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 Today in health it, we have a great conversation with a senior information scientist with the Rand Corporation, Bob Rudin, who has just, uh, as part of a group, has just published a, the results from a two year study on optimizing health it to improve health system performance. And we're gonna go in depth into that study.

Have a great back and forth. I think you're gonna enjoy the show. My name is Bill Russell, former healthcare. CIO coach, consultant, and creator of this week in health. It a set of podcast videos and collaboration events dedicated to developing the next generation of health leaders. I wanna thank Sirius Healthcare for supporting the mission of our show.

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So, without any further ado onto our show. . , some research was just published on the topic of optimizing health IT to improve health system performance. And today we're going to explore that research with Bob Rudin, senior information Scientist with the Rand Corporation. Welcome to the show, Rob. How you doing?

I'm doing great, bill. Thanks for having me. I keep going back and forth between Rob and Bob. It's Bob. Bob is more common for me. Yeah, there you go. I'm excited. I came across this, uh, research and I was reading and I thought, this is really interesting stuff for our, for our listeners, and you make some distinctions in the research, but before we get there, I have to establish it.

So te tell us a little bit about. What the RAND Corporation is and, and, and the work that you guys do. Sure, yeah. The RAND Corporation is a nonprofit, uh, think tank. We are a research organization. We do research, uh, in the public interest and we publish lots of stuff. All the stuff that I work on is in healthcare, but we do a range of different topics.

Some people work in the military side of things and yeah, we're we, we do a whole range of different research. What most relevant for us today is . In the healthcare domain. And for that we do population health systems, all kinds of stuff related to that. Yeah. So the paper that was just published by you and your colleagues, uh, tell us a little bit about.

The, what's the origin of the study that you guys did? Sure. So I should, it's important for me to mention that this study was funded by the Agency for Healthcare Research and Quality. That's a, it's a, a grant that, that was awarded to Rand and the All of us, uh, big, large team of people worked on it, including people outside of RAND as well.

And the idea behind this was to get a better, the, of the larger project was to have a better understanding of health systems. And what I mean by health systems are vertically integrated, so hospital. Hospitals and clinics, not just standalone like hospitals or standalone clinics, but like this, uh, larger entity and we're specifically interested in that 'cause it's becoming more common.

So as I'm sure you experienced in, in your time working in this space, bill is like. These systems are growing, they're getting bigger. There's mergers, they're consolidating on the whole, they're more and more the type of work that if you're gonna go to see someone as a patient, you're gonna probably see someone who's affiliated or a member of these larger health systems.

So that was the, the gist of this. Large grant that a series of projects that was funded by AHRQ and this project in particular was looking at health IT in the context of health systems and how health systems were trying to use health IT to improve their performance. And we talked to help with executives from 24 health systems around the country to try to get a, a, a sense for how that's happening.

So 24 midsize to large size IDNs, uh, integrated delivery networks essentially is, is who? Yeah, I, I would say we, we had a few on the smaller side where they had maybe only a couple of hospitals and not too many clinics, and then it ranged all the way from large, dozens of hospitals spanning multiple states, and there was quite a number in between.

So we tried to get a, a diverse range of health systems. In terms of geographic location. We picked four different states, and also in terms of size and some other characteristics too. So give us an idea. I'm not as deep into academia and these kinds of studies as, and maybe some of our listeners aren't either.

How do you go about collecting the information? Is it predominantly through interviews? It's all over the map for these studies. It, it depends on your study question, so I. For, for this particular study that we did on Health it, everything was derived from interviews with executives. So we tried to basically interview essentially the whole C-suite CIOs, CMIOs CEOs as anyone who has relevant experience in the IT space.

We looked at, at data from them, we interviewed more than a hundred executives, but we also looked at, in part of this part of the study, some other studies, which I . Happy to, to, to give references to you or your listeners, but we also looked at some quality measurement data, and I think there was some survey data.

There was some survey data, uh, as well. So we, we collect data from all kinds of different places, use secondary data where we, where it makes sense to, it's the type of methods and data, it's all over the map. Whatever makes sense for the study. So what's the hypothesis or. What's driving this? What were you looking to identify with this specific study around optimizing health it for this the, when we started this study a couple years ago, and the impetus behind this was that it had been about a decade since the passage of the High Tech Act, so about a decade since we as

As a country decided to invest on many billions of dollars in our, in our health IT infrastructure in this country, and to promote adoption of electronic health records and, and, and other forms of health it, and we said, now is a good time to look back . And understand how things are going. Now, from a macro perspective, if you look at the the big numbers, it's hard to see a great impact from all this investment.

