Month: February 2018

Podcast Episode #1: “Patient first” with Ed Marx and Chris Donovan of Cleveland Clinic

Episode #1

Podcast with Ed Marx and Chris Donovan of Cleveland Clinic

"Patient first"

paddy Hosted by Paddy Padmanabhan

In this episode, Ed Marx, CIO and Chris Donovan, Executive Director of Enterprise Information Management & Analytics at Cleveland Clinic discuss how the Clinic operates on the mantra of putting patients at the center of analytics and IT-led innovation programs.

This is Paddy, today our guests are Ed Marx, CIO of Cleveland Clinic and Chris Donovan, executive director of enterprise information management and analytics at the clinic. Cleveland Clinic as many of our listeners would know is one of the largest and most respected hospitals in the country and indeed in the world. Ed and Chris, it’s a real honor and privilege for me to have you as guests on the bigunlock podcast and welcome

Paddy thank you for having us. It’s a joy to be part of your first podcast

Yes, thank you very much

All right Ed, I am going to start with you, Your new role for a little under six months, right? You want to share some of your thoughts on what has been like? By the way, I read your blog on the first 90 days is great stuff there for leaders coming into new roles

Thank You Paddy yeah, it was very fresh on my mind obviously sort of the first 90 days. We all know how critical that can be to onboarding successfully in a new organization so as I went along that journey myself, Hopefully for the last time, I thought it might be good to write about it, and I had some other colleagues of mine who recently started new jobs also to contribute so hopefully it’ll help other people who make that transition and one of the things that I was really interested in coming on board was where we were with analytics and I’m pleased to say that of one of the many fine things that the Cleveland Clinic does is utilize data? To help us run our business and when I say a business of course. I’m talking about both the clinical and financial aspects of things and so we have a very robust enterprise analytic foundation and so that’s why I’m thrilled to share the stage the podcast stage with you today with Chris Donovan who leads that efforts on behalf of our organization, so it’s been very interesting to see all the different things that we have going on. It’s very progressive an innovative organization as you know? and analytics again one of the sort of highlights of my discoveries in my first six months.

That’s wonderful, it’s great that we’ve got Chris on the line as well. Chris, you’ve been at the clinic for a long time and now we are in the post EHR implementation era and analytics is center stage, right? Can you talk a little bit about you know where you’re seeing the highest value at the clinic for? Analytics, and maybe talker you know talked about a couple of successes that you’ve had

Sure, You know we’re really trying to drive in our organization or trying to drive analytics as an enterprise capability, So we’re looking at doing this work across a broad spectrum of domains, I think when you think about some of the top of mind certainly population health is a key component of our strategy right now, I think that’s something that’s in the forefront of most leaders and Health Care’s minds right now and we’ve been doing a lot of work in, The last year to try and apply some of these advanced analytic capabilities in that space, You know if you think about the transition that everyone’s going through and healthcare related to population health It’s really about that idea of how do we go from taking care of people who are already sick to keeping people from getting sick and in the space of analytics. There’s a ton of potential methodologies and approaches that we can apply to that so similarly things that we’ve done and if you think about analytics kind of broadly not just the advanced analytics meaning the math and the algorithms and that side of it, but also all the work that goes into making it successful, so building the right skill sets hiring the right people the data ensuring you have the right data you have good governance around it all that leads up to your ability to actually use that data to make better decisions and so we’ve been doing a lot of work around that partnering with payers try and get innovative in terms of how we collect data. How we share data How we move data back and forth between our organizations to understand the populations that we’re now at shared risk for Some very specific thing that we’ve been doing are trying to understand and forecast risk so what patients or? members and the plans that were at risk for Do we believe in the next 12 months are going to have a spike in their healthcare costs and what can we do then to intervene and actually stop that from happening, so we’ve done quite a bit of work with our clinical teams to identify algorithms that help us forecast patients who we believe are going to be those high spend or high utilization. Patients in the next year I’m using that information we can identify a risk score. That risk score allows us to feed that information back to our care coordination and care management teams and we’re just in the beginning stages of being able to utilize that to prioritize and highlight who we think our care coordination team should go after in their care coordination efforts and so that’s been a real success and even though we’ve we’re just in the beginning of actually utilizing it changing the way we deliver that care to our patients, I think that’s been a real success in terms of building momentum building excitement and building key partnerships in our organizations. We couldn’t do any of this without our clinical partners, and clinical leaders in our organization and this has been a great testing ground for us to really build some of those relationships understand how we can bring their clinical knowledge and apply that to. The math into the algorithms that we’re building so they can really be impactful when you roll them into production.

