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- 01:41 - How have Healthcare Organizations Evolved due to COVID?
- 05:03 - Changes and Adaptions to Deal with Challenges of Staffing Shortages
- 10:31 - The Changing Role of Technology in Healthcare
- 19:53 - How to Better Utilize Internal Staff and Resources
- 29:28 - How Data helps to Predict and Forecast Scheduling Demands
- 49:40 - Q&As
Nick: Well, welcome everybody. My name is Nick Thomas. I'm an associate Editor on the finance team at Becker's Healthcare. Welcome to today's Webinar, a very topical subject, reducing your reliance on costly staffing agencies. And on behalf of everybody here at Beckers, thank you very much for joining us. Before I hand it over to the panel, I'm just going to walk through a couple of very quick housekeeping instructions. The way this will work is we'll have a presentation for approximately 45 minutes, and at the end of the last 15 minutes or so, we will have time for a Q and A session. You can submit any questions you have throughout the Webinar by typing them into the Q and A box you see on the right of your screen there. Today's session is being recorded. It will be available after the event, and you can use the same link you use to log into today's Webinar to access that recording. If you should have any trouble with the audio-video feed during the presentation, please try refreshing your browser. If that doesn't work, you can, by all means, submit technical questions into that same Q and A box, and we'll try and help you out. So, with all that said, I’m very pleased to announce today's presenters. We have Nanne Finis. She is the Chief Nurse Executive at UKG. Michael Hasselberg, the Chief Digital Health Officer from the University of Rochester Medical Center, and Tom Ross, Chief Executive Officer of Andgo Systems, who are sponsoring today's Webinar. So thank you all for being here today. And with that, I will turn the call over to Tom.
Tom: Right on. Well, thank you, Nick. And thanks to everyone for choosing to spend your time with us today. It is greatly appreciated. And so onto the topic, very topical, as Nick mentioned, reducing reliance on staffing agencies. And I think what would be helpful here is just to get a little bit more context and background about how we evolved to this point as an industry. And I know, Michael, in our conversations, you provided that breakdown of all the steps that you took there, and I think that would be fantastic for the group to hear here before we kind of dive into specific strategies. So, Michael, over to you to give that overview.
Michael: Yeah, thanks, Tom, and really excited to talk about this kind of timely issue. When I think about the staffing crisis, I look at it in kind of the totality of what’s happened during COVID and how we got here, which then better understand the problem and that can help us kind of figure out the potential solutions. And when that dreaded day happened three years ago in March and COVID hit our community, the first thing we did as a health system, which I suspect every health system in the country did, was like we shut down. We didn't want patients coming into our hospital or our clinical service lines. And our big focus on technology was the patient at that period of time. How do we create more access for our patients and keep them engaged without actually stepping foot within our hospital walls or clinics? And as a health system, we invested a ton of resources not only in just like telehealth but like the digital front door in general, of creating access and getting our patient portal penetration up. Our patient portal penetration at the beginning of COVID was like 30%, we quickly got it up to like 90%, and several things then kind of happened. COVID lasted, and it's still happening much longer than we expected. And our frontline staff started getting sick and exposed themselves and just getting even further, kind of stretched thin and burnt out. But all that work we did to create access and engagement for our patients created more touch points for our clinicians and providers that weren't there prior. And now, our patients have a lot more direct access to our clinicians and providers through SMS texting and messages through the EHR beyond those traditional methods. And now we've got a current situation where we have a burnt-out workforce who is, in some areas looking to leave the healthcare vertical altogether. Those left are getting inundated now even more with messages from patients, and they’re really feeling overwhelmed, and that's what we are seeing in our health system.
Tom: Yeah, absolutely. I appreciate that distinct overview of where it is and picking out a couple of themes that you mentioned, Michael. Around this transition happened, it changed the way you thought about work in terms of access points, particularly as it wore on. The impact on staff, particularly as they got ill, they covered staff, their hours increased, they had burnout, and then led to this point where they're perhaps leaving the profession on mass or just stepping back for a time of period, which has introduced this, well, we need folks. We need folks to carry out this work. And so if we don't have them internally, we have to turn to these external agencies, and the costs there are two, three, four times as much. And so you see the outcomes of those kinds of events resulting in the state where we just saw Beckers here report the top 20 organizations agency spent was cumulatively over $9 billion in 2022, which is incredible for the wrong reasons. It comes down to this theme of time, right? Kind of looking at this analysis of time, if we don’t have people here to do the work, we need to bring people in, or we need to find ways to enable our teams to be able to do more with less. And then that's something that's been sort of said quite a bit. And so when we focus on time, what’s interesting in our conversations is that there are many ways to look at this. It's a very important one, of course, time savings. The other one is who's carrying out these tasks. And Nanne, I'll kind of turn it over to you here just as far as sharing some of the changes and adaptations you've seen in your organizations that you're working with, as far as, like, rethinking that team composition and how that helped folks and organizations deal with this challenge.
