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Healthcare by AI, at what cost? · Cultural Wars | America Out Loud News

• 0:06
  Welcome to the unto Take a deep breath.
• 0:11
  Take the higher road.
• 0:13
  That's what they always say.
• 0:16
  They won't take it from me.
• 0:20
  But don't ever dump yourself with slap and just a dream.
• 0:24
  You made your own so kid can scream.
• 0:27
  The people who laugh with a never ending force.
• 0:31
  You never have the chance.
• 0:33
  So watch it win for my friend, because this is whole.
• 0:44
  It's time and this one.
• 0:54
  Welcome back to another great episode of the Nurses Report here on America Outloud.news.
• 1:00
  We are your Friday QA crew here on The Nurses Report.
• 1:04
  My name is Ashley Grog.
• 1:05
  I'm your host today.
• 1:06
  I've got David Wayne who does a lot of the heavy lifting and Nurse Nicole who is as sassy as ever.
• 1:13
  But I can't say much because we are hashtag twinning and pretty much the same person.
• 1:19
  So today we're just gonna talk about headlines.
• 1:21
  We are gonna discuss the different things happening.
• 1:25
  We are gonna just have fun and chat about the things that matter and create discourse.
• 1:32
  So uh without further ado, I'm gonna toss it over to Nurse Nicole, let her introduce herself, and then we'll go to Nurse David Wayne.
• 1:39
  Yes, so for those of you that don't know, I go by Nurse Nicole, I'm a Central Florida registered nurse of 20 years, predominantly in the cardiac field, uh, do a run a large program for chest pain in the area, and also work on a local and state level with some organizations in the medical freedom movement to promote informed consent and bodily sovereignty and to protect our rights, get people involved to protect medical freedoms in Florida.
• 2:06
  My name is David Wayne.
• 2:07
  I'm a nurse with a background in hospital psychiatry.
• 2:10
  I was a COVID dissident, and uh now my one of my passions is just raising awareness about the about the side effects of antidepressants and the number of people out there who are being gaslit and harmed by that medication class.
• 2:27
  Yeah, that's fantastic.
• 2:29
  That's why I love these two.
• 2:30
  Uh, as you know, my name is Ashley Grog.
• 2:32
  I have been a registered nurse for 20 years.
• 2:34
  I love high-level critical thinking, and I love to ask questions, and apparently that pisses people off.
• 2:39
  So here I am on Nurses the Nurses' Report.
• 2:42
  Um, causing trouble, also author of Resuscitating Nursing Trying to Corrupt More of our professions so that way we can bring back ethics and morals.
• 2:53
  So without further ado, I'm gonna toss it over to Dave.
• 2:56
  He's got a really interesting topic.
• 2:59
  This is probably gonna take up the first half of this um this episode.
• 3:04
  AI in nursing.
• 3:06
  So tell us what's happening, Dave.
• 3:10
  Yeah, I mean, it's clear that this has been something that's coming down the line.
• 3:15
  We just kind of don't know what shape it's going to take.
• 3:19
  So if you've worked as a nurse in a hospital recently, maybe you've seen some of the new technology where you have uh you walk into a patient's room with a smartphone, and the phone listens to the conversation between the nurse and the patient and starts to document everything.
• 3:38
  We also have uh cameras and microphones in a lot of patient rooms now, and we have services like virtual nurses who will come into the TV in the patient's room and talk to them about things.
• 3:51
  So ask them admission questions when they arrive at the hospital, they'll review their new medications and that sort of thing when they're going to be discharged from the hospital.
• 4:01
  And that nurse on the TV screen is a real life nurse, but they're in a cubicle in an office somewhere, and and they're just piping into these different patient patient rooms and and doing these sort of tasks.
• 4:15
  So this kind of uh technology enabling these kind of um I I think it's safe to say impersonal interactions between uh between the patient and the the system there.
• 4:30
  Um I I guess that's where we're at right now.
• 4:34
  So before we talk about where we're going, let's just pause right there and talk about where we're at.
• 4:40
  Uh you know, I haven't been a patient in a hospital since I was uh since I was a little kid.
• 4:46
  So uh, but you know, I have uh talked to quite a few patients who do not like all the all the cameras and all the microphones and the smartphones listening in on things, and same thing, same thing with staff.
• 5:00
  Staff uh staff don't like it either.
• 5:02
  So what are what are your first thoughts?
• 5:04
  Ashley, I know it's been a while for you since you've uh been inside a uh been an employee of a big hospital system, but Nurse Nicole, this might be um something more more recent to your experience.
• 5:17
  Uh so you know, for me, I know this is also something that I feel like it's all by design.
• 5:22
  We have a shortage of nurses, and there's many reasons for that lead to them leaving the profession altogether, and so I feel like this is a way over time that they have been able to usher and plan to have this AI because they're saying they can't find nurses and we can't keep nurses, and this is the largest shortage to date, and this is a more cost-effective way essentially to bring in other technology.
• 5:46
  Uh, it's more reliable, right?
• 5:48
  Can't have call-outs with AI and different things, and so for me, we do have this in our hospitals.
• 5:54
  There are virtual nurses that basically are to I'm using air quotes for those of those that are not watching us uh to help the nurses on the units to create an environment to get some of these clerical type things done.
• 6:07
  What happens is though, is that it can cause a disconnect in communication.
• 6:11
  There are, you know, inconsistencies and assessments, there are possibly urgent things that happen that still would require a real person, a real human being to be able to be acknowledged and come in and identify.
• 6:23
  And at the end of the day, it's just another way, in my opinion, for more of a security breach because you have these different types of technology that are live, if you will, being actively engaged in, and anybody could come in and potentially hack it or get these things that you are talking about, uh, break through those security walls.
• 6:45
  So for me, it is something we're seeing, it is becoming more predominant in the field.
• 6:49
  They're again saying it's because we don't have enough nurses, it's more cost effective, and essentially it's you know, providing this environment of um, you know, uh efficiency, if you will, because we don't have the nurses, but then it also is really an invasion an invasion of privacy when you have all these things in there that can be utilized that you may not know about, right?
• 7:00
  If you will, because we don't have the nurses, but then it also is really an invasion an invasion of privacy when you have all these things in there that can be utilized that you may not know about, right?
• 7:11
  When you are changing or you're going through something as a patient, an assessment and having cameras and microphones on you.
• 7:11
  When you are changing or you're going through something as a patient, an assessment and having cameras and microphones on you.
