1 00:00:00,105 --> 00:00:01,375 - Hello everyone, and welcome 2 00:00:01,395 --> 00:00:03,375 to the Becker's Healthcare podcast series. 3 00:00:03,835 --> 00:00:05,375 On today's episode, we're going 4 00:00:05,375 --> 00:00:08,255 to listen in on a recent interview between Scott Becker, 5 00:00:08,255 --> 00:00:10,255 founder and publisher of Becker's Healthcare 6 00:00:10,715 --> 00:00:14,615 and Mohan Gudas, the Chief Executive Officer of Lean Toss, 7 00:00:14,825 --> 00:00:16,855 where they discuss artificial intelligence 8 00:00:16,855 --> 00:00:18,015 and the healthcare workforce. 9 00:00:18,865 --> 00:00:20,495 Thank you all so much for tuning in. 10 00:00:20,545 --> 00:00:21,695 Let's go ahead and get started. 11 00:00:22,815 --> 00:00:24,985 - This is Scott Becker, the publisher 12 00:00:24,985 --> 00:00:26,025 of Becker's Healthcare. 13 00:00:26,395 --> 00:00:30,825 We're joined by the Chief Executive Officer of Lean tos, uh, 14 00:00:30,965 --> 00:00:34,545 to to have a session to discuss making AI work 15 00:00:34,545 --> 00:00:37,745 for the workforce, empowering staff and systems to thrive. 16 00:00:38,505 --> 00:00:42,225 We're joined by Mohan Rados, uh, brilliant, 17 00:00:42,425 --> 00:00:44,185 brilliant leader, uh, Mohan. 18 00:00:44,285 --> 00:00:46,145 I'm gonna ask you for to, to take assessment. 19 00:00:46,235 --> 00:00:47,705 We're gonna talk today about making 20 00:00:47,965 --> 00:00:49,145 AI work for the workforce. 21 00:00:49,765 --> 00:00:51,745 Uh, so much has been discussed about ai. 22 00:00:52,085 --> 00:00:54,065 Before we get started, I'm gonna ask you to take a moment 23 00:00:54,205 --> 00:00:56,425 to, uh, to introduce yourself 24 00:00:56,565 --> 00:00:58,305 and tell us a little bit about yourself, 25 00:00:58,495 --> 00:00:59,705 lean Tass, and your background. 26 00:01:00,875 --> 00:01:02,435 - Terrific. Thanks Scott. It's terrific to be here. 27 00:01:02,735 --> 00:01:05,635 I'm Mohan GDAs. I'm the founder and CEO of Lean Tasks. 28 00:01:06,385 --> 00:01:11,275 Lean Tasks is focused on ai, mathematics, data science, 29 00:01:11,295 --> 00:01:14,835 and software to unlock capacity in health systems. 30 00:01:15,375 --> 00:01:18,595 We currently work with about 180 health systems in the us. 31 00:01:18,765 --> 00:01:22,275 About 800 hospitals across the country use one 32 00:01:22,295 --> 00:01:23,515 or more of our products. 33 00:01:24,135 --> 00:01:26,635 We unlock capacity in three specific areas, 34 00:01:27,555 --> 00:01:31,555 infusion centers, where we power, uh, 12,000 chairs, 35 00:01:31,555 --> 00:01:34,435 roughly 30% of the infusion capacity in the us. 36 00:01:35,255 --> 00:01:38,875 IQ for operating rooms unlocks capacity in ORs. 37 00:01:39,255 --> 00:01:43,035 We power about 5,000 ORs in about 500 38 00:01:43,395 --> 00:01:44,635 hospitals, uh, across the country. 39 00:01:45,295 --> 00:01:47,795 And our third and newest product is inpatient 40 00:01:48,285 --> 00:01:49,715 where we unlock capacity 41 00:01:49,715 --> 00:01:51,955 and improve patient flow and inpatient units. 42 00:01:52,535 --> 00:01:56,675 Uh, we have about 20,000 beds that we currently optimize. 