Nanne: Thanks, Tom and Michael, I love your points and maybe taking off from where you just shared. Our most precious resources in all of our organizations are our people. And as you talk about burnout and the stress and anxiety levels, I can't start kind of talking about the team without reflecting on the perspective of work has changed, has changed in all of our lives, has changed in our employees' lives where they’re really looking for life-work balance. Not work-life balance, but life-work balance. We talked about that often at UKG meetings, that work has to fit into a changing life that so many of us have experienced. So Tom and I were talking earlier about teams, and for those of us who perhaps grew up in team environments, and I did, working in the emergency department for many years. Many of my best recollections of practice were with teams of physicians and nurses and advanced practice nurses and respiratory therapists, and all of the allied health team members. So I think as we look at the situation that many of our hospitals particularly are facing, and this goes really for all care settings, patients are more complex, and patients' expectations are more complex. And then, we have the employee situation that we briefly shared. How do you really think about that team composition? The focus really has to be on the team, the right team, serving and caring for the right patient at the right time. And so that is a challenging dynamic to put into place right now. We at UKG and I know you know this, Michael and Tom probably can't do this in the future in its complexity without some technological support. And what we're looking at nationally is there aren't enough registered nurses perhaps to go around and to really fulfill the needs as we know them today for the future. And the same thing goes for physicians. So what are the tasks that our nurses are doing? Some estimates are that 46% of nursing work doesn't need an RN license to perform. And I think there are some corollary statistics with physicians. So when you think about that, I think many of our customers and others are looking at that team composition to say, how can we really make sure that the tasks that we're asking our staff, our precious resources to do in their busy work life are demanding their capability, their competency, their skill level? And then how do we streamline that work on top of that, to make sure that we are at all costs giving back time so that these caregivers can give that precious time to the patients and their families for which we're there for? So, Tom, I hope that's kind of a summary of some of the challenges. I was trying to be focused, but it is a broad conversation, as I know the three of us have shared.
Tom: Totally, and it certainly makes sense. And I think what just sort of that concept here that we've sort of talked about with regards to time and I guess, you know, focusing on, like, who's conducting these tasks and perhaps challenging and rethinking, you know, that composition of does it need to be this individual? Does it need to be this title? Are there opportunities to introduce other folks to help contribute so that these bottlenecks that we’re seeing along the way, how do we increase the size of that bottleneck? Or perhaps how do we reroute a route around it? As far as other things? Nanne, you mentioned something there that I want to pick up on, just this concept of giving time back. And I think this kind of leads us into that next concept of time. And I know, Michael, the work that you've done and we've talked about as far as ways to both assess and look at and evaluate where time is being spent and how can you give time back to the folks as they're working. I know one of the concepts you mentioned, Michael, was the digital front door, and I would love to hear kind of you explain that concept for our audience and for Nanne and myself, and the work that you're doing on that front.
Michael: Yeah, the way we conceive our digital front door is in several buckets. It's all based around the digital patient portal, which for us is our patient portal of our electronic health record. And that's kind of where we want our patients going to receive information about their care and education. And from that patient portal, we really focused on standing up, online scheduling. That wasn't something pre-pandemic that we had, but that was a big priority for us. From there, we needed to digitalize that check-in process, all of those forms and those questionnaires and insurance information that we had frontend staff collecting at the beginning of appointments. Like, how can we collect all of that before the patient ever arrives to their appointments on their own device, and then if they don't have the technology to do it at home, can we create almost like what you have at the airlines, a Kiosk station where I can do my full check-in right there. From there, our front door actually pivoted back to telemedicine. And when I say pivoted back, every health system in the country, we had to turn on telemedicine in a week. And we did that, and we did a good job, but where we didn't do a good job was like on-demand telemedicine and like kind of urgent care. Like, I need to see somebody right now. We didn't have that capability. So we stood up on demand telemedicine, and then the end of our digital front door is that kind of express pay, how can I just pay my bill with a click of a button versus getting a sense? So that was essentially our digital front door in terms of time. Some of the things that we've seen benefit-wise is, for example, the e-checking process has saved us, on average, about four minutes per patient than the regular check-in process, which then creates more opportunities and more time for our patients to engage. I think one of the biggest struggles we had was culture change. I think folks, specifically the frontend staff, were nervous, am I going to not have a job anymore? If we use kiosks and online scheduling and check-in and we reassure them that that absolutely was not the case, we just re-skilled them and repurposed them into other positions within our system. In most cases, folks felt actually increased self-worth or value because, in a lot of ways, we connected them to maybe you're the person that kind of sets up that video conferencing experience with the patient before they launch with the provider. And so even kind of a more direct connection to that patient care experience, which then kind of what Nanne was getting to, started to take some of the low scopes of work stuff off of our clinicians, like our nurses and our physicians, which then again, created more time.
