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 Welcome to this week in Health It where we discuss the news information and emerging thought with leaders from across the healthcare industry. This is episode number 42. Today we venture into the world of data governance and we take a look at a story that is really a call to action for, uh, for healthcare and healthcare in institutions.

To shout out to all CIOs attending the Chime fall forum in San Diego. I'm gonna be, I'm gonna be there and doing one of the special episodes that we do for this week in health It where I sit down with CIOs for about 10 minutes. I have four questions. In fact, this time I'm gonna do it a little different since there's so many CIOs in in.

C m I O is gonna be down there. I'm actually gonna have three different sets of questions and you get to choose which set of questions you want to answer. It can be on technology, ex execution, or culture. Are the three topics I, I would like to go deeper on. So I have four questions in each one of those categories.

If you have some time and you would like to, uh, be on the show, uh, we, I will just sit across from you. Uh, we record on the iPhone and then I spl. I will ask a bunch of people the same set of questions. So, um, if you're gonna be there and would like to be on the show, please drop me a line at Bill at this week in health it.com.

And one last thing. Uh, we now have, uh, an Alexa skills enabled for the podcast. Uh, you can just say, Alexa, play this podcast. Uh, play the podcast this week in health. It, or you, uh, you can enable the, any, any pod skill on your, uh, echo and say, Alexa, ask any pod to play this week in health. It, uh, and I think it's fitting that I would announce this on this show since our guest today and I discussed.

The transformational power of voice in health it on our last episode. So today's guest was gracious, gracious enough to step in, uh, when one of our guests wasn't able to, uh, follow through based on a scheduling conflict. Uh, a friend and accomplished C M I O. Lee Milligan joins us once again with Asante Health.

Good morning, uh, Lee and welcome to the show. Good afternoon, happy to be out, but, but we're, we're ruining the illusion. 'cause this gets, this will get released on Friday morning. I don't want people to, to see the beautiful sunlight behind me and, and recognize that we're actually recording in the afternoon.

Yes. Good day, . Good day. Exactly. So you're, you're just getting back from the, uh, the HIMSS conference up in, uh, Washington. Uh, give us a little idea of, of what went on up there. It was great. They have a semi-annual, uh, conference up there and they invite a variety of folks to, to, uh, come in and speak. They had, uh, folks from the clinical realm, they had vendors.

Uh, they even had some folks who represented the government. There was a, there was a guy there who was from H H Ss, um, Mr. Graham, and there was a lady who was a representative from the, uh, the state who was there as well. Uh, I thought they did a terrific job of executing on the conference. That's great. I, I just did a, uh, podcast with Sarah Richardson, the SoCal Hims podcast.

And following me, she was, uh, interviewing, uh, a gentleman who's running for lieutenant Governor here in the state of California, uh, who is an ophthalmologist who, um, who was talking about all things health it. And that's pretty exciting. In fact, she just released that episode, uh, the SoCal Hims podcast today.

So a lot of, you know, it's political season. A lot of, uh, good conversations happen happening, and I'm glad to see, you know, the, the politicians starting to weigh in and become a part of the, uh, uh, dialogue. So we're getting a two-way dialogue going. It's kind of nice. It's especially interesting seeing the, the nurse who is also a state representative because it's a practicing nurse.

Uh, I think the state rep deal is kind of a part-time deal, and so she really could represent from the clinical front well, um, and she was well spoken. Yeah. That's awesome. Alright, so it, it, it's been a little while since you've gone here. And so one of the things we like to do before we get going too far is, you know, what, what, what are you working on these days and what are you excited about?

Uh, there's a lot . Uh, I would say the, the one word that comes to mind right now is prioritization. Uh, it sounds a little bit on the dull side, but trust me, getting this right is key to our survival and our sanity in this world. Um, particularly around analytics. We found that we had, uh, just such a large amount of requests coming in.

We really had to rethink our strategy. We're maybe three years into our original roadmap, and I thought we did a pretty good job of paring that down a bit and having some prioritization, but we realized. That despite our progress, we still had an impasse. And so we worked very hard to go from a whole number of queues that we had previously down to a single queue, uh, for work.

We added a queue recently to, uh, address population health and some of these new business models that are coming out. And that new queue, I'm really, really proud of. Uh, it has representation from a variety of, uh, departments. It's got population health, it's got quality. It's got analytics, it's got finance, um, it's got operations, and they work together to come up with a process around prioritization that's really healthy and transparent, um, and works well.

