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Executive Interview: From Data Exchange to Data Utility with Dr. Steven Lane and Mike Cordeiro

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I'm Bill Russell, creator of this Week Health, where our mission is to transform healthcare, one connection at a time. This is an executive interview

quick powerful Conversations with Leaders Driving Change. So let's get started.

Bill Russell (2): All right, today we have an executive interview. I'm excited to be joined by Dr. Steven Lane, chief Medical Officer at Health Gorilla, and Mike Cordero, senior Director, interoperability [00:01:00] Market and Product Strategy with MEDITECH i'm looking forward to this conversation.

This has been a passion project for me since I got into healthcare back in 2011. I came in from outside the industry and it just felt to me like I worked in banking and everything else. It's like this interoperability thing should be pretty easy. And then when I got into healthcare, I realized this is not quite as simple as I.

Thought it was going to be, but interoperability efforts have really come a long way in just the last few years. Where are you seeing this impact healthcare the most at this point?

Steven: that's a great way, to start the conversation. I think, you know, as a practicing physician, I can tell you it absolutely impacts care at the bedside, you know, or in the doctor's office.

We have done tremendous work over the past 25 years. In building a foundation that supports interoperability both in large and small practices, in urban and rural settings. And and it's wonderful to see that moving forward, we're [00:02:00] now seeing billions of patient records being transacted, being exchanged every month across the existing national networks and frameworks, as well as more local and regional networks.

People have really integrated this into their workflows. So when I see patients, routinely, I have access to data not only from my own institution, but from other institutions and facilities where the patients receive care. And this is important in so many settings. I mean, in primary care where I work, where patients move around and see multiple specialists.

In the acute care setting, whether you're talking about the emergency department, where people will drop in, and you really need rapid real-time access to data in order to provide safe and effective care. Maternity care is a great example where prenatal care. Delivery care, postnatal and pediatric care are often provided in different institutions, and we need to move that data around and make it available.

And that doesn't even begin to get into the challenges of value-based care [00:03:00] population, health management, and public health, where you really need to be able to access data on populations of people. So, you know, it's very exciting. We've laid a tremendous foundation. We're seeing progress and now we find ourselves at the dawn of the AI era where we have.

Seen historically that when you provide clinicians and institutions with more data, sometimes they don't know what to do with it. It's more data than they can manage cognitively. And with AI where you can actually review that data, come up with actionable insights and help to inform the care that it's proving to be tremendously important.

We're seeing today providers increasingly integrating AI tools into their decision making and their patient care processes. But oftentimes that involves. You know, hopping between applications or picking your favorite app. But what we need to see, what we wanna see is those tools integrated into the daily clinical workflow where the AI will be able to review all the data both locally.

Externally [00:04:00] that's come together to see what's happening in the course of the encounter and to provide the actionable insights that, that we're all looking for. So it's a very exciting time to be involved in healthcare, to be involved in health data interoperability, and happy to be here to talk about it.

Mike: Yeah I couldn't agree more. It's definitely been a journey from the e HR perspective, you know, and kind of from my vantage point we've, you know, moved beyond, you know, static documents like the CCD and the expectation today and time from interoperability standpoint is real time data exchange.

It's structured and it's essentially meant to have utility around it. Like you said, Dr. Lane removing the cognitive load on clinicians and surfacing insights directly at that point of care. MEDITECH you know, we launched Traverse Exchange, our own data sharing network first in Canada now in the States.

And the intent was to enable bidirectional data sharing across, you know, the MEDITECH ecosystem and outside of that ecosystem. So a non MEDITECH facility. And with our consolidated patient summary, we deliver those insights directly within [00:05:00] workflows helping clinicians make those faster, more informed decisions.

I think the other kind of key component here too is, and it's importantly is that government backed frameworks like tef are leveraged, are leveling, you know, the playing field. So they remove the historical barriers that force community health systems to consider mergers, to gain access to, to, to data.

And now will these national networks and frameworks in place organizations, whether they're independent or part of a larger system, can participate fully in, in in data sharing. So I think it's been a, a. A pretty big shift overall, you know, a shift towards scalability, sustainability and kind of equity as it relates to healthcare data.

Bill Russell (2): I think you guys really touched on this, the, but you know, I remember the first time I popped into an EHR and I saw the, and I was sitting behind a doctor watching them. Practice and they were going through PDF after PDF and I was like, oh my gosh. How do you do this? How do you practice medicine going through this and the you know, not having that structured data, we now have us, [00:06:00] CDI, we have LLMs, we have teca as you guys mentioned.