So we look at the big impact in terms, the big numbers in terms of costs. Costs of healthcare have not gone down and qual by. The best quality measures we have, they still are not where we like them. We still see roughly on any given quality measure, something like 50% that you're about half likely to get that recommended treatment as you are not to get it.

Quality is very complicated to measure, but still those are some indicators that yes, we're not really making huge headway. So we said. If we, maybe let's go in and try to figure out what's going on, like what, what's happening. Let's do some qualitative research and try to open up the box, the black box, and see what's happening inside and say what, you know, if, if it's not coming, if we're not getting this value from these, from this technology.

Why not? And what could we do better? What are the opportunities for making improvement? Because clearly there's opportunity to make better use of technology in healthcare and in many other industries like it's, you see it in every industry, all kinds of efficiencies happening. What's why isn't happening in healthcare?

We've got technology everywhere now. What's the problem? What, what is really going on and what's the problem? So we did a in-depth investigation into these 24 health systems and tried to talk to the, the, the leadership and see what we could learn. Wow. Actually, as you're talking, I'm writing down, like I'm writing down like my hypothesis as to why we haven't seen major gains over the last 10 years.

But before, before, I'd love to hear your hypothesis. It would be great. And I think, I think we're, you know, I'm, and actually I'm going to, I think I'm gonna go there, but first. I want to get some of the findings so you have Sure. You have some great tables in here, and I love the distinction you made of improving the performance of it as opposed to improving the performance of the system.

Give us some idea of some of the findings that, that you guys, uh, identified as you did this work. Yeah. The first thing that we, we, after we collected all this data and looked at it, we saw that the things . Fell into a couple different buckets and what, and what these health systems were trying to do. One of it was they were just trying to get the foundation.

They were just trying to get some real fundamental things, um, in place, and I'll talk about some of those. Then the other thing they were trying to do is once, and this is you have to do one before the other. It's trying to use the foundation to actually create value. It's like trying to build a house and then figure out how to live your life in it.

So the first step, step where they were doing things that, it sounds really basic, but gosh, they took a lot of work. So for example, a lot of the TE systems we were talking with, they were still trying to get whole, their whole health system onto one unified electronic health record. This is, and they the, there's, I think we can say from this study and

I, I haven't heard anything to contradict this. There's now the industry consensus. It seems that it's better to be on for a health system to be on one electronic health record than on more than one. There's just a lot of efficiencies that you gain from doing that. And we only found one health system of the 24 that was not on one, that actually was on a separate inpatient and outpatient and was not planning on changing.

And we asked them, we're like, . We didn't know at the time they were the only one. Everyone else was either in the process of merging . Or had already merged. And sometimes they were on separate instances. They had the same vendor, but they're on separate instances and they were working on merging instances.

So it's not enough to just be on, they have to, to be integrated on one platform. So we, we asked 'em, we said, why not? Did you have you thought about that? And they said. We, we did think about it, but it took us 10 years to tweak our system to get it to where it is now. It would just be so painful to have to, you know, rip it out and replace it.

But they did say, looking back, it, it would've been good to be on one system. So I. That's one thing we learned. So that, and like I talk about the more of the foundational in, in a bit, but once you get the foundation, then it's a matter of figuring out how to use it to improve value. And the, that's things like trying to identify variation in care, trying to to integrate latest evidence into practice through different means and make the the IT configured so you can enable that.

So we found . Those two buckets. And I think a lot of people when they, when we initially started 10 years ago with high tech, we assumed maybe that we just throw the technology in place and it would create value immediately. And I think what we're seeing is that there is this foundational level at the beginning that really is a lot of work for health systems.

And once you get that in place, then you can start really doing the stuff that creates value that where you can start analyzing the data. You can start. Finding out where you need to change your processes. So let me tell you on that, on that foundational part, there were two things that really jumped out and we didn't plan on this going in.