They developed a tool that has a weighted score, uh, based on different categories. And they run the request through that tool, and then a number pops out. And that's kind of a starting point for, uh, where it's prioritized. The great thing about it though is when folks, um, want something done and they look and they say, Hey, it's not making any progress, they can clearly see on our SharePoint side how it shook out and what the discussion looked like.

What I've noticed is that folks, uh, have a lot more literacy about that process and very quickly understand kind of where their, uh, individual request lies. Yeah. And, uh, I'm looking forward to this 'cause the, the whole series of questions that I have for you, um, this afternoon is, is really all around data governance and really getting pragmatic about it.

I mean, how do you, it just. One of the things I remember, of course, it's been, um, what it's been about three years since I've been c i o, but one of the things I remember is just the sheer number of, uh, regulatory of compliance, the ones you actually had to do. Yeah. That list was pretty big just in and of itself.

I, I agree. And the problem with that is it shuts down everybody else. So if you're a nurse manager, uh, in the, in the hospital and you have a great idea about how to improve care or throughput or something, You bring it to a committee and all those regulatory ones get scored really high and you get kicked out.

So coming up with a mechanism to be able to support those folks who are doing great work and really want information to inform their work while not letting down the regulatory folks has really been the trick. Yeah. And that's, it's interesting, uh, you almost wish you could say no to some of the regulatory 'cause you're looking at it going, what are we doing?

Uh, does this pass the sanity test of should we even be measuring this? Um, yeah, so, so true. Well, we have done, well one of the things we have done in terms of the, uh, the payers we're interacting with, and this is a very recent thing, we decided to tier our payers based on whether we're in a novel contract with them.

So if we're in a MA contract with a payer, , that is, that's a high end deal. We both have skin in the game. It's a true partnership, and those folks are entitled to a whole bunch of work from my analytics team. If you're a typical payer and we have just a, you know, a regular contract and maybe there's, you know, a little bit of paper for, for performance, uh, as part of it, that doesn't allow you to get additional efforts.

So in other words, our team has some standard reports that can come out, but extra stuff requires extra commitment. Awesome. Are you, uh, are, are you writing any of this up in like white papers or, or stuff that you're gonna share or is it just mostly speaking engagements and that kind of stuff? I've been on, uh, talking about this here with you today,

There you go. All right, well, we'll, we'll start getting it out there and, uh, see what happens. All right. So let's, let's get into the, uh, Because I, I really am looking forward to asking you questions around data governance. So, uh, our show breaks down into two segments in the news and soundbites. Uh, you've been traveling and, uh, because you're gracious enough to step in here, we're gonna do one story, and then we're gonna, uh, I'm gonna do a, a small section where we repeat tribute, uh, To, uh, Paul Allen with a, a little blurb that, uh, that Bill Gates wrote about him.

Uh, I think anyone in health it has to, uh, recognize with the passing of Paul Allen, one of the, one of the people that really helped to usher in, uh, the era that we currently live in. Good, bad, or indifferent, in terms of, you know, the, the complexity. Uh, he was, uh, one of the people who saw it early on. So here's our, our first story comes from the Keckley report, and this is gonna be a little harder for us to, to talk about 'cause it's.

Uh, it's a call to action and it's a wake up call for us, and, uh, if you want to get to this, It's uh, www.paulkeckley.com and this story is distrust in the US Health System. Are we paying attention? And he has a chart in here and it's the, uh, Gallup poll measures, uh, how people feel about, uh, from a trust standpoint, our various institutions, military, police, business, church presidency, Supreme Court, you name it.

Over the 40 year period, trust in Congress has fallen 34%, and trust in our medical system has dropped 38%. Uh, these findings parallel polling done by Pke Research, Harris, and others trust in the US healthcare system is low. Edelman called it an extreme trust loss. And, uh, it goes on and it says, uh, stories about fraud.

Uh, where's, where's it coming from? Stories about fraud, price gouging, uh, coverage, denial, excessive profit, avoidable error. Ethical breaches and unhealthy work environments cast doubt and, uh, uh, compromising truth in our healthcare system. The frequency of news coverage and social media attention to our misdeeds is intensifying lending to the general distrust in healthcare, uh, surveys.

