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Episode 41:

Love as a Health Informatics Strategy

This week, we're joined by Siraj Anwar, Sr. Vice President and Chief Health Informatics Officer at Harris Health System as well as Dr. Rod Brace and Dr. Michael Shabot of Relia Healthcare Advisors to discuss the role of informatics in driving leadership behaviors for high reliability. And as always, we dive into what love has to do with all of this. 

Speakers

Feel the love! We aren't experts - we're practitioners. With a passion that's a mix of equal parts strategy and love, we explore the human (and fun) side of work and business every week together.

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Frank Danna
Host

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Siraj Anwar_square

Siraj Anwar
Sr. Vice President, Chief Health Informatics Officer, Harris Health System

Rod Brace_square

Rod Brace, Ph.D.
Founding Partner, Relia Healthcare Advisors

Michael Shabot_square

Michael Shabot, MD
Founding Partner, Relia Healthcare Advisors

Transcript

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Jeff Ma

Hey, everyone. Before we get into this week's episode, I wanted to explain what we intend this episode to be about. We're going to be having real talks about lived experiences around race, identity and other dimensions of diversity. When we get into the conversation, you may experience some level of discomfort. And that's the point. This episode dives into some tough conversations and we hope you listen with an open heart and open mind and ultimately, embrace the power of being uncomfortable. Enjoy.

Frank Danna
Hello and welcome to love as a business strategy, a podcast that brings humanity to the workplace. We're here to talk about business. But we want to tackle topics that most business leaders shy away from. We believe that humanity and love should be at the center of every successful business. I'm your host, Jeff Ma. I'm just kidding. It's me. It's Frank. I'm hosting, it seems that I I'm the one who hosts when Dr. Rob Brace was with us. And now that that tradition has been set, cuz this is the second time I've done it, I think that's what we're gonna do. For the remainder of loves a business strategy. I am a director at Softway, a business to employee solutions company that creates products and offer services that help build resilience and high performing company cultures. Each episode of love is a business strategy , we're diving into one element of business or strategy and testing our theory of love against it. Today, we've got quite a few special guests. I think this is the first time in Love as a Business Strategy that we have more guests than team members from Softway and I'm very excited to be outnumbered. We've got Dr. Rod brace, a previous guest of the show, as I mentioned earlier, we've got Siraj Anwar and Dr. Michael Shabot. It's packed. Welcome, gentlemen.

Siraj Anwar
Thanks, great to be here.

Frank Danna
Okay, so I'd like to introduce each of you in a little bit more detail. So I want to start with Dr. Rod Brace and Dr. Michael Shabot. You are both founding partners of Relia healthcare advisors, which provides expertise and high reliability organizational models, quality and safety cultural assessments, service line and ambulatory network design. I guess I said that correctly and leadership strategy. Dr. Shabot you formerly served as executive vice president and system chief clinical Officer of Memorial Hermann health system in Houston, Texas. Dr. Shabot also serves as an adjunct professor at the UT Health School of Biomedical Informatics and UT Health School of Public Health. Michael also serves on the Board Quality Committee of the mercy system St. Louis, Missouri. Dr. Shabot received his medical degree from the University of Texas Southwestern Medical School. He is board certified in general surgery and surgery critical care. Dr. Rod Brace is a retired as regional president and chief learning officer for the Memorial Hermann health system in Houston, Texas. Rod served 30 years and operational positions including chief regional operations officer and hospital CEO, COO and nonprofit and investor owned health systems. Rod is a national speaker, author and executive coach. He holds an MBA and PhD in Management with a research emphasis in employee engagement, organizational cultures and leadership. Remember, I told you listeners This is a packed house It is indeed packed. Last but certainly not least, I have Siraj Anwar.

Frank Danna
This gentleman is the Senior Vice President of Chief health informatics officer at Harris health system, also an adjunct assistant professor at UT Health School of Biomedical Informatics. Wait a second, there's a connection here and voluntary clinical assistant professor at University University of Houston College of Medicine Department of clinical sciences Siraj obtained his medical degree from the University of Mysore, India, and worked as a primary care physician before pursuing a full time career in informatics. He currently serves as the chief health informatics officer at Harris health system, which is the fourth largest safety net health system in the United States. In this role, he leads the informatics and data science operations for the entire health system. Siraj is passionate about leveraging Information Technology, data and human relationships to provide patient care that has high quality and high reliability and has been doing this since 2001. Gentlemen, I read all that. So now I am ready to break the ice a little bit and have a quick conversation. We start off with icebreakers with in this podcast. Rod, you're familiar with this and I by way by the way, we he goes,

Dr. Rod Brace
Yeah.

Frank Danna
We know Rod and Michael very well, to the point where if it's okay, I can I can say Rod and Michael, in our conversation here. Okay. Thank you, Dr. Brace. So, Rod, first question to you. Would you rather get away with every lie you told or be able to tell when anyone was lying?

Dr. Rod Brace
Oh, be able to tell when others are lying. By far. I mean, there's so many interactions that the end result would change drastically If I had known that they were lying. That would be a superpower.