We didn't know what we were gonna find. We had a few questions in the interview guide, but we ended up talking a huge amount about standardizing data and standardizing processes as in workflows and, and stuff like that for those two things. Each of those. We used standard qualitative methods and coded them and assembled them for each of those codes.

There were 200 pages of single space texts that these executives talked about. There was the most material of any other topic that we looked at. So I was, I, you know, had to read through all of 'em, but the message was really clear, and that was, in order to get value, you've gotta standardize your data.

'cause you can't do analytics on data that's not standardized. It's just so messy. You can do analytics, but it's a lot less, less valuable. And then the processes, if everyone's doing their own processes, it's hard to make improvements. It's hard to integrate new evidence, and it's also hard . To even to give a guarantee to the patients that they're gonna get the same experience no matter where they go in the system.

So that was the, those two things were, I think by far the most amount of work that health systems were investing their time into it. And some were much farther along that path than others. Yeah. It's interesting. It feels like we just got to the starting gate. It just took us 10 years to get to the starting line.

And so now we have, uh, you know, things like standard systems and interoperability, some standard data sets. We're looking at, uh, U-S-C-D-I, we're looking at fire, we're looking at. A whole bunch of things that are going to, uh, open this up, but it took billions and billions of dollars in investment. It took a, a fair amount of, of a fair amount of, uh, time and effort and, and create, quite frankly, created some, some challenges for the health system along the way.

And so it, it, it's, you know. You know, improving the performance of it. Part of the frustration I think with physicians and when you talk to health systems is we spent so much money and they, I think they expected, once we get the EHR in, everything is going to all of a sudden take off. But the reality is you just rattled off a whole bunch of those things of, hey.

Getting that system in requires us to, to, to standardize our processes, to standardize our codes, to, to standardize our appointment types, to standardize our, and that work ended up being a lot more, I think, than what health systems anticipated going into going into the EHR. And then as they finished. They, they, they kept growing and so they merged with somebody else and they'd take on, you know, additional systems and they'd merge with somebody else.

They take on additional systems and so the, it's, it's not like there's a beginning and an end date. It's, it's a, it's a beginning. Get those processes, get the data, and then you're. Constantly moving in that direction. I, I don't know if there's a question in that. I'm just throwing out some of the things that I've seen that have really kept us from optimizing in the first 10 years since high tech, but I think.

There's some promise moving forward as well. I, I, I think you're spot on with that. It's, you mentioned some interesting examples. So appointment types. We talked to one health system that they, they said that in order for them to do analytics and to do appointments like in a consistent way, they really only needed something like 15 appointment types for, you know, that's, that's, that's all they needed.

That they needed everything to . Mapped to those 15 and that's, that would capture all the different variation of different types of, of patient appointments. When they went in to try to look at it, they found that they had 20,000 Right. Appointment types. And it's 'cause they let, they basically had let every clinic, every hospital just decide this on their own and make this up.

And they said, go ahead. You guys figure it out. So everyone built it slightly differently. Lots of overlap. But if you can imagine, if you wanna try to act as a system and have some kind of analytic view or do some consistent scheduling process where you can schedule, get a a, a viewer, you can schedule at any clinic in the

Same unified way. You can't do 20 for all those vis types. Like you can try mapping them, but then you have to update and keep track of all. It's just so they were spending an enormous effort trying to harmonize all that data. I. We were trying to roll out a new digital front door on top of our EHR. I remember just a number of meetings.

People would go, how hard can this be? Yeah, I just go to open table and I go. I said, fine. We had that same thing. It started with appointment types. It was like, all right, there's 20,000 different appointment types and we have to narrow that down. By the way, the health system, that's an awful lot of meetings, an awful lot of governance, an awful lot of you just to get through it.

That those appointment types, you think, okay, we're almost at the starting line. Nope, not even close. Then all of a sudden you have to start to to worry about the number of forms, right? Because the number of intake forms. Popped up over the years and now all of a sudden you're sitting down with doctors going, alright, we wanna standardize this intake form.

Here are the 800 different intake forms that we have. Let's get it down into a single one. When you get down into a single one and you accommodate it, everybody, the intake form is so long that it doesn't feel like an experience that you would get from OpenTable. It feels more like an.

Sat, yeah. . It was, it's underestimate clean. Of how we, the administrative side of how we ran healthcare and the accommodations we did. 'cause we didn't see 'em, we, it didn't matter to us. As long as they collected the right information in a paper form and then entered some of that stuff into the computer, it, it didn't matter.