• 7:18
  Um, but then there's another side to this that sometimes violence and health care because it's gone up 50%.
• 7:18
  Um, but then there's another side to this that sometimes violence and health care because it's gone up 50%.
• 7:23
  Some people say that they like knowing that there might be cameras and different things to show what really happened.
• 7:23
  Some people say that they like knowing that there might be cameras and different things to show what really happened.
• 7:29
  So there's
• 7:29
  So there's not as many people excited with that, you know, and agreeing to this old technology and AI.
• 7:35
  Much more people are against it.
• 7:37
  Even patients, they feel like it's a breach of their privacy.
• 7:42
  You brought up a couple things there.
• 7:44
  One of them was the staffing crisis, and the other one was safety, and what always irks me.
• 7:49
  Hospitals, hospital administrators, they always talk about how safety is their top priority, and they never act like it is because by far the number one way to have a safe hospital unit is to have experienced staff and to have enough of them.
• 8:07
  Nothing else matters.
• 8:08
  Like if you have that, doesn't matter what kind of technology you have, you're going to be fine.
• 8:12
  That's what you need.
• 8:13
  You need experienced staff and you have enough of them.
• 8:15
  And what we see currently is hospital administrators could not give a crap about having tenured staff or having good retention because it actually saves them an incredible amount of money when that nurse who's been there for 20 years leaves and they get to hire somebody at minimum nursing wage who has absolutely no experience.
• 8:33
  It's actually uh that's a pro, not a not a con.
• 8:36
  And that's just, you know, healthcare has become such uh a business at this point.
• 8:42
  Um I think that goes right into the fact that we are obliterating critical thinking.
• 8:50
  This is going to be an increasingly more hostile environment for anybody who dissents or pushes back on whatever is being done.
• 8:59
  Well, predictive modeling says this.
• 9:01
  This is what we have to do because follow the algorithm.
• 9:06
  Yeah.
• 9:06
  This is the protocol.
• 9:07
  Follow the protocol.
• 9:08
  This is the standard of care.
• 9:10
  That flipping term standard care, like red flag should go up.
• 9:15
  But also when you hear the term standard care.
• 9:17
  But just to add really quick, Dave, one of the things that really just gets me with the AI is that a lot of these AI sources are outsourced to other countries that have individuals that are not necessarily trained like we are, not necessarily have the same standards of care, like you mentioned, and they're being utilized behind the scenes for these AI technologies to monitor and to elaborate on you know what is going on with the patient.
• 9:45
  And I I find that's a real problem that we have these things not necessarily being even kept in the United States or sourced through our own, you know, uh employees or communities.
• 9:57
  It's it's actually going overseas, and that's something that they've seen in other areas as well, with like CMS and insurance companies and different programs they use for um with AI that these are outsourced and and being looked at and and managed again, air quotes by other countries with different individuals that um you know it may not necessarily do the same things that we do, is what I'm trying to say in the United States.
• 10:22
  Right.
• 10:22
  We started with outsourcing our healthcare systems uh physical assets like medications, like all the equipment we use.
• 10:30
  Like we don't like any of that stuff in the US anymore, and now we're also outsourcing our hospital personnel wherever we can.
• 10:37
  If we can do things over a screen, we're outsourcing that too, which is just an incredible setup for failure in this modern world, especially as we see things like this ongoing war in Iran and the instability that comes from that.
• 10:54
  Like, look at how many medications we import from India and how much of our hospital equipment comes from China, and as as there's instability and uh and uh um restructuring of global power going on right now, like this can have incredible repercussions for our healthcare system when we have shortages of equipment and shortages of of really important medications at in in our hospitals.
• 11:19
  Like this is uh it is it is not good that we are outsourcing all these things.
• 11:25
  Well, and we think about how like AI developers were like, oh, don't use please and thank you because it eats up space and stuff like that.
• 11:32
  We see how much energy is being consumed by AI, um, how much water consumption to cool all of these things, and we're talking about doing how many of these different processes, what kind of impact is this gonna have on our electrical grids?
• 11:48
  What happens when we have staff that's completely dependent on AI, and then it goes down.
• 11:58
  Yeah, that's uh that's a good question, and uh it's also a question what happens when our staff become AI and then the AI goes down, because that's also uh clearly uh direction that this is going is that um you know it's way easier, uh way more cost effective for hospital administrators to purchase uh software platform and an AI platform than it is to pay a bunch pay a bunch of people's payroll.
• 12:26
  Uh so that's gonna be the direction that this takes.
• 12:28
  There are so many things that AI uh can do well that uh I think a lot of uh I think a lot of nurses in administrative roles, they're the ones who are happily ushering in this new AI age, oblivious to the fact that they're the first ones who are going to get replaced.
• 12:50
  The the nurses, uh all these hospital administrators, a lot of them masters or doctorate degree nurses who have left the patient patient bedside for these more administrative roles, people who do things like billing and scheduling and case management and and you know doing all the quality reports and attending all the Zoom meetings and making the power points and all that sort of thing.
• 13:13
  They're gung-ho about all this AI technology, not realizing that that's all stuff that AI is actually incredibly good at, and they're gonna be the first on the chopping block because all that payroll that they're gonna save from just uh uh buying the program, like yeah.
• 13:29
  Um I have to admit, sorry, I have to admit though, getting rid of that middle management with AI.
• 13:37
  They're they're not directly taking care of the patients.
• 13:41
  Right.
• 13:41
  Yes.
• 13:42
  I I hope they go back to the patient bedside, honestly.
• 13:44
  Yeah, but that's of course not that's of course not what's going to actually happen.
• 13:52
  Yeah.
• 13:52
  I think AI just cut the power in uh Ashley's house because it's going to be dark there.
• 13:58
  We're experiencing some really bad storms right now, and I'm hoping that we last the things.
• 14:00
  Bad storms right now, and I'm hoping that we last the things.
• 14:03
  So, you know, we'll see what happens.
• 14:03
  So, you know, we'll see what happens.
• 14:05
  There's my there's my light.
• 14:05
  There's my there's my light.
• 14:07
  The power did flicker, but hopefully we'll we'll be good for the rest of the episode.
• 14:07
  The power did flicker, but hopefully we'll we'll be good for the rest of the episode.
• 14:12
  I wanted to add that recently with AI, they had uh one of the insurance um there's a there's a lawsuit against one of these insurance companies that had used AI to basically go through and identify appropriateness of um, you know.
