HCA’s AI-Driven Patient Safety Evolution, Part 2

00:00:01:10 - 00:00:31:17
Tom Haederle
Welcome to Advancing Health. The impact of artificial intelligence is showing across nearly every aspect of health care delivery today, and continues to grow in reach and importance. In the second of this two part podcast on patient safety, we hear from a major health system about its steady integration of AI, how to govern it, and lessons learned from putting AI to work across many of its systems.

00:00:31:19 - 00:01:03:21
Chris DeRienzo, M.D.
Welcome back. This is part two of a terrific conversation with Dr. Randy Fagan from HCA. Again, I'm Dr. Chris DeRienzo, the chief physician executive for the American Hospital Association. Dr. Fagan serves as the chief quality officer of HCA Healthcare. And part one of this podcast went really deep on patient safety and how HCA is both thinking about and acting on patient safety at a scale that is incredibly challenging to rival within the American health care ecosystem.

00:01:03:28 - 00:01:29:07
Chris DeRienzo, M.D.
We got into a conversation around AI enabled technologies on patient safety, and it made us wonder, there's a deeper conversation we should probably have around AI. And really, I think that starts with governance, because I've got to imagine when you're talking about something like 190 hospitals, across 2000-ish other rooftops, that you have no shortage of people wanting to utilize AI in their workflows.

00:01:29:07 - 00:01:33:00
Chris DeRienzo, M.D.
And that's got to require a pretty significant governance arm.

00:01:33:02 - 00:02:01:10
Randy Fagin, M.D.
You're 100% correct. And, you know, we've put into place a pretty robust governance structure that goes beyond just our clinical leaders. It involves all of our functional areas from operations, finance, marketing, development, supply chain, you name it, we've included those folks to be a part of the table because it's important, as we look at the use cases, that we're looking at each use case through all lenses.

00:02:01:12 - 00:02:28:29
Randy Fagin, M.D.
As we prioritize use cases, we look at them quantitatively based off of the risk and the opportunity in each one. You know, it's interesting, as we've looked at the opportunities, it's not always about average performance or going from this average to this average. One of the greatest opportunities that AI offers us the opportunity - and it doesn't matter which lane we're in, whether it's operational efficiencies or clinical performance - it's about variance reduction.

00:02:29:06 - 00:02:57:20
Randy Fagin, M.D.
And, you know, being able to reduce variance is one of the, I think, most powerful things that AI can do for us inside the clinical space. When we look at areas to prioritize, we look at where we have areas of high variance, whether it's variance by clinician experience, variance by patient presentation, variance by geography. How can we reduce variance to try to improve the consistency with which we deliver care to our patients?

00:02:57:22 - 00:03:17:16
Chris DeRienzo, M.D.
I love the focus on variance. One mentor of mine that framed it this way that when you're looking at a challenge, you have to ask yourself, is this a batting average problem, or is this a slugging percentage problem? Because sometimes you're right. I've got to move, you know, a whole big boat from below the Mendoza Line, which is 200

00:03:17:16 - 00:03:36:18
Chris DeRienzo, M.D.
in baseball, for those who are baseball fans, to 300. But sometimes, it's I just need seven more homeruns or I need to not strike out 17 times. And it sounds like you're taking a version of that approach that is not baseball related to health care. And I love that thinking because it really does branch into very different pathways.

00:03:36:20 - 00:04:06:19
Randy Fagin, M.D.
100% agreed. And as we do that, one of the critical things that is kind of the next layer beyond governance is who you involve. And it's critical that we involve frontline staff early, the people who are closest to the work being done. It validates the problem and ensures the relevance and buy in. And as smart as the executive team may be, it is critical that we get the people closest to the work involved early in the process to help to shape that work.

00:04:06:21 - 00:04:22:27
Chris DeRienzo, M.D.
For those who are listening only and not seeing me nod my head as vigorously as the head can be nodded right now, I just want to narrate that for you. Because I remember like, ten years ago, we had developed this terrific machine learning model to predict readmissions in the health system I was working at the time.