But now all of a sudden, when you're talking about systems that are going to touch. Multiple geographies, multiple, multiple patient types and those kind of things. Now all of a sudden you're like, Hey, you know what? That is the promise of digital. The promise of digital is that not only can we create those experiences, but the promise is also that we can do, uh, the research, right?

So it's, we were gonna get all this information in there, but let's just take oncology. It's like, oh, great, we got all this oncology data. And then when people started to break it out and start to do reporting, they're like, I can't do the reporting because you call something this and you call something this and you prescribe something with 10 tablets of this and you prescribe things as three tablets of this.

And it's actually the exact same thing. And, and so our analytics team were just spinning and taking so much time to clean that up or, or so, I'm sorry. I, I'm sort of just telling you why I think we're at the starting gate, and that's essentially what you're, you described here is the two things. Improving performance of it was all about getting that EHR and maybe even the ERP solutions and other things.

But now we're starting to see this shift to improving the performance of the system. What does some of that work look like? I honestly, like most of the systems, . We're just beginning to get there. They were working on this foundational stuff. They were working on standardizing the data, standardizing the processes, getting everyone on the same EHR, and only just beginning to, so we have a sense of what they were doing in terms of the adding value.

But the emphasis that came across really clearly is most of the, the health systems, even the more advanced ones in . These activities were telling us that they were just beginning that journey. So I, but I can talk about some of them. I first wanted to mention though, you mentioned governance, so we didn't include it in this paper just because we didn't have space, but we also learned quite a bit about governance and also some of the, the, one of the kind of early foundational activities is to try to figure out a governance plan.

Like some of these health systems we talked to, they were still just trying to figure out how to make decisions like they, most decisions were . Made an ad hoc, they'd created an ad hoc committee for almost every decision, whereas some were actually pretty far down the line in terms of, uh, having very structured processes for, for governance.

So that's. A whole other dimension, which we didn't even include in this paper, but we're, we're, we're thinking about including in maybe a future paper. Yeah. So, go ahead. No, I just, trust me, I, when, when we went to roll out the portal, I had to talk to five different boards and each board wanted to speak into the user interface, into the data elements, into everything that we were doing.

Uh, so we finally got agreement between those five boards to appoint some doctors who were part of a committee. That would essentially, instead of going back to all five boards every time we wanted to do a change, uh, that they would do that. But just that process in and of itself once even after you get all those doctor's to agree and, Hey, the portal looks good and we're a portal, the.

The app we were gonna roll out looks good. You still had to get approval from those five boards before because they're not, uh, in the state of California, they're not owned by the health system. They're part of a foundation model. And I think that's part of the, uh, that's part of the comple I came from outside of healthcare.

That's part of the complexity I didn't appreciate. It's just every system is built a little different. There are, there are joint ventures, there are management agreements. There are, uh, wholly owned subsidiaries. There's so many different, there's so many, I don't know, personalities and politic politics associated with rolling out the technology that I don't think people recognize is actually, is actually there.

I I, you're, you're spot on. And also that plays into what you, another observation is like that people's expectations are that it's as, it would be as simple to use as their, like consumer apps, like OpenTable you mentioned. That's . If you're not, if you haven't, you know, built these or have, you know, some experience, you're initially think, oh yeah, I'll just adopt some tools, throw 'em in there, and everything will just work just like OpenTable.

But to get that to work, like I, and I'm not an expert in OpenTable, but they had to get agreement on those processes. All of the people who, who, all the restaurants they need . To abide by certain rules and follow the instructions, and the workflows are not nearly as complicated as they are in healthcare, but it, it gets at one of, one of our big observations with this is just how inefficient this is.

Like every health system trying to figure this out on their own, like harmonizing all the data. And figuring out all these processes, like for the most part, we didn't see that they were able to learn too many lessons from others. Some had figured out and were able to standardize, and it certainly wouldn't be possible to have everything perfectly standardized across the whole healthcare system.

But we couldn't help but notice that there was a lot of reinventing the wheel going on. On these fundamental activities? Yeah, so people are starting to do work on essentially improvement, improving the performance of the system. Obviously things usually start with monitoring and providing feedback to the providers, but then we start to move to some more sophisticated things, population health.

