Data Points

8. Healthcare Interoperability: Part 1 (Russ Leftwich)

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Data Points
8. Healthcare Interoperability: Part 1 (Russ Leftwich)
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This episode features the first part of our interview with senior clinical advisor for interoperability at InterSystems, Russ Leftwich. In our discussion, Russ tells us about the history of healthcare interoperability, modern breakthroughs in its technology, and some of the biggest challenges that modern systems need to overcome.

To check out the new series of InterSystems IRIS Tech Talks mentioned in the introduction, head over to https://www.intersystems.com/intersystems-iris-tech-talks.

For more information about Data Points, visit https://datapoints.intersystems.com.

 

EPISODE TRANSCRIPT:

 

Derek Robinson 00:00:02 Welcome to Data Points, a podcast by InterSystems Learning Services. Make sure to subscribe to the podcast on your favorite podcast app. Links can be found at datapoints.intersystems.com. I'm Derek Robinson.

 

Adam Coppola 00:00:16 And I'm Adam Coppola. And today we'll chat with Russ Leftwich, Senior Clinical Advisor for Healthcare Interoperability at InterSystems, about modern healthcare interoperability.

 

Derek Robinson 00:00:38 Welcome to Episode Eight of Data Points by InterSystems Learning Services, and much like last episode, I'm joined by a fellow co-host at Online Learning. Adam, how's it going?

 

Adam Coppola 00:00:47 It's going well. Thanks for having me, Derek.

 

Derek Robinson 00:00:  Cool. So today on Episode Eight, we're going to be interviewing Russ Leftwich, who I'll have Adam introduce in just a moment, but first a little bit of housekeeping at the beginning here. First of all, we hope you guys have been enjoying these episodes. And like we mentioned, we're doing these remotely right now. So bear with us, as we're trying to do the best we can with our audio and our setup here. Technically, everyone is remote, not in our office, so hopefully everybody's staying safe and sane and everything else, and making sure that we're getting through this together. One quick shout-out for something that is being done by the Marketing group at InterSystems that is coming up soon are these InterSystems IRIS Tech Talks. So I put the link to those Tech Talks in the description of this podcast; you can hop over and check that out. The reason I suggested is because the first Tech Talk is featuring three of our prior podcast guests, Tom Dyar, Carmen Logue, and Benjamin De Boe. So, they're covering machine learning, AI analytics, some good topics there, and these Tech Talks will be continuing throughout the spring. So go check those out. Definitely some good content that you can gather from some of our best experts here at InterSystems on those topics. So check out the Tech Talks, and now moving into Episode Eight where we're featuring Russ, Adam, give us a little bit of an introduction of who Russ is and why he's such an exciting podcast guest for our listeners to be excited about.

 

Adam Coppola 00:02:02 Sure thing. We're really lucky to have him. Russ practiced internal medicine for 25 years before retiring to start a second career in clinical informatics. Russ has been at InterSystems for five years as a Senior Clinical Advisor for Interoperability. He's the standards guy here. He has been involved with standards development at Health Level Seven International, otherwise known as HL7, and a number of other organizations that work on developing interoperability in healthcare.

 

Derek Robinson 00:02:27 Nice. So obviously qualified. And I think as you'll hear in our interview with him, I think that comes through quite clearly that he's very qualified to talk about this stuff. He really has a breadth of knowledge on all these topics. And so as a result, we really had so much in our interview with him that we are breaking it into two parts. So Part 1 of this interview is in this episode, in Episode Eight, and what can people expect in Part 1, and then what is going to be broken into Part 2 in a future episode?

 

Adam Coppola 00:02:53 So in Part 1, we'll go over some of the history of healthcare interoperability standards. We'll discuss some of the major innovations, as well as how the demand for new standards has driven some of the technological advancements. In Part 2, we'll really focus on one of the new standards, which is FHIR, Fast Healthcare Interoperability Resources, and we'll go into a little bit more about how InterSystems supports FHIR and other standards.

 

Derek Robinson 00:03:20 There you go. So exciting stuff. So without further ado, let's kick off Part 1 with Russ Leftwich.