00:04:23:03 - 00:04:36:27
Chris DeRienzo, M.D.
We spent nine months in development. Like, the numbers on the model were terrific. And then we showed it to the people who are going to use it, and they said, what's this? We don't need this. And by the way, I don't want to use that. It took us a whole nother nine months to walk through the people side.

00:04:36:27 - 00:04:45:02
Chris DeRienzo, M.D.
So that is a lesson that you learned exactly once in your career. And it sounds like it's being put to use by your group at HCA.

00:04:45:04 - 00:05:01:24
Randy Fagin, M.D.
Agreed. And as you bring those folks forward, one of the things that we try to make sure we're focusing on is augmentation, not necessarily automation. How do we enhance human decision making, not replace it? Especially in the clinical space, we think that's a very important decision point.

00:05:01:26 - 00:05:33:06
Chris DeRienzo, M.D.
Yeah. There are there's a great article that was in Axios a few months ago that the two editors of Axios wrote together about the impact of AI on their own professional infrastructure. They recommended all leaders ask themselves the question, what are the things that I and my team need to do to be incredibly successful? And then ask the follow up question, how can AI either automate some portion of that so I can focus my human time on a different part that's going to make a big difference?

00:05:33:12 - 00:05:44:11
Chris DeRienzo, M.D.
Do you have some specific examples, Randy, about how you're seeing that put to use and how perhaps those ideas have flown through the governance process and then into action?

00:05:44:13 - 00:06:11:05
Randy Fagin, M.D.
Yeah, there's a few areas that we've addressed. I'd mentioned in the last episode, working towards being able to reduce variance in the way that we staff our nursing units. And it sounds kind of banal, but it's remarkable when you think about the variance in how we staff those based off the individual who's staffing it and the time it takes them to do that.

00:06:11:07 - 00:06:21:18
Randy Fagin, M.D.
It is incredible. And by offloading that burden from them, it allows them to actually lead rather than spend hours of their day managing a schedule.

00:06:21:20 - 00:06:49:16
Chris DeRienzo, M.D.
The staffing example is fascinating because I interviewed Dr. Schlosser two years ago, and, Mike Schlosser, for those who didn't listen to episode one, is one of the HCA leaders who helped drive this technological transformation across the enterprise. And I remember him describing that nursing model in some detail, because the number and degree of variables about weekend option versus not weekend option - Tuesdays and not Fridays.

00:06:49:24 - 00:07:09:14
Chris DeRienzo, M.D.
And for a human to try to manage - your nursing unit can have hundreds of nurses - who you're trying to mix and match in a way that meets personal lives as best as possible with patient and clinical needs. This is exactly the kind of problem that AI is built to solve, because AI find patterns and helps develop the solution, right?

00:07:09:14 - 00:07:38:08
Randy Fagin, M.D.
And on the clinical side too of that, Chris, you know, this isn't just an exercise in how do you staff a nursing unit with the right number of humans for the number of patients that are there? There's the ability as you head further down that road to say what kind of patients are on that unit today on this shift, at this moment? Disease states, resource intensivity, and then try to match that up with a dynamic of nurses who meet those needs.

00:07:38:11 - 00:08:18:11
Randy Fagin, M.D.
You don't want to staff an entire unit with all new grads, nor do you necessarily want an entire unit of all 20 year experience nurses. How do we create the right dynamic of skill sets and experiences to meet the needs of the patients? There's a clinical value in the work that's done beyond just the offloading of that administrative burden from folks. You know, on the offloading administrative burden, I know a lot of folks have been using AI as a vehicle to assist with documentation where physicians, nurses, PAs, whoever, can just talk and patients can just talk, and that information is then aggregated and then put into the medical record in a way that

00:08:18:11 - 00:08:56:02
Randy Fagin, M.D.
it is consumable and it understands nuance. It understands context and it plugs things in regardless of the order in which you ask the questions, it plugs it into your documentation. And the idea of creating a greater level of completeness of our electronic health record has an incredible value to us. I mean, one, - on the on the administrative burden side - it can remove literally hours worth of work of our physicians who need to be entering the information, editing the information, signing off on the information, all of that stuff

00:08:56:02 - 00:09:18:07
Randy Fagin, M.D.
that's just an administrative burden. It literally can offload hours of it. Also, when you think about having a more accurate, complete medical record, the ability to transfer knowledge from shift to shift, and the ability to make clinical decisions based off the complexities of the individual. It's just better for patients. And I really see a value in that space.