Frank Danna
That indeed would be a very powerful tool. Okay, Michael, question for you. Would you rather visit 100 years in the past, which would put us in pandemic and, or rather 100 years in the future?

Michael Shabot
Well, I'd love to do both. But given the choice, I would love to visit 100 years in the future. I'd like to see what what's coming.

Frank Danna
Excellent. You go. You go 100 years in the past and folks are still wearing masks.

Michael Shabot
Well, they got roughly around 1821 but they did wear masks, and it was controversial at that time as well, by the way, not political, but just controversial, controversial.

Frank Danna
Yeah, I saw a I saw a picture of an entire family standing there. And they had a little cat. That one what the gentleman's holding a cat and the cat had a mask. So Siraj I wanted to ask you a question. Would you rather have infinite battery power for your cell phone? or infinite fuel? We could say battery power for your car.

Siraj Anwar
Hmm. Oh, my goodness. That's a tough one. Um, I am. I am a car enthusiast. So I would say the unlimited ability to just drive around, I would take that over to the cell phone. So unlimited battery or fuel in the car. Anything to and you can recharge your phone from

Frank Danna
there we go.

Siraj Anwar
Good point. Good point. I was I was just gonna leave that I was just gonna leave the phone at home send me while I'm driving. But yes.

Frank Danna
You don't even need it. But yes, you have an infinite power source for your phone. So everybody wins. So thank you, gentlemen, I appreciate it. And I want to get us started because I use the word informatics a lot. And and I want to I want to get everyone up to speed they're listening to loves the business strategy. Siraj, I would like you for you to kind of kick off what you're doing. Tell us a little bit about the world in which you live in and and what this world of informatics actually is and does.

Siraj Anwar
Absolutely, I think speaking to what I do on a day to day basis is actually the best way to describe informatics. So, in my role, what I'm responsible for in Harris health is ensuring that all of the IT and tech I mean, techno information technology in general, how are we embedding it into the clinical workflows of our physicians, nurses, pharmacists, anybody who takes care of the patient, Anybody who has something to do with the patient experience, How do we ensure that it is optimal for their workflow? It isn't adding undue burden, it isn't introducing new errors or new issues that might reach the patient. So that's one aspect of the work that I do. So I have a team that is, you know, focused on, you know, the physician experience aspect, the nursing experience, aspect, and everybody else, obviously, right. So pharmacy, you think about it, as well, they're probably the three key players. So how do we ensure that all of the tools and technology that are being used by those different clinical users is optimal for their workflow. So working with them closely, understanding their workflows, understanding their needs to make the right decisions throughout the steps of providing care to the patient. That's one aspect of it. Now, once you implement information technology into the clinical workflow, there's going to be lots of you know, hands on the keyboard, a hands on the mouse, and lots of interactions, lots of documentation, lots of clicks, lots of navigation. What that does is it creates this enormous amount of data. Okay, so the the other aspect of my job is taking that data and building something meaningful, that helps us to understand how are we performing as a healthcare system? How am I performing as a physician or a nurse? So that second aspect of my job I like I use the analogy of, you know, you have this truckloads and truckloads of Lego blocks. And then you have to figure out, Okay, can I make something really beautiful and meaningful out of it? So we take those data elements and build it into something that's meaningful. So it could be in the form of a report that shows how, you know, often we are scanning medications, as well as the patient's identification, band 100% of I mean, are we close to 100% of the time, you know, that's an example, are we documenting the risk that a patient may have for a fall when they're in the hospital system every day, and as soon as they come in? So it's, it really helps us to tell the story of either success, or failure, or opportunities for optimization of their clinical workflow. So you put that all together, that is your world of informatics.

Dr. Rod Brace
Siraj sounds like somebody that have the ability to bring that information, that amount of improvement to a team would have people lined up at their door wanting you to help them. experience tells me that that's not the case that people oftentimes push back on this, maybe talk a little bit about the dynamic of what you do, and maybe the challenges of getting people to accept that data.

