In this episode of Elevate Care, hosts Kerry Perez, Nishan Sivathasan, and Liz Cunningham engage in a roundtable discussion about the evolving landscape of healthcare staffing models. They explore the relevance of traditional 13-week assignments, the demand for flexibility among clinicians, and the integration of virtual nursing and AI technologies. The conversation highlights the importance of adapting to workforce preferences and the potential for innovative care teams that leverage technology to enhance patient care and clinician satisfaction.
In this episode of Elevate Care, hosts Kerry Perez, Nishan Sivathasan, and Liz Cunningham engage in a roundtable discussion about the evolving landscape of healthcare staffing models. They explore the relevance of traditional 13-week assignments, the demand for flexibility among clinicians, and the integration of virtual nursing and AI technologies. The conversation highlights the importance of adapting to workforce preferences and the potential for innovative care teams that leverage technology to enhance patient care and clinician satisfaction.
Chapters
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Welcome to Elevate Care. I'm your host, Kerry Perez, and I am joined by two of my favorite people at AMN Healthcare, Nishan Sivathasan and Liz Cunningham. Welcome to the show, fellow Elevate Care hosts. Thank you, Kerry. Thank you. Awesome. We're doing a little bit of a different format, a roundtable. And today we wanted to talk about flexible staffing models and even maybe rethinking traditional 13-week assignments. Let's even talk about the 13-week assignment. Is it still relevant?
Thank
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And why did it exist in the first place?
It's a great topic. You know, I'm a big believer in just revisiting things. I think the 13 week assignment has been out there for, you know, an extended period of time. And as with all things, we should always revisit stuff just based on, you know, new world order, right? So it's likely relevant in some cases, but maybe not all. And so it's about having new tools, options, and flexibilities to meet the workforce where it is. So number one thing I'd start off with is just workforce preferences.
Right. And if you look at recent workforce preference surveys, you can see that folks just want flexibility. Ultimately, if you think about the modern workforce versus prior workforces, I think some of the things you'll often hear from our clients is when, a 10 year person has been in the role for 30, 40 years leaves, I almost have to find one and a half people to fill them. Because you think about work life balance and all these things have just, they're just very different. And.
It's almost like there's an unwritten rule of the rewriting of the social contract here effectively. Right. And so I think it's a unique opportunity for us to explore and revisit these things. And I would say first you start off with the workforce. So what's important to you? What do you want? What do you value? And how do you find workforce models that fit their needs? This component of this gig workforce stuff is really picking up is not directly translatable into healthcare just yet, but what are some
constraints that need to be removed to actually allow that so You know said otherwise I think this is a great opportunity to kind of approach it from a first principles framework So if you were to say hey, what's the what's the problem? What's the job to be done? How do you break it down to its most basic components and then rebuild it up based on what we have today? You could come up some really really cool alternatives
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Well, we're even seeing the differences in the flexible models impact some of the outcomes that Nishan was talking about. So I think right now, average hours worked per clinician is the lowest that it's been in the last 10 years. I think it's like under 35 hours per clinician. And we're also seeing attrition, the lowest it has been, right? So you could say, you know, there's a slight correlation between number of hours worked and, you know, clinician satisfaction and overall retention.
I do think this is just an idea, but right now, the traditional 13 week, you're really committing to that full length of the assignment and you really have to do your time off ahead of time. Yes, it's flexible in the 13 weeks, but within the 13 weeks, it's not flexible. Is there a future world where as float pools become more common space and as more advanced scheduling solutions are out there, where you're maybe committing to 13 weeks or committing to 16 weeks, but you're actually being scheduled within it in a more frequent basis like a float?
clinicians. So you're actually committing to the time, but then you can have flexibility within the schedule. I don't know, that might be a nightmare for some of our clients. But just trying to think about what trends we're seeing that then gives our clinicians flexibility within that commitment that they're making. Yeah, it's an interesting conundrum because, Nishan, as you referenced some of the surveys, it's not just nurses, it's physicians as well as leaders who are all experiencing burnout, thinking about maybe leaving
maybe not the profession, but their role within the next year. And interestingly, all of them said, if I had more flexibility, I might be able to be retained more. So you're seeing it not just within frontline, but also within leadership. So it is something that's pervasive. I think what is kind of maybe a math equation is, hey, how many more people do you need to actually be able to hire when you are going to be having maybe more flexible shifts or shorter shifts?
And does that sort of outweigh what you might be able to, or what you might lose if you don't provide something more flexible? So I think some of the questions in talking with maybe some clients is, hey, they might not necessarily have the infrastructure set up to even be able to think about hiring X percent more people to satisfy the desires of a clinician and their preferences.
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Not really a question there, but if there's any sort of comment. Yeah, mean, to your point, if you are going to have a highly flexible model, you have to have the underlying data to tell you if you're staffing the right amounts of people and that you're not completely bloating your costs, that you're not creating too much headache for your central staffing office, that you have to have the analytics to be able to manage something like that, which is probably why the conversation is happening now, because people have tools in place that can help with some of that.
