Charlie Harp is joined by Logica’s Chair of the Board, Stan Huff, Chair of the Nursing LOINC Subcommittee, Susan Matney, along with Clinical Architecture’s very own Chief Informatics Officer Shaun Shakib and EVP of Client Services Carol Macumber to discuss the history and impact of Logica on the Healthcare IT Industry. In this first part of The Informonster Podcast’s first two-part series, they discuss Logica’s growth and accomplishments, and how, even with COVID-19, Logica gets the medical community to leave their “silos” and buy in while remaining nimble and responsive.
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Thanks for listening!
Charlie Harp is joined by Logica’s Chair of the Board, Stan Huff, Chair of the Nursing LOINC Subcommittee, Susan Matney, along with Clinical Architecture’s very own Chief Informatics Officer Shaun Shakib and EVP of Client Services Carol Macumber to discuss the history and impact of Logica on the Healthcare IT Industry. In this first part of The Informonster Podcast’s first two-part series, they discuss Logica’s growth and accomplishments, and how, even with COVID-19, Logica gets the medical community to leave their “silos” and buy in while remaining nimble and responsive.
Contact Clinical Architecture
• Tweet us at @ClinicalArch
• Follow us on LinkedIn and Facebook
• Email us at informonster@clinicalarchitecture.com
Thanks for listening!
I'm Charlie Hart. And this is the info monster podcast. This episode is part one of our two part series on logical health with me here today. I have Sean Shakib Carol McCumber, Stan Huff, and Susan manmade. And what I'm going to do is I'm going to go around the room and ask you guys to introduce yourselves. You know, a lot of people know you guys, but this is an opportunity for those that don't to get to know you a little bit and just tell us about what you do and how you got into this in the beginning. And anything else that you think might be interesting to people. So let's go ahead and start with Dr. Hough. So as Stan Huff, I'm the chief informatics officer at your mountain healthcare and also the chair of the board of logic. And, you know, I got into informatics immediately after my clinical pathology residency. And my special interest has been in how you represent medical data and information in a coded and structured way so that you can execute computable algorithms against that information. And so I'm excited to be here today and visit about logic and other things that are going on. Well, we're excited to have you on the podcast and thank you.
Speaker 2:Hi, I'm Susan Matney and I'm a nurse slash medical informaticist. And I have been a nurse informaticist for over 20 years. And I went to the nursing informatics program at the university of Utah because I liked computers. I didn't have any idea what I was getting myself into really, but I had developed, I was over the labor and delivery units and I developed a delivery log in FoxPro clear back in the FoxPro days. And when I was a director of nursing and Moab, I keyed in all of the pharmacy drugs. I was over the pharmacy for the billing office to be able to have average, wholesale price, average retail price. So I really liked computers and that's why I went into informatics. And then I right out of school, started working for Stan and learning terminology and modeling. And that's what I've been doing. My whole career. I am the chair of the nursing like sub committee. I'm the past chair of the snowman nursing working group. I'm the vocab facilitator for clinical information modeling initiative at HL seven. And I sit on the[inaudible] terminology authority with Carol everything, terminology and information modeling is what I do. So I'm happy to be here and talk about it.
Speaker 1:Thank you, Susan. It sounds like you're a pretty busy lady. I am. All right. Speaking of Carol Carol McCumber.
Speaker 3:Hi, Carol Machamer. I am, uh, the EVP of client services at concur architecture. How did I get into informatics? Uh, I think I was finished with my masters in biomedical engineering and, uh, had a few more months in my fellowship, uh, at the university of Tennessee Memphis joint program, you know, in my copious spare time between making mix CDs for my fellow graduate students. Um, I applied for, I think every job that had the words, uh, medical and engineering in it and came upon a, uh, a terminology company called Apollon here in Connecticut and ended up coming out and serving as the first a workflow manager for the, uh, distributed offering efforts for MTHFR T back in the day for the VA. Uh, as Susan mentioned, I'm also on the atrial seven terminology authority serving as its vice chair. Um, and my current atrial seven vocab co-chair and a previous member of the, uh, technical committee at snowman.