Tom: Yeah, interesting. A couple of things I've heard as far as you add these tools, you add these processes, and yes, they certainly improve things, but they leave a little bit at the end. There's a little bit at the end that needs this manual input or interaction. And then as you sort of accumulate and add a second program and a third program and a fourth program, and now you're driving these efficiencies on one end, but then you're left with this little piece there. And so, who's doing that? I think that kind of ties back nicely to Nanne's point about team composition. It perhaps doesn't have to be the RN. The clinician doesn't need to set up the telehealth appointments. There can be other individuals that perhaps are repurposed. And there's also something too about you talk about staff satisfaction of quality of work and work tasks and kind of processing forms and stuff is one thing. And so if that busy work or non-value add work, perhaps as it is sometimes considered, is eliminated from their workday and then repurposed into these other higher value-added activities, there's greater satisfaction which ultimately just leads to a more positive workplace. And so, Nanne, I'd love to kind of hear your perspective in terms of giving time back, particularly on that scheduling side of things, which you're certainly the expert on the call here about and what sort of that looks like in your experience and what you found that has been impactful during this time.
Nanne: Yeah, such a challenging period. And if you don't mind, I'll just reflect on a couple of things, Tom, that Michael said. I think that front door, that access that digital experience for care providers as well as patients and their families, as you've described, I think that's a journey that we're continuing to navigate. I think we're facing this period where we do know that face-to-face communication can never take place or technology really can never take the place of face-to-face communication and where to make sure that's inserted into that relationship, whether it’s the care provider, nurse, physician, patient or a patient administrator. I think there's just a lot of work going on there to say what's the right match. And what we're seeing is as we think about the patient in our sort of care model, as I'm thinking about it here, Tom, so many of us in our backgrounds and currently touch that patient in very different ways. How do we staff and schedule our own resources so that we are touching virtually or in person that patient at the right time and with the right skills? And we had talked about this a couple of weeks ago. We're seeing a lot of different models of care delivery that I think there's a lot of, if you will, experimentation going on with rigor and science to say what is the best approach to useless physical resources at the right time but have the right impact and obviously promote best patient outcomes. So what we're seeing is, like you talked about, Michael, with telehealth, telenurses, or virtual nurses as an example. There's now quite a bit of literature that's being demonstrated in some of these experimental models where nurses are virtually positioning themselves in partnership with inpatient nurses, typically on med surge floors right now. And we're seeing some demonstrated decrease of discharge times 20 minutes or so a patient. And we're seeing different data come in where the nurse who is virtually working can support that in-person nurse to document discharge, to make sure the patient and the family are educated well, some of that can be done virtually. And these are nurses that have organized their approach so that they're engaging with that family and patient so that there is a trusted advisor, if you will, on the other side of that virtual camera. So we are seeing pairing up virtual and in-person models that seem to be, and there are many different examples of this, but this is just one, I think that's quite prevalent as being tested across the country in very many regards.
Tom: Yeah, that's really interesting. You think of this care as a linear process delivered at one person at one point in one sort of medium. But this concept of, like, well, what if we were to separate that out and be able to provide that? That sort of again creates this idea of giving time back or looking at bringing in additional resources, accessibility to provide those specific care requirements at different times through different mediums and ultimately still leading in a positive patient experience because they can perhaps spend more time with these folks virtually discussing through the care and requirements on that front. That certainly makes sense. One of the things again, kind of going back to this main theme, and we talked about time, we talked about team composition, we talked about giving time back and looking at a kind of like dissecting what all the different places and areas in which work goes and how you start layering these concepts, team composition and giving time back. Michael, hearing you talk about some of the concerns that staff had, I think, is quite natural. And often, I think culturally, there's this viewpoint that it's an either-or situation. What I mean is it's either technology 100%, technology 100% sort of AI, which we'll talk about a bit later, or it's 100% human doing the work. And in reality, the future and the evolution of work is going to be that combination. It's going to be that combination of this enabling folks and people to do more work. And for anyone who is concerned about job security with AI and stuff in healthcare, the topic of this thing is the staffing crisis, right? There is a shortage here that we need to find ways to optimize and get more productivity out of the members that we do have. And eliminating some of this busy work or value that software can do certainly is an opportunity while elevating sort of that care requirement. One of the ones to talk about in my experience around time is what I refer to as this category of time utilization. And what I mean by that is what are you getting from the utilization standpoint of different folks within your organization? The problem that we sort of acutely deal with is around same-day staffing and finding folks to fill those vacancies that pop up, which is a surprisingly hard problem to solve, and it's really different from your schedule. Your schedule