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Data governance is often one of the most challenging projects that a CIO has to pull off. But it's more important than ever for health systems to approach data governance as an enterprise capability. What does a data governance framework look like for healthcare? How do you identify a data steward within your organization? How can the data be managed, leveraged and protected accordingly? It all comes back to a foundation of trust, which is especially critical in a clinical setting. The seven pillars of data governance provide the framework for a successful data strategy roadmap. Ultimately, if you don't have governance, you don't have modern data.

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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.

Thanks for joining us. My name is Bill Russell. I'm a former CIO for a 16 hospital system and creator of this week Health, A set of channels dedicated to keeping health IT staff current and engaged. Welcome to our briefing campaign on modernizing the healthcare data platform with CDW Healthcare's leaders in this space, Lee Pierce and Rex Washburn.

Today is episode five, a step by step methodology for creating a successful healthcare data governance framework. This podcast series is going to culminate with an excellent webinar panel discussion with experts talking about how to modernize your healthcare data platform, the right fit for every unique health system. That's gonna be on Wednesday, December 7th. Check out this week, health.com/webinars and click on the link to go ahead and register. We wanna thank our sponsors, Sirius and CDW, for making this content possible now 📍 onto the show.

So this should be a fun one. Data governance I've said many times on the show was one of the hardest projects I ever had to do as a cio. Now hopefully this has gotten a little bit easier and better, and we're gonna talk to, Rex and Lee and bring this home. What does a healthcare data governance framework look like for healthcare?

So, maybe I'll start just with Across industries, the way that we define an approach on data governance, I agree that this is a challenging topic but it's more important than ever that an organization can approach data governance as an enterprise capability.

First of all, when we talk about data governance we like to talk. It's, it's really people, process and technology. There's, as. much People in process, in data governance as there is probably more than there is about the technology. and that's, that's critical. Our definition of data governance really, it's a, it's about decision rights and accountabilities.

That's the people and process part of this, it's a program, it's not a project. So it's a program of decision rights and accountabilities to treat data as an asset. And then there are three areas that we talk about. In this definition, it includes managing, leveraging, and protecting data accordingly. And so that's really the definition.

You can see it's decision rights and accountabilities to treat data as an asset. So you know who's gonna do what with the data to treat it as an asset, as well as what needs to be done in order to not just protect it. You're not taking a view of governance, being just saying, No, you cannot have access to this data.

It's just as much about leveraging the data for the outcomes, like we've talked about in previous podcasts. The framework, as you take the next steps though, beyond the definition the framework really includes seven areas of data governance or seven pillars of data governance. The first that we talk about is data stewardship.

The second is data quality. Third is metadata management. Fourth is master in reference data management, fifth data security, six, data privacy, and the seventh is information lifecycle governance. Those seven. Pillars of data governance really become the framework around the application of principles that will support each, each of these areas and pillars support each other and being able to treat data appropriately as an asset. So that's the definition and framework that we usually start with regardless of industry.

Rex, I'm gonna come to you. You, you talked in one of the previous episodes about the core clean dataset and you were saying just, just having something as sort of a reference dataset that you could bring things in and create those views around.

And I want to, I want to use that as the example to say, Okay, that sounds pretty complex to do within my organization. Do I really need data governance? What's gonna happen if I don't have a good data governance program in place?

Absolute Armageddon, . so you can't have a modern data platform or data fabric or data mesh without data governance. So that's one of the things that's really changed within the data landscape that I've seen the most significant change is we've all come together and said, Data governance is core DNA for data. Right? And it's not just when we look at the pillars, not just looking forward as great we have, we have a catalog, so now we have a way for stewards to work with the metadata.

We can start really seeing what we have. We have to look backwards because all the healthcare organizations have been doing something to try to solve this problem to date. So that could be, I have a desktop BI tool that That I've been producing dashboards with where does that data sit on shared drives on laptops, things like that.

So that whole information, life cycle management, data security, those kinds of things, we have to sort of look backwards to what we have done while we sort of charge forward. But when I'm just looking at the simplest thing prior episode you'd mentioned a dashboard, right? For clinicians there is no modern data unless the people using that dashboard trust it.

I also don't have to boil the ocean to get started with this. I can start with when we think of the quadruple aim, right, what's going to drive the most value there? If maybe that's some data for a dashboard, I can look at that as a data product, which is something else that's sort of changed.

Instead of we must build all the marts or the monolithic warehouse. What data do I need to provide this value? Let's build a data product, iterate rapidly over that focus on quality and completeness of the data. I can then look at what the what the data's feeding into that, and then start addressing the specific data, quality issues, data data security issues in there. But ultimately, if you don't have governance, you don't have modern data.

Armageddon. I, I like you didn't leave any wiggle room there, so people have to understand that this is, this is pretty pretty important. Data Armageddon. Well, and it comes back to that foundation of trust. Right? Yeah.

So when you're looking at that data, you have to know you can trust it. And we get this all the time, or I used to get this all the time. When you go in front of physicians, like, where'd you get that number? And you have to be able to step back and say, This is where we got this number, here's what, And then you have to be able to say, Well, which definition of admission are you using?