Speaker 1:Thank you, Carol and Dr.[inaudible]. I am Sean Keith, I'm a medical informaticist and chief informatics officer with clinical architecture. I was a med tech in virology and I was sort of the computer nerd there, but I was doing all the evil things that we're trying to fix today. You know, I was building templates and server system for lab results, and I was reusing the codes just so that it got to the point where it printed out nicely. And I had no idea that evil I was doing at that time. But, uh, from there I got interested in the data and then crunching the data. Um, I got a master's in public health, and then I went on to do a doctorate in medical informatics at the university of Utah biomedical informatics program. During that time I was also working at 3m, um, worked with Susan Matney. Um, Stan was chair of my supervisory committee for my doctorate. Yeah, I've been doing this kind of terminology information modeling work for about 20 years now. Thank you, Sean. Um, and for those of you that are new to the infer monster podcast, I'm Charlie Harper, I'm the CEO of clinical architecture, a recovering engineer and general healthcare informatics miscreant. For those of you that listened to the podcast. I know we have different backgrounds of folks that listen, and if you're involved in healthcare informatics, you no doubt know the folks that are on this podcast today, if not, um, suffice it to say that the folks on the call today have all been, uh, pretty critical to moving things forward over the last several decades in healthcare, becoming more informed and more intelligent, more computable is a big part of what we need to do as an industry to make healthcare work better than it than it has. One of the things I want to start with is to talk about logic. And I think Stan, if you'd be willing to give us kind of the history of, you know, how logic has started and how has it kind of grown over the last several? I don't know, has it been decades?
Speaker 4:So logic? I hadn't been around for decades. Uh, I've been around for decades logic, uh, uh, actually started as the healthcare services platform consortium. And how it got started is that actually kind of interesting Intermountain was at a juncture where they asked the question, should we continue developing our own electronic health record system? You know, something we'd been developing working on for 30 years, actually starting back with Homer Warner or, you know, should we buy a vended system? And I was a proponent that we keep building, but building in a different way. And the different way that I wanted to do things was to create a service oriented architecture, where we could standardize the API APIs for accessing and using data. Those would be open and published and shared. We would then build with partners. So we would have a primary platform with the database, you know, security services, that sort of thing, but anybody could build applications that we could plug into that architecture. And at that time we were talking with Harris and especially Oscar Diaz who was at Harris and we presented that proposition to leadership at Intermountain. The long story short was I didn't win on an 11 to seven vote. They voted that. They just wanted to buy a vented system. And there's a whole, a whole story with that, that I won't get into. But what happened then is even though they wanted to buy a vended system, they really bought into the idea of this open ecosystem of app development. And so Oscar and I created, uh, the health care services platform consortium. Now Logica, it's a, not-for-profit actually a charitable, not for profit organization. And the mission is to create an open standards-based ecosystem of healthcare applications and services at the heart of what a lot of logic would do to create that environment is create the information models and related terminology. A lot of times we're not creating them, but adopting them. We're adding codes to link anchor, to snowman as we create models, but we're reusing the standards to try and realize that vision of Logica. And that vision has been helped tremendously by the emergence of the fire standard and other activities by ONC to create the U S CDI and, and really get from about recommending the use of LOINC codes and snomad codes for the representation of clinical data. So logic continues to pursue that, that vision as members, we have Intermountain the VA, a founding member that is now active, only as individual membership was Louisiana state university health in new Orleans. But then we have a number of both individual as well as corporate members. And we've continued to design a platform, progress modeling and terminology for those items created a developer sandbox where people can create smart on fire applications in a plug and play way and working on other relationships. You know, that's maybe more than what you asked for in terms of sort of how Logica got started, but good foundation, maybe for some additional questions.
Speaker 1:Absolutely. So when you think about the things that logic has done both under the HSPC heading and under the logic of heading, is there a particular example of something that you guys did that you think was a good example of the kind of thing that when you embrace this kind of open environment, you can accomplish something important.
Speaker 4:So there's a good example. It may be a good example because it's not perfect. So it's an illustration of exactly what we'd like to have happen though. One of our members was the OB GYN doctors, the American college of obstetrics and gynecology, and Steve Haisley, who was there, came to logic. He was a very active participant and said, we've got a contract with population health people in the government, um,
Speaker 1:Office of population affairs under title 10.
Speaker 4:Yeah, thanks Susan. That's a secret name so that people can't recognize that as a family planning division of the government. So they said, we're talking with people, we're trying to find out information about how, how we're doing, who's using our services, what they're using our services for. And so they wanted to develop a family planning, annual report, and they had a challenge. There are, I think, 4,000 plus family planning clinics in the U S no single EHR vendor has more than a hundred or so of those implementations. And so if they're going to collect that data, they truly have to standardize the data and they wanted to use fire APIs. They wanted to use standardize models and Susan and her team, Dan worked with Steve Haisley to create the data elements that, you know, describe simple demographic information, but also then things like sexually active. Do you want to become pregnant? Have you ever had a sexually transmitted disease? Have you been tested in the laboratory for those kinds of things? And so they developed a set of those codes and models. Then they created an application to collect that information and, you know, reading what was going on in the literature from the EHR vendors, they said, well, we're supporting fire. And, you know, we can support those data elements. So they hooked that application up to an Epic system and no errors, no warnings, they ran the application, it would go out and try to retrieve stuff and nothing would come back. There wouldn't be any errors, but no data would come back. The bottom line was when they got into that, you know, there were no mappings, the data existed. In some cases, some of the data just didn't exist because it wasn't collected in their system. But even the things that existed, weren't mapped to the correct loin codes or weren't mapped to any code. And so it was in a sense of failure, not because the technology wasn't good or that the idea wasn't good, but because we were too early and for the EHR to have really supported a robust implementation of, of the fire standard.