is your plan set ahead of time, but then a day off occurs, and all these changes happen. And so when you peel back the layers, it's surprisingly manual how organizations manage tracking and reporting of these sick calls and updating and finding fulfilling the subsequent absences or vacancies. And so the work that we're doing, we’ve kind of recognized that there are groups and segments within the workforce that are frankly being underutilized, and part of it is due to just the rigidity of scheduling practices within healthcare. And what I mean by that is you think of twelve-hour rotations or eight-hour rotations, and if you want to pick up a shift, those are your choices. You can take it or leave it. And you combine that with the factor that the average nurse age in the US is around 52 years old. And so some of these folks that are perhaps nearing retirement, the prospect of picking up a twelve-hour shift, let alone a twelve-hour night shift, is not appealing at all. And so creating this flexibility in how they engage with the schedule to meet their requirements. Beyond some of this structure, the folks nearing retirement are not the only ones. There are also these other groups around, say, young families, people that have a lot of demands on their time outside of work. And I think Nanne, you said that life-work balance. And so the evolution of the scheduling structure hasn't really catered to what you see here. Folks like we've all certainly heard and are familiarize with the gig economy. I think what's important to notice is that that's how one segment of our workforce population prefers to work, right, that isn't reflective of all. But having a scheduling practice flexible enough to be able to accommodate the scheduling preferences of different segments can help gain better utilization. So if you have these groups, these nearing retirement, or these young parents, perhaps, and if you can then create a process that's flexible enough for them to express interest in part of the shift, half of the shift, and what it does is ultimately, as an operator, you're going to say, listen, if we can fill the shift to 12 hours, great. But barring that, which we've kind of come to see a lot of, like, well, now maybe we find someone who can work 4 hours, and we have to find another person who's able to work another 4 hours. So now you can start kind of connecting the dots from a coverage standpoint, giving you that optionality, which is a key piece to reducing that reliance on that agency. And again, I think we're all very well aware this isn't a silver bullet solution that will solve everything, but we're talking about how we're giving time back. We're rethinking composition. We're looking at segments of our workforce and how to get more from them and making it more appealing for them. And the last group I'll sort of mention is like that part-time and casual staff on how you can enable them to perhaps we have that gig economy on the one side, which is that responsive needs I want to work at this moment and so let's go find a shift, and so accommodating them. But there are the other folks that are like, I’d like to have some certainty in the future. And so waiting by the phone every day to pick up the shifts is perhaps maybe not the best and sort of giving them that optionality, that self-service to go into the future there. And I'd love to, MMichael, hear a little bit of your thoughts just on sort of staff utilization and perhaps what you found. I know you've done kind of a lot of work, and if you've found some areas and how to connect and leverage your existing team members in a way that worked for them, I'd love to kind of hear your thoughts there.
Michael: Yeah, I think I'll start on the kind of provider side. The few of the areas that we are just hammered right now, and we are having a lot of trouble with a burnout on the provider side, is in the emergency departments, our urgent care centers, and even primary care. And we're trying to be thoughtful around that flexibility, and some of that work doesn't actually have to happen in a brick-and-mortar setting. And so that on-demand telemedicine service line that I was telling you about and why it was so important is it's helping us with recruitment and retention because we’re no longer just focused on you're going to get hired for 40 hours a week, and you have to physically be in the emergency department. We're saying like, hey, 2 hours a week, you can help serve our on-demand service line, which, again, actually can serve as a triage point for the ED and handles a lot of our urgent care volume and our primary care volume. And you can do that from home, and then three days a week, we really need you at the ED. And that has been really helpful for us for recruitment and retention of us as a system, being willing to have that flexibility with our clinicians. And they love it. They love it. Like you said, not everyone wants to work fully remote, and not everyone wants to work on-site all the time. And be able to have that hybrid opportunity has been a huge win for us. Around kind of the scheduling and the way I described this, especially during the first two surges of COVID, was kind of creating that bench that we knew, like if we had holes over here, who could we move to fill those holes? I'm going to tell you, and we have this discussion straight up. We couldn't do it using our current systems because our data that would allow us to do that was in a lot of different places. So like, which nurses or which providers have privileges to do certain things like working in the ICU versus working in just a general Med surge unit? Who could take these insurances on or not take those insurances on? All of that information was in-house in different silos. And so for us, we couldn't just take an out-of-the-box scheduling technology to help us solve that problem. We actually had to build our own kind of scheduling, create your bench technology in-house, and break those silos down in order to do that. But again, those weren't things that we were worried about prior to the pandemic. And I think that I'll turn it back to you, Tom. It'll be a nice segue into future technology and AI where the potential opportunities are, but also where we should be hold off and actually kind of think through a critical lens. Is our data in the right place to be successful with some of those tools?