Harris, pew and Gallup show that the public's trust in our systems, major institutions, hospitals, health insurers, and drug manufacturers at. Near all time lows and high profile disputes between insurers, hospitals, and physicians lend to public's suspicions that our talks, that our talk does not replicate our walk.

Uh, so again, is, uh, I guess where I wanna start this conversation is, um, Should we be worried about this? Is this, you know, is, is healthcare still local? That really, uh, you know, if you're a good local health system, that the trust level's gonna be enough that we don't have to worry about it? Or is this general polling that's going on across the country should, should we be concerned?

And is there something, uh, you know, we should be thinking about? Uh, well, in the spirit of good data governance, I think the first question that came to mind for me is define trust. Is if, if trust is this kind of blind thing where we automatically say, whatever this uh, entity is telling me, I'm gonna believe, then I'm actually happy that distrust has, uh, cropped up a bit.

And I think it's, you know, it's part of the information age with the internet and being privy now to all the frailties of institutions. I think it's, you know, just an. A natural outgrowth of that information is we're gonna have less blind trust. Blind trust, I should say, but I wonder if a better word would be confidence.

And confidence in my mind kind of has a portion of trust, but also allows for a little bit of nuance as it works for the system. But I was thinking about reasons why folks might not have as much trust in the system. There's a lot of things that are happening right now that I think plant seeds of mistrust, uh, in folks' brains.

One is when you just go see your doc and the doc spends the whole time looking at the computer. Yeah, because I think patients, you know, first and foremost wanna know, wanna feel like they're heard, and that the doc understands where they're coming from. And if the doc is, you know, absorbed by the computer, they're not gonna get that sense.

I also think about, you know, our process for releasing, um, health information to our patients. It seems clunky and cumbersome and, you know, to somebody who feels like, you know, that's my information. Why is it being withheld for me? I think it just sets up a dynamic where folks might feel like I. Um, there's a level of distress there, so outta the gate.

So what's appropriate? I mean, so let me, let me do this from a patient standpoint. You're, you're a physician, I'm a a patient and I'm coming to see you. What's appropriate for me? In terms of my lack of confidence, lack of trust. So I'm sitting across from you and you say, Hey, I'm gonna order this battery of tests, and I know that, you know, I just had these tests.

Am I, so I push back on you. If you're looking at the computer the whole time, do I say, Hey, you know what, Lee, my face is over here. Maybe you might wanna look at it. Or, I mean, what? I mean, how far does the patient go? I, I had a story this past week. A friend of ours who, uh, who's appendix burst and the first trip to the doctor, and they did the blood work and didn't see anything.

And then, you know, 24 hour hours later, the, the appendix burst and the co the, the, someone actually said to this person, yeah, you should have pushed the doctor for the other test. And I thought, well, that's interesting. I mean, the person who doesn't really know anything about healthcare is, is really the one responsible to push the doctor.

I mean, how, how far should the patient go with this? Well, the appendicitis example is a good example. I, uh, frequently docs, uh, rely on some blood tests associated with that, and yet we know the blood tests are awful. But it's one of those things in medicine that continues and it's one of my hopes with the advent of AI and different things that we do, uh, that our pathways will not allow us to go down and use these things that we know actually don't work.

But in terms of how far you push the doc, it's a bit of a delicate dance. On the one hand, you wanna be informed and you wanna make sure the doc is kind of doing their job the way they should be doing it. On the other hand, you wanna give them some autonomy to think through the situation and come to a good conclusion.

Um, in terms of, you know, over here, here I am, doc. Uh, if they're really spending that much time, sometimes I think it's beneficially, just call it out and say, doc, I can see you're kind of absorbed in that, you know, trying to navigate your E H R world, but I wanna make sure we have a one-on-one conversation here as well.

And sometimes that helps them reset. Yeah, I can see that. So, um, let's talk about, well probably two different directions here. Um, one being. Uh, have you guys, have you guys thought about this? Have you set up a team of people that's just focused in on the, uh, physician's, uh, experience during that visit?

That they're looking specifically at, uh, the clicks and how to get the screens out from between them and the patient and those kind of things? Do you have a, a, uh, maybe an experience team focused in on that? Is that something you guys are doing? No, I, we, we haven't done that, although I, I love the idea. Um, we do have our decision support team that's recently stood up that I co-chair where we're attempting to get our arms around this insanity of all of these things that are popping up in the docs face.

