of the Southern states as well. I know Novant Health, I think is also a part of it as well. So you really do have a lot of different areas and if I'm not mistaken, I vaguely remember the number, but it's somewhere between 15 and 20 some odd health systems that are participating.

So we're going to end up with an awful lot of records. Let me, let me give you a little bit of more detail to go. Improving the data, quality, underlying all medical research. And this is something I want to touch on with you. It's been challenging for medical research to include participants representative of the diversity of our country.

Right? This is what you're just talking about. Relying upon incomplete patient journeys viewed through the lens of only one of the many health providers we all visit throughout our lifetime. Traditional research rarely has access to social determinants of health, data, or mortality data since 65% of people die outside the hospital. The Truveta platform will now address all these issues, linking national clinical data, medical claims, data, socioeconomic data and mortality data using the LexusNexis patient-centric token which de-identifies as any dataset and allows it to be securely connected to the right patients across name and address changes and misspellings while preserving patient privacy. There's an awful lot there. Can you break some of that apart for us? What the LexisNexis patient token and de-identifying. What are they doing here?

Sure. So this is really important and this is the ethical and responsible use of healthcare data. So from me as a researcher, I don't need those identifiers and I really shouldn't have those identifiers. But in the course of my research, if I make a discovery, if Bill, if I find that you're from a genomic perspective that you're susceptible to, let's say Alzheimer's in the future or just from your clinical picture, let's say I'm building a diabetes type two predictive model. And I look at all the data on you and you're already a diabetic type two patient. It's just undetected or undiscovered if you will. So from a research perspective, it's always been a complete dissatisfier.

When you do find something untoward, as far as the patient's concerned and you can't get it back to that organization. So this will allow that information to get back. And what they're telling you is that they're doing all the requisite, they're taking all the requisites steps to ensure that privacy is protected and so forth.

It's interesting. Let me ask you this cause one of the biggest challenges, they talk about social determinants of health, data and mortality data and one of the biggest problems has always been matching data, which is what they're trying to address here. But it's also disparate data, right? So we're going across all these different health systems and data is brought in a little differently. Social determinants data has been hit and miss in terms of it's being collected. Mortality data is notoriously hit and miss. As an example, did you die with COVID or did you die of COVID?

Those are two different things and that's why we get some differences in terms of the overall numbers of mortality. If you were bringing this together, how are you going to, we use the word normalized data, but I'm not sure that's the right term here, but how do we get the data to be usable and trustworthy?

Yeah, from a right sizing perspective. Social determinants, we can get those down to the street level. Within healthcare organizations, we've built these great surveys and whatnot that are seldom filled out or not filled out properly. And Nielsen does it better than anyone, as far as social determinants. They've been collecting that data for years, there's for each individual, there's up to 35,000 different data elements that you can look at. So taking those commercial bringing that in. The universal from a EMPI perspective and whatnot, putting that tech into place so that as people jump around, address has changed using place like TransUnion for address reconciliation.

There's a lot of good tech out there that can help healthcare properly, put this together. And then from an ontological perspective ontologically right-sizing ICD codes snomad RX, norm Link and so forth. So applied technology to this is what they're going to be doing. So at the end of the day, we have a common data model, if you will, and data that can actually be used from a universal perspective, regardless of whether it comes in from Cerner, Epic, Allscripts or wherever.

Charles. I mean they're linking this data LexusNexis and Truveta. I'm thinking about this. This is for research, right? This is de-identified research. We're looking for cures. We're looking for equity issues and those kinds of things, but isn't this kind of data when combined extremely powerful for the health system. We've often talked about getting to the point where it's like Amazon. Where we can make recommendations. Where we know the patient well enough to actually partner with them on their health and say, Hey here's some things you want to consider.

And we start to take in other data, like device data, and we take in shopping data and that kind of stuff. And we start to make suggestions. If they start off in this direction. I assume they can't you know take this data and start using it in their CRM and being more proactive with the patients directly.

Well it's possible if they do from a contract perspective, they stick within the the confines of the individual organizations that they've contracted with and they can provide that 360 view, if you will back into the healthcare system. I mean, they would do the the combines of the social determinants and whatever they might combine and then push it back out so that when you pop in the clinic I've got a 360 view of you. Not just your clinical picture, but you know, the other determinants that makeup Bill. 📍

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I'm looking. All of these stories overlap a little bit. It's really, it's really interesting. Our next story is the ONC publishing the TEFCA details and it includes a FHIR road Give you a little bit of this. With the ONC for Health IT January 18th publication of the trusted exchange for it to TEFCA large health IT networks will soon be able to apply to become qualified health information networks as part of a nationwide data exchange. ONC also publish a roadmap outlining how TEFCA will accelerate the adoption of FHIR based exchanges across the country. And it has Micky Tripathi here. Nationwide health information network exchange has been part of the ONC vision since its founding in 2004.