Siraj Anwar
Yeah, that's a that's a good segway into one of my stories, right. So I'll start by telling the story about and I'm sure Dr. Shabot might have been at that meeting, if I remember correctly, but we were at a meeting, probably going going over some going over some, you know, new interventions that we had built into the system, we, you know, we call them clinical decision support alerts, it's a very commonly used form of an intervention that, you know, is called just in time, you know, this helps with just in time decision making. And remember, I can't remember the exact concept, but it was essentially, you know, physicians are taking care of the patient, and they're about to order something for the patient. And, you know, this alert pops up and tells them, Hey, Doc, Doctor, so and so you should really consider, you know, this piece of data that we're presenting to you, because it might lead to, you know, a potential adverse drug event, and put adverse drug events are pretty common in the healthcare industry, that's when a patient has, like, a bad reaction to a medication or a combination of meds. And I remember, you know, one of the physicians, you know, telling us that, you know, those alerts are so interruptive, you know, I get them all the time, you know, can we like, make them smarter, or, you know, make them less interruptive? Or intrusive? And I was just like, Oh, absolutely, I mean, that's the kind of feedback we're always looking for. And, you know, we're happy to work with you offline, we try to stay away from those types of conversations in these, you know, group gatherings, because, you know, I just think it's better served offline, in an intimate, you know, environment. So, of course, I go back, and I'm like, hey, let's, let's go find out what's going on with, you know, with the doctor, because he said that he gets these alerts all the time. And it's starting to be in, you know, intrusion to his work. So, like, okay, let's, let's go get the data. And we get the data. And, you know, to my surprise, of course, I scratched my head a little bit, because I was like, so this doctor actually got the alert, what, three times in a total month? How is that all the time? So I was like, Okay, I obviously need to have this conversation, right? Because I've got to figure out, is this three too much for him? Is it his perspective, that three is one too many, right? So I remember having the conversation like, Hey, you know, I have that follow up data, I would really like to get that, you know, sit down with you and go over it. And I know, I had the data in my hand. And I was just like, so doctor, it looks like you were getting these alerts. I'm glad we were able to validate that. But I was just a little surprised by the number of alerts that you got to chose here that you only got three, right? And I could just tell, you know, the look on his face. He was just like, yeah, yeah, you're right. And it was just like, Well, were any of those alerts inappropriate in your mind? And he was like, No, not really. They were appropriate. It was like, and did it take you too much time to, you know, bypass these alerts? I mean, is there any way that we can make them smarter? And of course, the conversation is no, not really, it's fine. So what we find is, often, you know, the first few times that we interact with people, and we're trying to add something into their workflow, right, that they're not used to, there's always going to be resistance, because it's, it's a matter of, yeah, we're taking care of these patients. We know what we're doing. Why do we need you to tell us, you know, this additional piece of information, I always check the allergies. For my patients, I always check whether, you know, my patients are on different drugs that they may be interacting with. But, you know, eventually once we sit down when we talk to them, I've received several anecdotes from physicians that I've, you know, over the years, obviously, I've built relationships with them. And I can't tell you the number of times I've actually had physicians have thanked me, it's like, hey, that new alert that you put in the new intervention that we put in, it actually, you know, prevented me and made me think twice, about, you know, ordering this medication. So it's that first I mean, to Rod's question about, you know, my experience, it's usually, you know, hey, this is, this is our domain, stay out of it. Usually, I preface my conversations with some of these physicians, by letting them know, right, I essentially qualify my conversations with them. One of the first things I say is, hey, by the way, I'm a physician as well, by background by training, I know what it's like to take care of patients. But, you know, once I say that, it eases them into the conversation. But once I build their trust, again to Rod's question, that's when I get inundated with ideas and questions and feedback. And it's like, it's like, I don't have enough time to give to them. So initially, it's that resistance but building that trust, working on those relationships equates to oh my gosh, there's just not enough of me to go around and help people. And you know, Dr. Shabot will tell you that once we really started doing this work, the demand was so immense. I was one person and one person only for the entire healthcare system.

Frank Danna
Oh my goodness,

Siraj Anwar
I By that time,yes, excuse.

Frank Danna
Oh, there we go

Unknown Speaker
really quick.

Siraj Anwar
Right, but but by the time I left, and this is in a span of about 12 years, we were a team of 2080 members. So it just goes to show that, yes, once you develop those relationships, and create that awareness in the healthcare organization, about the power of data about the power of informatics, people will really like, they won't hesitate to knock on your door.

Michael Shabot
But let me let me challenge a little something that particular doctor may have had three of those alerts in that month. But, and one of them may have stuck in his craw. And that's why he remembered to it was so distinctive, that he remembered to complain about it. But he may have had 300 other kinds of alerts and reminders. The advent of the electronic health record has not only produced a lot of data, it's produced a lot of opportunity for notifications, to clinicians, nurses, and physicians. And sometimes the easiest answer to a clinical problem is to add another task or message for a nurse or a pharmacist or a doctor. And it's the cumulative weight of all those that really, you know, gets gets gets clinicians down. And, you know, what's the answer that all these things and you know, I will confess to being, you know, among the worst meaning, wanting more and more and more of these, especially relating to safety and high reliability of these alerts and reminders going to clinicians, but, you know, how do you keep the sum total under control, with all the kind of inputs that you get from a health system?

Dr. Rod Brace
You know, Siraj, I think it's important, you pointed out the connection between trusting you the holder of this data, and willingly listening to it, because so many organizations over the history of time have used data as a stick as a punitive measure. And when you establish that relationship, that no, we're going to use the data to help you improve, then it's, it's less threatening to people. And just for the listeners, I think we can't underestimate the how hard it is for an expert to change. So in other words, physicians are experts. And the nature of being an expert, as Roger Michael knows, was years and years of study, and then typically go through a residency program that sort of indoctrinated them to a way of doing something 1000s and 1000s of hours of practice to make sure that they have a sense of security and knowing that the approach that they're taking to healthcare is safe and effective. And then all of a sudden, someone comes up to him in the hallway and says, I have a report that says you need to change, I think we have to recognize that that's a tremendous ask that person to sort of set aside those 1000s and 1000s of hours of work and study and knowledge that got them to that point. And so I think starting with that, here's the data. Here's the trusting relationship, it's a safe environment, good psychological safety here for us to look at this together. Important point that you made Siraj.