I will say in general, um, for most of the build that comes through that I'm a part of, I do spend a lot of my time ripping stuff out and getting rid of stuff that is, uh, in the doc's way, and sometimes that's extra clicks, sometimes that's extra icons and I, I. I kind of feel like it's part of my duty is to overlook that and make sure it doesn't happen.

Truth be told, it'd be better to have a whole committee of folks who can do that, but we're a, you know, we're a medium sized system. Yeah. One, one of the things that, uh, no, I understand that completely. So one of the things that Keckley goes on to say is that the erosion of public trust invites displacement by alternatives.

Uh, Medicare for all being one where, uh, government's, the solution, uh, Amazon Health being another that he cites, which is really, you know, creative entrepreneurs, uh, being the solution. Uh, And one of the things we talked about last week was that 40% of millennials, according to a recent poll, do not have primary care physicians.

They rely solely on, uh, clinics. So they're just going to, uh, clinics getting their one-off visit, and they're, they're done and then they, they go on. Um, are we, are we inviting disruption in here where somebody figures out a way to create that environment that. That a millennial will walk into and go, yeah, now that's healthcare.

That's how I want healthcare to be practiced. I, I think so that, that article is an interesting article. Uh, not surprising that, you know, with how mobile younger folks are and how healthy they are, it wouldn't make sense to have the, a same model that's been in place for a hundred years. Um, but to go back to just a couple of additional ways that I think we can undermine folks trust, I was thinking about, uh, a note I just read a couple days ago from one of my, um, partners and I looked at it and they've used Dragon and there was a whole bunch of Gobbly book in there.

It was, you know, words you can't understand at all. And uh, I looked at it and I thought if I was the patient and I reviewed that, I would think my doc is either, you know, they've lost their mind, they've done some L S D or, uh, they're not careful enough to review their own notes before they actually hit sign.

And so those are additional ways I think we're undermining trust. Yeah. Well, and, and we can go back to, you know, how we're managing physicians so that they have to sign those notes so quickly and, and just the, the whole R V U model and some other things, which I know that gets a lot of. Discussion as we.

You know, I wanna come back to the, uh, bill Gates Paul Allen thing at the end of the episode. So let's, let's go into the soundbites section. I, I do want to spend some time talking about data governance and some of the exciting things that you guys have been doing. So let's, let's start, I'll start with a set of rapid fire questions, and they're pretty basic, but I just want to level set people before we get going.

So, um, When someone asks you, you know, what's the definition of data governance? Or what is data governance? The, the principles and objectives around it. Why, why should I care? What, what, what do you tell them? Well, that word, first of all, I think, um, is a really confusing word. It sounds almost bureaucratic.

Yeah. Um, but really it boils down to exercising of decision making and authority for data. So you just have a team of folks who are charged with, uh, looking at the decision making. Scenario around data. And without having a structure around that, what you find is the data just falls apart. That if there is an accountability around it, people don't put data in the way it needs to be put in, and therefore it can't be taken out on the backside the way it needs to be taken out.

Um, and at the end of the day, if you do it right, your data is fit for business use. Not perfect, not, uh, and maybe not, you know, even a super high threshold, but fit for your intended purpose. Right? Yeah. And data, data governance essentially says, begin with the end in mind. It's saying, how are we gonna use this data?

Okay, now let's step back and put together a data acquisition strategy. And it would've been nice if we had started all the EHRs with a data governance program instead of implementing an E H R and then say, okay, we collected all this data. Now what do we do with it? So data governance really is a begin at the at how are you gonna use the data and then work your way back.

Yeah, it's true. Which is why, you know, having data stewards to really understand the, the workflow is key to the whole, the whole of success of the program. Yeah. And how do you, how do you embed those analytics and, and those things back in, so what, what are the elements of a, a good data governance practice?

We're gonna try to make this as sexy as possible. It's kind of interesting 'cause it's, people hear data governance, they, they turn off. But this is like, This is if, if, you know, I mean, as they say, you know, data is the new oil. Data is what runs Amazon. It's what runs Google. It's what runs Apple at this point.

Uh, and it's really what is, is at the core of what can really transform healthcare. And we know that. And data governance is just a way of us using data effectively within healthcare. So what are some of the elements of a good data governance practice? So we looked at a whole variety of different areas we could spend our time on, and recognizing we had finite resources, we boil it down to four main pillars for us.

