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Medicine is hard. But there's a lot of things that we can do in the automation front to make clinician lives and patient lives easier and safer. Using AI to perpetually learn and improve upon those things. That's really the most exciting part right now is automation to improve the experience and get back to the care of medicine.
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All it's news day. And today we're joined by Dr. Colin Banis with Dr. First Colin. Welcome back to the show.
Hey, good morning. Thanks for having me.
Yeah, last time we saw each other was at the conferences. We're not going to cover the conferences. I'll give you just a quick, what was your impression of the conferences that you went to?
I was pleasantly surprised that the turnout was as good as it was at both ViVE and HIMSS. I really, I was worried and hymns did not, did not disappoint.
Yeah, I was kinda surprised. I mean, if you combine the two conferences, there was over 30,000 people at the two conferences. So given that we aren't officially outside the Pandemic. Those numbers are really promising and it looks like both conferences have enough to build on going into next year. so we we'll see how that goes. I wanted to start with something with you as I'm getting ready, my daughter's going to graduate from college. And one of my favorite things is to pull up commencement speeches and that kind of stuff.
But I'm curious for you, you've had a bunch of commencement addresses, right? You've you've graduated a couple of times that, do you remember any of the speeches from those, for those commencement address?
No. I do remember one speech where a guy, a gentleman used an anecdote that I had heard before. And I said, well, that's clever, but it's not original, but yeah. In preparation for this. I couldn't remember any of them.
Yeah. are we at a major coup our economics department got one of the federal reserve chairman to come in and speak at our at our graduation. And it was quite the coup and I, there's a picture of my entire family sleeping in the back during my commencement during very it's a dress and a. That I, and I'm not sure, I'm not sure I stayed awake either. I just wasn't sitting next to them. So it was a,
I think the key is to keep them short and to, to keep them Humorous, like some of the most successful commencement speeches are not any more than five minutes max and sprinkle in some humor.
Yeah. I think, I, I think that's really true. Any idea what you would talk about if I asked you to speak at a commencement address.
I'd like to think that I'd be funny and, and witty. And I'd probably put some thought into that, but. I think it's an offshoot of a question. I get a lot about my career path and it's kind of, non-conventional, at least it was at the time to, to get where I am now. And the advice I give the residents and the interns who are asking me about careers. It's usually along the lines of never stop learning, which is of course, a common theme for a lot of these commencement speeches. It really is true. I just kept getting more and more degrees education just kept open to it.
And then the second thing is get involved. I would not have landed where I am now without getting involved in some really non-conventional committees or projects at the health system. And it's just, it's just funny how organic relationships and career paths evolved simply from just being involved. It was probably the two biggies.
Yeah. I, if I were doing an address, it would probably be the failures that have shaped me. And I would just go through my failures over time. And if I did it correctly what they would walk away from this is you're going to screw up a lot in your life. And it's really how you, deal with those things and how you move forward that make you who you are when you get to them, do your life and go, yeah, that was a, that was a life well lived as opposed to I wish I wish I was feared failure so much that I avoid pointed doing the things I wanted to do. All right. And I sort of feel like Matthew McConaughey here throwing out little, little pearls of wisdom. did you read this book?
No, I've, I've heard him give interviews on it and it sounds, it sounds like a great
re he's quite the philosopher. My wife and I had a long drive. We went from Pennsylvania to Florida and we decided, all right, what book are we going to read that's going to keep us awake. And it did not disappoint. We we stayed awake the whole time. he's a great storyteller. It was just a lot of fun to listen to.
Alright, first story for us. And this is an interesting one. Preparing clinicians for a clinical world influenced by artificial intelligence. And this is in JAMA network.com and it's an article that's out there preparing clinicians for clinical world influenced by artificial intelligence. Artificial intelligence, AI and ML machine learning are poised to transform the way healthcare is delivered.
AI is the use of computers, simulate intelligence ML is essentially how we train those computers for AI algorithms. While AI has been critiqued as being in its hype cycle, that's an understatement. Over time it is likely that every medical specialty will be influenced by AI and some will be transformed. I don't know about you. Did you run across some interesting AI or ML solutions while you were at the conferences?