That’s awesome. That’s awesome, Let me touch on a couple of things that you mentioned, one of them is data now we are in an era where there’s newer sources of data that are available to us, right? Now we’ve done the EHR implementations of the electronic health records, but there’s also new data source. There are genomic data, just to name a couple, So can you talk a little bit about how you are social determinants of health people talk about that a lot? Can you talk a little bit about how you’re integrating these various data sources and what does it mean in terms of? Your IT infrastructure in order to be able to deal with these different types of data and also this increasing volumes of data?

Certainly, as we designed our analytics platform, which we’ve been working on for the last couple of years we had exactly that kind of capability and those challenges in mind, so we’ve been doing what we’ve traditionally called decision support, or business intelligence at the including clinic for a long time and has been very successful at it, but as we look forward a couple years ago. We recognized some of the challenges that you were raising here around volume and velocity and variety of data so if you think about certainly the EHR presents a huge source of star for data So just from a volume perspective we needed to be able to accommodate that also inside of that our notes and other kinds of data that are unstructured that we really have a desire to be able to access and understand and utilize The machines that we have in our patients room so kind of the Internet of Things Ecosystem we recognize that that data is going to be coming at us, and we have an opportunity to leverage that, increasingly patients will be bringing their own data. So whether it’s through a Fitbit or other kinds of health devices like that Also patient enter data, so what can we ask our patients? How can we do a survey with them and learn something about them that can help us design their care differently so as we built our platform. We knew we were going to have to have capabilities across a much wider array of data types and speed and all that stuff that we talked about so from a technology perspective we really built a platform that allows us to build a standardized enterprise approach to this and create a platform that we can leverage for our entire organization and inside of that we have some core, or key kind of foundations and building blocks that allow us to do that versus that data integration piece, So we need to be able to capture the data interact with it go out collect that data normalize it standardize it when appropriate and then store what pieces of that makes sense in a structured data warehouse or structured data environment Next to that and tied into that from a technical perspective. We also have a Hadoop file system which allows us to capture unstructured data allows us to bring data in that We’re not quite sure what we want to do is and we want to experiment with we want to Unleash it to people to kind of explore and see what kinds of connections they can find in it and it also allows us to capture data at much higher volume than typically our structured data warehouse would allow us to do so we have those those two pieces together along with that ETL or ELT depending on what particular use case you have on the front end of that and On top of all that is the analytics platform So that we can access it a couple of examples of that we did some work. We partner with our Lerner Research Institute here at the clinic around genomics and so genomics is a hot topic right now lots of possibilities there in terms of improving care and obviously one of the challenges of genomics is just the size of the data and how do you store that how do you use it so we partnered with our partners over in our Research Institute and we identified a process in our organization by which we store both components of the genomic data, So there’s the BAM files which are those the huge full sequence files that contain every single genome for each person that has been sequenced, and then there’s what they call the variant control files and that’s really what our team is interested in variant control files are where they compare your genome to the perfect human genome and they find just the places where there’s variances and so where there’s something different and so we identified a process where we’re just pulling those VCF files into our analytics platform and Leveraging those in it we did a research kind of a POC with this in 2017. We’re able to link that genotypic data up to the phenotypic data that we have in our EMR that we pulled into our analytics platform and do some really interesting stuff and and one of the things that we did just as a real-life use case was we identified a small cohort of patients who had a genomic indicator for an increased risk of colon cancer and We could cross-reference them with our EMR and identify a subset of patients who had that increased risk, but who had never had a scree colonoscopy and so it’s that kind of work that we believe is just the taste of what the potential of bringing together the disparate kinds of data that historically you were never able to link effectively.