• 14:12
  I wanted to add that recently with AI, they had uh one of the insurance um there's a there's a lawsuit against one of these insurance companies that had used AI to basically go through and identify appropriateness of um you know uh needs for a patient, and they found that there was a ninety-eight percent ineffective or false uh positive, if you will, um for this, and and it just goes to show that although AI is being looked at as accurate, more effective, more efficient, all these other things, that there's still a lot to be done with it to improve it, and it's really scary to think that we could be using this for healthcare human beings, people real time, and you know, this may not be what it they think it is.
• 15:02
  Oh, for sure.
• 15:04
  You you look at AI being used for clinical research and things like that, and AI, you know, giving it a huge mountain of information and having it sort through it is uh it's very good at that, but it's also the issue of garbage in, garbage out.
• 15:18
  If you feed AI a bunch of Pfizer lies and you give AI the standards of care that were written by the Pfizer marketing department, you're gonna have a whole bunch of uh really expensive hospital visits with a whole bunch of really dead patients is is what you're gonna have.
• 15:33
  Well, and that's another thing that I you know is just rolling across my mind.
• 15:37
  So I somebody was telling me that most of the time when they run through wartime simulations and sending nukes in a war, AI, like nine times that's not the actual figure, but like nine times out of ten, a very high percentage.
• 15:54
  AI will send the nukes.
• 15:56
  And so we look at this in perspective.
• 16:00
  Uh obviously it's different, but if we compare that to health care, are we gonna see AI terminating patients?
• 16:09
  No pun intended, but kind of like um is it gonna start suggesting made?
• 16:15
  Are they gonna say that this patient is terminal?
• 16:17
  Are they gonna say that you know what is that gonna look like and how negatively can that impact, especially with everything we're seeing with youth euthanasia across the world and you know, the efforts that have been happening for years to get that here?
• 16:36
  Right.
• 16:36
  So, at what point will AI replace uh doctors, uh doctors' judgments?
• 16:41
  I I don't know.
• 16:42
  I could see it doing it for a lot of things where AI, you know, AI is incredibly powerful at some things.
• 16:48
  So you think about radiologists looking at x-rays or looking at scans, things like that.
• 16:52
  I could see AI being really really good at that if it's trained appropriately and used responsibly.
• 16:59
  There are some roles where the power of AI is just undeniable, but it's is it going to be wielded in ways that are entirely good for patient outcomes versus hospital profits?
• 17:13
  Absolutely not.
• 17:14
  It's it's going to be first and foremost geared towards the benefits of the of the corporation and of the um of those in power, and we can say that with complete confidence because that's been the pattern as we uncover these scandals within our healthcare system going back decades and decades and decades and decades.
• 17:34
  That like it or not, is our current system, and that's going to be uh our future system until we start uh seeing actual genuine reforms, which we which we still have not still have not seen.
• 17:47
  Will we start seeing AI used in the insurance industry to say whether or not claims are approved or not and do those instant?
• 17:55
  Are we gonna know when that starts happening?
• 17:58
  And are we going to be able to push for actual peer-to-peer, not peer-to-AI, uh reviews of these claims and stuff like that?
• 18:09
  I mean, just my mind is reeling with the possibilities and the way that this could absolutely go sideways.
• 18:16
  Yeah, and that's what's so hard is it's uh its pros and cons because if it's used appropriately, it it might be a good thing.
• 18:22
  But all right, Ashley, let me let me ask you this one.
• 18:24
  Fast forward 10 years, uh you have a loved one in the hospital and you have a couple microphones and a couple cameras in the room.
• 18:33
  Now, what how would you feel about AI watching your loved one while they're in the hospital?
• 18:39
  Because it can look for things like have they repositioned?
• 18:41
  Are they at risk of developing a pressure ulcer?
• 18:44
  Do I need to notify staff that um that this person should turn?
• 18:48
  Or do I need to uh turn on the TV in the patient room, give them an avatar of myself that I think that this person is going to find most appealing and ask them to reposition themselves or ask them what their pain is?
• 19:01
  Like, do you know when when we look at the current staffing crisis and uh a lot of hospitals do have issues with things like patients being repositioned in time to prevent pressure ulcers because of huge staffing issues?
• 19:16
  Okay, is this something where AI can step in and say like I have been watching this person every second of their hospitalization, I've seen them move in bed, this person's okay, this person in room 12 though, they need to move now.
• 19:28
  Like what how how do you feel about that?
• 19:31
  How does that make you feel?
• 19:32
  It's exactly like you said, if this is actually used just for that, but the problem is is we don't know the true capabilities, and you know, is that is the social credit score or the health credit score gonna be instituted and the patients who are compliance compliant with commands from AI then move their way up on their eligibility for you know health insurance coverage for X, Y, and Z.
• 19:57
  And I I think that that's where it gets really scary because you ask I would venture to say it's probably like nine point nine, you know, out of ten people, or let's say ninety-nine out of a hundred to make it a little bit more, you know, easy on the brain.
• 20:14
  If HIPAA protects your medical records.
• 20:18
  No.
• 20:19
  HIPAA provides a floor and tells tells hospitals and healthcare companies what they cannot do with your in information and what they can do.
• 20:32
  And so, you know, people are gonna assume that this information is protected and safe, but it's actually gonna be shared in God only knows how many different ways.
• 20:42
  And so just because of the the amount of information and data that that would be able to collect and then share, we talk about predictive modeling, we talk about facial recognition, we talk about the way that they could then really learn, analyze, and AI could understand your gate, your movement, the way your body moves and the ability to use that against somebody is just too high.
• 21:00
  And AI could understand your gate, your movement, the way your body moves, and the ability to use that against somebody is just too high.
• 21:14
  Nurse Nicole, how would you feel if patients were admitted to the hospital and we slapped a wearable on them that's keeping an eye on their temperature and their heart rate and that sort of thing, and and you know, looking at looking at all the ways that AI might keep a close eye on patients in.
• 21:14
  Nurse DeCole, how would you feel if patients were admitted to the hospital and we slapped a wearable on them that's keeping an eye on their temperature and their heart rate and that sort of thing and and you know, looking at looking at all the ways that AI might keep a close eye on patients in a medical setting, you feel good about it, you feel leery about it.
• 21:34
  Well, I mean, currently we all we always put heart monitors on them, right?
• 21:38
  So there are a lot of times they're already having their heart monitored, but when you start adding in actual visuals of the person and are able to have identifiable uh characteristics about these individuals, you know, I can see where people are going to possibly think that this is a good idea, right?