00:09:18:12 - 00:09:40:23
Randy Fagin, M.D.
And that's another one that we're exploring and pursuing is we've got an entire cohort of physicians, both ER physicians and hospitalists. We're exploring the cardiac space as well in Texas. That was our pilot area in the Dallas area that have been utilizing this and helping us to learn. How do we allow this to give time back to the doctors, more time at the bedside, less time at the computer?

00:09:40:25 - 00:09:52:17
Randy Fagin, M.D.
At the same time, enhance the information that is able to be transferred shift a shift, and the information that's utilized by each shift for clinical decision making. It's a really exciting space.

00:09:52:19 - 00:10:21:19
Chris DeRienzo, M.D.
Ambient AI, the technology that you're referencing, and there are a variety of companies who are in that space is one reason that when I talk to trainees so folks in medical school or residency or nursing school, I say, folks, you have picked the best possible time to go into medicine or nursing or health care in general, because you and I trained on paper, and we were walking around units with giant charts and and writing orders in triplicate, and then our entire world got electronified.

00:10:21:21 - 00:10:41:03
Chris DeRienzo, M.D.
And in doing so, we pulled people away from face time with patients. And I see the value in all of that structured data. And my background is a CQO as well, on a much smaller scale than you. So I love the fact that we now, thanks to the, the electronicification of health care have all of the structure, data and the metrics.

00:10:41:03 - 00:11:06:29
Chris DeRienzo, M.D.
But my gosh, we transferred such face to face to face to screen time that this ambient technology is giving it back. It really is a way not only to, as you indicated, improve documentation, which has never been anyone's favorite part of their job, but also, improve the experience of our workforce. It is such a crucial thing to focus on while we are in the midst of a workforce crisis that we will never be able to recruit our way out of.

00:11:06:29 - 00:11:08:02
Randy Fagin, M.D.
Completely agree with you, Chris.

00:11:08:04 - 00:11:37:06
Chris DeRienzo, M.D.
I think we've got time for one last question, and I'm just wondering, obviously you all have had a number of successful implementations. You've probably had some that, tried and were cut off. What other, you know, single biggest lesson would you have steering the AI ship at, you know, the, the 190 plus hospital entity that is is HCA health care or folks listening in who are perhaps trying to do the same thing within their own communities.

00:11:37:08 - 00:11:57:13
Randy Fagin, M.D.
I would tell you one of the most important things that folks can do. One - well, there's a couple of things. You asked for one, I'm going to give you more than one. We'll take it. One is, you know, make sure that, you know, if you're the clinical leader trying to use AI to advance care in your space, bring together a team that isn't just clinical.

00:11:57:13 - 00:12:15:24
Randy Fagin, M.D.
You have to have all different lines of sight to really solve these problems. Second, you want to define a single high impact problem that has a low risk, if you don't get it right. You want to make sure that if you fail, you're going to fail safely in this. And then the last thing, don't start with vendor selection.

00:12:16:01 - 00:12:28:12
Randy Fagin, M.D.
You know, that becomes a solution looking for a problem. You need to first identify the problem you're trying to solve, and then identify the solution that best allows you to solve for that.

00:12:28:12 - 00:12:44:23
Chris DeRienzo, M.D.
Wise words, and ones that I think could be applied just as easily in a critical access hospital in Oregon as they can to a multistate system like HCA Dr. Fagan, it is been a privilege. And again, my guess is we'll be asking you back again sometime in the future. Thanks for spending time with us today.

00:12:44:23 - 00:12:46:03
Randy Fagin, M.D.
Chris, an absolute privilege. Anytime.

00:12:46:09 - 00:12:48:24
Chris DeRienzo, M.D.
Thank you. Take care everyone.

00:12:48:27 - 00:12:57:09
Tom Haederle
Thanks for listening to Advancing Health. Please subscribe and rate us five stars on Apple Podcasts, Spotify or wherever you get your podcasts.