That’s fascinating stuff now you know let me touch on what may have been some of the challenges right Chris, I’d love to if you’re and I’m sure our listeners would love to hear as well worse than the typical challenges you have to overcome Both from a technical standpoint because you’re looking at different kinds of structured and unstructured data coming at different velocities That’s one part of it. There’s a technical challenge, and then there are there other challenges such as you know privacy

I mean you know the stuff that you just talked about Do people want to know I mean what I want to know if how do you actually release that kind of information? Yeah, those are those are really good questions. In terms of technical yeah, there’s a big challenge there It’s um all the components of this kind of along the ecosystem of data that you know this new Accessing these new kinds of data at the velocity and the volume the variety of data present challenges for our historic model and that was really why we had to take a new approach and invest in What we’ve called our analytics platform that allows us to interact very differently It means a couple of different things it means we have to be able to capture data Differently we need to be able to collect data We need to be able to normalize it when it’s appropriate We also need to be able to capture data, and not make any changes to it Just store it use it. We need to think differently in terms of how we connect with different systems and Increasingly we may not need to actually move data out of source systems We may need to just connect to those systems and leverage that data where it sits so all of those different things present significant technical challenges to us, and that’s why we Tried to build an enterprise platform that provided enough flexibility and agility To you know address each of those different challenges, but bring it together into a common ecosystem that our organization could leverage in terms of the You know privacy issue is that something we’re definitely wrestling with I think that’s why? An equally important pillar of a program like this has to be around data Governance and so as part of this effort here at the clinic. We established a data governance office. Which is the first time? We’ve had that in our organization in a very formal manner and as part of that We’ve partnered that data governance office with our privacy officer and with our security officer to ensure that we’re building a best-in-class tool in terms of guarding patient privacy, so When people enter into our IIM in a platform we have You know what we’re building is best-in-class ensuring that we’re HIPAA compliant We’re exploring technologies such as data masking so do we have? Opportunities to build datasets that are completely masked so that we don’t have to worry about pH. I being Shared inappropriately where we do have pH. I building all the policies procedures guidelines Around that data to ensure that our folks at the clinic understand the appropriate use cases for that they understand the minimal use Requirements that we should all be thinking about constantly and that they’re very aware of the need to protect our patients private information And that’s a real challenge, and that’s really important going forward That’s something we spending quite a bit of time on right now because we’re trying to balance we want to build a platform that Makes it data available so because we have a very much a self-service bias And how we want to do this our goal is not to Centralize all the information and lock it down and make everybody come through a central team It’s how do we get that out into the hands of the folks are going to be using it to make decisions and improve? clinical care and drive quality improvements and outcomes and at the same time recognize that we have to do that in a way that is appropriately protecting the protein of the pH I that we have inside of these data sets so a lot of thought and effort here Around that and certainly our data governance office is taking the lead on helping us make sure we maintain that right, right I’m sure folks are going to be very reassured by the fact that there is a governance process And it’s all been you know properly handled the switching to the infrastructure piece From from your comments. I gather that your Changing the data from multiple sources and not necessarily bringing it all in-house So is it fair to say that you’ve given braised cloud infrastructure and cloud-based? Solutions For setting up this platform And is it also fair to say that the interoperability challenges that the industry has been talking about for you know for a while now Those are somewhat under control is it fair to say that Well we’re not we’re not in the cloud yet So we took that when we built this a couple years back and laid out our roadmap we started with an on-pre m traditional on-premise solution and The reason for that ties back to your last question was we were unsure at the time. We were making these decisions of the pahi, and the and the compliance of those cloud vendors to make sure that we keep that information safe and we understood how the whole process of how That whole process around privacy was going to work. We did Ensure that in our roadmap and when we talked with our partners that we you know the vendors that we partnered with in this space That we recognized that quad is where we’re going to be at some point and so we have a roadmap to move in that direction and we have technologies that allow us to Leverage a hybrid environment So what do we want to have on pre m and where and why does it make sense to leverage a more elastic and a cloud? Environment so in this space at least in our analytic space we’re not in the cloud today. We have other Approaches and strategies across the organization more broadly across IT that we’re moving probably more rapidly towards the cloud But in this space we were a little more conservative because of those concerns that I noted In terms of interoperability, you know there’s still a lot of challenges with that. That’s one of the key things as we think about if you think about building a digital platform for healthcare organization That’s got to be one of the keys so how do we build those ecosystems or we can connect out? You know in a population health world? We may have an app that we have in the hands of a patient and that patient might want to be able to access their chart access some clinical information on their own refill a prescription Maybe build an earth set an appointment by themselves and that at the same time they may be Providing us information that they’ve collected on that device you know a Fitbit or some other health device that they have at home We need to build this platform that allows us to interact with those devices interact with that patient That information has to pass back into our core applications so that they can actually you know schedule an appointment They may need to reach out to a partner a payer or maybe a provider partner and we have to be able to leverage that data that they’re capturing off that device so that’s the Ecosystem more broadly that we’re thinking of and we’re trying to design around and ensure We have that interoperability through direct connections or api’s or however we want to However, we think we’re going to best achieve that and then we also think about across that ecosystem What are the different ways that we want to partner with? vendors in the in this space so do we want to build like we did with our core analytics platform that we build in-house Do we want to buy applications? So people are delivering already You know purpose-built tools into the space can we partner someone there and leverage that get to something faster or more efficiently that we could and Where do we want to innovate and really kind of drive the edge and be on the leading edge? so kind of discovery exploration partners where maybe we bring in a Third-party vendor and we create something together And so I think it’s through those different strategies that we’re trying to address both the you know the interoperability challenges And also think about our infrastructure, and how we have to leverage those different ways of interacting with partners