Implementing evidence-based procedures. You guys identify some of this stuff, reducing variation of care. You know, these, these are some of the, some of the initial projects that you were finding. And just so everybody's clear, you did this research over a two year period, is that right? We did, we, we did, we conducted the, the inter, the like 128 interviews, I think over a, over a two year period.

The, the, these are, these are like long-term, long-term efforts. So I, if I were to guess, I wouldn't guess there'd be that much more advance advancement in the last like couple years just because things take so long. Yeah. And . I've watched some videos where doctors are trashing the EHR providers or health it and those kind of things.

And, and some of it's, some of it's warranted to be honest with you. As I listen to their arguments on some of this stuff, I'm like, yeah, no, I get it. I understand where they're coming from because for we, we spent 10 years putting a foundation in place. Mm-Hmm. and . It. It didn't deliver on the promise because of all the work we had to do to clean up the health systems, but there's a couple other things that were pretty basic.

They're like, I haven't worked on these interfaces since I was in college. This is like word perfect 5.1 that I'm, I feel like I'm working and, and that reference like just flies over the head of so many people. But we used to have to print by hitting shift F seven, and I remember those. Yep. Now I sound old, but

But that's what they felt like. They felt like . In, in almost every other area, I could do a Google search. Relevant information comes to me. Uh, I can find just about everything I want, but when I go into this EHR, I've got to, you know, dive deep into, uh, multiple areas, lots of clicks, try to find things. The, the interface isn't intuitive.

It wasn't intuitive. Uh, it didn't use new methods. So the tech held us back. Uh, I think to a certain extent, the practitioners, this, a lot of this stuff was new. Uh, I, I, I look at some of the implementations and you go back and you talk to some of the people that were around in those early days, and it really was the Wild West.

They were trying to figure it out. At one point, we had hundreds and hundreds of EHR providers to choose from, and so you, you chose one, you implemented it. Three years later, you realize that provider's not gonna be around, and now all of a sudden, . The winners are starting to emerge and you go, okay, I'm gonna go in this direction.

And then three years later you realize that provider's not advanced enough and now all of a sudden it's down to really a handful. It's, uh, epic, Cerner, Meditech, and Athena, maybe a handful of others. Uh, Allscripts. And you know, that's, but when we started 10 years ago, that was not obvious that it was gonna be those players.

And so to a certain extent, you had . You had some bad implementations, you had implementations on technology that went away. That sort of slowed us down. I think the other thing that's happening now, which people don't want to talk about, I'm sorry, I'm talking a little bit too much. I usually just ask questions, but this is sparked some thoughts, is I, I'm listening to you.

One of the things that's happening now and people don't recognize it, is when you reduce the number of players in any field. And, and right now you could really say that the major players in the EHR are Cerner and, and Epic. For the most part, the amount of choice goes down, the amount of Masters that they have.

If you consider every implementation to be a master, I. That has needs and requirements. Every physician using it has needs and requirements. The pace of innovation goes down because they, they also have the same tech debt that, uh, we have in health. It, they also have the same challenges of staying up with, with the regulatory environment.

And now you pile on top of that, not just one health system's needs, but hundreds of health systems saying, Hey, . We need this, it becomes much harder to, to innovate in, in the ways that we're looking at. So now I need to form a question because I'm an interviewer, not a pontificator. Well, may maybe I'll ask you a question because you're, you bring up this topic of innovation and healthcare, which is always a major challenge, is how to create the right incentives for innovation.

And I don't think anyone's really figured that out. Right now there's a good amount of innovation in the research world and I, and it might be that for the foreseeable fewer future, a lot of the big innovations will grow out of academic medical centers or partnerships between, uh, academic medical centers and vendors.

That's how EHRs were created in the first place. They weren't created in, in industry, they were created as a research project. But the, the question I, I, I, I would ask is, is. If, if for to create these incentives for innovation, some of the hope is that as we create more ability to configure these EHRs and add apps to them, is that gonna be enough?

If, basically if you can add an app to these EHRs, will that be enough to create all kinds of innovation or will that just end up being just ? A little piece and, and not be used a lot that I, I I, I'd be curious if you have thoughts on that. I actually don't know the answer to that. Yeah, it's, uh, innovation's an interesting thing and incentives is an interesting thing too, because, you know, the incentive for, for me and somebody else to go into my garage, I guess that's where we're used to do coding and whatnot, but to go into our garage and create an app for healthcare that's gonna change things is the market.