Tom: Totally. No, I think I think that's absolutely fantastic, Michael. And yeah, the concept of building a bench and then recognizing data wasn't in one nice location that you could just go and look at and see it really required a lot of foresight and will, and nothing like a good crisis to kind of create that motivation to get those things in place. So I know Nanne about the scheduling side of things, right and sort of your world as far as where this sort of comes from and leads to as far as staff utilization, giving time back again here. I'd love to kind of hear some of your thoughts on this as well.
Nanne: Yeah. Thanks, Tom. And I just kind of reflect on just a few things. New staff coming into organizations are looking for digitally mature organizations to work with. So from a recruitment perspective, Michael, they are looking for organizations like yours that are really considering how to use technology at all levels going forward. They are also looking for flexibility in their work and in their life and that balance, as I shared earlier. So we, obviously at UKG and Michael, I know you'll be experiencing this soon, but we offer self-scheduling on a mobile device so that there's visibility to anything you would need to know as a care provider in the palm of your hand. But the important piece is that this really has to match the use of our resources because we have so few, and we'll continue to have less and less of each type of provider if you will. This has to match the patient need or the demand part of the equation in our organizations. And that's also a real challenge is, do you have visibility to what's happening across your organization or your system of hospitals? How have you scheduled staff accordingly to really begin to align that forecasted demand to the patient, to the staff availability? So when you think about two-hour shifts and four-hour shifts, and you mentioned this earlier, Michael, is it really meeting the needs of care you're trying to deliver? And how do you forecast that based on the history and what you are experiencing in your own world? So I think scheduling is an art, it's not a science. But as you mentioned, Tom, flexibility, meeting the demands of patients particularly and the care needs and making sure that we're not sort of inserting potential patient risk by being so flexible. That our patients and their families aren’t suffering from that. So it's a really fine balance that I think we’ll be taking a lot of attention to look at over the next several months in many of our organizations.
Tom: Totally kind of like it's a nice segue here to kind of Michael's other point. This is sort of that fourth pillar when we think of the concept of time and what we’ve touched on around team composition, giving time back, team utilization, finding those pockets and understanding why and how to engage them more effectively. This last one is being able to predict it, being able to forecast time needs, what are we actually looking at, and what does tomorrow look like? And, of course, those real-time visibilities. But I know, Nanne, you were also mentioning just some of the, frankly, limitations that we currently are dealing with as an industry in a sort of, you know, what those nurse requirements are, what the patient acuity care requirements are, and how it's not really a one size fits all. There are a lot of nuances there and a lot of variances within some of these tools. And I would love to kind of hear your thoughts on that aspect and ideas on improvement.
Nanne: Sure. And Michael, I'll be interested in your perspective as you hear this, but we're promoting soon. Not promoting but distributing a white paper where I really led the charge of looking at practices across the country and did a pretty extensive review of the literature. And I would say there is no standard way to look at the nursing intensity and workload for a patient. We look at patient acuity, the EMRs of record certainly will look at the tasks, the physician orders, and perhaps nurse orders and calculate a raw score that becomes the acuity score for a patient. But nowhere is there a standard approach to look at the time of some of the additional nursing tasks. For instance, as I spoke earlier, teaching, educating, emotional support, and feeding a patient things that aren’t captured in a discrete order set. And so when we look at how to staff appropriately, we have to take into consideration what's happening at the patient level. And we're really, I think, being quite bold to say it really does take sort of a three-pronged approach. One, as we've mentioned, the EMR looking at technically the orders for what that patient is requiring, what time does that take, then look at certainly the skills and tasks of nursing that I mentioned that might not be captured in that order set, but also to really look and to incorporate nursing judgment. We've all had patients that might be a low raw score as far as acuity that really takes an inordinate amount of time because we're translating a different language or getting to learn their parameters for what they're going to need at home, or they have food insecurity at home. We're trying to work through that issue. So it's really a three-pronged approach. And I think in the future, we will be able to look at that in one technology source of data. But now I think we really need to spend time to look at what is the workload that each patient does require of nursing before we start to kind of model this out house-wide, so that's just a thought that we’ve been having and something that we're publishing soon Tom.
Tom: Yeah, I certainly love that. And that's like this idea of data, right, this idea of data, getting data, labeling data. And I know, Michael, the work that you've done is fascinating, just as far as how you've approached this. And it kind of leads into this sort of this segue into forecasting tools and understanding the prerequisites to get to the point that, Michael, you and your organization have certainly made incredible strides at and would love to kind of hear your thoughts on processes and things that have worked for you from a data gathering, data labeling standpoint. It's one thing to have it, it's one thing to have it in the right form, and it’s pretty interesting the work that you've been doing here.