That’s great stuff. I’m gonna come back to that in a second, but I was reminded Something that Ed told me what when I interviewed him for the for the book that I wrote At one of your quotes for my book was features ready, but the student is not I simply love that and what he was saying there was there’s a lot of innovative solutions out there But the health care system is not necessarily ready for all of it you want to Expand on there or comment on that Yeah, I think

We’ve been laggards in health care in terms of exploiting the data That we have access to as you address in your book the big unlock the harnessing data and growing digital health businesses in this you know value-based Era of care I think we’ve been slow and when we look at other industries We see them picking up on technologies much faster. They don’t have the same interoperability hurdles So I give ourselves a little bit of grace that we might have in our industry in healthcare and the complexities around that and like Chris was saying all the additional safeguards we put in place because of the sensitivity of the data that we’re dealing with and That said you know that those are those are real obstacles to deal with and challenges that we are that we work through But I think we’re still behind some other industries, and I’m glad to be serving alongside Chris and some other leading organizations that are Taking what we do have the capabilities available to us and doing some pretty innovative things like Chris already described And there’s certainly some some other things, but my hope is that? Organizations like the Cleveland Clinic and as I mentioned There’s other peers of Chris’s that he works with quite closely in Other parts of the country that they continue to demonstrate the leadership that they’re doing in terms of delivering outcomes utilizing data, and that others will also step up and bring the realities of the potential to healthcare because data is the new oil as you describe it and It’s a way to really Transform healthcare we’ve been talking about transformation for quite some time but I think the ability to harness the power of data is really gonna help us get there and So we continue to push and as Chris was describing You know again a little bit behind. What some other industries are but in terms of leveraging the technologies available? But I think we we’re beginning momentum making strong inroads And I think that you’ll see more and more examples of some of that innovation Taking place like what Chris was describing. We’re doing here at the clinic That’s really that’s really helpful You know as the head of the idea function and I imagine you have to make decisions all the time About allocating your resources right you know what gets funded. What doesn’t what gets your support What doesn’t so what kind of a framework or mental model? Will you do you use to decide? which initiatives you support and related to that is this whole innovation agenda right because the flip side of innovation is risk and So how do you balance those? Would you care to comment on that? sure, we approach it a couple of different ways but First and foremost is what are our objectives as the Cleveland Clinic, so we don’t create our own Sub objectives or objectives that are different within I T or within analytics so we really take where the organization is headed as put out by our board and our executive team and then really see ourselves as a catalyst to enabling the realization of those particular objectives so for instance I Think analytics relates to all six of our primary objectives for 2018, but let’s just take digitalization and high reliability Organization and of course we’re patient first is our mantra in terms of our culture And so when you take in the culture and you take in two of these six actually all six But I’m just highlighting two the six major objectives for our organization for the Year analytics is Deeply entrenched in each one of those and make those a reality and so it’s it’s not too hard then to to interpret the objectives of the organization and see how we leverage analytics and so when it comes to prioritization We have to look at where do we get the biggest bang for our buck and certainly analytics? Taking the harnessing all the data that we’d already collect and improving our clinical outcomes improving our financial outcomes Is is really how we’re we’re driven so I could and I could answer this in a multitude of different ways but we do have a governance structure and Chris alluded to that and in in terms of analytics it’s a very high-powered governance structure includes primarily members of the c-suite so our executive team as well as some of our we would call our most dominant power users and In there, it’s all about again going back to the objectives. I mentioned about high reliability organization all about digitalization you know taking data that we have and making it actionable and all wrapped around this concept of our patient first culture where we’ve made a promise that we’re going to deliver the best healthcare Anyplace and so in order to do that you get that robust analytics so when it comes down to going back I think to the heart of your question in terms of funding prioritization it we’re all about analytics and if you in fact if you look at from an IT centric point of view how we interpret things When we talk about our our? goals that flow directly from the organization goals We have a wraparound that in all of that and that wraparound is called analytics So it is front and center of everything we do It’s the core to digitalization to digital health, so it gets the recognition and that’s the funding that it deserves to get because it’s really probably our biggest single biggest lever for impacting patient outcomes That is that’s just fantastic I’m sure that’s music to the years of you know folks who are like-minded Analytics professionals or or those who are looking to work with you? Now a related question that that probably comes up in all your conversation certainly some of your Conversations is how do you compute the ROI on this is this more of? You know we know this is the right thing to do and therefore We’re going to do it or Is it that no we’re going to look at you know even if it’s important and the right thing to do is still going to? Look at the hard returns before we move forward with anything, or is it somewhere in between Well I’ll take a first stab at that and then maybe ask Chris to comment based on sort of a historical Point of view, but I think that the returns are pretty demonstrable, they’re they’re pretty Self-evident when you realize you need to become a data-driven Organization, and you need to have just like we asked for evidence-based medicine on behalf of our clinicians whenever we’re Delavan developing pathways We’ve we’re starting to embrace that sort of discipline or have embraced a discipline when it comes around data as well and that we need to be data-driven and the only way to be data-driven is to have the ability to collect and analyze data So we’ve seen a pure return even in in my first six months. Just looking at the work. That’s been done in Hearing use cases which I give giving Chris here time to maybe set one up for you It’s been pretty demonstrable and what’s nice is the more we do this It’s a repeatable cycle Then the more confidence that our executive team gains and what we can do and is more apt to continue investments in Analytics because they do see that return

Chris do you have an example that we might be able to share whether it’s a clinical return or a financial return?