Uh, and we've stuck to those pillars for the last two years and it's been pretty effective. Um, we started out with accountability, um, and then we, uh, also have proper use, uh, quality and then movement, both movement within your system and from your system to another system. And that was plenty of work to get our arms around.

Um, on the accountability front, we ended up setting up a structure that has four layers to it. At our top layer, we have our data governance steering committee, which is made up of our, uh, primarily our C-suite. They meet every other month and they set strategy about where we really should focus our efforts.

Yeah. Reporting to them are both VPs and directors who make up our data, go our data governance council and. The, the Data Governor's Council really have a specific area of focus for their domain. So it might be finance or revenue cycle or quality or nursing, et cetera. And then below that we have our community of data stewards.

And those folks are the ones that really understand the workflow associated with the individual, uh, question at hand. And then below all that, we have our Office of Data Governance that supports those efforts. How, how often do you get all the data stewards together?

Yeah. And that's, it's been interesting 'cause the, the data stewards, we thought that would be kind of an even cross-section, but it's, it's, there's been a variety of different levels of folks who've been involved to really understand the workflow in a way that I didn't, uh, anticipate going into this. Uh, but if you get the right people understand the workflow, they can very quickly resolve a problem.

Um, but that's the key, is getting the right person. And the way we structured it around the accountability front is that each layer has a reporting relationship. And that was the key because we didn't have, uh, extra folks that could just kind of throw at this effort. These are folks who have full-time day jobs and we're asking them to do extra stuff on top of that.

We recognized it, despite the fact this is a institutional priority, uh, in general, and we talk about it, uh, at our, our meetings, et cetera. Unless you have an accountability built into that, we felt like it would be, uh, you know, prone to failure. Yeah, I can see that. So you're, you're steering your, your C-suite is your steering committee.

Are they just setting more or less the guidelines, uh, or the, the principles of the, of the program and then essentially acting as the, uh, escalation point for those things which can't be solved at those layers? Just below that? Yes. Yes. Both of those things. Yeah, for sure. And in the beginning it was really about educating the folks around the table.

About what we're trying to accomplish and we, we planted some seeds at that time. We asked them to start looking at their own reports 'cause they were all getting reports from different areas. But really pushed back on the people who are generating those information products and handing it to them and asking them to ask the people who gave it to them, what's the quality of this data?

How do you know the quality of this data is what you say that it is. And that has generated some interesting discussions. And then on top of that, they help evangelize what we're trying to accomplish and support the folks who are actually doing the work. The data governors, they meet, um, they meet monthly and they meet for an hour and a half and they have four subcommittees that work on individual, uh, topics.

And they've been very engaged in this process. But to have VP level and director level folks spending this much time on something. There was no way we were gonna do this unless there was an accountability structure that accounted for that. Right, right. And, and so when you say C-suite steering committee, how many C-suite, uh, how many people from your C-suite do you have on it?

It, it's a, it's a portion of it, so it's probably guessing It's a roughly half. Wow. So that shows a significant commitment from your organization around the value of data and the value of, of, uh, the insights that comes from data. I. I feel like that's the case. Um, our current C E o Roy Vineyard, he really did a great job of understanding why it mattered and evangelizing the importance of this.

And I think he set the tone for the rest of the organization. Right. So that, so that was the next rapid fire question, which was how do you get started? And I would assume you have to start at that c e o level and get, and, and if your C E O understands the value of data, Then it's a matter of coaching them on, okay, here's how we'll put together a program.

Here's what you can expect from it, and here's the communication that, um, really needs to come from the top down to, to get everyone really on board. Uh, but it sounds like if you had a c e O that was there, maybe was, was the c e o the instigator or was it sort of a, a dual kind of thing? There was a preparatory period where, um, I spent a fair amount of time talking to him about it.

Also, our c i o spent a lot of time talking to him about it as well. And he, he's a very, um, detail oriented leader and he really wanted to understand a lot of the details. And once it clicked, it became clear to him. Then he really started to evangelize why it mattered. And that, again, really set the tone in terms of starting, um, I would say call us out.

And I'm half joking when I say that, but I will say that our sys, when we put our, our system together, we, uh, spent time talking to a whole bunch of other systems out there that have been down this road before. We ended up collaborating with like 13 different, uh, health systems across the country. And it was really helpful to talk to other folks who were, you know, waging the same, the same battle in their institution.