Five years ago, no way. I mean, that would have been a central staffing office nightmare to try to figure out what that looks like.
Yeah, the only other thing I would add is, you know, we're on the verge of when you onboard a clinician, may, their coworker could be a digital twin or it could be an AI assisted sort of workforce, right? So that's going to unlock a lot of flexibility too, to really use that clinician to their highest and best use. And I think those are going to be really interesting models to see how they unlock flexibility in new, unique, interesting ways. And it could actually
Instead of 13 week, maybe we're talking about a 16, 17, 18 week, right? Could actually alleviate the stress of the role. So you can actually focus more on the patient because some of the other critical thinking tasks, you're really left to the last mile, right? Where you're served up a few decision points as opposed to have to come through all the data and information to figure out how best to triage or treat the patient. I think it's gonna be really cool and interesting. I think when...
Right now when you see AI being used in the workforce, there's two buckets I think about it. One is administrative, and that's where you see the primary uses for. And the second one's gonna be a more clinical workflow. That's we're a ways away from that, but I think once you start to dip your toe into that, it could unlock a whole bunch of really, really cool flexibility opportunities.
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Yeah, you talked about a little bit of the virtual sort of digital twin and you know, we've had a similar conversation last year, but even it feels closer today. Talk to me a little bit more about, you know, maybe do clinicians, have they been expressing maybe more interest in getting involved in sort of virtual nursing? I guess, spoiler alert, it feels like in some recent surveys more and more are.
Have you been seeing any of those same trends?
Yeah, I'll jump in first. Certainly have. think many of our clients are using virtual nursing as a way to alleviate burnout. So if you're by the bedside for X number of weeks, you know, why don't you actually go virtual for a period of time and then we'll put you back by the bedside. So from that standpoint, I think clients as well as clinicians have benefited from it. You're actually finding clinicians remain in the workforce longer when they have that sort of cycle or rotation through it. So I think it's certainly a way of the future.
Yeah, I think our clients though are still figuring out how that fits in their mix of their model. So to Nishan's point, you know, it is an option of a different type of flexible shifts that you can be on, but I haven't seen a ton of clients really nail integrating that virtual nurse workforce into the broader workforce. It's more of an or instead of an and. And then this is kind of random, but just one thought that came to my head as Nishan was talking about, hey,
virtual nursing or AI kind of removing some more of the day-to-day tasks and letting people work maybe more to the top of their license or something like that. You know, what's interesting to me is the locum space has never had a defined assignment length, ever. There are ER doctors that pick up a shift a month. There are CRNA clinicians that get told they're working somewhere for six months, but only get their schedule at the beginning of every single week. They don't actually know the shifts they're working until that week.
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We have primary care physicians that are assigned to the whole summer to do some coverage. So as we start to maybe have more flexibility and have our clinicians kind of working to that top of license, I don't know, does it look more like a physician's schedule at the end of the day? I don't know, but it's just that locum space, that comparison I thought was something interesting to think about. They don't have a 13-week assignment. Yeah, that is interesting. And also then, how do we think about them as teams, care teams, and not just individuals? I mean,
I don't know what exactly that looks like, but there could be some very interesting ways in which it's not just like the skill fit, but like the cultural fit together. Well, and then add a little robot into the care team, not to go crazy, but what we're seeing in very innovative hospitals is using robotics and AI to actually perform some of the tasks. So I've seen some recent, I won't call them proof of concepts because they're more than that out there that are using robots to check vitals, using robots to go to the pharmacy to collect the
the medication, using robots to do some more of the cleanup within the hospital beds, et cetera. So yeah, I didn't mean to be crazy sci-fi, but yeah, a little robot could be part of mean, robots robots are delivering Uber Eats orders now. That is true. That is true. That is true.
Got robots, drones, everything. Yeah, exactly. You're stuff flying through the hospital.
Nishan, anything on sort of that care team thought?
Speaker 2 (09:31.404)
Yeah, I think just anytime you can introduce new and innovative models, it's it's kind like technology. Once you put it out there, you think it's going to be X and then you put it out there in the world and it ends up being Y. Right. I think giving the workforce optionality is really key. And then you could find some new, really cool discoveries through it too. Right. And if nothing else, you learn something from those models that you can maybe apply to other ones too. But, you know, just fundamentally if I have is.
you know, the peak of human existence is shared experiences with people that you love and you care about. Right. So if there's a way to make more group oriented, right. A care team sort of thing. There could be a deeper connection or meaning in work that you find for some of these folks that, you know, unlocks just something really, really unique and special.
card. know that's great.
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not to keep referencing the surveys, but on the leadership survey, the number one reason why leaders decide to stay is because of their colleagues. So I think that's a fair point.
Yeah, the Gallup, what, Q12, the most important question there was, I have a best friend at work? Right? So hey, maybe there's a way to apply this to some of the stuff that we're doing. That could be really, really interesting.