Yeah absolutely, there’s a there’s a few that we can pick from and I just want to echo Ed’s comments that we really take that both sides of that approach so certainly we know that there’s Investments that we’re going to make that we want to have to return we do it because it’s the right thing to do But it’s equally important that we’re able to demonstrate Tangible value back to the organization so a couple of examples You know one that comes to mind is we had a third-party tool that we had in our organization that was focused around Some of our revenue cycle work and in the analytics that we were delivering out of that domain we were able to evaluate that tool and look at building that capability internally inside of our analytics platform and Deliver not only the functionality that we got out of that third-party tool But deliver actually new capabilities and exceed the capability that that organization delivered for us And that’s going to be somewhere around a seven million dollar return to the Cleveland Clinic over the the next four years So very easy to quantify that very easy to demonstrate. You know this is what we were spending This is a tool we were using we can in source it deliver more value at a lower cost That’s awesome fantastic. Yeah a couple. Oh, sorry good no bad No, no, there’s a couple other couple other examples. You know and this is really important crossings from in terms of delivering value We worked very closely with our folks on the clinical side and in our population health agreements You know making sure that we get accurate coding is really important, so we partnered with them on doing some work around HCC improvements, which is really a measure of how why you’re coding, and it’s important in your Medicare Advantage Agreements and we were able to achieve significant improvement and demonstrate that we are achieving approaching our 90% goal for compliance and that in that measure so Different different projects that we have across the organization tying a key metric that is measurable To those so that we could actually see the progress is really important to talking about the value that you’re delivering out of a program The only other thing I would say is that one of the ways that we try to do this is we’re very intentional about making Sure that While we have to deliver a platform And there’s you know like I said earlier that kind of data people process and technology we try to communicate the value of the program through What we call kind of these you know you know our product our product Product domains and so we talked about certainly the core things that we’re delivering That I talked about earlier across those four pillars, but we also talked about we’re delivering capability in Domains such as executive insights quality and outcomes making sure that we demonstrate how we’re doing stuff around physician and provider performance and those Those domains make it really tangible to the organization so when we talk to our executive team And our sponsors or we talk to people across the enterprise that’s a great way to translate from while we’re building a tool To we’re delivering value, and here’s how we’re delivering value, and here’s how we’re partnering with you to deliver that value That’s great, so that’s really helpful on inside so what $7,000,000 returned from one program That’s got to be that’s got to make people sit up and take notice I imagine Well, you know really yeah, and you know We can talk about analytics in today’s context without talking about some of the emerging technologies and the analytical tools and methods available out there So I’m going to throw a couple of terms out at you and you know add You know one of you can take a stab at what do you think of it one artificial intelligence? Can take a run at that ad I think artificial intelligence is a really exciting area right now. I think that term is Certainly surrounded by a lot of hype and a lot of different interpretations and definitions of what people mean by our official intelligence We’re applying a lot of capabilities that fit within that kind of large domain if you if you define it kind of the most in the most broad sense possible so a lot of those algorithms that we Were talking about earlier a leveraging machine learning capabilities to do forecasts for patient You know patient risk or rising risk patients. We’re building an all risk model for all of our patients leveraging those capabilities I think you know when I think of artificial intelligence I actually kind of prefer the term Augmented intelligence that you see more and more now as you do you know use your many different things on this Because I really believe that the opportunity that we’re going to have in healthcare especially Is to deliver on the promise of what we’ve always called clinical decision support And so I think we have the opportunity to