Siraj Anwar
Oh, thank you. Thank you. So let me address Dr. Shabot's. Quick question. I can clearly see he's wanting to put me on the hot seat. So yes, let me let me address the concern with the inundation of alerts or interventions. Right. So one of the things that, you know, is the principles of high reliability is is is deference to expertise, right? And who, who better than the clinicians that we work with, right? So if there's ever a problem that we want to solve, we we don't go out there and just say, Hey, here's a problem. And here's how we're going to solve it. This is what it's going to look like what we do is, make sure we have a good understanding of the problem. Let's let's figure out if there's data out there that will help us really understand the extent of the problem. And when you have that data that shows the extent of the problem, we approach those experts. And really, you know, ask the question of, Hey, you know, there was a recent event, right? A lot of times this is driven by an event, or something that happened. And so, you know, we take the premise of that event and work with these experts are clinical experts, more as, as a partner, right, not as a customer, but more as a partner. And we, you know, we just ask those probing questions like, hey, so this problem occurred? Can you help us understand? What are the clinical workflows, you know, that typically occur in this kind of a scenario? And it's like, what is the kind of data that's captured? And that really helps us to go and find that data to tell the story. And then you take that data, and you come back to them, and you say, you know, what, we looked at the workflow a little bit more closely. And here's some data to show, you know, the, the extent of the problem. And oftentimes, you know, the clinicians are like, Oh, my goodness, we didn't realize that, you know, this problem was so, so big, or so extensive. And then it comes down to Well, what do you think would help the clinicians to identify these kinds of issues or problems earlier on in their clinical workflow, so that these kinds of errors don't happen or issues don't happen. And oftentimes, when you approach them with that kind of a, you know, collaborative spirit, and of course, you're building trust along the way, right, because you're constantly listening, there's more listening, that happens during these stages. And, and what happens is that they become a part of the solution. Right, they're never the part of the problem, we never approach it that way. And we're not just handing solutions to them, because they're working with us on the solution. And so ultimately, what happens is, they're amenable to the changes that you're making, because they understand the extent of the problem, they understand what it means to the care we provide to our patient, the quality of care. And, and we're working on building something that is, you know, really not as workflow intrusive, there might be some workflow intrusion, but it's at the cost of, you know, making it safer for our patient and building that high reliability environment. But yeah, they have to be agreeable to it. So ultimately, you know, we're building something that they agree with. And the whole communication model that we usually cater is, we take those clinicians with us, and we let them communicate on our behalf. I'm never the first one to stand on the stage and say, oh, by the way, here's a problem that we're working on solving. And here's how we solve that. And here's what it means to you. We get the clinicians to talk to their peers and tell them, Hey, guys, here's here's a problem. I still remember the day that Dr. Shabot stood in front of all of the nurses and the physicians. And he had a picture of a burning platform. And he said, we have a burning platform, we have an issue. Here's our data. And of course, everybody in the room was like, Oh, my God, let's solve this. Right. So we, that's a great example of how we do that, in informatics. That is exactly what I do. I say, here's a problem. What do you all think, hey, should we get together and solve it? And there's a, there's a common term that I use, whenever I go out and speak to people is I say, you know, informatics is something that you do with the clinicians, not to them. So that's an important aspect of what informatics is. And of course, I'll address the second half of the question that Dr. Shabot posted, which is, how do you know what's going on? And that's where the data comes into play as well. We had built this catalogue of over 200 250 clinical decision support alerts that fire to that showed up to every single clinician in our healthcare system. Well, we actually built a robust dashboard that showed how many times each alert was firing, what time of the day, who was seeing it, and how many were they seeing per day per encounter, per per, per patient. And that way, we could quickly understand if there was somebody who was having some undue burden because of the work that we're doing. And it led us to create an optimization project, where we went back and actually optimized all of these interventions that we had built. So I mean, you will always see it's about problem solving to see if you're successful, see if, you know, their failures, and then it see if there are any opportunities for performance improvement. And this is where the performance improvement comes into play. By having that data continuously available at your disposal, you can quickly go back and identify those opportunities for improvement and just make things better until you get to the top.

Michael Shabot
Yeah, I had to add on. Going to, and that is that when clinicians bring Siraj a problem or informatics department a problem, and informatics help solve it with a reminder or alert or a change in the data. The great thing about is physicians in become advocates for it. They also feel like they've been listened to. And and and re energized reauthorized. And it's a it it for the clinical staff, whether it's nursing physicians or others, when their suggestions are put into place, not just for them, but for the whole system. There's a really a good feeling about that for the organization for them and the organization. They become they become the people that advertise it.

Frank Danna
And actually, that's that's kind of an interesting lead into a question I have around how data can help your systems and your behaviors. I think we've talked a little bit about how data can impact behavior. But I'm wondering how behaviors and systems are important to making the data valuable as well, and how it's sort of like an ecosystem? Can you can you speak to that a little bit?

