May 17: Today on TownHall Reid Stephan, VP and CIO at St. Lukes interviews Onur Torusoglu, Associate Principal, Digital Health Leader at ECG Management Consultants. Why is digital health and analytics so hard in healthcare? Is it a by-product of the complexities of our industry? Or do we just make it too hard on ourselves? What advice would you give to an organization today to make the evolutionary step from simply collecting and curating the data to actually using it to make insight driven decisions? How can a health system build an analytics program from the ground up? What skills should they look at when building out their analytics team?
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Today on This Week Health.
The model US healthcare model is designed so that unless it benefits certain parties, it will not be so easy for people to actually use data to make a difference. But putting all the difficulties aside, I think there's still a tremendous amount of success in the healthcare market from a using the data perspective.
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Welcome to the This week and Health community town hall conversation. I'm Reid Stephan VP and CIO at St. Luke's health system in Boise, Idaho. And I'm joined today by Onur Torusoglu an associate principal and digital health leader at ECG management consultants based out of Houston, Texas owner. Welcome, and thanks for making the time today.
Thanks for having me Reid.
All right. I always like to start with this question with folks that that come on for these conversations, because I think there's so much we can learn from the career path and twists and turns that others have gone through. Just take a few minutes and just share your education background, your career journey, and what's led you to the role that you have today.
Sure. I think there's a common pattern for any of us that is not a clinician who has fallen into healthcare. There's definitely compassion that falls into that piece. And I wouldn't put myself in that category as well, but I started. Many moons ago, my college education in architectural engineering. Realized it wasn't for me switch gears to economics because I've always been relatively good with numbers and working with them.
And it was an easy path for me to actually do something useful. Really did believe that I would go into the field of economics and do economic studies if you would. But that was my undergrad then went and got a master's degree for it was an MBA, but it had two focus areas.
One was operational management and the other one was financial operations. If you will. And always had a tie into process improvement and numbers and data crunching when it comes down to it. So that was always a natural ability coming straight out of college. I took on first job, first career job with Humana insurance organization, relatively large organization and my role was operation supervisor. As part of their expansion at the time. Within the year, I fell into this space of process improvement. So I went into the six Sigma program, got a black belt certification and started doing process improvement projects. Just my natural neck was.
And at the time this is 20 years ago or so a little over 20 I clearly had the challenge of collecting data. There were hardly any data quote unquote teams at the time. Most of the data was pulled out. If you had a buddy in it and who has some SQL skills, they would pull some data for you and you could do something.
And it became painfully obvious that I needed to go get my own data. So I started writing my own queries. I had SQL background from my college day, so I just started doing that. And started combining the data piece with the analyzing and turning it into useful information to improve improve operations.
And that took me down the path of digital and analytics. Very next role was I led a manager as a manager. I led a analytics team at Cardinal health progressed through there to lead their nuclear pharmacy division of, of their analytics and intelligence piece. Actually had one of my most fun projects to my careers total digital and analytic transformation project for the entire organization.
And I was the the technology lead piece for it. So it was a lot of fun. But from there I, and throughout, it was always healthcare ancillary, and then I directly fell into healthcare with Cleveland club. Yep. And then Ochsner health system and then St Luke's health system and ultimately now with ECG management consultants, which is a sole focused on healthcare from a consulting practice perspective but always has been in the space of analytics, space of digital space of technology.
Well, I'm impressed that you went through that whole thing. It didn't say university of Kentucky one time, and maybe that's just some kind of residual kind of pain of the tournament that just ended.
No, I do have a mental block. It's very true. I am a member of the fire, John Calipatria squad at this moment, but I'll get over it by the end of the year.
That's great. So you have just this wealth of experience in digital health and analytics. And so curious and just speaking really generally, but why is this so hard on healthcare? Is it just a by-product of the complexities of our industry? Do we just make it too hard on ourselves? Is it something else altogether? Just curious what your thoughts are.
Yeah. I mean there's combination of things. It, absolutely healthcare is difficult as we all know it and as many giants who went into market, like Amazon's first try with Chase and many other organizations have gone left and even IBM Watson is now on the I wouldn't call it downturn, but the original premise had, I don't think was fulfilled from, from that standpoint.
So the complexity is absolutely there. The model US healthcare model is also designed so that unless it benefits certain parties, it will not be so easy for people to actually use data, to make a difference. But putting all the difficulties aside, I think there's still a tremendous amount of success in the healthcare market from a using the data perspective. The challenge usually comes from the clinical sake of using data as an improvement hasn't gain as much traction because it is an expensive proposition as in using new technologies or developing these technologies.