I think you're spot on in that hype cycle comment. I think actually clinicians or potential partners are becoming numb to the term AI. And I think you've heard me say this before. I really hate artificial intelligence. I'd rather say something like augmented or advanced intelligence. The other thing is, and again, I'm going to repeat myself from prior talks, but I think there's tremendous opportunity for AI to do some of the smaller things in automation. And I've often referred to this as hitting a single, instead of trying to use AI to hit a grand slam so that the Watson experience, we were going to cure cancer with AI.
And we got a lot out of it, a lot of learning, but you know, medicine is hard. But there's a lot of things that we can do in the automation front to make clinician lives and patient lives easier and safer using AI to perpetually learn and improve upon those things. I think that's, that's really the most exciting part right now is automation to improve the experience and get back to the, the care of medicine.
Yeah. And I think I saw some of each of those at the conference of soul. One, one solution that was AI on top of mammography imaging. And it was again, assisted just like you said, pointing out some things that the, clinician might want to whoever's doing the reeds might want to take a look at and it improved the speed of those reads by 55% and also just the overall effectiveness of the reads in terms of error rates and those kinds of things went way down. The other is obviously with with voice and pulling in the voice and creating the note and that kind of stuff, all that stuff's really interesting and lends itself to that automation aspect that you're talking about. Taking the mundane work out of the clinician's hands and letting them practice medicine and the technology sorta comes around them and helps to support them in their, in the practice of medicine. The JAMA article goes on to talk about really five, five things that they they think would help.
And and one of them is. They do say don't, don't ignore AI. the fact is that AI is here. It's starting to contribute. It's starting to show up in different places. Their first statement though is welcome. Skepticism, avoid cynicism. Like AI doesn't exist.
You can't define it. Those kinds of things. Instead welcome it with skepticism. We should be asking questions about the algorithms. How's it making decisions. How's it determining what's coming in front of us as the clinicians or in front of you as a clinician? I am not a clinician, but what we are putting in front of the clinicians welcome the skeptics.
Because it is a computer algorithms could be wrong. It can be misreading the information and we can make them better over time. But avoid cynicism on the topic because we will likely see it really expand in it and its use. what are you hearing from clinicians or what, are your thoughts on, the adoption of AI in the clinical world.
Well, I think the cynicism comment is I think it is easy to become cynical about AI given some big ticket. Yeah, so sepsis prediction in some major EMR and having to walk that back, I mentioned the Watson experience I do think skepticism is, is a better Adjective for it.
I think trust, but verify is kind of a creative for the clinical world and all of this. And what you brought up really opens the topic of governance. How are we going to govern regulate AI? How do we know what went into the algorithm? How are we going to update the algorithm based on changes in medicine, changes in populations, et cetera.
And so there really needs to be a certain amount of transparency in these AI engines so that folks can understand where the outcomes are, where the suggestions and decision support are coming from. And I think that's the tougher part. The article actually also mentioned. It's a corollary to something that's a little bit over, almost two decades.
Now, the big when I was, when I was training, the big move movement was evidence-based medicine. How are we going to put evidence into our care sets into our decision support, et cetera. And you had to show the clinicians where the evidence come from in order for them to buy in and to trust it. So take that forward into the AI realm and it's the same thing.
Yep. Yeah. They, the transparency and trust clinical operations, appraisal guidelines and clinicians and patients shared decision-making. I think it's interesting that transparency John Halamka came on and talked about. Along the lines of a, a label on AI that says here's, what's in it.
Here's, what's coming. Here's where this data is coming from. Here's what the algorithms are doing. The the other thing, we talked to a bunch of CEOs and. Data scientists at the conferences and they kept talking about drifts and they kept talking about the, the challenges with the datasets. And we, we have to be cognizant of that.
This is where bias comes in. This is where we might be looking at a data set. That's not representative of the dataset we're trying to care for in our community. If we are. Trying to take a national dataset or even a statewide dataset may not be indicative of the people who are coming into your ed from eight o'clock at night to seven o'clock in the morning.
We have to really fine tune those algorithms to the, the populations that we're trying to serve. Absolutely.