Siraj Anwar
All right, is that is that question for me? Okay. All right. So yes. Yeah, that's, that's a tough one, but I will approach it with, they're all interdependent on one another. So people, systems, data behaviors, they're all interdependent. Sometimes you do have to make systems that will allow you to capture the appropriate data. A classic example of that is work that a lot of healthcare organizations have done in in the country and you know, all over the world. And that is documenting, all of the precautions that you take, before you insert a central line for your patients, a central line is is like a is like a life saving mechanism to provide nutrients and no medications to a patient, when all of the peripheral IV lines and everything else doesn't work, you put in a central line, because that's the last resort. But if you don't do it, well, you can introduce a whole lot of infections and people will die unnecessarily. So one of the things that we you know, when we were setting out to solve the problem of central line, you know, bloodstream infections associated bloodstream infections, or collapses, as they're called, is, how do we capture the data associated with the central line insertions. And unfortunately, there wasn't a good way or a structured way of documenting it. So they actually went out and created a documentation bundle. And so we had to create a brand new system for documenting all of the steps associated with, you know, the sterile process of inserting a central line. And of course, you also have to know who is inserting the central line, and who is assisting with inserting the central line. And then there's like about 12 or 13 questions. And so we didn't have that data to really understand, you know, are we following the appropriate precautions, while we build those documentation bundles? So going back to your question, sometimes you do have to build a system. And you take that system and work with the people to make sure that they are in agreement, it goes back to the problem, here's the problem, here's how we're going to solve it. And having those people amenable to entering these 13 brand new data fields, right. So once once they're agreeable to it, and they all buy into solving the problem, then you have data being generated, because that's not data we had. And once the data gets generated, you're feeding it back to those people. And you're making amendments to the system. Right. So I remember when we introduced this, we had, I think, only eight questions. And then we started to call it the data. And then of course, there's always new research, new evidence being published. So you know, we modified it further, I remember the use of an ultrasound prior to inserting a central line became the premise of reducing those infections even further. So guess what, we added an additional question that stated, did you use an ultrasound prior to inserting the central line? And of course there were people in the room were like, what one more question and what I have to use an ultrasound now, I've done it for all these years. I've never had to use an ultrasound. So of course, you know, you have those conversations you get people but you know bought into it, you leverage you know peer pressure to get them to use it. But you know, once you start to look at the data, and there is a direct correlation between 100% of the time we're following the sterile precautions for central line insertion 100% of thetime we're using the ultrasound prior to the central line insertion, so that we don't get any complications. If we see a cause and an effect in the data, that's a no brainer. Yeah, these practices definitely reduce our risk of central line associated bloodstream infections, which can be fatal. Oh, I mean, that's how you, I hope that example helps you identify how the interplay is between those three? Yes.

Dr. Rod Brace
I was gonna say, just, if you if you think of the system, as all the things that are going on in the health system, the data is is just numeric, right? It Right, whether you captured or not, the system is emitting this, this data. And so I think the problem that we've we have in healthcare is a lot of times people bring confirmation bias to the data, they say, Okay, I'm only going to look at the data that supports my cause. And I'm only going to support I really want the system to change this approach. And if I can find even small bits of data that are imprecisely analyzed to make that point, I'll do that.. Yeah. And so the, what we then have is sort of a faulty system, because it's really put in place without a true understanding of the data. And then secondarily, it doesn't really take the personal aspect of the people that are having to work within that system. So in high reliability, one of the one of the principles is this deference to expertise. And so once we have a systemic change that we want in place, we really have to run it by the physicians and the clinicians and other people in place there. And if we have that psychological safety, that culture where transparency and truth is there, then they're able to say, yeah, that really won't work, or Yeah, let's try this or now the way you're interpreting that data is faulty, because all data has to be interpreted. And sometimes it can be used for wrong causes in the development of that system.

Michael Shabot
And Rod brought up a very important point, he talked about transparency of the data, which is and transparency of information, which is just totally crucial to high reliability and safety. I've been in organizations where results were clinical results were kept under lock and key. Sounds like I'm picking that up. But I'm not as a, as a chief officer, I had to go to individual locations and ask for it to be unlocked, so that I could review it, although not copy it, you know, just like for eyes only, and these are, you know, clinical quality results. And that that is that doesn't work in a high reliability organization, there has to be that trust. And not only, not only the will to improve, but also forgiveness for what's happened in the past. Those things are just absolutely crucial. For high reliability organizations, I had the opportunity yesterday, to listen to a presentation on our liability from an individual who is on the National Transportation Safety Board, the NTSB who served as the chair of the NTSB for years, and he talked about transparency in the commercial airline industry and said something that I didn't know and that, you know, we all know about the black boxes, which are recovered, God forbid, if there's a crash, what I didn't know is that for routine flights, when they pull into the gate, the black box data is uploaded to and and, and de identified it as the in terms of the personnel so that they can see if there's an incidence of landings that are too fast or whatever, whatever, whatever comes out of the data, and so that they can implement safety procedures in general, not just punitive to one individual. And, you know, that kind of transparency of data and analysis. You know, we don't do and in my view, we don't do enough of that in healthcare, and we really need to, but it's, it's people like Siraj, and that kind of position that Siraj is in that can help make that happen.