• 21:55
  Because they may not be able to be everywhere.
• 21:57
  And wouldn't it be nice that you could sit at a desk?
• 22:00
  But we actually have some of these already implemented when you have patients that maybe have behavioral issues or maybe need to be watched closer because they're having a mental health crisis.
• 22:10
  We have rooms that already have cameras and microphones in those rooms that are to basically watch these individuals around the clock, what they're doing and make sure that we're that they're being safe, right?
• 22:21
  So we already have this, but expanding it further so that you have now have a unit of 30, 40 people, and now you have all this exposure to every single thing about them at every single moment of the day is extremely intrusive and it's really concerning.
• 22:37
  But again, when you come into the hospital, it also makes you wonder about your rights, because there's a lot of things that we know right now that you don't really have certain things that uh are protected, as evidenced by what happened during the pandemic, and and those things, you know, were highlighted then.
• 22:55
  Right.
• 22:55
  Your consent for treatment when you sign into the hospital is going to be that AI watches you every second you're there, and then that's going to be on the paperwork that you sign on admission when you when you go there, Ashley.
• 23:06
  Whether you realize it or not, because they'll just slap it in there and you're signing a digital screen, and oh, this is our privacy practices, and then it's done.
• 23:16
  And the other thing is if they're implementing all these things, if they've invested the money into these wearables, which we know they're gonna end up in the laundry because let's be honest, that's what happens with our heart monitors.
• 23:27
  Um, or they get stolen by the patients, even though they can't connect to any of their technology, like that would happen all the time with our, you know, heart monitors, but don't worry, the AI will watch for that too, so they won't be so it beeps annoying.
• 23:43
  Right.
• 23:44
  But that's just the thing is then what's gonna happen to the nurse-to-patient ratio.
• 23:47
  You have a 40-bed unit.
• 23:49
  You used to have uh let's just say it was a great unit and you had a four to one ratio on a like a telemetry, you know, or ICU was truly ICU and it was uh uh, you know, one-on-one or one to two.
• 24:03
  Um, but then they justify, well, everything's being watched by AI.
• 24:08
  We don't need your human eyes, and so we drop the numbers down.
• 24:12
  Oh, the computer can give the medication, and we don't even need you because we're just gonna hook an IV up to them, and then we're just gonna administer all meds via IV.
• 24:24
  Or it's gonna be a uh a cat treat dispenser, and it's just gonna dispense the the right medications at the right time, and then we're gonna be able to monitor.
• 24:34
  So we really don't we really don't need you, and we really don't need text.
• 24:38
  Um no, for real.
• 24:40
  What is it gonna do to uh nursing ratios, nurse to staff ratios?
• 24:45
  Because you look at what it's doing right now today, and it's doing a lot of documentation.
• 24:50
  It's doing that by listening to the conversation between the nurse and the patient.
• 24:55
  But what about when we get to a point where it's just the AI watching and listening, and the AI is able to complete most of the nursing assessment by itself from what it's watching.
• 25:06
  That the AI can do a face's pain scale every 10 minutes or every 10 seconds if it wants to, just by watching the person's face.
• 25:15
  It can chart their movement, like I said before.
• 25:17
  It can chart their respirations, and it's gonna do it dramatically more accurately than a human could, to be to be honest.
• 25:24
  That's the sort of thing that it's amazing at.
• 25:26
  So, what about skin?
• 25:27
  What about rashes?
• 25:28
  Right now, we already see people like, what is this rash on my leg?
• 25:32
  And they'll take a picture of it, send it to AI, and AI is incredibly good already at not just diagnosing things like that, but uh uh giving them recommendations for over-the-counter treatment.
• 25:43
  So we see dermatologists being replaced by AI.
• 25:46
  And and yeah, I mean, uh staffing is by far the biggest expenditure that these hospitals have, and man, I bet they're salivating at the bits to think about uh uh 40 to 1 patient to nurse ratio because what's going to be left for the nurse to do?
• 26:01
  Okay, passing medications.
• 26:03
  That's actually not that hard to automate, and you can have an uh uh you can have an AI camera, look at the pills to make sure the right they're the right thing.
• 26:12
  You can have somebody with a high school diploma trained to place an IV.
• 26:16
  A lot of places right now are that's what they're uh program.
• 26:19
  A lot of hospitals now, that's what they're doing.
• 26:22
  Their IV team is that's their specialty.
• 26:24
  They don't have uh nursing degree, they don't have any degree, they're just trained to place IVs.
• 26:28
  And so, yeah, I like that's somebody because they don't have that four-year degree or or more that they're getting paid minimum wage, and boy, hospitals love paying people minimum wage.
• 26:40
  Yeah, that's right.
• 26:41
  Well, we are up on a break, and this is the nurses' report on America Out Loud.
• 26:46
  You are listening to Nurses Dave Dwayne, Nurse Nicole, and Nurse Ashley.
• 26:50
  We'll be back after this quick break.
• 26:52
  Uh, we'll look forward to seeing you on the other side.
• 26:56
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• 29:09
  Welcome back to this episode of the Nurses Report here on America Outloud.
• 29:13
  You heard on the first half, Nurse Nicole, Nurse Dave, and I talk about AI impacting our patients and what this looks like moving forward for hospitalized care.
• 29:25
  We are going to take a quite uh a little bit of a shift.
• 29:28
  We're still going to stick with the topic of AI, but we want to talk a little bit about how AI is going to impact the nurse, because we absolutely can see some of the benefits.
• 29:39
  And this is a great tool.
• 29:40
  And that's what Dave was talking about in the first half is how if used properly, this tool can be an amazing benefit to patients.
• 29:51
  But what we're concerned about and what we want to talk about is the way that it can be bastardized and you know, either used improperly that causes harm or used to eliminate the human factor and really create some issues there.
• 30:08
  So let's talk about first the way that AI and the computerization is already impacting the nurse.
• 30:17
  And I know, you know, it's been quite a long time since I've been in the hospital.
• 30:20
  We didn't really have AI back then in the dark ages, 10 years ago.
• 30:25
  So Nurse Nicole, do you want to talk a little bit about how you see these different things being used currently uh in your practice?
• 30:34
  Yeah, so you know, there's a lot of ways that we use AI in the first half.