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One of the things I want to talk about. Because it was the number one issue that I heard at the conference, which was labor and and staff. Right. So staffing on the clinical side, staffing on the on the administrative side, every area of staffing from the custodial to to the, the physicians to it, staff or whatnot is, is a challenge.
And I, I saw this story in the USA today. We don't often talk about the USA today on the show. But it talks about this concept of boomerang employees and they are, what they're talking about is employers are seeking out former workers. And they're trying to tap into them. And in some cases, these should be retirees and other cases, it can be people that have specialized skills that have potentially moved on to other employers.
And they're going back after them. Former employers might be thinking differently about. A hole in their resume in a tight job market. So they are, they're looking at those at that group. And then the other thing they say here is when it comes to compensation and benefits, there are questions for both parties to consider in that the calculus has sort of changed when you have a challenging labor market. Employers have identified an area that they can't fill a former employee would fill that well. And sometimes they're they're thinking different about the compensation. They're thinking different about the work environment. So they can essentially say don't come into the office is now a pretty common thing to say, and they can work from their retirement location, provide some to fill in it could be three days a week.
Could be all zoom based and whatnot. what are you hearing out there with regard to to staffing levels and, finding good talent in your circles?
Yeah, I think what you were, what you would, what the common theme of what you were just mentioning is, is having to get very creative to recruit and also to retain talent. That term boomerang employees I've been with Dr. First for three years now. I've, I've come across at least three or four. Employees who have come and gone and come back like a boomerang. And I think it, I think you're spot on in terms of where folks are in their career trajectory and what they want, and the fact that the employer is having to offer so much more latitude in order to, to fill the need.
that is one of the great accelerators that came out of the pandemic. Is this. This flexibility, this movement towards, towards remote. And last time we talked, I actually mentioned I'm, I'm not a fan of it. I recognize it's important, but I still miss the in-person part of it. But the other thing on the clinical side from my colleagues and you mentioned on the clinical front, especially.
Very hard times getting and retaining clinical talent. Massive signing bonuses aren't even cutting it anymore. And so that's to link the two articles together, that's where something like AI, or at least automation can come in to at least give you that force multiplier for the existing staff that you have. But it is, it is a tough market out there.
Yeah. So we are going to see technology. Be called upon to step into some of these gaps. It will be interesting to see where it can play. I may have mentioned this to you before I saw it a cartoon where The nurse was sitting across from whoever the hiring person was.
And they were saying, look, we're not going to be able to give you a pay increase. You should go somewhere else. the next screen obviously is that nurse going to a traveling nurse company and she gets hired. And then she goes back to the original employer and they ended up paying her twice as much to be a traveling traveling nurse at the time at the same location and I re it's one of those things that you read and you sort of scratch your head and then you talk to people and they go, no, that's actually happening.
Absolutely. Yeah. It's sad.
it's kind of crazy, but I think what happens in the longer we're going to talk about innovation. In fact, we can go next to what kills innovation conversation. ' cause one of the things we're hearing is tight budgets. One of the things that's, that's creating tight budgets at these health systems right now is this wage inflation, I guess, is what we're calling it. But essentially it's we, we have to retain talents or paying them more.
We have to find talent. So we're, we're filling gaps with temporary workers, which is costing more. And the work really hasn't subsided. There's still the same amount of work to get done. and so there's wages we're seeing on the bottom. It'll be interesting to see when we actually get the numbers. A lot of this is anecdotal, but we're seeing almost a 10, 20% increase in wages at some health systems. That's a serious bump up to the highest cost of running a hospital.
Yeah, one of the things and correct me where I'm wrong in this, but I, I remember you telling the story once back in your CIO days where you very much encouraged innovation on all fronts. A lot of that was in the form of automation, whether it was virtual servers or whatnot, and the idea of. What can you guys innovate around to get some of this spend down? And if you, yeah, I love that story because what it told me is that you very early on had instilled a culture of innovation for the health system and that it, it paid off.
And I think one of the, in that article what kills innovation. Lack of commitment to innovation the most progressive health systems no matter how dire it is, are still making that commitment on some front to innovate.
