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November 28: Today on the Community channel, it’s an Interview in Action live from HLTH with Don Woodlock, Vice President of Healthcare Solutions at InterSystems. How has the HealthShare product line evolved? How can applications and new services be written on top of the data and why would some systems do that instead of over the EHR? Why is data quality important when discussing using AI to parse it?

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Transcript

This transcription is provided by artificial intelligence. We believe in technology but understand that even the smartest robots can sometimes get speech recognition wrong.

interview in action from the:n action live from the Health:

Is that, is that a, what's your role?

So I run our healthcare solutions business here, basically, which is. Lines Track care, which is an outside the US emr and a pro, an integration product line called HealthShare. So those two are mine.

Yeah. Intersystem, we're gonna talk about HealthShare. Great.

My audience is predominantly healthcare providers in the States. Awesome. Now health share's been around for a while now.

Yeah, about 15 years.

15 years. Yeah. How has it evolved? I mean, when we, at St. Joe's, when we first implemented it, we were essentially pulling all this data from all these disparaged sources.

Yep, yep. We were trying to deliver metrics back out to our clinically integrated network. And the data quality was a challenge. Data governance was problems. And then getting the data back out into the workflow. Yes. That's what I remember. 10 years ago. Yes. That's right. That's right. That's right.

Uh, So

how has it evolved? Yeah. We still do that as a foundation. So we'll pull data from all the different data sources. We'll aggregate it, we'll normalize it, we'll duplicate it, and kind of integrate it into a nice data model. The data model itself has evolved to have more data sources. So not just clinical data, but claims data, social determinants, data, those kinds of things.

So you have a more holistic picture from a data aggregation point of view. And then we present it as a viewer and we integrate that view. To the clinician experience. So we've done a lot more work with integration back into the workflow from those days. So we can embed right within the Epic frame, right within the Cerner frame or Thena Healthcare.

So you can see that unified care record. But we can also do notifications, alerts, outbound transactions, you know, do other sorts of things to sort of get the benefit of that flow of information to the caregiver. So he or she. Is what's going on with their patients.

Well, and that was one of the things we were using it for is we had everyone said, well, if you get all the EHR data together, you're good.

Yeah. But there was so much other data we wanted to work with. Yeah, yeah. Correct. In order to really deliver on our population health objectives. Yeah.

I mean, claims data is really critical. There are things that you find out in the claims process, like leak from a C point of view, leakage and other activity that the patient has that if you can get access to that holistic claims experience, those sorts of things, then you know, More about what's going on with , your patients.

So I'm gonna go in the direction of talking about use cases and that kinda stuff. Sure. Uh, We have a tester fire knowledge behind us. Yes. Back in the day, we've, what we had envisioned was a set of APIs on top of this data set and start to create applications on it. Correct. And now you're using fires.

Well, talk to me about those capabilities, the capabilities of writing new applications, new services on top of it.

Sure. So, we integrate that data together. We present it in a viewer, as I described, but we also present it as a fire gateway basically. So you can get the entire patient record, or part of the record the last two years of lab tests or whatever by making rest requests to this fire gateway.

So we have customers that have built applications on top of this. So two examples would be one of our customers in New York and New Jersey area built their whole kind of patient experience framework on top of. Basically on top of this health share data. So they're doing kiosk, they're doing a mobile app, they're doing a portal, kind of all built by them, but leveraging the data and the data to their application developers just looks like fire Requests.

Why would they do that? I mean, I know the answer to this. I'm gonna ask you anyway. So the, yeah, go ahead. Why would they do that instead of Doing it on top of the EHR itself.

In their case,

]there are some APIs like that

in their case they had outside data that they wanted to integrate in as well to this past experience.

So their whole CRM system and the EMR system and the pop health system are all brought together in health share in this case. And the experience that they wanted to have with their patients really was enabled by the data from all three systems. That's fascinating. Yeah. Yeah. It was really cool and.

Just, it's just a great new world now that you can kind of get the data out of your various systems, put it in a place, build applications, innovate in a way that, 10 years ago you would have a hard time,

hard time doing it

. And really at this point, it's just your imagination is the limitation.

I mean, because if we, one of the things we're always talking about is , we can't clean up the data. The data's too unruly to work with and those kind of things. But now it's in turn, I mean, You open up the entire canvas to work with. I mean, oh, go

ahead.

The reality is there's still work to do on data quality always.

You know what I mean? So, so I won't, I won't mislead

you.

It's, it's not a magic bullet. No, I know that.

But it's a better, it's a better world. I think in terms of kind of the flow of information and those kinds of things

📍 📍 All right. We'll get back to our show in just a minute. We have a webinar coming up on December 7th, and I'm looking forward to that webinar. It is on how to modernize the data platform within healthcare, the modern data platform within healthcare. And I'm really looking forward to the conversation. We just recorded five pre episodes for that. And so they're gonna air on Tuesday and Thursdays leading up to the episode. And we have great conversation about the different aspects, different use cases around the modern data platform and how agility becomes so key and data quality and all those things. So great conversation. Looking forward to that. Wednesday, December 7th at one o'clock. Love to have you join us. We're gonna have health system leaders from Memorial Care and others. CDW is going to have some of their experts on this show as well. So check that out. You can go to our website thisweekhealth.com, top right hand corner. You'll see the upcoming webinars. Love to have you be a part of it. If you have a question coming into it, one of the things we do is we collect the questions in the signup form because we want to make sure that we incorporate that into the discussion. So hope to see you there. Now, back to the show

is, is there anything around AI models and machine learning in terms of layering stuff on top of your data sets is one of the challenges we're having with implementing AI models on top of the data is, is a data quality problem?

I think data quality has to be this high. Let's say if you're a human looking at a chart, right? But it has to be higher when you get. Analytics, machine learning and those sorts of things because you don't have the human brain able to sort of digest different ways of putting the same thing.

So I think the data quality bar is actually rising even higher as we all try and put the data to use in analytics, research, machine learning, those kinds of things. So, we appreciate customers that really value data and value having it be nice and clean cuz we kind of specialize in the technologies and allow that.

That's fantastic. But I do think that AI and ml, I'm not sure they're really gonna take off outside of radiology, let's say, where they're working radiology until the data is It's administrative. Yeah, yeah, yeah. Until the data gets a little bit, little bit cleaner. I, I just think that, that that's a necessary step.

Takes a little bit of time. Yeah. Don, I wanna thank you for your time. Yeah, sure. I see you again. Appreciate it.

Another great interview. I wanna thank everybody who spent time with us at the conferences. I love hearing from people on the front lines and it is Phenomen. That they have taken the time to share their wisdom and experience with the community, which is greatly appreciated. We also want to thank our channel sponsors one more time, who invest in our mission to develop the next generation of health leaders. They are Olive, Rubrik, trx, Mitigate, and F5. Thanks for listening. That's all for now.

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