Frank Danna
Yeah. It's, it's very interesting to me, because it seems like I mean, you talked about how systems kind of, you know, When, when, when the data is there, you have systems that help lead to right behaviors that actually end up saving lives, right, the information is presented in such a way where people recognize the value of it and then that behavior is able to then illustrate opportunities to improve the system so that people are able to stay engaged. to it, and you brought up some words like trust and forgiveness, and I'm hearing things like empathy, as we're talking about this, and it, it sounds a lot more human than most people think when when you think about data, and how it informs decision making, that sounds more like a human thing than a cold robotic thing. And that, to me is very fascinating.

Dr. Rod Brace
Yeah, it's really human behavior sheds numbers, right, these Numerics that come out, and we capture them as data or we don't, or we ignore them, or we deploy them in the wrong fashion. And so the the problem with sort of that suppression that Michael just mentioned, is data in the past has very often been used for punitive measures. It's, it's the I gotcha. And so when people have found history to teach that to them, then they automatically want to suppress that data or they want. Because, you know, just imagine if you're a physician, and you've invested hundreds of 1000s of dollars and years and years of training in this, and now all of a sudden, you're fearful that this new computer system is going to fire off these error codes, and somebody is watching those thinking, Oh, well, Dr. Shabot had 200 of those. And, and so maybe he's not a great doctor. And so there's this, this misunderstanding or suspicion about how data will be used that I think, probably rightly so, suppresses people from embracing it until people like Siraj come along and convince them that there there is trust, there's a he, he has a relationship with his medical staff that has to be built on trust, otherwise, they think it's going to be used against them.

Frank Danna
Yeah, I'm wondering, I want to talk a bit about that. And how do you create a psychologically safe environment for for those individuals Siraj, when they're, your, as you talked about Rod earlier, something like this, you'd think people would be lining up, right. And ultimately, it actually is a hard sell, to get people to buy into the fact that this is for their good, and it's for the benefit of everyone. So how do you create that psychological safety when it comes to bringing people on board with this? And and and then how is that actually kind of brought to the organization?

Siraj Anwar
Yeah, so I gave you the example of that physician in a public domain, you know, bringing up a topic and I will use, I usually use the approach of Oh, that's great feedback. Could you tell me a little bit more? And then if I start to sense that there's a little bit more detail that's needed that can be, you know, accomplished in a public domain? I will typically say, All right, I'll talk to you offline. And, and defer. Right. So what that allows me to do is, is do it at my own pace versus the pace of that public domain. And I will typically, Well, the first thing I do is I make sure I introduce myself, I let them know who I am, what my role is, I will always do what I call my, my schpeel. Like, so what I just described earlier on in the podcast about what is informatics, I will do that, that elevator, elegant, elongated elevator speeches, I call it but then if it's not possible to have that conversation, right, then in there, I make sure I follow up. And I set aside enough time to get to know the person. So if I'm really meeting some clinicians for the first time, you know, after those encounters, I take the time to get to know them. And I give them the opportunity to get to know me, and, and why I do the work that I do. And why am I even here doing what I do in my role. And that's usually a really good icebreaker for lack of a better term. And then when when when I start hearing, you know, their issues and their problems. One of the first things I do is I empathize. I say, you know what, that must be so frustrating, or, you know, I'm sorry to hear that you're going through that. Well. Let me figure out how I can help you. I think that's what clinicians need more than anything else. They want somebody who can listen to them. So part of my job, I mean, you read it out in my, in my bio, right? You said human relationships. Yeah. So that's what I try to do. It's a part and parcel of my day to day activities. I get to know people on a personal level also, I try to find out what some of their hobbies are. And, you know, I use that to sort of just build that trusting relationship. And then, you know, I will slowly ask for Hey, you know, we get your cell number. Here's my, here's my cell number. Why don't you I mean, yeah, texting me back so that you know, we're in touch. I'd love to hear from you. I use the term love a lot in my conversation. If you were to ask my coworkers, they're probably tell you Yeah, he uses love a lot. But it's just, you know, it puts the people at ease, right? It's a different kind of love. I really am looking forward to hearing from, you know, my clinicians, the people that I work with. So I typically will leverage some of those just human relationships first, to build that trust. And, of course, like Dr. Shabot and Rod said, and once I deliver on something for them, then it's that's it, I mean, it's a done deal. It's like, we're on a, you know, first name basis, we'll get text messages at odd times of the day. Of course, nobody does that now. But I'm just saying it's possible, and I welcome it, if somebody were to messaged me, on a Saturday, I will respond, because I know, that's how I continue to build on the trust, I feel like that's really helped me. With my day to day job, my activities, that's something that I didn't do initially, in my role, my initial experience, from, from what I remember was, was very transactional. And I only realized that, for me to be able to really, you know, affect change, I have to work with these people a little bit more closely. And I have to build their trust. And they have to see me as someone who is their partner who's willing to help them overcome issues, and not as someone who just comes in to solve problems, because I'm a problem solver. And I will do it very in in a very transactional manner. So, I feel I feel like that that really helps to build that trust. And it's, it's just one of the first things that I always do.