• 30:38
  You know, Dave mentioned a lot of it can be in like radiology, the reads, we have uh like telehealth, there's certain things that can be utilized on the computer screens uh that can um also be driven by AI, and again, the thought processes that it's quick, that it's able to be um, you know, utilized in a more efficient fashion, and you know, there's even wearable devices or the phones, the voceras, there's different types of um communication uh devices that we wear as nurses that you know can basically clock where you're going, you know, where are you in the hospital, how far you may be interacting in a patient's room, and it's basically being tracked, right?
• 31:19
  And then you have AI for uh interactions with virtual nursing, like we said in the first half, and also other things with when it comes to assessments, uh, again, and that is something that we're currently seeing expand because of the nursing shortage.
• 31:35
  And so it's it's really important that people understand that a real human or someone who's able to physically look at you, assess in real time, you know, uh uh case in point, you go somewhere, you're not feeling well, but you want to go to do a telehealth appointment, and people say, Oh, it's so convenient, I don't have to wait in line, I can just show up.
• 31:54
  But the thing is is that you don't have that human interaction, you don't have that actual stethoscope on your chest, you don't have them physically looking at you, which can really dictate how we assess the patients and the course of action for treatment.
• 32:06
  And so it's really important that people understand it's not the same, and where it may be convenient, that convenience can really cost you, and that AI program and that way that they are utilizing it in healthcare is basically dictating and driving how we're reading scans, how nurses and doctors are doing assessments, how they're interpreting tests that again at one point were read by actual humans and other things when it comes to the actual um outcomes with patients.
• 32:35
  So it's it's becoming way more widely accepted and as a cheaper and quote unquote efficient option.
• 32:42
  But like we've said at the beginning of the show, there are many areas that have come to fruition that have shown margins of error and really highlighted the problem with AI as a whole and how this can affect patients, insurance claims, etc.
• 32:58
  Uh, backfiring on us instead of actually being more positive.
• 33:02
  Yeah, it's that human element and that human connection that draws so many people into nursing as a profession, and you just don't get that over a screen like you do in person, and it's going to be far worse when you're interacting with an AI agent, not even a human on a screen instead of an actual human being.
• 33:23
  I've seen uh system where uh neurologists are brought in virtually to do post-stroke assessments on patients, where the neurologist is basically a little kiosk that gets wheeled into the broom that has a monitor with a camera on top of it, and that's who's doing these post-stroke assessments.
• 33:46
  It's insane to me.
• 33:47
  I've heard mixed things about it from staff.
• 33:50
  Some people say it's actually very convenient, other people uh really really don't like it.
• 33:55
  People's opinions are mixed, but um it's it's clearly the direction things are going.
• 34:00
  Ashley, have you heard about uh things like that?
• 34:03
  Yeah, I I always wonder about outcomes.
• 34:05
  When I worked in the hospital, though one of the last things that I did in hospital was developing the heart failure program, and so I was looking at outcomes and interventions and things like that.
• 34:15
  And so for uh you know, a rural rural community hospital that's not gonna have access to something like this.
• 34:26
  Okay, fine.
• 34:26
  You know what?
• 34:27
  That's probably not a bad idea.
• 34:29
  It's a s it's critical access, right?
• 34:31
  That's just like a band-aid station and you have somebody come in the ER, it's gonna take them 45 minutes to an hour, six hours to get to the nearest regional hospital with the capabilities to care for a patient like this.
• 34:44
  Yes, of course.
• 34:45
  Wheel the screen in and let the neurologist uh assess this patient.
• 34:50
  Absolutely, because that patient's outcomes are probably gonna be improved.
• 34:54
  You know, if if the doctor, if a real live doctor is on the other side of that screen and can interact with the staff that's present.
• 35:00
  Of that screen and can interact with the staff that's present.
• 35:03
  Hey, tell me what you're seeing with this.
• 35:03
  Hey, tell me what you're seeing with this.
• 35:05
  What does this look like?
• 35:05
  What does this look like?
• 35:06
  How are the patient here?
• 35:06
  How are the patient here?
• 35:07
  You know, there is that collaborative work that's going on.
• 35:07
  You know, there is that collaborative work that's going on for a patient who otherwise wouldn't receive the same level of care, hundred and ten percent.
• 35:14
  For a patient who otherwise wouldn't receive the same level of care, hundred and ten percent.
• 35:20
  But if we're talking about just digitizing and having this, you also have the factor like when we see with locums, locum hospitals, hospitalists.
• 35:20
  But if we're talking about just digitizing and having this, you also have the factor, like when we see with locums, locum hospitals, hospitalists, they come into the community, they're there for a couple weeks and they leave, they don't have the connection with the community, they don't have the connection with the people.
• 35:38
  Um there's not the rapport between the staff and the physician.
• 35:43
  There are all of these human elements that play such a big role in driving those positive outcomes.
• 35:49
  You can't always factor those into your interventions and and what the outcome of those interventions is going to be.
• 35:57
  And so again, I'm not saying don't use it, and I think that that's been the running theme of this whole conversation.
• 36:04
  It's not that we don't want these applications used, it's that we have to make sure that we are working to make sure they're used appropriately, that the critical thinking is there in the staff to say, okay, enough is enough, and that we as nurses, and this isn't just a shameless plug for my book, but we as nurses know how to advocate for our profession and our patients to ensure that these applications are not being applied incorrectly or for just the sake of convenience.
• 36:35
  Yeah, amen.
• 36:37
  Go ahead, Dave.
• 36:38
  Oh, go on, Nicole.
• 36:39
  I was just gonna say that it's it's like chat GPT, right?
• 36:42
  I know a lot of you guys like to use it, and there's a lot of good things to it, but if you're not careful and you implement things that are not easily regulated, then you start running into problems where you know you're relying on this technology, and all this critical thinking goes out the window.
• 36:57
  People don't second guess, they don't fact check it if you will, they just go with what they're being told is accurate, and you know, it can be really dangerous.
• 37:05
  And again, we're speaking about human beings, individuals, a life force, and and and putting all this infamous emphasis on technology and essentially removing the human part of this that to me is much more isolating, much more room for error, you know, much more of a of a capability to be again hacked or security breached.
• 37:27
  There's all these things that now are opening up Pandora's box to come to this like just different way of life when it comes to health care.
• 37:35
  It just doesn't seem like it would be ethical or empathetic, compassionate.
• 37:40
  How does that equate to those types of you know, feelings when you're when you're interacting with people that usually are human and not a robot or an AI because there's even robots, and I mean there's like things in hospitals right now that have actual robots doing things in place of humans?