go far beyond you know alerts And kind of rule based things that pop up in the EMR Which have a have their place and are important and certainly have driven value But also have a some sort of limit or a ceiling on how useful they can be And as you think about the ways You know the opportunity that we have to actually impact the way care is delivered I think there’s some fundamental things that are going to shift and AI is going to be at the center of that You know historically the way you deliver care and the way a physician or a clinician really drives that it was really dependent on their ability to kind of amass and to be able to access the store of knowledge right so the patients that they had seen the cases that they’d reviewed the journals that they’re keeping up with obviously their Education and medical school their ability to kind of look across all of that bring it together You know put it in context of the particular case they’re doing in brought arrive at a diagnosis, or a recommendation is really the key to be at your delivering successful clinical care and The fact is that today knowledge is largely becoming a commodity and so we need to think Differently about how can we take some of that? Need to do that off the shoulders or the clinicians and really free them up on that Diagnostic side and the gray they deliver care and to me That’s that augmented intelligence so can I provide to our clinicians in their clinical workflow the ability to? Access information and go through it and parse it and drive correlations that they would never be able to do on their own But we can deliver much more context to them so Can they see when they’re in the midst of making a clinical decision? What are the potential outcomes? What are the predictive models around cost and? Quality and how can we present to them not just an alert that says hey these two drugs have a bad interaction but information That helps them make a better clinical decision and provide them with options. I think we’re a long way from AI or a computer making clinical decisions I Still think that that you need that human in the middle of that or at the end of that process But I really think we can revolutionize the way that our caregivers provide that care through AI and to me that’s that augmented intelligence, so that’s what really excites me about that phrase and the potential of applying that in healthcare I think it’s so important to understand the distinction that you just made Cris between AI you know and this notion of AI as a job killer or replacing expert humans or whatever it is and really positioning it in a more nuanced way to really help people understand what it stands for today. I think I think you did you know you Did it you did a fantastic job of articulating that that difference in the distinction over there one more blockchain? Yeah blockchain is another one that has a whole bunch of hype around it now. I think there’s a ton of potential in this idea of kind of a distributed ledger in healthcare I think we’re really early in that, but if you think about you know one thing that kind of excites me in that space is the ability for were a patient to own their medical record and to own their clinical information and they would have the ability and the power to release that to caregivers that they wanted to share it with and to keep it from Folks that maybe they didn’t want to share with it for some reason so I think there’s a lot of potential uses for blockchain and that that kind of core technology of like I said that distributed ledger kind of technology But I think that that ability you know that that Healthcare record ability and being able to get a healthcare record in that technologists potentially the most exciting Maybe the maybe one of the hardest ones to actually get to but very exciting in terms of its potential This is a clinic doing any pilots one blockchain right now Where we’re not doing any active pilots with blockchain like Chris says we believe there’s great potential with The technology and we’re waiting to partner with one of our partners in terms of perhaps doing an application With them, but at this point we’re not going to do it for the sake of doing it So we’re waiting for the right use case to in which to apply the technology the only other thing I would add on our sort of approach to augmented intelligence is that We always talk about Having our providers operate at topic licensed well Augmented intelligence or artificial intelligence, however you want to couch it, but I appreciate Chris’s terminology and nuance is It’s weird rude. That’s how we’re driven so however we can make the clinicians processes that much more efficient and effective so they can focus on uncaring for the very sick and utilize all of their In you know collective experience, that’s that’s how we want to leverage that particular technology