Speaker 2:I just want to chat a little bit about this since this is, you know, uh, clinical architecture, terminology stuff. We got the form from the office of population affairs. And the first thing that we do is we do analysis on the data to figure out how it's going to be coded. And there was things that it was pre coordinated that we had to break apart, things that were ambiguous, other things that there was real high levels. So they wanted to know, for example, if they had a positive or negative HIV test, well, if you go into LOINC, you've got more than 10 different types of tests that are HIV tests. And so we ended up making, you know, all the models for all the HIV tests. Sometimes what you see on a form is not at all what you're going to end up with when you get it standardized and encoded for interoperability. But to just elaborate on what Stan said, they didn't even get race in ethnicity. Now, this has been about four years ago, but race and ethnicity didn't even retrieve out of the systems. I hope I hope it would now because it's mandated. And then there's an article in Jamia that describes this whole process. So I'll stop there. Go ahead, Stan.
Speaker 4:I think the thing that the point I wanted to make is that it really illustrates the kind of solution we're trying to make. The idea would be that instead of each of hundreds of EHR systems, especially, you know, in the outpatient environment, there truly are hundreds of EHR systems that are in clinics and physicians, offices, et cetera. Instead of having every one of those organizations create a program for collecting the family planning data and then creating an interface to store that data into the EHR system and then creating a report to pull the data out, et cetera,
Speaker 1:The vision and goal is that you could create one smart on fire application. And if, if the vendors then supported the standards, both the data retrieval, you know, the fire standards, as well as the smart standard that allows those kinds of programs to be embedded in an EHR, they can truly have one program for collecting the data at one program that would submit the data to a registry or to the family planning population database. And it would be one thing that they could all use. I mean, literally it would be, you know, 1% of the cost and effort to create that application and use it across hundreds. And in this case, thousands of family planning clinics, that if you will, as sort of an example of, of what we're talking about, I'll stop there again. I can, I can talk more about the motivation about why we think that's so important than other things, but I'll, I'll stop there and see if there are other questions. No, I think Stanley made a great point. It's kind of a metaphor for the kind of thing we struggle with in health care all the time. Our nature in our history is very siloed and we all kind of toil away in our silos and reinvent the wheel. You know, the nice thing about what you guys have done and are doing with Logica. One of the nice things is that when you look at other industries, they kind of look at us funny sometimes and say, why are you guys making this so hard? Why is it so difficult in healthcare healthcare to inter-operate and to do these things, it's, it's a complex beast. It's highly critical. We have this data that lives in silos. It's a Herculean effort to try to shift from, you know, one EHR application or one platform to another. When you're trying to keep the hospital running and doing all the things you need to do, but we're never gonna make progress. If people aren't doing the kinds of things that the logic has been doing and that, you know, clinical architecture has been doing, which is why, instead of everybody going off and trying to solve the problems themselves in their silo, we need to come together. We need to evolve and iterate on the problem, and we're not always going to be successful on the first go, but we're going to learn why we weren't successful on the first go so that we can be more successful on the second go. And that's a lot easier problem to get at if you're not doing it by yourself, if you're doing it as part of a group of like-minded folks.
Speaker 2:So, uh, so this is Susan and I'll, I'll go into another example because I mean, what we really want to highlight is the importance of what we're doing. Having terminologies is words. And you need to put those words in sentences and in paragraphs, and that's the structures. You know, we create the models that are the structures, so that you can exchange books of information about your patients. And there's an initiative going across United States to standardize nursing documentation. They've pulled 8 million instances, six institutions run analytics to find out what documentation is being created. And then they come up with what they call a knowledge model that has the interventions and the assessments and outcomes that comes to terminology and modeling group. And then to Logica. And we have been creating information models, we've taken the ballot, the skin and wound assessment. And so if you have a patient, this is where I'm going to talk about the importance. If you have a patient that's admitted from a nursing home that has, you know, a pressure injury that comes into the hospital, you want to know the size, you want to know what it looks like. You want to know the, you know, what does a wound bed look like? Is there tunneling worse? The direction that the tunnel goes, what's the body location. We structured all of that in one model so that you can assess a wound. And so then if they go to the step down unit and then they go to the back to the nursing home and they go home to home health, there's an app, there's a tissue analytics app that has adopted this model. Now that takes a picture actually of the wound and can calculate all the dimensions and everything, and has fire enabled their app using our fire profiles. This allows you not only to track and trend for one patient, but then you've got data that you can run analytics against it and start looking at the evidence and seeing what makes a difference, because it's all structured the same way, no matter what setting they were in.