The other thing you said, Nishan, was just, hey, sometimes you try something, it doesn't work, but it gives you insight into something else. Curious, off the cuff, if there's things that you thought were ahead of its time and it didn't get adopted and maybe we should look into it again, since I asked the question, I'll go first to give you some time to think. But I invested in an AR, VR company, because I was like, this is going to be it. Obviously, Metta, they thought we're all going to be living in this world.
But there did seem to be some cool applications of being able to train people with using VR and maybe have people come and get oriented before. So that's just an example of, didn't really quite have the adoption. Maybe there's still an application in a different way. People love watching movies on that thing. That's the only thing I've heard. Yeah. So it might not be, but I don't know if anything comes to mind.
think there are examples all over the place, right? So one of the things, I'm a big whoop user. So I've got my whoop. think some of y'all have an Auraring or whatever it might be, right? There's Apple watches, but those are just new, interesting biometrics. And honestly, sometimes it's data overload, right? I'll look at it and I'll overanalyze. And if I know it's going to be bad, I'll just take it off and I won't wear it, right? Because I just don't see the data. But a cool application you're hearing in some cases is some physicians actually say, hey, download your data and send it to me ahead of time, right?
Speaker 2 (12:00.652)
So they're not just measuring your heart rate at that time you're at the hospital, but they're seeing it over a sustained period of time. And you can actually walk them back through the history and some of those pieces. Right. like that, it's ahead of its time because people aren't using it. But, you know, maybe at some point there's a reimbursement code that says, Hey, looked at XYZ or you prescribe some of these things, but, things are always evolving. think, you know, the reality is our, our systems, our structures.
policies don't always evolve at the same rate and pace. It actually reminds me of a book, Thomas Friedman wrote, Thank You For Being Late. And in his book, one of the things he talks about is technology is evolving at a faster rate than humans can actually absorb. And it takes you about seven years. So you think about Airbnb, Uber, some of these newer models, it took about seven years before you saw laws and regulations wrapped around them to fully adopt and extract the full value of them while not.
you know, minimizing the risk and so forth. So when you think about technology, whether it's AI, other things, there's a long arc, right? You're experimenting and everyone's always concerned about the risk, but there's also all sorts of opportunities and possibilities too. And it's just how you thread the needle as you work through that. But recognize where you are on that adoption curve.
And I always believe you either you win or you learn, but you never fail, right? So the key thing is just taking whatever learnings you get and translating it into the next thing that you do.
to Nashan's point about AI. think there's lots of different schools of thought, but I think there is the optimist that, AI is going to take over everything and we really need to start. If you're not leveraging some sort of gen AI solution every day, you're going to get behind. But there's also this more pessimistic reality side of the traditional trend of adoption it takes, like Nashan was mentioning, with seven years, where I think it's like 40 % of adults use AI, gen AI, but only using it for an hour a day.
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So are people just using it to write a love poem to their partner or whatever? It's more novelty versus adoption. So I think there's so much hype around AI right now. It'll be interesting to actually see what the adoption curve looks like versus maybe the hype right now. So that's going to be something interesting for hospitals to try to figure out what's the balance there.
Yeah, no, before I was going to say, you know, one of the things I used to do previously was I'd go to up to new people and just be like, Hey, what are the top five apps on your home screen? Right. And it gave you an indication of what to expect. Like what are the key adoption trends? And now as you both know, I've got three young boys, right? So I look at what they do. Right. So where I would traditionally go to Google for stuff, my 11 year old son goes to chat. Right. And it just.
There's, you know, it used to be called digital natives. Now maybe there's AI natives, but it gives you a glimpse into maybe how society will start to use these things in the future. Right. And influence how we think about embedding them into our day-to-day world.
I feel so boring. What are the top five apps on your home screen? Well, chat GPT is certainly one of them. I am now like your 11 year old son. If I do need to Google something like, well, this is going to be a lot easier and also give me some insight. Yeah. Right. Yeah. I guess I use copilot. I'm the more corporate. Yeah. The corporate galley is on my home screen.
I use it for real, you know, real like planning vacations, all that. Well, we might've lost the plot towards the end of this conversation, but you know what? We're trying out a little bit of a different format of having more of a dialogue. I found it to be insightful and organic and hopefully educational entertaining for some of our listeners as well. Anything else to sort of round out? We started with 13 week. Is that the right model to innovation in healthcare and trends of 11 year old sons? But.
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I think we were able to cover a good gamut here. And anything else you want to end with? Should we make an over under bet? It sounds like Nishan thinks we're going to go over 13 weeks, and I think we're going to go under 13. So let's see what happens in a year from now. Very good. Well, you'll have to let us know afterwards what's on the line for whoever wins. All right. Thanks, everybody, for joining us on Elevate Care. Nishan and Liz, thank you, too. Thank you. Take care. Thank you for joining us today on Elevate Care. If you found this episode valuable,
I'm down with that. I like that.
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