And that cuz right? So you do have to, you do have to be able to, to tell that story in order to build the foundation for trust. And the foundation for trust is, is everything, especially in a clinical setting. I wanna talk about stewards for a minute. Not to, I mean, look, you, you laid out a lot of pillars.

We could talk about this topic for the next 45 minutes. Yes. We could and we're gonna talk about it for probably another seven or eight minutes. And at the end I'll, I'll ask you to maybe we can find a resource that they can hit to get that model that you that you talked about I think would be be helpful.

But I wanna talk about Stewart's for a minute. Because one of the things, you talked about a program. This is a program, it's a, it's correct. It's an organizational decision that we are gonna use data as an asset and we're gonna build a foundation of trust on that, on that data. And you really do have to get stewards from all over the organization, don't you? Right. Correct.

Absolutely. the stewards are assigned, You have to organize yourself in a way that allows you to assign stewards to inappropriate set of data. And typically we talk about that as a data domain. Many times those data domains are defined and are aligned with how the organization is structured from a clinical and operational perspective.

But it has to touch all of those, and it has to touch, you have to have stewards also for the data that is shared across all of those different departments and domains. And that's where master data comes in. I, we like to talk about data governance is a team sport, and that's where the people on the team is defined is by focusing on data stewardship and really what their accountability is and helping them realize the critical role that they play on the team.

As you think about treating data as an asset, the role that they individually play related to their data domain that they play, to make sure it's clean, make sure it's well understood and documented and trusted because there's no one size fits all. It takes, it takes that that team effort. Subject area by subject area data domain by data domain to be able to manage it and apply data governance principles to be successful.

I think one of the way I look at it is the stewards become the chief trust officer for that data domain that they're stewarding, right? Yeah. Because when I say Bill, you'd said how do I trust that number? Where did that number come from? I can go to a steward and they can leverage their catalog platform and look at the entire lineage, everything that's happened from the data, the number that's displayed, all the way back to the source systems and the transformations that have been done to it, right?

And then explain what definitions were used, where did we come from? Even if you have two numbers that are utilized slightly differently with the. Same name in two different domains. I mean, they can differentiate that. Yeah. So they become a critical element for it. And it's, it's not an IT thing, it is that team sport because it is the support, the enablement, they're, they're part of it. But if data governance sits in it, it's not a complete data governance program.

So who, who chairs the data governance program. In our organization. When we kicked it off, it was, well, first of all, because we were bringing it to them of, Hey, we need to do data governance. They said, Great, you go do it . Go do it. And so I, I grabbed the chief strategy officer, so the two of us really. The, the foundation for it. And we quickly realized that we needed a clinician to be a part of that leadership team as well. And I, I, I tried every which way to step out of it at that point because clinical data is a significant part of the data and strategy was a significant part of the data.

And I thought, but they, they needed a lot of guidance. What, what generally works? Who leads this initiative?

Yeah. Well coming back to the team sport aspect of it, yes. You need to identify, I guess using that analogy, you need to identify a coach and a leader. Somebody that's gonna be able to organize the potential data chaos that exists needs to bring order to it.

And make sure that everybody is playing from the same playbook and understands the playbook book. In the end, it's not that the IT teams and the technology teams step out of it and are not involved. Part of the team sport aspect is you have to have technical expertise and you actually have technical data stewards by data domain.

And then you have your business and clinical, depending on the data domain, you have to have their expertise and knowledge. And it's the combination of that technical and business and or clinical knowledge. Because really to understand the data, you have to be able to understand clinical processes that even generated that data, let alone the underlying systems that that data is stored in.

So to answer your question about who, who leads it, I have seen successful data governance programs led by various. Members of that, of that team. But ultimately, typically what we see is you have an executive leadership team and that you have either a clinical or strategic leader similar to what you saw teamed up with either the chief data officer, chief analytics officer, or cio, even at that executive team level.

The next level down though they, they're kind of a die almost of leading those the data governance efforts. But then you go down to the next level of the detailed work that needs to be done. Again, you need that diad of technical with business and clinical leader leadership. just to be that the coach and the assistant coach to be able to help all of the army of data stewards and team members be able to effectively deliver on. The various aspects of data governance.

All right, gentlemen, I wanna thank you for five wonderful episodes. I really appreciate we're gonna close this out with a webinar and I'm looking forward to catching up with you there as well. Thank you very much for your time. Thank you. Thanks you 📍 so much.

What a great discussion. I wanna thank our sponsors for today, Sirius and cdw, for investing in our mission to develop the next generation of health leaders. Don't forget that this whole series ends with a great webinar on Wednesday, December 7th, Lee Pearson, Rex Washburn will be joining us along with Jared Nunez, Executive Director Informatics and Analytics at Memorial Care.

We're gonna take this discussion one step further by including you and your questions. So go ahead and register at this week, health.com. The link is in the top right hand corner and don't forget to drop your questions in the form so we can make sure 📍 to cover. In the webinar. Looking forward to that discussion. Thanks for listening. That's all for now.

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