The market is the incentive, right? Or, or, or at least it is in almost any other industry. When Jeff Bezos got started, it was, the market is what drove him. When Google got started, the market drove them. But in healthcare we have perverse incentives. Yeah, and, and we also have roadblocks. So if I want to develop something that's gonna be used to, let's say, improve the performance of a health system, so my primary buyer is a health system, then I need access to that EHR data.

In order to get access to that EHR data, I now have costs. There's cost to get access to that EHR data. 'cause no one, somehow through . Contractually or otherwise, the EHR providers, or at least one specific EHR provider has a pretty significant control over how that information gets accessed and used. And that was before 21st Century cures and before fire, you had to go through them and you had to pay the toll to get access to that data.

And by the way, . There's almost no way to get it back into the EHR and, and so you're limited in terms of what you can actually build and what you can actually do. And so a lot of, a lot of providers have that first roadblock. The second is, uh, distribution. How am I gonna get it out to the masses? How am I gonna get this app out to the masses?

And I know this 'cause we developed, uh, we had an innovation arm and we developed some apps and, alright, so now you're gonna try to get it out there. You can try to go sell one . By one, in which case you have to have a pretty effective sales organization. But if you're a startup and you're trying to ramp something up, you wanna model like an app store.

Oh, they have an app store, that's great. So let's utilize their app store and let's get it out there. Now all of a sudden you start to read the contract that comes with the, uh, getting into the app store and you realize, oh, wait a minute. If, if I do this, I'm essentially signing away the rights to my intellectual property.

I'm signing away just I, I'm signing away essentially my organization, anything that we've done just so I can get access to that market, and by the way, my choices are sign away my intellectual property or don't get access to that market. Right and it is like, it, it, they're just, it's perverse incentives and so yeah.

Now they come out with 21st century cured. And this is, by the way, the only way I think you can break it because it is now either provider led or EHR led. And so now what you need is, the only thing that can break a monopoly is the federal government. And so we have bipartisan legislation that comes through, which is 21st Century Cures, which establishes essentially information blocking rules and those kind of things.

So now you can't necessarily get the e uh, information back into the EHR, but you can start to get parts of it out through fire. And now you can start to be creative. And so we talk about this 10 year foundation being laid, but I will tell you that it was really five years ago when 21st Century Cures was signed into, into law that we saw the, the seed, if you will, of where innovation's gonna go next.

And by the way, it's taken five years. Just to get to the starting line of this, because at every turn they say, okay, here's, let's get the, let's get the rules defined. Let's get a agreement on the rules. You get pushback. Because to a certain extent there's protection of, there's protection of markets and there's protection of revenue and those kind of things.

Not only from the health systems who believe that if I have your data as a patient, there's, you have more proclivity to come to my health system. But also on the EHR provider side, they don't wanna make it easy for you to get the data out. 'cause if they make it easy for you to get . Data out. Now all of a sudden, instead of them creating the next, what they would call a module to their EHR, you have.

Really the entire innovation community, not only Silicon Valley, but the entire innovation community in every university system across the country, even across the world, looking at this and a, a couple of, a couple of people with a team of three or four people could. You know, get together on a weekend and start to really piece together some really interesting solutions.

And, but not only that, uh, you, you have, you have a drive in 21st century chores towards, towards standardizing the data as well. Right? So this is where U-S-C-D-I comes in. And the common data interface is start is, is going to define things, but also it has given the industry that push to start standardizing the data and to define, define those common.

Uh, dataset. So you can have someone like Mayo and Cleveland and Cedars and Providence get together and say, Hey, let's define a dataset around oncology that, that researchers can use and that, and that innovators can use, and those kind of things. And as they do that and submit that work, that could become the defacto standard for and around the oncology dataset.

And so I think we've now started to create . Market looking and market feeling incentives for people to innovate. That was probably a longer answer to, to the question than you anticipated. Yeah, I hope it happens. Like in that case, that would help also with some of this reinventing the wheel, like where everyone's trying to look at their own health system and try to harmonize the data.