43 00:01:58,245 --> 00:01:59,915 - Thank you. And I've watched the growth 44 00:02:00,015 --> 00:02:01,435 of Lean Toss over the years, 45 00:02:01,495 --> 00:02:04,435 and it's been brilliant to watch this sort of working 46 00:02:04,495 --> 00:02:07,675 to make things work better for systems and, 47 00:02:07,695 --> 00:02:09,715 and fusion centers and, and a lot more. 48 00:02:10,685 --> 00:02:12,195 We're gonna talk today about one 49 00:02:12,195 --> 00:02:13,995 of the biggest challenges facing healthcare. 50 00:02:14,385 --> 00:02:16,595 This, this lingering workforce shortage 51 00:02:16,855 --> 00:02:20,275 and the role that AI powered technology can play 52 00:02:20,575 --> 00:02:24,035 to helping a constrained workforce better operate at the top 53 00:02:24,035 --> 00:02:25,435 of their business, the top of their license 54 00:02:25,615 --> 00:02:27,995 to in a much more efficient, much more efficient way. 55 00:02:28,935 --> 00:02:30,515 So, so Juan, let me get started. 56 00:02:31,215 --> 00:02:33,915 We, we know that workforce challenges are top of mind 57 00:02:33,915 --> 00:02:35,035 for healthcare leaders. 58 00:02:35,515 --> 00:02:37,875 Probably nothing more top of mind, both in terms 59 00:02:37,875 --> 00:02:41,115 of the rising cost of labor, the shortage of clinicians, 60 00:02:41,215 --> 00:02:43,595 and the ability to sort of work through throughput 61 00:02:43,595 --> 00:02:45,315 to make things actually work efficiently 62 00:02:45,895 --> 00:02:46,995 in this challenging time. 63 00:02:47,775 --> 00:02:49,755 The, eh, a's latest, it show 64 00:02:50,025 --> 00:02:54,275 that there's been a 20.8% increase in hospital labor cost. 65 00:02:54,575 --> 00:02:56,395 And so just trying to make sure things work 66 00:02:56,395 --> 00:02:57,675 relatively efficiently. 67 00:02:58,135 --> 00:03:00,605 Uh, we've also seen that that increase 68 00:03:00,605 --> 00:03:04,605 of 21% almost from 2019 to 2022. 69 00:03:05,315 --> 00:03:07,445 There's also, I think the latest numbers 70 00:03:07,445 --> 00:03:12,165 that we saw are 33% more open nursing roles now 71 00:03:12,165 --> 00:03:13,365 than they were three years ago. 72 00:03:13,945 --> 00:03:15,245 Uh, and, 73 00:03:15,305 --> 00:03:18,645 and we also have at least a hundred thousand physician 74 00:03:18,925 --> 00:03:20,805 shortage, 90 to a hundred thousand physician shortage. 75 00:03:21,145 --> 00:03:23,925 And that number with 330 million people in our nation 76 00:03:24,385 --> 00:03:26,365 and only 1,000,070 thousand physicians, 77 00:03:26,595 --> 00:03:28,405 that gap is becoming bigger 78 00:03:28,505 --> 00:03:31,645 and bigger of the sort of clinicians needed, the providers, 79 00:03:31,645 --> 00:03:32,645 the nurses, and the techs and 80 00:03:32,645 --> 00:03:33,645 everybody else to make these work. 81 00:03:34,225 --> 00:03:35,845 And, and let me ask you, you work 82 00:03:35,885 --> 00:03:38,365 with more than 200 health systems, more than 5,000, 83 00:03:38,365 --> 00:03:39,445 6,000 operating rooms. 84 00:03:40,235 --> 00:03:43,085 What are you hearing anecdotally from leaders about 85 00:03:43,085 --> 00:03:44,925 where this is getting worse, better? 86 00:03:45,065 --> 00:03:46,445 The same? What, what are you hearing 87 00:03:46,445 --> 00:03:47,525 from people that you talk to? 88 00:03:48,175 --> 00:03:49,485 - Scott? That's a huge issue. 