Michael: Yeah, thanks. Tom. Yeah. I love data. And actually, to get back to your point, Nanne, I think the problem that we're going to have and why we can’t get to the level of kind of labeling, that same kind of analogy of acuity over to the nurses. And what the nurses do is because that data has so much noise in it, so much of it's missing, and it's not kind of systematically collected. And what happened during the COVID actually, I think, exacerbated that because now we have nurses working in places and on units that they potentially are typically not comfortable with, and so their documentation into the EHR is going to be different than that nurse that is on that unit all the time and vice versa. When we had all the traveling nurses come in who were brand new to not only the system but the EHR, the data coming in from the traveling nursing agencies weren't kind of systematically coming in. And that's where before we can look at artificial intelligence as being like the silver bullet to fixing this problem, I think there's promise there. I do think AI and machine learning is going to really help us take a big leap forward. It's actually cleaning the data going in and making sure that it's properly labeled and it’s being systematically collected, and there are opportunities today to leverage technology to clean that data and so we can get to a place to predict. And it is things like machine learning technologies. So one of the areas in healthcare where machine learning has done really well is computer vision because image data is pretty consistent versus language data that you would find in the EHR. And so you can take cameras and IoT devices that are already in the hospital and kind of capture some of those things that nurses are documenting. So, for example, a nurse in the OR needs to document when did everybody in that room wash their hands, when did the patient roll into that, or when did the surgeon do the first cut? Like, we have a nurse at a computer doing that documentation. Now, when you have traveling nurses coming in, it’s not going in consistently, but at the same time, do we really need a nurse doing that? And is that what our nurses wanted to go to nursing school for those cameras in the OR? We've got technology today that can capture that. The camera can pick up, hey, hand washing is happening right now and can document that right into the EHR. Patient rolled in, document it. Cut happened, document it. That technology is here already. And now that is systematically putting that data into the EHR, which gets us to a point where we can start measuring things like the acuity analogy you had and start kind of predicting. And that's what really excites me off, again, kind of standardizing and cleaning that data on the same thing, less so on the voice recognition. It gets back to what you were describing about as like the telenurses kind of coming in and supporting the nurses on the ground. Those types of services can also be leveraged to, again, clean your data. And so it helps those cameras and those IoT sensors better train their models. For example, we're seeing nurses going into the room and putting an IV in or doing a blood draw on a certain arm. And when they're in, they're talking to that nurse in the sky and actually saying, I'm putting this gauge needle into this arm and this IV. And that nurse is essentially labeling what the cameras are catching. And so the next time around now, the camera scan picked up was the left arm, potentially this size needle and doing that documentation. And that's how those models get better. So we can predict, I would argue, to health systems now, and I see this happen a lot. There are a lot of AI vendors out there, a lot of people moving into the machine learning space who say, I can solve your staffing problem for you. I've got the solution to kind of predict who you're going to need when you're going to need it, and match them to the right patient at the right time and in the right place. I would argue that they probably don’t. And the reason is because if your health system is anything like my health system, the data that we have is not in a good place for those models to work. And so garbage data going in, you're going to have garbage data going out the back side of those models. We really need to be focusing on where the opportunities are to better collect our data, label it so we can do those cool things in the future.
Tom: Yeah, that's kind of understanding the difference between what's possible and all those things. I can't help but get excited listening to you talk about the things that you're doing in your organization. Like, it's incredible. And then it's like, hey, let's move forward with it. But I’d like sort of your kind of like warning there or kind of sign of caution is yes, this is what's possible when you sort of have the prerequisites and put in the work and have the systems to understand to get to that. And even then, it's not a linear journey, it zigzags. There are some bumps along the way, and you're kind of constantly refining, and I guess that's ultimately kind of that. Yes, there are these amazing things that are happening, and they certainly create an immense amount of value. There are a number of prerequisites required before you even get to the point where you can start to actualize and realize that. And I just love to kind of hear some of your thoughts on those early days at going back to what Rochester was able to do at the beginning of the pandemic and understanding in terms of building the bench. Right, like bringing in data, being able to label it. And now you've done the first ten steps. Now 11, 12 and 13 is now possible because you've done that work, whereas someone aspirationally, maybe an organization, is a bit kind of on a different spot in their journey. Step 13 isn't a reality until they get there. And I think that's sort of just that pragmatic approach of understanding where these organizations are in that journey and encouraging them.
Michael: Yeah, again, having an enterprise data warehouse or at least starting that journey to develop an enterprise data warehouse is, I think, going to be critical for any organization to be successful going forward. Now, data is also kind of a catch-22, right? So as a nurse myself who's out there in the field, I would argue, I don't need any more data, stop giving me more data. I need insights. Right. And so we also have to be really thoughtful about how we package that data and how we present it back to our clinicians and our providers. And we have to make it meaningful. And again, to get there, you have to understand your data. You have to set up that data governance. You have to do the dirty work of cleaning your data, aggregating that data, creating the data dictionary, that's the hard work. Creating the model and running the model in a lot of ways. That's the easy side of the equation. So I would encourage health systems really kind of roll up those sleeves and really start breaking down your data silos and understanding where the opportunities and where the gaps are that will really set you up for success in the future.