And we learned a lot. So I'd be happy to connect folks who, uh, may be watching right now to kind of jumpstart it. But in terms of where to actually start, I think you really have to have two people in the saddle out of the gate. You have to have a, an executive sponsor, so that's typically A C M O C F O, or C M I O.

And then on top of that, I think you have to start out with a data governance program manager. Somebody who can really devote their time to understanding what we're trying to accomplish and putting in place a framework for accomplishing it. Yeah, it was interesting. I was on a, um, I was on a webinar where they asked, you know, who should lead, who should be the executive lead of the data governance, um, program.

And as you and when people answered, The most. Uh, so the c i O was like 20%. The C M O was like 18%. C F O was only 2%. Um, c o o was like 20% and other was 20%. And so it was interesting that there wasn't a consensus on who should really own it. And do you, so do you see across different health systems that different people own the data governance?

Y Yeah, I, I've been disappointed to see a lack of, um, C-suite or executive sponsorship for it. It, I, I can tell at least so far, it feels a little bit like a hot potato and they, they know it's important, but they also know that it's kind of in its early stages. It's almost like an early I p o and they, you know, they wanna, they wanna be a part of it, but don't necessarily want their name attached to it.

Um, but I think you just gotta, you gotta identify somebody who really A, understands it and b, recognizes how it's gonna benefit the organization who can really champion the effort. Yeah. And it's, it's, and it's a leadership role, right? So it's, it's a, you are influencing, you're changing the culture around data across your entire organization.

So it requires a special person and it's not something that you can just. Throw over the fence. I see a lot of health systems now hiring chief data officers and saying, okay, we're gonna give it to this person. Well, okay, that's fine, but don't hire somebody that's just really good with data. You have to hire a leader who can, uh, who's respected across the board, who can interact really well with the leadership and, uh, and, and move the culture forward with, with education and, and other things.

I would think. Yes, really well said. I, I would say that, um, in our organization in the beginning, the first year or so was all about educating folks about why this matters. And one of the reasons, or one of the things that we did in order to accomplish that is we profiled our own data. I think I might have mentioned this before, but when we decided to profile our data, we were initially gonna purchase a tool to accomplish that.

And we were, um, we were trying to do this on the on, on a budget. And then we ultimately, um, built out a tool, a SQL based tool to query our data. And, um, the, the program manager, mark Stockwell, who I'm really fortunate to work with, um, built this out and we applied it to some really straightforward cases.

So that was the case where we looked at the, the number of patients we had who were older than 125, and we had like 4,000 patients over 125. We recognized pretty quickly, Hey, we got a problem here. We looked at our A one Cs and they were, you know, they were kind of all over the map. But then when we asked, you know, good, hard questions like how many patients have an A one C, that's physiologically impossible, and we had like 300.

And so when we start to find those cases, presenting that information back to the C-Suite to begin to understand. How much it matters to get this right. And then, uh, the other piece about this is for several of the regulatory, um, uh, programs, either the C m O in our, in our system, the C Q O or the C F O, have to sign off on the validity of the data before it's submitted and showcasing some of the data issues and then showing how we're working the problem allows 'em to feel confident about signing off on that data.

Interesting. So by profiling the data, what you're doing is you're going into the raw data, you're pulling things out, and you're asking questions against that data and really doing more of a sniff test to say, Hey, how, how good is our data? Yeah, yeah, exactly. Because there could be a lot of erroneous data that's underneath that crazy threshold that we set.

Right. We said 1 25. That doesn't mean that everybody who's below that actually has the right birthday, but it does, as you say it, it does kind of provide some information in terms of a sniff test of how our data's doing. So, uh, you know, one of the people I respect a lot on this topic is, is Dale Sanders, uh, health Catalyst, uh, chief, what is he?

Chief Technology Officer, I believe. Um, and he wrote a, a paper where he talked about the triple aim of data governance, and I, I am sure he got it from somewhere else. May, maybe it's original with him, I'm not sure. But triple aim of data governance is, uh, number one, ensuring data quality. Number two, building data literacy.

Number three, maximizing data exploitation for the good of the community. Um, so let's walk through these real quick. So ensuring data quality, what are, what are some of the best practices that you have seen either in your system or in the industry for ensuring data quality? So I think you gotta start by, by assessing current state, I think it's hard to say, um, you know, you can't really work on it unless you know where your starting point is.