Dr. Rod Brace
Siraj, while you're talking about that, it strikes me that your professional reputation, your role, your future career, is highly depend upon the accuracy of your data. So in other words, if you bring a lot of stuff forward, that's indirect and accurate, you're likely not going to have a job very long. But yet, the people that you're not the person that's inputting all the data, you're not at the source of all the data. So how do you balance out that? How do you how do you keep data integrity, when you don't have total control over the whole flow? Just If nothing else, to protect your job?

Siraj Anwar
Wow, I can tell you just just the other day, I had such a situation where, you know, we're presenting data. And then it took that one additional doubt, or concern that I had, because I looked at the data again, and I recognized some names. And I put some of my, you know, prior knowledge and experience with these folks, and I said, you know, that person doesn't sound like someone who would be doing this, right. So it was some type of a followed, and I was just like, that doesn't sound like someone who would do this. And, and I actually picked up the phone, and I call them and I said, Hey, I'm looking at this data. And, you know, I got to ask, do you remember why you may have done this way? And, and of course, I told them, Look, I'm not calling you for any punitive reasons. This is just for my own edification. I'm trying to find out if my data is inaccurate, right. And so, so we go over it. And he, you know, he tells me that, oh, yeah, that order. I remember discontinuing it. And I was just like, oh, boy, are we including discontinued orders in our data set? Wow. Okay, no, that's not good. So I immediately I immediately went back to the team, and I said, Hey, does this data report include discontinued orders? And of course, the answer was, Yes, it does. And I'm like, Huh, that's, that's, that's going to be a problem. Can we edit this report really quick? I want to see how different it looks with the discontinued orders. And, of course, you have to be careful to understand that by excluding the discontinued order, are you excluding something that may be telling a bigger story? So obviously, we're in the midst of doing that now. But when we rerun the report, without the discontinued orders, this physician that I knew was like 100%. Perfect, right? So how do I balance that? I think you never take data as its face value, you definitely want to spend some time what I like to call a sanity check. And if the sanity check, goes, Okay, then you still want to spend some time doing what I like to call a chart audit. So look at the data, look at the events that transpired in the medical record and make sure that they both coincide. Oftentimes, we'll find that you know, there's a there isn't a direct correlation between what's in the chart versus what's in data. So sometimes it might require you to go back, talk to the clinical users and understand, can you walk me through the sequence of your workflow with what you documented? And then we may end up also going back and saying, hey, looks like there might be a data field or a column that we, you know, we left out, that doesn't tell us the full story. I will tell you, yes, my entire career does depend on data accuracy. But remember, the whole beauty of engaging the clinician early on in this process, is they become a part of that data validation. So if the data is wrong, guess what? We're all wrong. So it's not somebody pointing their finger at Siraj and his team. So um, so building that, again, it goes back to that relationship and working with them on the solution, they become a part of that solution. So, you know, somebody will say, you know, what, we validated that data with Siraj and his team, that's probably something we didn't think of, we'll go back, we'll revise it, and we'll rerun the report. It's all about accepting, you know, when you do go wrong, I think that's a part of our role. Also, as you know, in from informaticists and informaticists leaders, we shouldn't, I mean, it goes both ways. We also shouldn't, should not be hesitant to say, yes, we've made a mistake, or feel feel vulnerable, right? Because, yeah, by admitting that you made a mistake, you know, you are vulnerable, you're like, Oh, my God is somebody keeping track of how many times we've made a mistake. But I think you learn from your mistakes. And again, that also helps to build that trust, like, hey, Siraj and his team are not afraid to admit when they've made a mistake, and they're working on fixing it. So they can be, you know, honest, upfront with us and tell us if they made a mistake. I mean, mistakes happen.

Michael Shabot
So that's what I would say that sometimes it's, I'm recalling a situation where it's, it's not, we're not even directly under your control. Again, with the inputs there, they're not only the inputs that come at the front end, from clinicians, or from other systems that are putting data in. And of course, there's analysis on the back end. But in between, there are databases and interfaces. And I recall a situation with Siraj, where one well behaved alert that had been all tuned up and was going along fine. You'll remember this Siraj, at some point, some date, it just went off the rails, and it began alerting all the time, two or three, four times what its baseline alert rate was. And that was due to either a, an an operational system, upgrade, a database upgrade, or or a change in the formulation of the drug in the pharmacy. And that required a fix. But in the end, until we until it was caught by your routine monitoring, I remember the graph, they just like given date went off the rails? those things happen. And they will continue to happen in in, in, in systems as complex as a hospital and health system, where there are many, many different not only inputs, but things that happened to the data on the way to the analysis charts.

Siraj Anwar
Yeah, I remember that incident like it was yesterday. And those are not uncommon to your point, they will happen, just because there are complex systems, lots of moving parts. But it's important for you to have that that data architecture in place to help you identify those errors earlier on, rather than, you know, waiting for weeks or months where our clinicians are suffering and they're just too busy to pick up that phone and tell someone Hey, what's going on with the system? This is ridiculous. And I remember nobody reported it. I mean, that. Yeah, nobody told us and it was, it was happening for I think two to three weeks, until we got the data and I was just like, oh my goodness, Why didn't anybody tell us anything? It was like, again, we have to empathize with these clinicians, the poor folks, they're just doing so much. They're like, hey, it's okay. I'll just keep going. I'll just keep going. And, and it's our responsibility to be responsive when we do find out those kinds of issues that we fix them quickly as a priority. So yeah, that's a that's a great example that Shabot I had forgotten about that.