• 37:56
  It's it's wild.
• 37:58
  Yeah, fast forward ten years when the robotics has advanced and the AI has advanced, and you know how they have the uh patient lift tracks on the ceiling of the hospital room.
• 38:08
  Okay, how long before the little motor that's up there now is replaced by a robot that has hands on it that can reposition payments and that has cameras and microphones on it, and it's like it's not even gonna be a human coming into your room.
• 38:21
  It's gonna be this AI voice coming down from the ceiling that says, Hi, Nicole, you haven't moved in a couple hours, so I'm gonna help reposition you, and then the little AI hands are gonna come down and and move you so you don't get a bed sore.
• 38:32
  Like I mean, seriously, think about hospitals will uh save in staffing from having uh uh things like things like that installed.
• 38:40
  But hold on a second.
• 38:42
  So this is a two-parter, right?
• 38:46
  Okay, so whose license is on the line?
• 38:52
  When accidents and injuries happen, who is liable?
• 38:57
  Is it the hospital for improper maintenance?
• 39:01
  Is it the company that runs the AI or drafted the program?
• 39:06
  Is it the nurse that's on duty?
• 39:08
  If the nurse and and this is that second, let's let's start, let's stop there.
• 39:13
  So let's talk about it's 100% the nurse because the nurse costs the hospital money.
• 39:19
  It's never a doctor because they generate revenue for the organization.
• 39:23
  The hospital also has to have an ongoing good relationship with these vendors.
• 39:27
  So of course it's going to be the nurse that's thrown under the bus every single time something bad happens with one of these technologies because it's gonna be in their job description that they're gonna monitor this and that and that sort of thing, and doesn't matter what the staffing is, doesn't matter what the extenuating circumstances are, doesn't matter the way that they were set up for failure.
• 39:46
  The fact is the nurse has uh no power and no value to the organization, uh they are an expenditure to the organization, and that's that that's that's just the reality of it.
• 39:59
  Okay, so Nicole, do you have anything to add to that?
• 40:02
  He's just he's right, he's a hundred percent right, and that's the sad part about it.
• 40:07
  So I mean, that that's that's been the pattern going back years and years and years, regardless of AI or technology.
• 40:13
  It's that nurses are an expenditure, doctors generate revenue.
• 40:17
  Uh, when something goes wrong at the patient bedside, it's it's almost always going to be the nurse that takes the fall from the hospital.
• 40:26
  So, part two.
• 40:28
  How is it handled when AI doctor says this needs to happen with the patient and nurse says no?
• 40:40
  How how does that escalate?
• 40:41
  And and the crazy thing is, is like this could go either way because maybe it's AI nurse feeding information to the doctor, AI nurse misses information to relate to the doctor, and then the doctor gives the wrong order.
• 41:00
  Is it still the doctor that's liable?
• 41:03
  Is it like I people who say no don't last long in this system, they're trained in nursing school to it it's so regimented and so hierarchical.
• 41:14
  You're trained to be obedient to the higher powers in the system, and people who tend to say no a lot tend to not last.
• 41:23
  That's part of why we have such a such a crisis.
• 41:26
  The people who um last in the hospitals are just salty people who have learned to keep their head down and are trudging slowly towards retirement uh and just swallowing the bitterness every time they swipe in at work, or they are the true believers who who are just uh um gosh, captured by the mass formation psychosis and don't question anything and and just nod their head and go along with whatever they're whatever they're told.
• 41:55
  I don't think that's what God meant when he said be the salt and light.
• 41:59
  I'm just saying anyway.
• 42:00
  Anyway, sorry, Nicole.
• 42:01
  Sorry, Nicole.
• 42:02
  I feel like Dave just went for my jugular.
• 42:02
  I feel like Dave just went for my jugular.
• 42:04
  Hey, I'm still in the hospital, Dave.
• 42:04
  Hey, I'm still in the hospital, Dave.
• 42:05
  Jeez.
• 42:07
  You call me salty?
• 42:07
  You called me salty.
• 42:08
  No, I'm kidding.
• 42:08
  No, I'm getting no, he's he's right though, right?
• 42:09
  No, he's he's right though, right?
• 42:11
  There's a lot of people that are compliant, and that's why we're the third leading cause of death in the United States because mistakes happen, people don't question it.
• 42:11
  There's a lot of people that are compliant, and that's why we're the third leading cause of death in the United States because mistakes happen, people don't question it, people are scared to speak up because of what happens to nurses, essentially.
• 42:19
  People are scared to speak up because of what happens to nurses.
• 42:23
  Essentially, you know, there's a case right now about a mom who went in for a tummy tuck mom makeover.
• 42:24
  You know, there's a case right now about a mom who went in for a tummy tuck mom makeover.
• 42:29
  There, I don't know all.
• 42:29
  I don't know all the things, so this is just allegedly physician takes nine hours, then all of a sudden he's suing the nurse, one of the packing nurses.
• 42:36
  This is what happens.
• 42:37
  Nurses constantly take the fall, and so to know that you could have actual AI robotics and different things of technology that you would have to oversee, you know, again, like where does that go with your scope of practice, your standard of care, what would be the escalation processes?
• 42:53
  How would you be able to safely safeguard you know, uh inaccurate reporting, like you said, and then again, who takes the fall for it?
• 43:00
  But as Dave says, notoriously, hospitals go after the staff, especially nurses because they are the easy targets and the ones that you know typically do not have um you know the the wherewithal the means if you will to fight back these huge organizations, whereas physicians have a little bit more due to money and and access, but not always, so it's just it's really sad.
• 43:24
  But this is also what I feel is part of the process to eliminate as many nurses as possible.
• 43:30
  Say it's due to the shortage, bring in all this technology, bring in this AI, make one nurse to like 30 patients, and then when a code happens, what would happen?
• 43:40
  You know, you're just gonna start grant rabble, you know, people are gonna start dropping from the sky.
• 43:43
  I I don't know, and then like at what point, like do you do you have a do you have a Lucas at your hospital yet?
• 43:49
  One of the automated CPR machines.
• 43:52
  So we we have our EMS agencies that use it, and we had a situation that um was was reported to So stop for just a second.
• 44:03
  Please explain to the listeners because I I know what this is, but a lot of our people are not gonna understand what a Lucas is.
• 44:11
  Go ahead, Dave.
• 44:12
  You can explain it, and I can tell the story if you want.