So that's that whole profiling piece. But it also has to do with engaging the data stewards in the process to better understand how it's, um, how the data's coming in. In addition, when we report on that data, it's important to engage the folks who are consuming the information products. To ask them, how does this, how does this shake out?

Um, once you do that, I think, um, you have to identify which areas you're willing to work on and which ones you're willing to let go. There's just so much data in a health system. It's um, it's hard to, uh, focus on everything. So you gotta pick your battles and zero in on things that you think are gonna be the kinds of things that when you accomplish it and you evangelize it, it will be impactful.

But also that the specific thing that you're working on really benefit the institution. So, um, you know, we looked at some simple things to begin with. We looked at things like length of stay, and it turned out we had 13 definitions of length of stay, none of which were actually correlated well with each other, and they were used without further defining them.

So people didn't really know what they were getting when they were looking at the information. And that goes back to that data literacy that, that he points out. I fully agree with his assessment that that needs to be a key component of this. Um, but people were looking at reports, looking at information and seeing descriptions, but not really knowing what it meant and then interpreting it and doing something with it.

And so, you know, getting ahead of that and putting in place a system to, uh, to provide literacy to folks who are using these reports is a key component of it. Yeah, it's, it's, it's interesting 'cause that's one of the places we started. Um, a lot of the things you're, you're echoing When we did our, when, when we did our, uh, data management and data governance, uh, solution at the health system, I was at the.

One of the things we created was a metadata repository where we actually went through our data and one of the hardest things we had to do was to say, what does this data element actually tell it? What is it actually? And, uh, length of stay was a, was a great one. I mean, it ended up being a, you know, multiple meeting conversation to get to an agreement on what length of stay was.

And it's, um, and, and, and there's, there's, obviously, there's a lot of others. All right, so second question. I'm sorry, go ahead. In that particular case, so just to, to showcase a little bit how we actually went through this process. So we had 13 different definitions we identified and the data governor for that was our director of, um, of, uh, finance.

And she brought together the right data stewards and the right team to really work the problem to, number one, assess current state, and two, identify what are the needs of the organization. She ultimately worked with that team to compile a list of five separate definitions. But they're, they're different for different reasons.

Yeah. And they're clearly defined now, and they're published and they're transparent. So now when reporting goes out, it doesn't just say length of stay, it'll say length of stay A or length of stay B. And you can define that so you actually know what that means. A simple example, but I think really impactful in terms of interpreting the information.

Absolutely. Alright, so second question. Every, every role in healthcare in, in healthcare at this point has some aspect of, uh, data analysts role in it. And, uh, how have you been able to build data literacy across, uh, uh, an organization and for, uh, from an outside looking in, it looks like a growing organization.

So you're constantly not only educating the people that are there, but you have new people coming in. Uh, you try to hit it from a lot of different angles. Um, I've written a number of, um, internal articles for our organization that gets, uh, published with our newsletters, uh, to start the conversation.

We've also, uh, educated and then asked our C-Suite data governors to push back on folks, giving them information as I said before, but our most recent efforts, uh, re revolve around an actual data literacy project. And within my team, we have a principal trainer. Who, uh, is focused on analytics, which is a bit unique, uh, in this space, and we're kind of leveraging her abilities around, um, I'll call it supported self-service for the most part.

But in addition to that, uh, she's been tasked with coming up with a program for data literacy throughout the organization. What I found in my initial evaluations of this is that information products are being delivered to folks. Is really over their heads that when they look at it, the data is presented in such a way that unless folks have some specific training or skillset, they really are not probably fully understanding that.

So we wanna get ahead of that really quick. And so she's working on that right now. So we're on the front end of that. I hope next year if we, if we talk again about this, I can give you a little more feedback in terms of how far would the dial. Yeah, definitely. We'll definitely come back to that. So let's get, let's get, uh, pragmatic on this.

Uh, what are the areas that you believe can utilize data to have the greatest impact on the communities that we serve? Communities that we serve? Well, I think. In our case, we're a medium-sized health system and we're not owned by a larger system. And we feel like because we know the community really well, we can provide great service, but in order to do that, we have to be financially solvent.

And so, uh, surprisingly, I think I would, um, start out with some financial data. I would talk about cost accounting. Um, for example, uh, we talk about, um, one of our pro projects right now is to focus on, um, accounts receivable rejections. So it turns out that when you get rejections that come into your big bucket of rejections of, uh, uh, payer claims, uh, they have numbers on them that correspond to the payer, but they don't correspond to any kind of, um, general interpretation.