You know, what are the barriers keeping the data from being actionable and what shifts are needed to move from data collection and data movement to really data utility, for the clinicians.

Steven: So a lot of work is being done on those very issues. Data usability is the word that has caught on.

And the idea is, yes, you can get your hands on huge volumes of data, but if it's not structured, if it's not normalized, if it's not de-duplicated it's very difficult to really see it. in A holistic way so that you can make decisions. I think you pointed out that the structure of the data is very important and we need to be able to normalize that if we're going to be able to integrate even data generated within a single provider or health system, but certainly when you're going across systems.

So that's a challenge we've been working on for a number of years, but I think we are definitely making progress on that. The challenge of integrating externally [00:07:00] sourced data and reconciling it into the local record. Also very important. You know, how do you know really what medications the patient is taking?

What are their medical problems? What are their allergies? Who's on their care team? All these things are incredibly important. The data exchange brings you that data, but if you're having to sift through it, as you said, PDFs, you know, or even CCDs, you know, it's very difficult. What you need is to be able to receive the data, either receive it discreetly or receive it in a document format, and then tear it apart into the individual elements.

You know, these days where using the FHIR the fast healthcare interoperability, resources, standards for that and then you can bring all of that data together at the point of care to inform what's going on.

Mike: Yeah, I definitely agree, and I think there's kind of been a shift, right? So interoperability, you know.

Was potentially or, or has always kind of been looked at from my perspective maybe as a compliance driven thing that, folks had to do. But now that we see the value of data and how data is driving health it forward, you [00:08:00] know, looking at these frameworks like Teka gives you access to that data.

But once you have it, like you were saying, you need to have, understand the intent of that data, have structure, have codes behind it so you actually use it. And drive insights from it. So, so it's not just about, you know, putting the plumbing in place to exchange the data, but putting the utility a, around the data, either through AI or more advanced technologies around, you know, bringing surfacing insights and using the data to drive operations, right?

So, data needs to be part of an organization's in my opinion or overall strategy. It's not just about collecting it, but it's collecting it with intent, making sure that you have the tools behind it so you can codify it and then use it.

Bill Russell (2): Can we talk about one of the banes of my existence was we had partnerships with with payers and we had different programs and whatnot, and interoperability.

Across, I mean, because it's a larger ecosystem than just the healthcare system. So it wasn't just our EHR sharing with another EHR or even within our clinically integrated network. We had to figure out ways to [00:09:00] get that information back and forth between the payers. what is that gap and what's the cost of continuing to ignore that gap that exists in, in, in what I believe healthcare, hopefully.

We're getting closer to solving this, but it was a significant problem for me when we were setting this up back in the day.

Steven: I mean, the cost is huge. The. Investment that we all make in exchanging data between payers and providers is really unconscionable. You know, we came to this point very organically.

You know, we started sending documents, we data files, you know, we built pipes. Everyone was trying to develop ways to make, Billing and payments much more efficient. And they came up with all kinds of creative ways. There were some standards that HIPAA brought us at standardized transactions, but we still see a very bespoke landscape, where different payers have different solutions that they use, different vendors.

What we've seen in clinical data exchange, you know, between providers for the treatment exchange purpose is real [00:10:00] standardization. And continued standardization. And now with the advancement of the national frameworks, you know, whether you're talking about TEFCA whether you're talking about the work that CMS is trying to support what we're seeing is a real effort to bring payers into the mix so that the standards, higher security, the greater data privacy that we've built into clinical data exchange.

Can also benefit the payers. The Da Vinci Project. I'm sure you're aware Bill has done a lot of work on FIHR based exchange between payers and providers. I've helped to support that work. There are tremendous opportunities for cost savings and efficiencies in getting that exchange to be more standardized and more integrated.

And from a clinician's perspective, I wanna know what the payer knows about the patient. Oftentimes the payer knows that a care gap was closed. For example, the patient may receive a mammogram or a pap smear or colonoscopy somewhere, and it's not available to me, through the clinical data connections that I have, but they can tell me that they paid for it and then I know that it was taken care of.

So [00:11:00] there are a lot of opportunities to make further progress. But you're right, it's still a challenge.

Mike: Yeah, I think that's a great example because that's something that some of our clients are asking us for today and time as well is, you know, at the point someone presents for a wellness visit, being able to query that payer.

Get that care gap information. So it can be closed, during the episode. But I think, like, to just double click on a few things that Dr. Lane talked about I definitely see an uptick in, you know, the curiosity around payer provider interoperability. And I think that shift from fee for service to value-based care is probably gonna kind of drive more of that curiosity as health plans become participatory in, in, in patient care.