Fantastic fantastic all right any final thoughts you’d like to share for the benefit of your peers in the industry Or for technology providers who may be listening to the podcast?

Chris you go ahead look go ahead, okay?

I was just going to share that I think this work is incredibly important, and I would just want to make sure that we Message that this is the work of a team that you’re you happen to be speaking with Ed and I but you know we have a lot of people that were working with And our clinical partners first and foremost we couldn’t do any of the work that we’re doing without The great clinical leadership that we have in partners such as Tim Crone is our medical director And well Morris is one of our associate CIOs You know that’s what makes the this really hum at the Cleveland Clinic is The ability to work hand in glove with our clinical leaders and get them engaged in this work and excited about this work So I just think it’s important that if you’re building these kinds of programs. You can’t do it in a vacuum You can’t do it in isolation You’ve got to get out and get key leaders in the organization and especially in a healthcare organization. You got to get those clinical leaders Engaged in the process early on My closing comments were very similar and Chris covered them quite eloquently and just to emphasize what he was saying Analytics doesn’t report to IT analytics doesn’t report to operations IT doesn’t report I mean analytics doesn’t report to Finance, but it’s embraced by everyone in such a way that through our unique governance structure We spoke about or spoke to a little bit earlier It is supported embraced and actualized as sort of this shared resource, and it works very well And it can only work that way in this Patient first type of culture and where everyone whether clinician or other type of care giver as we call ourselves Working together to doing the right thing for our patients, so that’s what that’s the real secret sauce if anything Patient first, I love that gentleman it’s been a real pleasure speaking with you.