Tom: We talk about these organizations, and I know just in the space, the amount of amalgamation that has occurred. And you're bringing these large organizations together. In our line of work, like finding common ground, commonality on standardizing definitions of what overtime is, what seniority is and how it's calculated, and recognizing these are sort of those prerequisites around standardization that then can lead to automation, which then creates these data warehouses that can be labeled. And all that hard work until you get there. I guess the one thing to leave folks with is that there is value realized at every step of the journey, right? It's not something that's only realized at the end. And getting down here is going to provide a lot of benefits. So I can't believe we're already up on time. Before we kind of move on to questions, I just kind of like to hear some final thoughts. Nanne, I'll start with you on the subject.
Nanne: Sure. Thanks Tom, and I love the conversation. And I think we are right on for what I see happening across the country, data silos are so challenging. I was listening to a chief nursing officer of a large, large system this morning, and she was giving the example of we have patient experience data here and quality safety data here. We don't merge the two. We're starting to look at that. And so when you think about even our work with productivity is data, the 24 hours census, if you will drive staffing numbers, and yet there's so much in and out of our patient beds every day, we're not capturing that sort of workload as it occurs. So maybe in the ADT system, the Admission Discharge Transfer system, we're capturing all of that volume, and then we have staffing and productivity data in another silo. I think in UKG, and probably most vendors, are really looking at how do we open up our data sources so that it is consumable by organizations so that they can use the data. I know this is our plan, is that organizations can use all of our workforce data and bring that together with quality safety and other data so that you can get, as leaders, a real view of how does workforce labor really impact quality, safety and financial. So just, that's probably a real takeaway is we are on the cusp of obviously all of us doing that. And I think the industry at large is meeting that, as you described, Michael, so very much right now.
Tom: Yeah, awesome. Thanks Nanne and Michael, love to hear your thoughts here.
Michael: The healthcare industry is in a scary place right now, but an exciting place, I think, at the same time, scary in the sense that the staffing crisis, the labor costs that continue to rise, is not sustainable. The old way of doing things is not working, and there's an opportunity there. We have to change, we have to pivot, and we have to start thinking differently. And I see that as an excitement for the future of healthcare, where I think it will be a better place for the patients and the clinicians. On the other side, again, my take home is culture change is hard. You have to start that process early, knowing that healthcare has to change for everyone, the patient, the health system and the clinicians, to win. So start that now. And as Nanne said, why some of these retailers do really well when you go on e-commerce, and it can predict like what you want to purchase before you even think you want to purchase it, and it pops up on your screen. The only way they've been successful doing that is because of data and investing in data and organizing data. And if we want to get there as a health system or an industry in general, we need to make that investment on the data side. That is not an area, especially in these financial crisis times, that you should be, as a system leader, cutting your resources. If anything, you should be, in my opinion, pouring more financial resources into your data and digital transformation.
Tom: Awesome. Right on. Well, thank you for this. I know we got ten minutes left, and I just flipped it over to Nick. As far as I see some questions out there, we can answer as many as we can in the time we have left.
Nick: Thank you, Tom, and thank you, Michael and Nanne, for a great presentation. So we're going to begin the Q and A session. We got a lot of great questions that came in right at the end of the presentation, and we'll try and get to as many as we can in the next final ten minutes or so. And feel free to put in more questions if you like. We can't guarantee we'll get to all of them, but you can always follow up with the panelists afterwards. So, first question, maybe direct this to Tom. And I know you talked about it because I remember you addressing this, but could you give a specific example of where you've seen an organization actually able to “give nurses time back”?
Tom: Yeah, great question. So there are two ones, very simple, and I’m going to focus on staffing and don't dismiss them because they're so simple, but when you look at that staffing process, there are two areas. One is how does your organization receive employee sick calls? So if an employee’s ill and needed to come into work, how are they notifying the organization? And some of them have a centralized number, some of them have kind of an online portion. But shockingly, a lot of organizations rely on the employee to call in. And now, who are they calling in? Sometimes they're calling into that nurse manager. And then, that nurse manager needs to check the message, needs to answer the call, needs to update the schedule. And so that's a thing right there that software can do for you and give that time back to that nurse manager. Now on the other side of that is like once that absence has come in, it needs to be filled. We have nurse managers, one customer prosper we were just chatting with said, yeah, in ED, we have a nurse manager who spends all day trying to fill these shifts because they’re trying to bring people to work. So they're out there texting WhatsApp, messengering, like all these things to come into it. And this is, again, is another thing that that software can do for you. So those two examples around staffing receiving that sick call and then notifying and alerting folks of that subsequent vacancy is something that you can give time back. And so when we look at kind of statistically nurse managers who are responsible for scheduling for their units, that's about two to 3 hours a day. That's significant. That's a significant amount of time that you can put back into the patient side. So I'll leave it there. I know there are a lot more good questions, but yeah, those are kind of two specific areas, I would say.