Yeah. There's some interesting, interesting things here. The you have Christine who who's been a guest of the show from common spirit health, health systems are just recovering from the COVID surge. And there's a lot of concern about staffing levels and financials, which is hindered innovation as the health systems have been focused on immediate issues rather than future investments in innovation. And what's interesting about. And I, I know exactly where she's coming from because it's tearing the tyranny of the urgent what's what's in front of you, what needs to be solved.
But the problem is if you stay there, you will always be there. If you don't at least look out one year ahead, if not two or three years ahead, there's, there's no way to break out of that until you start to look one or two years out and say, okay, how are we going to do this a little differently? And but I know a lot of health systems are really focused right now on.
How do we solve these immediate problems that are in front of us? And if you take a short-term view, and we've seen this cycle over and over again, not but it's well, our number one cost is staffing. Therefore we have to reduce our staffing to get our costs in line, and you just create this really vicious cycle instead of being creative and innovative in terms of how you come out of.
I think it's spot on. It's no different when I was doing my CMIO role, we got so laser focused on things like meaningful use or the joint commission or whatever crisis do juror was, and it, they, they never stopped. So it just kept coming and.
There's always another crisis is that there absolutely is.
You never let the crisis go to waste, but at the same time, we absolutely lost our way in terms of innovation. And that's where I like to say that those things sucked a lot of the oxygen out of the room because early on, I really did have the latitude to innovate. And I think from a personal perspective. That was, the most fulfilling in my CMIO role was the innovation.
Khalila Eskandani and vice president chief information officer at children's national hospital in DC. What kills innovation is inaction and not leveraging the pandemic lessons to continue developing novel solutions. It's interesting that crisis, the pandemic as a crisis. Catapulted innovation because it changed the environment we were operating in and we had to think differently. We had to say, all right, there's no status quo here. We haven't addressed anything like this in our history. And so a lot of really smart people went into rooms and said, all right, how are we going to going to do this?
And what I think you hear this chief innovation officer calling for is let's keep that creativity. going And that's, that's hard to do. It's hard to create that burning platform that people are constantly looking at it going, allright we've got to change this. we've got to continue to innovate on top of this.
One of the things I think from my colleagues, it really broke through a lot of the friction and barriers related to governance. You were able to shorten the cycle for decision-making out of necessity around technology, implementations and innovation. So. I if one of, if that's one of the lessons that we could preserve going forward is more rapid cycle iteration and reduced, reduced bureaucracy of, of governance that is sometimes pervasive in larger health systems.
I'll hit on these last. These are actually all really good points. Brand Brad shank, administrative director, and innovation of innovation at use Methodist. There's too much concern over failure. I don't it's when I hear that, it's I understand what they're saying, fail fast and whatnot. But I also remember my CEO coming to me saying, Hey, you've got to watch what your words are using.
This is healthcare, and I know you want to move faster. I know you want to fail fast, but failure cannot meet causing harm. Failure cannot mean all these things. And she goes, so sometimes I, she goes, I understand completely the verbiage you're using, but the Silicon valley verbiage doesn't always translate real well when we come into healthcare.
Yeah. I think that's fair. I had a CEO similarly. He was actually very supportive of innovation and he would say things like. If you throw 10 things against the wall and one of them sticks, that's still worth the investment to me. Obviously you can deconstruct that a little bit, but at least there was a culture of innovation that he was instilling. I do think you're, you're spot on though. You're not allowed to potenitally harm in any way in the cycle that is, that is verboten.
Yeah. And there's, there's a lot of ways. There's a lot of ways to minimize it. And we did certain pilots, we did information alongside other information so that the physician could continue to practice the way they were. And then they saw this other information and they could mark it and say, Hey, your, your algorithm was spot on or your algorithm. Is not giving us stuff that is going to be helpful here or whatever. And so we, we would innovate in a parallel track. So that.
Yeah, that is, that is spot on in, and this was a constant tension between me and it is they, they called it tantamount to testing in prod which it really wasn't, it was more of a parallel process, but that's where your informaticist come in, who are fully aware of. Can we make changes for this select population of users? And can we get real world feedback on real patients as to what the, what we've changed and how it affected the experience and the outcome. I think that is super important. And the fact that you were able to do that is, is huge.