Thank you once again

Thank you for the opportunity, thank you

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About our guest

Edward Marx is Chief Information Officer at Cleveland Clinic, an $8 billion medical system that includes a main campus, 10 regional hospitals, 18 family health centers, and facilities in Florida, Nevada, Toronto, Abu Dhabi and London. He is responsible for the development and execution of strategic planning and governance, driving optimal resource utilization, and team development and organizational support. Ultimately, he will develop leaders and leverage digital healthcare technologies to enable superior business and clinical outcomes.

Prior to joining Cleveland Clinic, Edward served as Senior Vice President/CIO of Texas Health. In 2015, he spent over two years as executive vice president of the Advisory Board, providing IT leadership and strategy for New York City Health & Hospital.

Edward began his career at Poudre Valley Health System. CIO roles have included Parkview Episcopal Medical Center, University Hospitals in Cleveland and Texas Health. Concurrent with his healthcare career, he served 15 years in the Army Reserve, first as a combat medic and then as a combat engineer officer.

Edward is a Fellow of the College of Healthcare Information Management Executives (CHIME) and Healthcare Information and Management Systems Society (HIMSS). He is on the CHIME Faculty for the CIO Boot Camp, training aspiring healthcare technology professionals. He has won numerous awards, including HIMSS/CHIME 2013 CIO of the Year, and has been recognized by both CIO and Computer World as one of the “Top 100 Leaders.” Becker’s named Marx as the 2015 “Top Healthcare IT Executive” and the 2016 “17 Most Influential People in Healthcare.”

Ed received his Bachelor of Science in psychology and a Master of Science in design, merchandising, and consumer sciences from Colorado State University.

Christopher Donovan is the Executive Director of Enterprise Information Management & Analytics at the Cleveland Clinic.

Chris joined the Clinic in 1992 and has worked across a wide range of healthcare financial performance management, decision support and analytics efforts during his career. In his current role, he is leading the development and implementation of the enterprise information management and analytics program for the Cleveland Clinic system to enable the organization to acquire, manage, and use information in the transition to a value-based healthcare model.

During his career, Chris has been responsible for multiple aspects of the operation across the Cleveland Clinic physician practice and hospital network. This work has included service line cost and profitability analysis, utilization and length of stay initiatives, financial planning and budgeting, decision support and enterprise business intelligence and charge master strategy and pricing. Chris has also been involved in operational and financial performance management and has a special interest in Lean and continuous improvement, for which he helped develop and pilot an enterprise wide application of Lean continuous improvement principles and practices across the Cleveland Clinic Health System.

Chris has co-authored several articles and speaks both nationally and internationally on a variety of topics including analytics, information management, business intelligence and Lean continuous improvement applications in Healthcare.

Chris is currently a board member of the Healthcare Data and Analytics Association and participates as the Cleveland Clinic lead partner on the Analytics Leadership Consortium for the International Institute for Analytics.

Chris completed the Health Management Academy GE CFO Fellowship program in 2013.
He received a BS in Business Administration from Miami University in 1992 and an M.B.A. from Cleveland State University in 1997.

About the host

Paddy is the co-author of Healthcare Digital Transformation – How Consumerism, Technology and Pandemic are Accelerating the Future (Taylor & Francis, Aug 2020), along with Edward W. Marx. Paddy is also the author of the best-selling book The Big Unlock – Harnessing Data and Growing Digital Health Businesses in a Value-based Care Era (Archway Publishing, 2017). He is the host of the highly subscribed The Big Unlock podcast on digital transformation in healthcare featuring C-level executives from the healthcare and technology sectors. He is widely published and has a by-lined column in CIO Magazine and other respected industry publications.


The Healthcare Digital Transformation Leader

Stay informed on the latest in digital health innovation and digital transformation.

The Healthcare Digital Transformation Leader

Stay informed on the latest in digital health innovation and digital transformation

The Healthcare Digital Transformation Leader

Stay informed on the latest in digital health innovation and digital transformation.