But I think. In my opinion for this really to evolve I think there needs to be some trust and transparency around providers and payers, you know, relative to that data. I often hear the the fear that, you know, if I overshare my denials will go up, you know, so having that transparency around the data and how it's used and the impact it can have on the patient.

Care [00:12:00] on the patient themselves, I think is how we push this forward In addition to obviously the standards and the frameworks that Dr. Lane mentioned.

Steven: I think if I may, you know, the concern about denials is real. But I think on a broader level, providers have historically been reticent about sharing data with payers because they're worried about their contract rates, they're worried about their patients and how they're being underwritten.

And, you know, there's this thought that the. the provider is protecting the patient from the payer. You know, in an era of value-based care, those. Relationships change and we should be seeing more collaboration and cooperation. The other thing that comes up a lot is under hipaa, so long as you receive data for a permitted purpose, you can then repurpose that data and use it in any way you want.

And I think that there is continuing concern on the part of providers. That payers might misuse the data that they get. So I think there's still [00:13:00] this sense of not wanting to share more than is absolutely necessary. But it's challenging as you say, because now that we're moving to more value-based care, we've got payers involved in prior authorization and pre-approvals, and it's becoming a major barrier to care.

And so I think providers are changing their feelings about this because they really can't move forward until these. Barriers are lowered and remove the burden from workflows like prior auth.

Mike: I a hundred percent agree with that and I think, you know, one of the things I didn't mention, and as I'm having conversations with provider organizations and payers and in.

Especially on the payer side when asked like, how do we continue to be able to automate some of these data sharing processes? You know, it, I think it's an education thing, right? So there's some responsibility on the side of the health plan to help educate relative to what the value adds are for automating this and putting transparency around how that data is being shared and used and ultimately keeping the patient and always in mind.

Right? One of the things I learned recently is, some [00:14:00] payer organizations are. You know, trying to drop that word payer right. And rebrand themselves as health plans because they're part of that healthcare journey. So I think, education is definitely gonna be a key component relative to kind of how that data is shared and the impact

Bill Russell (2): it's one of those things of we didn't know what we didn't know. We used to have a, a a technology gap which kept us from doing interoperability well, technology and policies. And now that we're able to move the data as seamlessly as we are now, we're learning that there are there, there's other barriers to sharing that data and fears and concerns.

I, along those lines, I wanna talk about the patients. I interviewed a patient whose son had uh, cancer and it was interesting to talk to her about how she was using ai and she said every, every diagnosis, everything she gets from a physician now she's putting through ai. And I think that's becoming more and more the norm of saying, oh, I've been prescribed this medication.

What [00:15:00] does this really mean? And that kind of stuff, and explain it to me in a way that I can understand it. It's so these tools are being used that way. And I don't really wanna go down that path as much as you know, I mean. The, this interoperability that we're seeing that really the dawn of this right now, what does this mean for patient empowerment?

That was always the promise the that we were gonna empower the patients with data and they were going to start to participate in their health journey. So I'd love to hear from you guys. where are we at and what does this mean for the patient?

Mike: Yeah. I definitely think that patients are becoming kind of the central players in that, you know, I think frameworks like TEFCA have definitely been able to enable that because of doubling down on that trust element relative to that framework. And those use cases. So individual access services for instance, you know, patients have control over their data, right? They have the right to gain access to their records.

They have then the right to use their records. Like you mentioned, in order to kind of help drive their care, right, either throwing it through an MIA model, using an app to help track their progress or be able to [00:16:00] share records with their care team and ask questions.

So I think that it's not just about data access um, for the patients, but now that they have access is how they're using that data to help. Inform their care decisions and talk to their providers. But I think Dr. Lane definitely has some perspective here as well.

Steven: we implemented one of the very first patient portals 25 years ago.

We've been at this again for a long time. It's kind of similar timeframe to interoperability and patients getting access, you know, was a very new idea then. And then with the legislation that was passed by the government, you know, we opened up that access further. Really, you know, making the prohibitions on information blocking, making data available to patients in more real time.

And I think also there's just been a move towards more and more patients taking advantage of this. What we're talking about with individual access services as it's been coined, is really patients being able to query, you know, any of their data holders. Being [00:17:00] able to bring that data together and aggregate it in an IAS application where they can then have access to it.

Very different than portals. I mean, if you've seen a dozen different providers over the last 10 years, you know, you might have 10 different portals and you can't integrate that data. But with IAS, you can bring that data down discreetly in a fire format work with a vendor that will allow you to make full use of that.