So most organizations are looking at it from the economic standpoint. How do I turn a buck from, from this puzzle? But putting all that aside because of the advancements in the analytics space, a lot of those technologies have become cheaper and thus, a lot of success in the last few years has had come from already proven.
I'm not going to use the term cheaply, but more inexpensively available capabilities being utilized in the market to be able to do some success. In a nutshell, that's, that's the general census that I have. And to add to that most of the healthcare organizations now the new general, and I will put myself in this category, I'm becoming a dinosaur myself too, but many of the organizations are still have a lot of old guard, maybe old guard isn't even the right term, but you know, folks.
I didn't grow up in the age of smartphones and you and I still can easily remember the the rotary phones and the household to maybe three channel TVs and so on and so forth to now the technology, my six year old knows how to operate just about every single technology piece of equipment, a lot better than even myself and Hilary. So that's, I think that's the difference. There's a lot of generational talent that's coming and that's not, I think it's going to change the pace and the the velocity of what data will do for healthcare. But till then we still have a lot. Folks that want to stick to the Hey, I trust my gut. I know how to run a business and I will run that business. I don't need a computer or an analyst to tell me what I need to do differently. There's a little bit of that.
It's such a great point. Like we're in this era of just this increase of these digital natives coming into the workforce, who I think will bring with them perspective and not be shackled by any historical confinements and the way they think or the way they kind of view the art of the possible.
Great. So then what would your advice be like as a dinosaur, which you're not by the way, but what would your advice be for an organization that today they're simply collecting data. They're storing it in a warehouse, in a lake, but not really driving a lot of insights out of that. How did they make that kind of evolutionary step from simply collecting and curating the data to then actually using it to make insight driven decisions?
Yeah. Great question. I think. It definitely starts from the perspective of having the right skillset. And I would say, even in an organization who's only collecting and curating the data, maybe there is the skill set of folks who can actually analyze the living bejesus out of it when it comes down to it and actually provide a lot of actionable insights.
So that foundational layer of enabled analytics function needs six. So, and then the next step to that is really jump in, do it. There is no small or big project. Go start solving the problems that you really are dealing with. I mean the last few years We always I'll use a non analytics example of virtual care, and nobody used it outside of a, maybe 10% to a 20% ratio.
COVID forced everybody's hand. And we're maybe back down to 15, 20% some organizations higher, but you know, when push comes to shove, everybody said, okay, this is something that's useful and we're going to use it. The same thing can apply in analytics space from my standpoint whether you want to improve your clinical outcomes, whether you want to improve your nursing staff schedules or you want to look at simplifying your registration process.
There's a lot of analytical capabilities that can come into play and digitally native tools that can come into play that can actually make things easier. And it's, again, it's not call it maybe five to 10 years ago. That could have been an expensive. It really isn't today. You can simply start by as long as you have the foundational layer of the skillset, data science, team members those sorts of skills in home and you already have EMR is in place that the data is already available for you to capture.
You can really start simplifying and taking out the non-value add steps out of the process. Whether again, it's in the clinical setting of, of capturing a code to on the nonclinical setting from anywhere from pharmacy side of the world, to, to the supply chain side of the world. There's a lot of necessary steps, but not necessary for a human to do that can be taken out of the the puzzle that can actually improve processes.
And then you can then further into predicted predictive prescriptive capabilities that can actually then help leadership teams make or anyone from ground up, make decisions faster, easier, better, so on and so forth.
Yeah. Okay. Last question. So you've had the chance, at least twice in your career to come in and build a analytics program from the ground up. So as you hire staff outside of just the, the technical expertise that they may need to have for the role, what are some of the intangibles that people should look at when they're building a team to ensure they don't just have the book smarts, but also the emotional intelligence, the healthcare savvy, whatever they might need to really be effective.
Well turn that right back around at you. I've absolutely learned a lot from you in that side of the puzzle too, but I will put it this way. The one skill that I look for and I use a lot of sports analogies in this space. Hopefully it'll be relevant in this case though. You need a system.
You don't necessarily need scores rules it, digital analytics, all of the support functions need to be enabling functions. So when I look for my teams that I form, I look for assist leaders or a support cast that they can shine under every light, but they don't need to score the basket.
or put The ball through the goal when it comes down to it. So in our case, we have lots of clinical staff and lots of administrative staff that are running the hospital side of the puzzle or the healthcare system side of the puzzle. Our role is to make the, those people's lives easier to be able to do so you need a cohesive team that's full of superstars, but again call it magic Johnson Steve Nash, those type of players, or is what's needed. So that's what I look for as a intangible, if you would.
Yeah. A great analogy and just really wise, wise insight there. So thank you. Onur as always great to visit with you today. Thanks for making a few minutes. I appreciate your time and have a great week.
Thank you. Likewise. Thanks for having me.
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