And so folks end up working those problems kind of one at a time, and it's incredibly slow. So what we wanna do is really have a, a mapped, um, evaluation of all the rejections that come in so that folks, when they come in, they immediately understand what the problem was and they can work to a, rectify it for that individual claim, but b, put in place a process so it's not rejected in the future.

And that's really the essence of data governance versus data cleaning. Data governance is really about not just fixing the problem, but putting in place the process so it doesn't happen again. Yeah. And there's, um, when, when putting together a data governance program, one of the things that it's, it's not wrong to focus in on the financials first.

And the reason that I say that was, uh, and, you know, and we were a faith-based ministry and, and it was a ministry and, and, and, uh, first and foremost and we were about the needs of the underserved. But at the end of the day, um, you're trying to get a data governance. Program in place to improve quality, to decrease costs and all those other things.

And you need to get it funded well. There's a whole bunch of areas that if you do it well, you'll free up a whole bunch of money that will fund this so that you can, um, really grow the program and continue the program. So it's not wrong to focus in on, on money originally, uh, on, on a program like this. Uh, but I, so let's, uh, Give us one or two use, use cases to highlight what you guys have been able to do at Asante Health, uh, with, uh, over with your data over the last couple of, uh, last couple years since you put this program in place.

So, um, one of the ones that comes to mind is, um, again, a simple example, but our problem list. So the problem list is, um, something that's used by the inpatient docs and the ambulatory docs. It's commonly used, but it's commonly used incorrectly. So what ends up happening is folks, um, are seen by their doc and they get this ever increasing problem list list, uh, that becomes increasingly inaccurate.

And it's one of the, um, strange aspects of having an E H R versus a paper record. With a paper record. There was this, I'll call it a, a natural attrition that happened with the problem list. The doc would've to actually write the thing again, and unless it was worth it, they wouldn't actually write it. So stuff that was old or irrelevant wouldn't make it onto the newest problem list.

But in the E H R world, it just gets pushed forward and there's not really a lot of standards about what actually constitutes the problem and when a problem should be resolved or removed. And the reason why this is so important is because a lot of our registries are based on the problem list. Okay. It asks really simple questions like, is the patient alive or dead?

And if they're alive is X problem on the problem line? And if the answer is yes, they go into a bucket on a registry. So getting that wrong has a lot of implications, but we put together a team about a year ago, uh, and it has six ambulatory docs and six inpatient docs coming together to work the problem and.

They've met every month since then and they put in place policy and procedure and they've evangelized change around what qualifies as a problem and what doesn't. And it's really been terrific to watch that process move forward. So that's, I, I'll call that a win in our, in our box. No, that's great. Well, um, you know, we, we'll definitely, uh, definitely come back to you on this as, as the journey continues.

Uh, I, I do want to close out, I'll close out with this, uh, story. Bill Gates wrote a nice little, um, Note about his time with Paul Allen. And in this, just to give you guys an idea of who Paul Allen is, uh, Paul for, uh, this, for Bill Gates', words, Paul foresaw that computers would change the world even in high school before any of us knew that personal, uh, what a personal computer was.

He was working. I was going to college. One day he came and got me insisting I rush over to a nearby newsstand with him. When we arrived, he showed me the cover of the January issue of Popular Electronics. It featured a new computer called the Altair 8,800, which ran a powerful new chip. Paul looked at me and said, This is happening without us.

That moment, mark, the end of my college career and the beginning of our new company, Microsoft, it happened because of Paul Allen. And he has done the same thing in a lot of other, not only in the computer world, but with philanthropy and some other things. So I, I, uh, just wanted to give him a shout out, uh, when people make that kind of contribution, uh, especially in the world of health, it, we wouldn't even have a lot of the stuff we're talking about today.

The work that those guys did early on. So, uh, Lee, thank you again for coming on the show. Uh, what's the best way for people to follow you? You seem to be everywhere these days. Uh, on Twitter it's, uh, Lee md, it, uh, and I'm on LinkedIn. You just look me up on LinkedIn and then my email is is lee milligan@me.com.

Great. Uh, also, you, uh, you can, uh, you can follow me on Twitter at the patient cio the show at this week in h i t, our website this week in health it.com. And the shortcut to the YouTube channel is this week in health it.com/video. And please come back every Friday for more news information and commentary from industry influencers.

That's all for now.

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