If they can just harmonize it to a standard reference model that's pretty well defined, then it. That's a lot easier than having all of them just make up their own individually and then worry about have it not make it, then worry if it's not interoperable with some external standard. I worry when I, so that's the data side of it.

When I think about the process side of it, I think it's might be even more mess yet. So this is another kind of open question is. Across healthcare, there's always gonna be some variation in processes. There's different types of professionals who do lum with different type of things, but that when you have different processes, that makes it hard to create applications.

'cause every, everyone has a different workflow. A lot of the EHR vendors, they require the health systems themselves to create the, the, the flow sheets, um, and figure it out. And so it's not just buying the an EHR, it's buying . Like, uh, the rudiments of, of things that they have to then configure and spend years and years figuring out how to customize.

Well, if there was a, a, a bit more standardization of processes, then that process, that of cus like setting up an EHR might become a lot, uh, a a bit more straightforward. That, that's a question that I don't think honestly has been studied that well. Is, is all this variation and process, is that just, is, is it mostly idiosyncratic or does it, is it there for a good reason?

And I'm curious to know what you think about that from your experience. It's interesting when we look at these mergers, when, when I talk to people about the mergers, I'll say, why did you guys decide to choose that partner? And they'll say. Their, their clinical processes, their clinical workflows is their secret sauce.

So when I partner with this academic medical center or when, when I merge with this academic medical center, and when I agree to use their community connect or the system and those kind of things, one of the reasons is. The, the, the workflows and the, the clinical stops and other things, that's all integrated into the technology.

It now becomes, the technology becomes how you become a partner to a major academic medical center and take advantage of all the things that they have. And to be honest with you, I'm not sure that smaller systems have the wherewithal, uh, to keep up anymore. And I think it's one of the things that's gonna drive this, this

Push over time to fewer and fewer larger and larger health systems. And, uh, because I think it is, people might say that, Hey, our, our competitive advantage is how we do these workflows and those kind of things. But the reality is it's probably only a competitive advantage for the top 1% for the Mayos, the Clevelands, and the the large academic medical centers.

Across the country. I keep using Mayo and Cleveland. I should give somebody else some airtime, but it's top 1% really that have the workflows that should be replicated. Yeah. But I, I don't think they are being replicated very well, so I. What we heard about was some of the larger health systems. They were saying within their dozens of hospitals and clinics, they were finding all this variation and the experience of the patient was different.

The, the protocol, the clinical protocols were different. The, the order sets were different. Usage of the order sets were different. Any anything related to the, you know, actual nuts and bolts work that . The, the staff were doing was that a lot of variation and they were very explicit and we heard this from pretty much every health system.

They wanted it standardized. They wanted the patient experience when they go into the door in one clinic to be, yeah, it's a different person. They might have some different clinical judgment, but they wanted the workflows in the processes to be very much the same no matter where you go. If that name was on there.

They wanted consistency and I know the, the real question is. If they're able to do that, if they're able to make consistency across very diverse environments within these large health systems, maybe there should just be a reference. I. National reference for how to do this, rather than having every health system try to figure this out on their own.

And that's kind of one thing we came to. It's I, maybe this is just America's way of doing it, where we like to have lot, just let a thousand flowers bloom. Okay? At some point you let the thousand flowers bloom. Some of them bloom, and you say, okay, we're gonna take those and use those. 'cause they're the best ones.

I think it's time to start getting those best practices when it comes to workflows. It comes to using these it and spreading it around a little bit more than we have. And the reality is that, I'll tell you how that happens, is it's the same half dozen companies doing the major imple implementations across the country.

So if I went to Philadelphia or Southern California, NorCal, Texas. Yeah. Uh, it's, it's the same six large system integrators that are doing this. Yes. And so some, sometimes that stuff. It sort of propagates that way. The other way it propagates is through the EHR providers that they collect that, although I think people are a little disappointed in they, I think they're going to get very, uh, prescriptive processes and those kind of things given to them when they go with a search EHR provider.

But I think they've not been as per, they're prescriptive, don't get me wrong, but not as prescriptive as what some might, might want or might think. As you were talking about that variation, Mark Harrison spoke at Mark Harrison, uh, CEO of Intermountain. Mm-Hmm. spoke at the JP Morgan conference, I think this past year, and the past year or the year before.