 

Adam Coppola 00:03:28 OK. Russ Leftwich, thank you so much for joining us this morning on

Data Points podcast. Can you please tell me a little bit about yourself and what you do at InterSystems?

 

Russ Leftwich 00:03:37 So, five years ago I came to InterSystems as a Senior Clinical Advisor for Interoperability. I'm the standards guy; I've been involved in the work that goes on and the standards development organization, Health Level Seven, HL7, as well as a number of other organizations that work on developing interoperability in healthcare.

 

Derek Robinson 00:04:04 Nice. Talking about innovations in healthcare, tell us a little bit about some of the innovations that you've seen over the years in healthcare and especially in electronic record keeping and how that has evolved.

 

Russ Leftwich 00:04:15 Well, most people don't usually think of healthcare data standards as innovations, but in a very big sense they are, and it started 40 years ago or a little more when hospitals started to have electronic systems, more than one system, in the hospital. But at that point, the use case was really just about connecting those systems. And that was a big challenge because it took engineers working for weeks just to connect two systems. And as hospitals started to get more systems, a registration system, a laboratory system, scheduling, in radiology, and a pharmacy system and so forth, they had to connect all the systems together. And that led to the formation of the standards organization I mentioned, Health Level Seven, which is a healthcare data standards organization, and they were formed because there was a need for a way to address that use case of connecting systems within a hospital. It was not at all about sharing data across organizations or with the government. It was just about connecting the systems in your hospital. So those first data standards, one of the very first ones was HL7 Version 2, which people use just HL7 at the shorthand for that data standard. It's still in use. It's the most used data standard in healthcare, but it doesn't meet interoperability needs that have evolved over the past 40 years, you know. And until 20 years ago, most of the data in healthcare was still in hospitals. Now in the past twenty years, we've seen this explosion of sources of data that are outside the hospital, everything from genomic sequencing labs to the Internet of Things, to wearable devices, mobile devices. So there's an entirely new use case for healthcare data standards.

 

Adam Coppola 00:06:38 So Russ, can you tell us a little about what all these standards cover? You've talked about sharing data within institutions and across institutions, but what kind of data are we talking about?

 

Russ Leftwich 00:06:50 So we're talking about a lot of data, and the types of data continues to expand. In the 1980s, it was mostly about administrative data, not even what we would really call healthcare data. It was a patient's identity and demographics: where the patient was located in the hospital, what they were admitted for. And then starting to add to that their diagnosis, the reason they were in the hospital. Laboratory data was one of the first forms of electronic data in healthcare. But then we started to add other data and started to electronically document the care of patients, where the data included the history of the patient that was written down in a narrative. The problems diagnoses that the patient has, that had to be encoded in a way that machines could understand. And doctors and other clinicians in different hospitals, different places would know they were talking about the same thing. And then there were data that's electronic data like electrocardiograms, monitoring data that is physiologic data in a sense, and comes in a stream of electronic data. But you need a standard to capture that data and exchange it between the device that captures it and the electronic records system that needs to store it and record it, so the nature of data has continued to expand. The types of data have continued to expand. Now we've got genomic sequencing data that is something completely new in the past decade or so. So we have to continue to create new standards. Early on, the standards were fairly simple, but they were in a sense complex to implement. And in the beginning, it took experienced engineers weeks just to hook up two systems within a hospital. And when they changed the software version of one of those systems, they had to do it over again. That was increasingly time-consuming as hospitals started to have more systems. A few years ago, somebody observed that the average hospital in the U.S. has over 80 IT systems within its walls. So interoperability sort of starts at home. You've got to connect those systems first. As you start to share data more broadly across organizations and across countries, you need increasingly sophisticated, let's say standards, because everybody has to agree on the same concept of the data that's being exchanged. We call that agreement a data model. In the beginning, there was no real data model except what was worked out between two teams of engineers working with different systems. Now we've reached the point that we have to create fairly elaborate, fully specified data models to describe not only the values of the measurements in the data, but the context of that data as well. And we do that with terminology bindings, value-set bindings. So a standard specification for a data model includes the terminology, which is an entirely separate, if you will, set of standards, that communicates what we mean when we say systolic blood pressure, for example.