And this was Micky in a briefing to reporters. I think it is also part of everyone's intuitive sense of interoperability, but it's important that information is exchanged securely and reliably. He added that's what we're able to begin with the implementation phase of TEFCA today.

It is through the consistent vision and dedication of many natural coordinators. And he goes on to tip his hat to some of the coordinators. I know, I was looking over here at some of the documents in here. So now what you're going to have is you're going to have these health information exchanges that utilize FHIR.

They have some principles they want them to follow. They want them to start using standardization. They want them to be open and transparent with the parts of their practices. They want cooperation and non-discrimination, this is an interesting one. HIN should collaborate with stakeholders across the continuum of care, to electronically exchange digital health information.

Even when a stakeholder may be a business competitor. Yeah, I find that one interesting. And then they go on privacy, security, safety access equity, and public health, or some of the other principles that they have around this. How is this going to change how we bring data? I mean, a lot of this has been point to point over the years. Are we going to see that evolve and change? Is that the direction we're going?

That's the direction where I'm supposed to be going. That's the direction that's intended to go. And again, what's hampered us in the past is the competitive nature of healthcare. It is a thing. We'll see what the participation looks like, Bill. I've always advocated for a national HIE if you will that's legislatively mandated. To me, that's the end goal, but let's see if this is a next step FHIR from a resource perspective. From a tech perspective is a lot easier to deal with and what we're dealing with from a HIE perspective with the CDAs and whatnot.

So from a get and put tech perspective, this is an excellent path forward. For I just stated before for normalization, for standardization, this can actually happen, but we need everybody to participate. It's like autonomous cars. It doesn't work very well unless it's done completely. We didn't do ICD 9 to 10 incrementally.

This really needs to be done where everybody does participate because non participant that's a break in the link, chain if you will.

Yeah, it's interesting to me, Charles, because I say these two stories overlap, but they're two parts of the same story, really. I mean, you have a bunch of health systems coming together and saying, look, we're going to bring all of our data together for the good of research and whatnot. And before we think too highly of them for a phenomenal valuation of the company Truveta. So it is an investment. In all the JP Morgan presentations.

It was in the investment section and the innovation section. So I mean, granted there is a mission aspect to it, but it's also, there's a financial aspect to it. But with that being said, they're bringing all this data together. They're linking it with LexusNexis which by the way, I think you and I talked about at least five years ago, it must have been eight years ago now. We talked about this whole, this whole concept. If we could bring all this data together, how powerful it would be to impact the health of a community by giving us more touch points in between visits and more informed touchpoints, right?

So we're not just sending blanket messages out to people. We're actually getting to closer to that N of 1 that, that personalized message to the individual in your community to help them live a healthier life.

And that truly is healthcare Bill. What we're providing now is sick care. They're only coming to us when they're sick. We're not really providing health care, but as we go forward if you think about this from a national perspective, and then again with your aura ring and all your wearables and whatnot, actually helping citizens through the day to maintain health.

But that sort of. So Truveta's sort of a private direction. A private solution that's trying to solve this problem. The ONC is the public solution. They're saying, okay, we're going to take all this federated information. We're going to bring it together around a set of standards. And that's going to be the through FHIR. They're going to bring it together and through the common data model, but essentially that's the public facing. And to a certain extent, these could be in competition with each other.


Yeah. If I'm investing in Truveta and all that data now also becomes available through the TEFCA framework and it can be accessed by entrepreneurs and others. You're going to have competitors be able to rise up. All they essentially need to do is tap into that data. And also LexusNexis. There's competitors to LexisNexis. They can go in a couple of different directions there. But anyway, that's a public and a private way of bringing that data together. Let me go to this one, cause I find this story interesting and it sounds to me like a case study or something you would you do in your class. And this is Trilliant health published this. The data behind Z codes for social determinants of health. Let me give you some of this. It was well established that social determinants of health drive 80% of health outcomes. Okay. So that's pretty common knowledge at this point, particularly for identifying barriers to care, determining necessary social care and both financing and facilitating delivery of appropriate resources, even so STOH specific z codes which are poised to address this gap in care have been under utilized. Primarily because of administrative burden and lack of provider awareness. Okay. So you have that challenge. They go on to talk about C codes, which can be used in any health setting, by any provider type collect data on economic, social, and environmental factors.

Right. So education literacy, employment, housing, food security, occupational hazards in October, CMS issued a report on STOH Z code claims, limiting their analysis to fee for service Medicare among their findings. CMS reported that although Z code claims accounted for 0.1% of all claims the most frequently used Z codes were related to homelessness disappearance and death of family member problems raised to living alone problems related to living in a residential institution and problems in relationship to spouse or partner.