Yeah, well, that wasn't step one, but that was when we were getting close to implementation. That's what it looked like. Cause we needed that real-world background. We also needed the clinician back at the clinic clinician feedback and we tried to minimize the impact on their workload. And still get the feedback it's so we made it real simple, like little one-click buttons spot on, missed the mark.
I mean, just, it was as simple as it could be because you can't see 12 patients in an hour and then also. Doing it, it work on the side. So Scott Jocelyn, who's also been on the show friend cause he was a CIO in a neighboring hospital down in orange county, says what will kill innovation is an organization within an organization is lack of commitment, just proportionate funding and not placing the right people in the right place.
And that really gets back to what you were saying. I mean, If the culture supports it, it will likely happen. If the culture does not support it, they're not going to fund it. They're not gonna allow people the time to innovate and give them the freedom to innovate. That's likely going to be the thing that kills it off the quickest.
Yup. I want to go back to an article. I shot this over to you because I wanted to get your comments to nine clinicians last week talked about CMIO 3.0. And so I have some comments on last week's new state show on CMIO 3.0. But since you are a CMIO and have practices as CML, I'm curious what your thoughts are on, on this article. The 3.0, iteration of the CMIOs role
Yeah. And we might even be up to 4.0, depending on how you slice this up, but the traditional model and I can't claim credit for this. This is a lot of my colleagues, but CMIO 1.0, was. the MD who was good at it and therefore got tapped to help with the EHR or the HR implementation 2.0 was holy cow. We have this thing, but it's not at all tweaked modified optimized. And then 3.0, at least the way I used to frame it in my mind was data. How can I leverage the data that I'm getting out of this, this new EMR flow. In order to really manage and make decisions at a population level and also implement evidence-based interventions directly into EHR workflows.
I think if you wanted to go a step further and say there's a fourth iteration, it's now it's, it's around. Experience, I think either a patient experience, digital front door, whatever you want to call that there's a piece of that now that is falling in some version of CMIO. And then also innovation as we've we've been talking about a lot today.
Yeah. And in the article they say 3.0 is so at one point I was EHR implementation 2.0 is optimization and making it work for us three point of they're there they talked about, I think I agree with you. I think it's more 4.0, data really makes sense. It's 3.0 4.0, is this new set of tools that's coming down the pike and leading those efforts to, to bring AI and ML into the environment safely with governance and it really leading up that charge. I think that's the CMI that would make sense for the CMI to do that.
It would but I'll go back to the you can't manage what you can't measure. The 3.0, in my mind being that analytics or enterprise data warehouse, I think you can't overstate that. Not, I don't think you want to squish that into innovation and AI. I think you have to have that firm foundation before you go down the path of, of experience AI and ML.
Yeah, absolutely. The CMIO role really has changed. I mean, it used to be an adjunct in the it organization to help with the EHR implementation. I know when, when we did our EHR implementation, the CMIO had, he didn't report to me and had a staff of, oh my gosh. Again, this is a $7 billion health system, but I think he had a staff of about 60 people, 65 people. Helping with all that stuff, that's that didn't include contractors for the EHR implementation, but that 60 was like the ongoing and by the way, it still had all the EHR staff over here to keep it running and, and optimize, and those kinds of things the reporting and whatnot fell over under it.
So again, these are, these are two significant organizations now, whereas it used to be. And we got this doc who really knows technology. Let's see what he can do now. It's like, no, no, this, this is a this is a seasoned role that will likely have accreditation attached to it. Who is a leader within the organization, a change agent, a change leader, as well as somebody who can lead a staff effective.
Yeah, it's leadership, it's change agent. And then the third thing I put in the job description is translator. So it's effective translation between clinical needs and nerd speak. Being able to go back to the analyst and say I didn't need my informaticist to be able to code.
I certainly couldn't code in CCL Cerner command language, anything like that. But I can speak it. And I could, I knew the limitations of the system and I, what was, and wasn't possible. So I think those are the three biggies in terms of what you look for in a seasoned CMIO.
Fantastic. Colin, always great to catch up with you. thanks for the time today. Really appreciate it.
Absolutely love being here.
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