• 44:14
  Lucas is a machine that is wrapped around a person whose heart has stopped, and it basically does the chest compressions.
• 44:25
  I've seen it in action, and it is incredibly violent, but CPR by a person is also incredibly violent.
• 44:32
  So it's it's terrifying and it is terrifying, yeah.
• 44:35
  It's we use it a lot because of the codes that you know, EMS agencies, they they usually have one medic in the back.
• 44:43
  If there's a code happening and we can't grab a firefighter on scene that's a medic that they will use the Lucas device to help so that they can give the meds and everything else.
• 44:50
  But when they come to the hospital on a Lucas device, we're not allowed to remove it, it has to be removed from the actual EMS agency.
• 44:56
  And we've even had, and again, this is one time, so this is not typically a common thing, but one time the device that was put on punched a hole through the person's chest.
• 45:07
  Now they were gone prior to this, but like went through the sternum.
• 45:11
  So again, there are things that can happen even with devices that have been tried and trued, and and this was um you know, something that uh you know, at the time had to be investigated for was this the cause or was this a secondary issue?
• 45:25
  And so again, it's um technology, it's robotic technology, if you will.
• 45:29
  It's a machine that's being utilized to help.
• 45:32
  The theory is to help, but in some cases, if you don't place it correctly, if you don't have the right speed, you know, all of these things, you could cause significant damage.
• 45:41
  And most patients afterwards have significantly broken ribs, they've had burns, or you know, the skin where that sternum area is is completely rub raw.
• 45:49
  So as a nurse, you kind of can see and identify these patients, and we have to document when these patients come in that it's been a Lucas device, so then if something happens, you can trace it back to the actual device that was used or not.
• 46:01
  So, again, very good point here, and something that we use um and is becoming more popular because of the lack of staff even in our EMS.
• 46:10
  Well, and not even that.
• 46:12
  I mean, when you think about it effective CPR breaks ribs.
• 46:17
  Let's just be really honest.
• 46:19
  This is not easy.
• 46:21
  You have to compress the the chest to a certain death because the goal is to squish that heart muscle and and push that blood out.
• 46:28
  So it is a very violent process.
• 46:31
  If you're not breaking ribs, you ain't doing it right.
• 46:33
  Like I can remember being told that very clearly, and just you I did CPR unfortunately a lot, and you cringe every time you hear those ribs crack.
• 46:44
  It's and it it's you can feel it.
• 46:46
  It's disconcerting.
• 46:48
  Yeah, because you and you feel it as you continue doing chest compressions, and so it's terrible.
• 46:54
  And so there is that certain level of trauma that's expected.
• 46:59
  You have to get that blood pumping, and the reason they use these devices is because allegedly it increases survival rates because the CPR is more effective.
• 47:10
  You don't have that human hesitation of, oh my gosh, I just broke this man's ribs.
• 47:16
  That stops that, but you also have to account for of I mean, if you would look at any one of our chests, we're all different.
• 47:24
  You know?
• 47:25
  And so the depth of uh and the pressure required to move my musculature versus Dave's versus Nicole's is all gonna be different as well.
• 47:32
  And so there are a lot of variables to be accounted for, and that gets messy really quickly.
• 47:39
  I would be horrified.
• 47:41
  Could you imagine telling a family, please don't lay your hand on your loved one's chest because oopsie we well?
• 47:50
  I mean, at this point too, you know, because if you've ever done true CPR on someone, you tire out very quickly.
• 47:56
  The accuracy, the efficacy, you know, uh efficiency is what I meant to say, is decreased with time, and that's why you have to rotate.
• 48:04
  And so again, like I can see where these devices and certain things could be of benefit, could be of help because we don't always have the staff.
• 48:11
  We coded someone the other day for an hour.
• 48:12
  We had a line of people that we were rotating.
• 48:15
  We did not have a Lucas device that we could use at the time.
• 48:17
  We borrowed one from our flight team, which was a uh different version, uh, if you will, but you know, nonetheless, to try to help kind of eliminate uh staff because at that point, people did we just had nothing left in our tank.
• 48:29
  Over an hour is unheard of, but there was extenuating circumstances with that case.
• 48:34
  But so again, there are situations that this could potentially be utilized for good, but there is always underlying things that have to be looked at because there's room for error because it's not a human, if you will, that can always kind of negate or you know, navigate, excuse me, what we're doing in that time.
• 48:54
  Because at when you put those devices on, you cannot see what it's doing while it's doing it.
• 49:00
  It.
• 49:00
  There's this there's a level that you cannot see, and and you don't remove it until everybody knows it's time to remove it, and you have a backup.
• 49:00
  There's this there's a level that you cannot see, and you don't remove it until everybody knows it's time to remove it and you have a backup.
• 49:06
  But once you do, you never know what you're gonna find, is what I'm saying.
• 49:06
  But once you do, you never know what you're gonna find, is what I'm saying.
• 49:11
  Brutal.
• 49:12
  Brutal.
• 49:13
  I want to switch gears a little bit to bring in a theme that we've covered in various episodes that applies here.
• 49:13
  I want to switch gears a little bit to bring in a theme that we've covered in various episodes that applies here.
• 49:19
  We talked about it recently, where the people who cause a problem, or even the people who cause us cause a disease are also the ones who are selling us the cure.
• 49:19
  We talked about it recently, where the people who cause a problem or even the people who cause us cause a disease are also the ones who are selling us the cure.
• 49:29
  So right now we're
• 49:29
  So right now we're being told that all these new technologies and all these virtual providers and AI providers, this is great because of the incredible shortage.
• 49:40
  Well, this shortage is self-inflicted.
• 49:42
  We just had well over a thousand doctors graduate from medical school here in the US that didn't get matched to a residency program.
• 49:50
  We also brought in thousands of foreigners instead of using American doctors, and this shortage of doctors in the pipeline has been ongoing for quite a long time and is totally unnecessary.
• 50:03
  And this is part of why we have all these gaps in rural health care.
• 50:06
  We have made it so that A, we don't have enough doctors, and B, the doctors that we do have, it is just not viable to practice medicine in some of these rural locations because of the current economics of health care.
• 50:19
  So you create a crisis and then you create a solution for it, and that's that's part of what's going on here as well.
• 50:27
  So I want to take a step back.
• 50:28
  One of the things unless Nicole, do you have anything to add to that?
• 50:34
  I want to take a step back.