He had just taken over. So I think it was a year and a half ago he had just taken over and it's like, how do you follow somebody who's done amazing job at Intermountain? Their margins are, I mean, it's JP Morgan conference, so we're talking financials and performance and that kind of stuff. It, you know, they, they just hit on all cylinders in a lot of different areas and he decided to address the, the exact thing you talked about within Intermountain, who's widely considered one of the most efficient, uh, health systems in the country.

And he found, not he, but they're under his direction. They found tons of variation. Some of which led to adverse outcomes. And what he said is, look, if we're getting this outcome here, we should get this outcome here. And what they identified was the process difference and, and following. The standard or the evidence-based practices and those kind of things.

And you know, again, having sat in these meetings, I know where it goes. The evidence-based practices, you'll have people go, Hey, here's the evidence-based medicine. And if you don't have a very top-down organization, you'll have physicians that look at you and go. Yeah, I'm not doing that . I, I, I've been practicing for 30 years.

Uh, that makes no sense to me. I don't understand. And it's like, it's evidence-based medicine, can we all agree that evidence-based medicine makes the most sense? And the answer to that is not always. Yeah. It's a change, ma. It's true. And all the health systems, they had diff some of them, the more advanced ones had different strategies to manage that.

I will say we did talk to one health system and they said in specifically one of the draws that they were trying using, one of the, the carrots, they would say, come on, join our health system. We'll let you do whatever you want. and . We'll do a little bit marketing we'll, but you can set everything up. And then now they're getting all these requirements.

They wanna join ACOs, they wanna do public reporting, they wanna do some more . Like evidence-based, um, medicine, and they're, they have built this whole culture of independence and it's really hard to do, just for the exact, exact reasons you're talking about. I appreciate this conversation. It really sparks a lot of thoughts in my mind, in my mind.

Uh, I have one mind, so in my mind, . Uh, is there gonna be any, you referenced some other work. Is there any additional work that you guys are gonna do on this study or other studies around this area? There, there are some other studies. There's some stuff that's already been published in the, on the health systems front and, but in terms of health, it, we may have one more that around this governance issue that I just need to honestly find the time to write it up.

Doing it, you're. You should have tons of time. I, I had tons of time until my, my daughter was born three months ago. That's, oh, congratulations. Thank you, . That's great. So is that, is the beard, like since Covid or since her birth? Uh. It was since C-O-V-I-D and it's, but yeah, it's been there, it's been there ever since she was born.

So I can't shave it now because this is how she knows me. This is how she . Uh, she'll, she'll she'll know. She'll know you in other ways, I think. Uh, . I think so. , but congratulations. That's, that's fantastic. This, this is great work. I, I appreciate it. How can people find this work? How can they read this? We issued a press release, so you can see some summary of it.

The press release, you can, I, I don't think it's open access, but you can at least see a summary of it. It's published in this journal, this journal Healthcare, it's a delivery, science and innovation. So if. Member if, if you're a member of a academic institution or healthcare institution, I'm sure they subscribe to it.

If not, I, I can help facilitate that. If you just want to email me, honestly, I can make sure to try to get you a copy. , I, I can have done that. I, I will tell you. Search a Rand Corporation. Your name, the, the title of the of the study is Optimizing Health It to Improve Health System Performance, and I think it's a work in progress.

Is that right at the end? Title A work in progress. Yeah, the paper's not a work in progress. The paper's done. The, the, the optimizing health it and health systems, that's is a work in progress. That's what we found is a work in progress. Well, if, if they search that I actually downloaded the PPDF, they, they, uh, let you download that from the site and there's a fee for it.

It's, it's a couple bucks. But if you're a part of an academic medical center or a university, uh, institution, more than likely you have access to the uh, to the research. Hey Bob. Thanks. Thanks for your time. I really appreciate it. Sure thing. It was fun. . Yeah. And next time you, you have a, another one of these studies, shoot me a note and I'd love to, I'd love to talk through it with you.

Sounds great. Will do. Thank you. That's all for this week. Uh, don't forget to sign up for clip notes. Send an email, hit the website. We wanna make you and your system more productive. Special thanks to our channel sponsors VMware Starbridge Advisors, Galen Healthcare Health lyrics, Sirius Healthcare Pro Talent Advisors, HealthNEXT and McAfee for choosing to invest in developing the next generation of health leaders.

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