Nick: Great, thank you. And Michael, again, I know you brought this up, and you specifically talked about the digital front door project during the presentation. But if you could specify one thing that's delivered the biggest return or impact with that, that you’ve noticed.
Michael: By far, the on-demand telemedicine it was a huge win for our patients. They love it. They love the convenience and the ease, and they can still get the same high-quality care that they're getting in person through it. And it was a huge win for our clinicians. They love it. They love the flexibility of being able to work from home and deliver the same care they would have done in that urgent care clinic, in that primary care clinic, from the comfort of their homes on those days. So by far, that was the biggest win for us.
Nick: Great. And I think this is a really interesting question, personally. Obviously, staffing agencies have really raised the cost of labor. The alternative, of course, is then spending large amounts of money on technology to try and reduce the reliance on that. So how can you do the two? How can you reduce the reliance on costly staff games without then spending enormous amounts of money on technology to do so? Who wants to take that one?
Michael: I could take a first stab. I think you have to be savvy enough to understand what the technology can and can't do. So I'll give you a really good example of a technology that, as a system, we invested into that really helps save time and staffing on our nurses. So in our health system, if a patient was at a fall risk, pre-COVID times, you literally put a nurse or an aide sitting next to that bed with that patient, which, again, is totally not sustainable. Telehealth comes in, and now you can have a telenurse looking at, let's say, nine rooms and watching the patients on camera. And if a patient is at risk for falling, can call to the nurse on the floor to go see it. Now let's take it even a further level. So now apply computer vision into that telenurse program. And now you can have one nurse seeing 200 rooms. The computer is identifying when the patient is at risk for falling behaviors. That nurse can then hone in on that one specific video in that room and then call the nurse on the floor to go see. So that's an example of understanding the technology and where the benefits are. And that was a huge win and freed up a lot of our sitter time of our nurses and made us more efficient use of the nurses that we have.
Nanne: Great. And if it's okay, Tom, just to add just a point here to that, Michael, you asked how to really contemplate reducing agency costs with technology or without technology. And I don't think there's a way to do this challenging scheduling without technology in the future as we really aim to be much more flexible for each of the staff that we employ. So what we're seeing is, number one, listening to your own staff and finding out where there is an opportunity to be more flexible. We're seeing quite a number of organizations that have developed their own internal agency across hospitals, across the system, across the geography, paying perhaps a different level of compensation and using those staff to travel, if you will, and to float across different settings. Reducing agencies some of them have reduced the cost of contracting agency, external agency to zero. So there are some models that are working, but with that, you have to have visibility of your staffing, your scheduling, where the needs are. And I don't think you can do one versus the other, at least in a process that is sustainable.
Tom: I’ll sort of add some comments there, just pragmatically. You're spending the money on these expensive staffing agencies, and there's no return. Right. Sorry, that's not the right way to say it, but the return expires at the end of the shift, and so it's kind of being a little bit more proactive and directing that money into technology to help, sort of layer that to kind of get more of a ten to one or 20 to one return earn is some of those opportunities to look at in addition to all these other elements. Those are kind of the main areas here that I see, and I know we're coming up on time. And Nick, I'll leave it to you. I don't know if we have time to sneak in one more question or if we need to wrap up.
Nick: Yeah, yeah, let's do one more question. And I think it kind of is a segue from what you're talking about there that Michael talked about the technology and the cameras and being able to actually look at multiple patients at one time. Somebody asked a question about HIPAA laws. Will those laws and other regulations need to be changed prior to allowing camera machine learning to document care that's delivered in the patient area?
Michael: Potentially. It's kind of how, I guess, you set it up. So for us, the nurse that is kind of watching the telesitting cameras is one of our nurses, and so it's our patients. You can in machine learning, and there are ways of building models without actually needing any patient identifiers. In computer vision - and I keep going back to computer vision - it's just one of the more mature areas, at least in healthcare, from machine learning. And in that type of modeling, the HIPAA concerns depends on the use case. It may not actually be relevant because you can build models without needing any PHI to do it.
Nick: Okay, all right, well, maybe we should wrap it up there. Obviously, we didn't get to all the questions, but if you look at all the attendees if you look at the resources section on your webinar console, we have included ways to get in touch with our panelists via LinkedIn, and there are also some more material there for you. So please feel free to do that to continue the conversation. Thank you, Michael, Nanne and Tom, for an excellent presentation and to Andgo Systems for sponsoring today's webinar. And thank you to all you attendees for spending an hour of your time with us today. Please fill out a post-webinar survey and provide us feedback, and we hope you have a great rest of the day. Thanks so much for joining us.