• 50:35
  And we originally said that we're going to talk about how this impacts how AI impacts nurses in the way.
• 50:41
  I I want to touch on that because I feel like I feel like we really need to be having these conversations again.
• 50:49
  And I said this in the first half, and I'm gonna say it again.
• 50:52
  We need to be aware of what's coming down the pike so we can identify it because half of the problem with this AI stuff is people aren't going to be recognizing and understanding the consequences of this.
• 51:04
  Because would you ever have thought that the Lucas device would be boring holes into people?
• 51:11
  I I mean, no, you know, so we need to have these conversations.
• 51:16
  Let's talk.
• 51:16
  Nicole had mentioned about um I don't know if it was on this episode or in the past, and it still like is burned into my memory, but the badges, and because I know that our local hospitals they have the badges that track you in and out of rooms, how far I think you said that this this episode going into the rooms.
• 51:35
  How does that change the behaviors and the willingness of the nurses to interact with their patients and truly develop that rapport and really address the needs?
• 51:49
  I we don't I I've not been in the hospital since those have been a thing.
• 51:52
  What do you guys?
• 51:55
  Well, I mean, there's a lot of animosity because nurses don't like to be scrutinized on that level when supplies and resources are already at an all-time low, you're putting excess pressure on nurses to perform tasks that are not genuine.
• 52:11
  And dare I say, because I'll say it that there are nurses that will go in certain places just for it to tag and not necessarily do anything, you know, at that point, because you there are ways to work around it, is what I'm saying.
• 52:23
  And so it creates a false sense of um accomplishment, and there are things that are getting reported that are not accurate because they're not actually doing what it's intended.
• 52:33
  Uh, in some cases, I'm not saying always, but there are things that come with this because when you don't talk to the people that perform the job and you don't provide them the resources, they're going to find workarounds, they're going to find things to do because in 12 hours when you don't have enough staff, you don't have enough resources, your acuity is very high, and then you're wearing this thing on you that's tracking you and trying to tell you when and where you're supposed to be somewhere when you don't have all these things going your way and you have no help, uh, you start to do things that are not always designed as they should.
• 53:05
  And you know, who's at fault for that?
• 53:07
  They blame the nurse.
• 53:08
  They don't look at the systems, they don't look at the hospital's greed and how they decide to implement things, and it becomes very troublesome.
• 53:15
  We've even had situations in the past at different hospitals where I've seen the nurses set them down, and where you set them down, it's going to tag that you're somewhere that you may not be.
• 53:26
  And so at this point, that is another concern, right?
• 53:29
  And the hospitals, they know it happens, they know it goes on, but they're just collecting the numbers to say, okay, every hour this nurse was here, or they were, you know, this and that, and then it gets reported out, and it's not accurate.
• 53:41
  So I hate to be that bear of nurses, but that's just what it is.
• 53:45
  No, it's not accurate.
• 53:46
  People game it, and it's just so incredibly Orwellian, and a lot of nurses don't like it, and good for them, they shouldn't like it.
• 53:52
  It it's uh it is really disconcerting to be tracked every minute of your shift, and that's where nurses are already at this point.
• 54:00
  And when we talk about the way that AI is going to impact patients, there's definitely pros, there's definitely cons, but AI is also going to be watching nurses incredibly closely.
• 54:10
  It's going to be watching every second of their shift.
• 54:13
  It's going to be watching everything they put in the patient chart if they're still doing the charting, and it's not AI just doing the doing the charting for them.
• 54:21
  But um, yeah, it it it's it's already uh very big brother-ish inside our hospitals, and AI is only going to make that worse.
• 54:30
  That was a selling point that the company of BioVigil was putting forward as they're promoting their product to hospitals.
• 54:36
  These are those tags that track hand hygiene.
• 54:40
  Uh, one of their selling points was, oh, you can use our tags to track your nurse over the course of their entire shift.
• 54:46
  And that's not just something that the biovigil tags do.
• 54:50
  That's also something that a lot of a lot of people's uh name badges do now.
• 54:54
  They've they've got um trackers in them, some of them have um panic buttons built into them, but all that is is uh, yeah, wherever you are is being tracked every minute of your shift, and soon AI is going to be taking a really really close look at those things, and it's gonna be saying, you know, nurse Nicole, your med pass is 13% slower than the average on your unit.
• 55:16
  What's going on with that?
• 55:17
  How can we how can we make you more efficient?
• 55:20
  How can we support you to you know bring yourself up to the unit average?
• 55:24
  It's it's uh um except you're not gonna be having that conversation with an actual human manager, you're gonna be having that conversation with an AI agent who's now managing your new unit because so many of these administrative roles are gonna be better done by AI than they are by the current dusk jockeys doing them.
• 55:42
  So, man, I don't know.
• 55:44
  We've only got about a minute left.
• 55:46
  Um could you imagine getting feedback on your patient care from AI while doing it?
• 55:54
  Could you imagine an AI voice coming over and saying something?
• 55:58
  Uh any clothing closing thoughts from either of you.
• 56:00
  Closing thoughts from either of you.
• 56:03
  I mean, I just wanted to add that even with great intentions when you know that you're being filmed, you can make someone very nervous, and you know, it can really cause a lot of you know discourse when it doesn't need to because you're just so worried, right?
• 56:03
  I mean, I just wanted to add that even with great intentions, when you know that you're being filmed, you can make someone very nervous, and you know, it can really cause a lot of you know discourse when it doesn't need to because you're just so worried, right?
• 56:16
  That you're gonna do something wrong, or you know, my opinion of how you nurse or how you talk to someone can come off really differently than somebody else, and just having that scrutiny and all of that difference of an opinion that can make anyone mess up or not do a task.
• 56:16
  That you're gonna do something wrong, or you know, my opinion of how you nurse or how you talk to someone can come off really differently than somebody else, and just having that scrutiny and all of that difference of an opinion, it that can make anyone mess up or not do a task correctly.
• 56:30
  And and it's just so to me, it's gonna create a lot of um more uh heightened experiences, and you're just gonna lose more nurses, and that may be the point, but the nurses will not stay when they don't feel supported.
• 56:41
  Um and I feel like it's just be another thing to tag them as, you know, like you said, not compliant or not doing something right and calling them out in real time.
• 56:48
  Well, nerd uh AI is already listening to nurses at work, and that's only going to escalate escalate as well.
• 56:55
  But we also appreciate the nurses who listen to us here on the America Out Loud News Network.
• 57:04
  It's time to get a