And they, they go on a little bit. Building on CMS's analysis we quantified use of Z codes nationally in other payer populations, commercially insured, Medicare advantage and Medicaid. Our analysis considered Z code claims from January, 2017 to 2021 and CVS with populations over 200,000 as of 2020 with any examine three SDOH related characteristics. Housing insecurity, food insecurity, and poverty level in those same CBSAs to rank the markets based upon Z code to utilization. Interestingly, the most frequently used Z codes in this analysis were problems related to unwanted pregnancy, other specific problems related to primary support group problems in relationship to spouse or partner homelessness and problems related to housing and economic circumstances.

This really does sound like the kind of thing that that you would teach in your work in your class, right? You, sort of take all this data and say, okay, I mean, what can we learn? What does this data tell us? What can we learn from this data?

And Bill, we call this exposome data on the academic side. So this is your exposure to everything outside of the, of the healthcare organization. Let's say we build, and this is how we use it. Let's say we're going to, again, we'll go back to your predictive model for diabetes type two. We have all the clinical information and we get a certain level of efficacy with that model, we then combine that with the social determinants of that specific population and that specific geolocation. And then we actually enhance enhance that model, that predictive value of these Z coated social determinants is quite high. And you mentioned that the big ones around food deserts ability from a transportation perspective income level and then the others, the high rates of pregnancy for this particular age group in this particular geolocation. So absolutely is essential and they absolutely do boost this work, but what's more important is this has to get back into that clinical workflow or it's pretty much.

So let me ask you this. As I talked to CIO's our data and analytics capabilities have improved through the pandemic because we were asked to do so many things. But what's required to do this kind of work? Is it additional datasets? Or is it different skills than what we currently have?

What do we have today that we can use? And what are some of the things we're missing in healthcare organizations today, with regard to our ability to do this kind of, kind of research?

Sure. Let's look at it from a team perspective. Masters level or PhD data scientists most likely does not have the requisite health care skills.

So surrounding that team with the requisite analysts and subject matter experts to keep them on track and keep them moving forward then from a data perspective you need to be able to put these datasets together with these social determinants, so you can do the work that I just described.

And it's really important from a geo perspective that which was built in Orlando is not going to work well in Seattle, Washington. S o teams that understand that whatever the exercise that you're going to partake in and whatnot that you understand this isn't a one size fit all.

So again, it's, I think we've talked about it in the past. It's that robust data science team, if you will, with its combination of data, scientists, analysts clinicians and so forth that really understand the clinical picture operational or financial picture as well as what's needed from a data side to get to that point.

Do we have the data sets we need at this point?

Yeah, here's the interesting thing. We have the data sets that we need, but they're all over the damn place and they gotta be brought to a single environment, because the last thing you want your data scientists to be doing is knocking on the doors of 60 subject matter experts or subject matter people. And I'm kind of being exaggerated a little bit to get that particular dataset. And it's a pain in the butt because you deal with that. I got to go to the lab person. I got to go to the pathology person. The EMR person. I get the data that I'm looking for. I'm working, and things are going well. And now I discover I need a different data element and now you're back to the well. So having everything in one place is absolutely essential to making all this work.

All right. So Charles, I'm going to go off script here. You and I have done a couple of episodes where it was CIO, CTO, sorta going back and forth on things.

I'm hosting some CEO's at an event. First event we're putting on at This Week in Health IT. It's not a huge gathering. It's a small gathering just to figure out what we can do together. And I've talked to each one of them individually over the last couple weeks.

And I said, all right, so what are the biggest challenges you're facing? So your, my CTO. I'm going to, I'm going to throw out some of the challenges they gave me. You consider what we could do from a technology standpoint or how we could approach these things. So the first one is staffing.

So it's from two perspectives. One is we have a shortfall of clinical staffing somewhat because people are getting sick with COVID. They're actually in the bed next to the patients that they used to be caring for. And so we have a clinical shortage and then we have an IT shortage. Is, is there some ways that technology can be applied to this problem?

Yeah, it's called the problem falls under what's called operational research. And that is an operational problem. Fortunately right now we have what two years worth of data that we can actually use for this exercise.

Now, I'm not going to say that the outcome of this is going to be what we expect. We may get to a place that's not any better than a flip of a coin, as far as how, how to staff, who to bring in. But we do have the ability to, from a data science perspective to, to run these types of exercises.

And I've done this work in the past prior to COVID and whatnot. And you don't just look at it from staffing, an individual RN or an individual pharmacist or an individ. Well, what's their skill level, what's their background? And what's the best combination of those folks on a unit at any particular time to be as highly effective as possible?

Do we have to expand the scope now? Are we looking national and then looking regional and then looking local to really understand the landscape and what's going on.

Oh, I think this is, is, is very much regional. I'm going to put it out there. That's my original hypothesis that I think things are a little bit different in New York city than they are in Southern California or here in Florida, I think there's legal aspects, there's organizational policies and state policies and so forth that have to be taken into consideration as well.