Speaker 1:That's a great point, Susan, it's the canonical, the semantic, having all that information aligned so that we can, we can reason over it. A great example of that is what's going on with COVID 19 right now, and our ability to wrap our heads around that. Carol McCumber. You wanted to, you had a question.
Speaker 3:Yeah. I mean, I'd love to kind of hear your, your perspective on, you know, how Logica kind of breaks down those silos. Right. You know, there's a huge part of it is, you know, getting community buy-in, you know, cause we can build these models and we can create standard terminology, but if people don't pick them up and use them and, and tell their friends to use them, the impact is damping, right. So how do you balance, you know, striving for that community buy-in, um, and contribution with, you know, remaining, nimble and responsive as a lot of people might say, Oh, with the standards processes, it's a monolithic, it takes forever. Um, so I I'd love to kind of hear, you know, your kind of approach to that in logic is ability to kind of lead from that perspective. Because I think, you know, looking at the COVID 19 fire idea that you guys have worked on, as it is a great example of how it's possible, right? I mean sure. You know, there are still things you want to do with that. And it's a piece of work that's in progress, but I think, um, you, you you've shown, you know, that it's possible. Yeah.
Speaker 1:So that's a challenging question. And I thought about it a lot. I mean, Logica, first of all, is we want to make the barriers to implementation as low as we possibly can. And so the models and terminology that we make are open and free for everyone to use. And we want that to be the case forever, because if it's something that people have to pay for, or they have to be a member of something in order to access it, or, you know, it just creates barriers to being used. And the goal is that it takes work to create it. But once it's created, you want people to be able to access it and use it and create useful capabilities. And so Logica has number one makes our models and the terminology that are created as value sets and bindings for those models are completely open for people to use. And so that's one thing, but the next thing is that the standard bodies don't control implementation. In the end, you have to talk to providers or anybody that has a patient care system. It doesn't matter whether actually, whether it's providers like Intermountain healthcare, or it could be, you know, it could be a public health office or it could be an insurance company. It, you know, it could be anybody, but they're, they're the ones who can determine whether they want to use the software or not. And a lot of times it's just a matter of getting people together and, and agreeing that you're going to do something together for the common good, that's what we've approached. And then in a new relationship that Logica is working on with the new company called graphite, that's the strategy we're pursuing there as well, that we can get a group of people who essentially say we agree. We, we know that there are well, we, we know that there are multiple ways that we can represent this information and that we can share the information. Even if you make the assumption that you're using fire and snomad and LOINC, you've got the kind of situation as Susan talked about things that can be pre coordinated or post coordinated and different ways that you can represent them. And they're all legal according to the standard. But if you want to get to real interoperability, you need a group of people that say, we're going to agree to do things the same way to create this kind of plug and play interoperability. That's what we're striving to do is now work with implementers, get them to join. Not because they have to join to get the models or the data, but join to be part of a group that says we're going to do it together. And we're going to buy common agreement to do things in an interoperable way. We're going to agree to do things one way that enables that marketplace and enables the value of being able to share software and data across different organizations.
Speaker 5:I guess, just to add a little bit to that, Carol,
Speaker 2:You know, we have so many specialty organizations and the FDA is a member of Logica that when it came to do the COVID-19 and our partnership with clinical architecture as well, we just started going out to all of our people and saying, can we pull this together? And what do you, what do you need? And, you know, I have close relationships with both snowmen and Mike, and that's how the COVID-19 interoperability Alliance got started is to make sure that you had the correct value sets and some medical with clinical architecture, and that we could use those for our bindings within the COVID 19 IgE. So you really need a cadre of people. It's not easy, it's hard. And so trying to you pull together everybody and have consensus, and there's still issues with, with HL seven, they only index their IGS. They don't index the profiles. So there's another group working on a COVID-19 IgG for the world health organization. They don't want to reuse our profiles inside our IgE because they can't index it with their IgE. So they're rebuilding the same profiles and putting them in there and then our IgG. So there's always going to be things that you're trying to fix when it comes to standardization. And that's one of the reasons why we like doing things with Logica, as we can keep the momentum going, you know, we try to align with the standards as much as we can, but we don't have to go back every single time and say, is this okay? Is this okay? Is this okay? We just, we just pull together our members and do it.
Speaker 1:It's part one of our episode on Magicka health. Please join us for the conclusion in part two, as always. Thank you for listening to the info monster pop.