Michael Shabot
He has a question about and different kind of quiet on the other end of your of the analysis. You know, one of the problems of electronic health records is that there's just terabytes and terabytes of data. And, and it's, it can become mind boggling as as results go up to the C suite as to you know what to look at how to look at. I mean, I've seen dashboards that have 7- 800 data items on them numeric items, that couldn't possibly be, you know, intelligently assembled in someone's mind on a monthly basis. How do you make the data understandable? For an actionable?

Siraj Anwar
Yes, that is a common problem. I'm sure every healthcare organization is facing it today. And now. And and it boils down to one thing, right? The people who are the audience have the data, I think it's important to ask them for their feedback. And oftentimes, yeah, some, some, some people will say, yeah, there's too much on that report. What should I be worried about? or What should I be proud of? I mean, those are the two things that you always want to be able to quickly identify, what should I be worried about? And what can I, you know,celebrate. So I'll tell you that what we've been doing is, as more and more data, more and more metrics become available, it's important to, you know, obviously identify those successes and failures. And so we've been adding an additional layer of what I like to call mathematical models, or statistical, you know, analyses that really help us to call out the problem areas. Now, you know, you can always have random variations right in the data or events. And it's important that you not become, you know, overtly excited, or disappointed with those random variations. We see that all the time. So what we've started to do is to actually look at all of those different data sets, and, you know, do some simple regression models to really understand, are there statistically significant increases or decreases. So of course, if there increases in the wrong direction, you want to pay attention to it. And if there are, you know, reductions in the right direction, you celebrate it, and you say, well, that's good, I'm just gonna lean back and enjoy this moment. But I think it's important to really focus on you know, what's meaningful. As an example, if we, if you find, you know, just raw numbers, they may, they may tell you something, or they may not tell you anything, but when you have a more easy to understand metric that, hey, you know what, right now, it looks like, you know, where we're at a five or six times higher chance of getting a, a bed altar while you're in the hospital, in our hospitals, I'm totally making that up, right? You obviously want to do something about it. Versus, yeah, we're like, you know, 1.1 times more likely, but you know, the Federal, the federal government and everybody else who will penalize us, if we go higher than 1.2, you'd rather focus on I mean, leverage all of your resources to solve the problem, that's five times more likely to happen, versus the one that's 1.1. So having that that power, of knowledge and insights available to the people who can make the difference, I think is something that we have to start doing. Because, you know, there's just so much more data and metrics coming on, I think you have to start calling out what is something to celebrate about, and what is something that you should, you know, put 100% of your attention onto. And that's something that we're, you know, actively working on right now. So, it's, it's very beneficial to focus to really focus our attention on

Frank Danna
well, gentlemen, this, this has been very fascinating. I am not in the healthcare space. And, and even just listening to the conversation that we're having today. I found that kind of funny. Somewhere in one of your stories, you're telling Siraj, I started thinking about the fact that if data has humanity built into it, and human relationships are at the heart of data, then you have no excuse for bringing humanity to your workplace, when it comes to if data has human like relationships built into it. And that's how you make data work, then it's probably something you should consider as you're working, maybe not in the data field, maybe not in the healthcare space, but in any organization in any any relationship that you're working with other human beings. You know, it's so interesting, because informatics is relationship building, like, like that's, that's what you're ending up doing is building relationships to the data to the behaviors of the team members, to the mindsets and attitudes that people have in regards to how they perceive that data. And then when people are able to feel that trust and engagement with you, and you're creating, essentially a change network of people who will constantly be able to feel like they can bring you the information that you need to do your job even better. It's fascinating to me, when you build advocates, and when you create an environment where people feel like they can bring their failures, they can bring their frustrations to a safe place, and have them addressed and answered in a very unique way. I mean, it's, it's really cool. I honestly was a little worried coming in, that a lot of this would be challenging to kind of understand. But when I'm listening to what all three of you have been talking about, we're really talking about addressing how we can make systems work for building better behaviors that impact patient outcomes and patient safety. Right and, and creating an environment where clinicians feel like their voices can be heard. And they can be a part of the solution instead of pushing back against the problem.

Siraj Anwar
Well, well said, Frank, that is a that is a absolutely perfect synopsis of what we've been talking about.

Frank Danna
And so Gentlemen, I think now's the best time to say thank you, because I appreciate all the time that you've been able to, to, to give to us today on our podcast. So Dr. Rod Bryce, Dr. Michael Shabot. Siraj, I just so appreciate your time and energy and passion for this conversation in this topic. And here at love as a business strategy. We're posting new episodes, every Tuesday. If there's a business topic that you'd like to have us cover, maybe something that's a little bit atypical or tangential to what a typical business conversation is, we would love to talk about it. Let us know at softway.com/laabs. And if you liked what you heard today, please do leave us a five star review and subscribe on Apple and Spotify. And if you know someone who might enjoy this content, don't forget to share the love as a business strategy. Pun intended. So Gentlemen, thank you all so much. And for those listening and watching, we'll see you next week.

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