 

Adam Coppola 00:11:01 So now we're talking about two different levels of data standards. The first is the data model or data structure, which allows machines or devices to reliably communicate with each other. The second is the terminology or context, which allows an end-user or machine to interpret the contents of data. For example, if an observation is made about a patient's blood pressure, a context code is paired with the data to say what type of blood pressure it is, or how the measurement was taken.

 

Russ Leftwich 00:11:30 So those data models have become a requirement if you will, for Interoperability, as the use case has matured to this idea of sharing data across organizations and data that actually sits in many different systems, and bringing that data together.

 

Derek Robinson 00:11:56 Right. Yeah, it's really a complex problem. And I think a great explanation of all the different pieces involved in solving that. I think personally, you know, I have friends and colleagues that work in the medical space as doctors and nurses, and I've kind of laughed at times when I've tried to have some of these discussions with them, and they oftentimes don't even know anything about these messaging standards that go on underneath it. And so it kind of speaks to the challenge of all these different systems and all these different, more and more modern applications and systems coming into the scene that you need to really be able to work between them. You kind of talked about having sophisticated standards and being able to really encompass a lot of different things. And I want to transition that into one of the most popular, probably the leading standard that we talk about today, which is being discussed everywhere, is FHIR, right? One of the most sophisticated standards that we have. Can you introduce FHIR to our learners and kind of at a high level, explain what makes it such a powerful model to use, when we're talking about solving this problem of healthcare interoperability?

 

Russ Leftwich 00:12:52 So FHIR, which is an acronym for Fast Healthcare Interoperability Resources, and that's resources, as in a URL resource, in a computer sense, FHIR was first proposed about 10 years ago, and it was proposed as a solution to what was increasingly being recognized as the interoperability need of the 21st century. This idea that we've just talked about, that data is in a lot of places and a lot of forms, and you need to bring it together. And FHIR was based on the way we do that in other businesses on the internet. FHIR is in its essence a Restful API. It's a basic data model for healthcare data that you can use to build more complex models or particular use cases. And FHIR was meant to be a way to leverage the internet and web technology in healthcare. We had gone over the past 20 years or so from a time when all the data was in servers, in the basement of the hospital, offline, to where much of the data is online, even in the cloud. And as I've said, in many different places. So we needed a standard that could connect all that data and could be implemented as a data model. And that's what FHIR is. The other necessity of that interoperability is that two different systems, or rather all the systems that are sharing data, need to be using the same data model. The challenge is that you could, for many concepts in healthcare, you could create more than one data model that seems reasonable to a human, but if two different teams or organizations create two different data models for the same thing, there is no interoperability. So part of the idea of FHIR is that it's a technology that makes it easy to share those data models…in a machine-readable sense, share the data models and implement them.

 

Adam Coppola 00:15:33 So thanks again, Russ, for joining us. In light of standards like FHIR that make interoperability easy for a lot of developers, we sometimes take for granted how this stuff hasn't always been easy, and how far we've come as an industry.

 

Derek Robinson 00:15:47 Yeah, absolutely. And I think hearing Russ go over some of the history of the healthcare and operability technology that exists and kind of how that's evolved over time, it's definitely interesting for a layman, certainly like someone who isn't involved in the nuts and bolts of the actual technical interoperability of healthcare, even for clinicians and doctors and nurses that don't get exposed to that underlying technology. I think just hearing someone with as much knowledge as Russ talk about that is quite exciting and quite interesting and thought provoking, I think, into how all of that works and how it's all evolved.

 

Adam Coppola 00:16:18 Yep. Definitely. Each one of these systems require specialized knowledge, not just of general standards, but also how the standards are implemented in new situations, how the standards are changing with every update, and all the layers of standards, like Russ said, from terminologies to the data structures.

 

Derek Robinson 00:16:35 Yeah. So it's a lot to unpack. And of course in Part 2 of this interview with Russ, we will be going over a lot more InterSystems-specific discussion on how InterSystems technology stack works with all this healthcare interoperability that we brought up and discussed in Part 1. So keep an eye out for that, and it should be coming soon. So that's it for Episode Eight. Thank you guys for joining us, and we'll see you next time on Data Points.


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