Yeah it's interesting. So let me ask you, I'm not going to get down to the cybersecurity route. Clearly that's top of mind for some of these CIOs. Let's talk about digital platform. So during the pandemic, a lot of digital initiatives were I don't want to say launched. But they were scaled faster than we ever have scaled them before we saw you know bots go into play. We saw some analytics things goes into play and whatnot.

But telehealth, this is what everyone talks about. But now we're sort of looking at it going, Hey, we, we didn't do this from a platform perspective. And now we have to step back and we have to think through how we're going to get into the clinical workflow, how we're going to be able to innovate quickly and bring all that data together from these disparate digital systems.

How important is it to start with a platform and a mindset of bringing the data together and the integration points and setting it up so that the entrepreneurial community can innovate with us? I mean, how important is that, or can we just bring these various applications together after the fact?

No. I think that platform first that's kind of what we do. And the reason for it, bill is from a healthcare organization perspective, all of these different applications that need to be brought in you end up with an air traffic control problem of what to bring in first. And you can only bring in so many at a time. But with a proper platform to connect all this then you basically have the plumbing taken care of, and you're just putting these various applications on top of the plumbing and ensure that they're interoperable. Your boss should be part of your conversational agent programming, whatnot.

So there's no reason why these various apps that we put in for, from a COVID perspective, they absolutely should be able to communicate with each other on this platform. And from a research operational research that we just described, or even clinical research from a, just a straight organization perspective, it's important that this is all on a platform. Otherwise you're going to be delayed, delayed, delayed, and producing results.

It's all about agile, but also being able to respond rapidly. But if anything, we learned through the, through the pandemic, you don't know what's coming next. And our ability to respond quickly is going to be one of the things that differentiates one system from another.

And in order to do that, you have to have thought through the architecture before you move forward. So I sort of asked the leading question I believe.

No. And you have to ensure yourself that this platform is absolutely as future-proof, as, as possible. And the other thing you as a CIO, I would say, Bill do not sign a three to five-year contract with your your bot folks or this, that, or the other thing sign one year contracts that I'm telling you, the advancements that are going to be made by potentially by competitors and whatnot. You're going to want to jump from one to the other because you don't want this stuff to pass you by, but from a platform perspective, if you've if you picked the right technologies and whatnot, then you can change modules, change components out as it advances improvements come forward. Because you don't ever want to replatform your platform.

Yes, But we've all been there. Haven't we.

So I'm going to close with this story and I pulled this story out because it's such a nerd story, and I like to nerd out with you. So this is a robotic suits, supercharged human workers, and I figured you would appreciate this. Part human part robot, all business, this new wearable robotic suit can boost human strength.

It is powered by artificial intelligence. Taking human augmentation to new levels. German bionic just announced an exoskeleton called Cray ex with a plethora of features. It includes assisted walking, waterproofing and an updated energy management system. The AI based system can send alerts to users regarding ergonomics and safety.

Not only does the exoskeleton give users a power boost, but it has a brain too called the smart safety companion. The AI based system can send alerts to users regarding the ergonomics and safety. German bionic has been providing back support for heavy lifters for some time reports, smart industry employees at companies like BMW and IKEA have been wearing earlier versions of Cray X, but the new version has assisted walking supports to body regions and add 66 pounds of lifting power.

This is interesting to me. I mean, I've seen the exoskeletons have been around for awhile, but if this ever gets mainstreamed, it's it really will change the nature of some of the jobs that did.

Well, I guess Bill, since I'm a nurse with my exoskeleton, I won't need too many peers to turn a patient I guess, or transfer them to a gurney to a bed. And with COVID, we're, proning a lot of patients. So I guess instead of having five of us proning a patient, I guess two of us could do it.

My concern with an exoskeleton is my body. My body can only do so much. If you put an exoskeleton on it, is it going to push me beyond what I can or does it help me to make sure I don't go beyond what I can.

Oh, I think it's it's to make sure you don't hurt yourself. That's how I look at it.

Yeah, it'll be interesting. I, I like these stories. I think they're interesting. And just sort of a snapshot into what the future could look like. If I'm a baggage handler for an airline that's something I could see. Picking up those bags, moving them all day. If you have something like this, it could reduce the strain on your body from that repetitive.

Again from a gurney to a bed or from a bed to a wheelchair, whatever that might look like. Maybe, maybe this will work. Yeah. Lower back, lower back strain.

Lower back strain. Charles. Thanks. You came off the airplane came right to the show. Completely jet lagged. You've been in airports and airplanes for the last, what? 40 hours.

42 hours Bill.

42 hours to get from India to Jacksonville. There you go, man, I'm sure there's a story in there in and of itself, but that has to be for another time. Thanks again for doing this. I know it's been a busy couple of days. I look forward to the next time we get 📍 together.

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