As you mentioned, you came from financial services, it's like being able to connect all your bank accounts, you know, and see all of your data in one graph, in one timeline. What have you do? Planning. That's where we're heading with patient. Access to their own data.

And again, with ai, it changes the game entirely. You know, if you're gonna go look up every problem or medication or whatnot, that's one thing. But if you've got AI agents that have been tuned to support patients and they can look at all of that data, the new pieces that come in the context of what happened to U 10 and 20 years ago, we're gonna be seeing a [00:18:00] lot more patient empowerment.

It's further changing the provider patient relationship. You know, where patients, some patients at least, are much more informed and come in, you know, and that can challenge providers. I mean, you have to, we all have to grow in our capabilities of how to leverage the data for good.

Bill Russell (2): You know, I've had an Anish Chopra on the show a couple times, and we talk a lot about the different stakeholders here and get gaining alignment of these stakeholders has been a challenge. And but it's not only that it's shared accountability across the entire ecosystem.

what mechanisms, models could actually drive shared ownership of. Of the data quality, utility and innovation across the payers, providers tech partners, I guess is the question?

Mike: Yeah. I mean, I think from my perspective, you know, the industry is the mechanism for moving this forward.

I think Dr. Lane initially talked about Sequoia as an example of an industry group that's. Trying to take on the challenge of, of data quality [00:19:00] relative to interoperability, right. So, from my perspective, I think it's industry coming together, putting governance around, you know, the data sharing use cases, putting structure around the workflows in those use cases and enabling governance around how to tackle some of the problems relative to the data exchange and standards.

So I, I think it's. It's a coalition of many to kind of move this forward. I think, you know, CMS is kind of, looked at this and that's kind of part of their framework right now with the CMS aligned networks is bringing in a coalition of, you know, big tech EHRs payers.

So, anyone participating in the healthcare ecosystem to help drive this innovation forward and provide this governance and standardization around it.

Steven: So Bill you asked about, you know, how do we manage the governance of the data. We've talked a couple times about the Sequoia Project and their data usability initiative and two versions now of implementation guides that have been published.

And we're starting to see. [00:20:00] Federal and state legislation pointing at those frameworks as ways where we can start to quantify the usability of data. Another framework that has grown up in the last couple years is called the Peaky Framework, the Patient Information Quality improvement framework where very.

Bright folks have come together and really started to say, how can we quantify data quality? And once we do, how do we measure it? How do we remediate it? How do we improve it as part of this framework based exchange. So I think we're gonna see real progress in data quality. And again, that makes a huge difference whether you're, you know, in the office at the bedside.

Doing public health or running an AI agent, you have to have quality data if you're gonna get quality decision making. And I think the industry is finally at a point that we're gonna be able to do that. The other thing is, you know, how is this governed? You know, who cares, who's watching this? I think these frameworks will help us to be able to identify, [00:21:00] where's data quality good?

Where is it bad? But it's really the patients that know what their health story is. I think we are increasingly, as you, we were discussing before, seeing patients accessing their data, but then saying, Hey, this isn't up to date, or this isn't accurate, or this isn't my data, it's somebody else, you know, who has this, maybe has the same name.

So I think patient access is going to drive data quality in the, you know, different way than AI is gonna drive it in a different way that PO than population health. But there are a lot of reasons for us to be focused on the quality of the data.

Bill Russell (2): looking forward for MEDITECH.

What's the vision for advancing healthcare delivery through data networks and interoperability?

Mike: Yeah. So I mean, one of our mission is just not to respond to change, but actually designing the next generation of data-driven care. So, interop really is just no longer about connecting hospitals.

It's about widening the circle widening the circle, include health plans, apps and all of these nuanced data [00:22:00] sources because ultimately there's a lot of. Entities that participate in care delivery. So, you know, we're using modern standards like FHIR, embracing U-S-C-D-I data elements and data as a platform to support richer clinical workflows and close enclosed care gaps faster.

You know, so our vision is about enabling timely, actionable insights, whether for a single patient or entire population. So the objective is to provide better care in a better patient experience.

Bill Russell (2): Fantastic, Dr. Lane. Mike, I really appreciate your time. Really appreciate you guys uh, sharing your experience and the progress that we're making.

This is an definitely an exciting time to, uh, to be in healthcare.

Mike: Awesome. Thanks for having me.

Steven: Thank you so much.

Thanks for joining us for this executive interview with me, bill Russell. Every healthcare leader needs a community they can lean on and learn from. Subscribe at this week, health.com/subscribe and share this conversation with your team. Together we're transforming [00:23:00] healthcare.

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