89 00:03:49,845 --> 00:03:52,085 Staffing shortages have actually been an issue 90 00:03:52,105 --> 00:03:54,285 for quite a while, even before the pandemic. 91 00:03:54,835 --> 00:03:57,765 What the pandemic did was high heighten the severity 92 00:03:57,785 --> 00:04:01,765 of the situation and the urgency for health systems 93 00:04:01,905 --> 00:04:03,245 to make a concerted effort 94 00:04:03,625 --> 00:04:07,405 to get better at optimizing their approach to staffing. 95 00:04:07,985 --> 00:04:09,925 And the reason it's important is it 96 00:04:09,925 --> 00:04:11,365 affects all type of staff. 97 00:04:11,595 --> 00:04:13,565 Provide a burnout is a real thing. 98 00:04:14,225 --> 00:04:16,005 The EHR was supposed to have helped, 99 00:04:16,385 --> 00:04:19,845 but instead, providers are spending more time on EHR screens 100 00:04:20,075 --> 00:04:21,485 than they are talking with patients, 101 00:04:22,345 --> 00:04:23,885 and they have a lot of pajama time, 102 00:04:24,015 --> 00:04:26,845 which is their short form for catching up on 103 00:04:27,685 --> 00:04:30,485 EHR documentation from home after dinner 104 00:04:30,555 --> 00:04:32,045 because they need to do that. 105 00:04:32,725 --> 00:04:34,335 Nursing shortage is also real. 106 00:04:34,655 --> 00:04:37,495 Hospitals are spending much more money on travelers 107 00:04:37,495 --> 00:04:40,495 and on contract nursing than they ever have in the past. 108 00:04:41,275 --> 00:04:43,615 So the way this manifests, uh, 109 00:04:43,755 --> 00:04:47,975 and we see it every day, is hospitals operating well 110 00:04:48,185 --> 00:04:49,695 below their rated capacity. 111 00:04:50,045 --> 00:04:52,855 They're running fewer beds than they're licensed to run, 112 00:04:52,995 --> 00:04:54,935 or they are running fewer operating rooms 113 00:04:55,285 --> 00:04:56,535 than they've actually built. 114 00:04:57,115 --> 00:05:00,015 And so this shortage in capacity 115 00:05:00,405 --> 00:05:01,655 then affects everything else. 116 00:05:01,795 --> 00:05:04,135 And so it's a real problem and, and pretty significant. 117 00:05:05,435 --> 00:05:07,855 - No, thank you. And this is what we hear and see as well. 118 00:05:07,995 --> 00:05:09,935 So thank you for sharing that vantage point. 119 00:05:11,075 --> 00:05:14,575 We toss has products that help sort of work and, 120 00:05:14,635 --> 00:05:17,375 and logistics and drive efficiency and throughput 121 00:05:17,795 --> 00:05:20,015 and help people manage their operating rooms, 122 00:05:20,015 --> 00:05:22,775 their infusion centers, their inpatient bed beds better. 123 00:05:23,675 --> 00:05:25,935 How do your solutions help staff do their jobs better 124 00:05:26,035 --> 00:05:29,015 and reconnect with the joy, the sort of pleasure of actually 125 00:05:29,705 --> 00:05:32,455 practicing or taking care of people versus spending 126 00:05:32,515 --> 00:05:33,695 so much time in the e emr, 127 00:05:33,695 --> 00:05:34,975 so much time on their own screens? 128 00:05:35,315 --> 00:05:36,575 How, how does that help? Uh, 129 00:05:36,595 --> 00:05:37,735 how does this help your workforce? 130 00:05:37,755 --> 00:05:38,755 The workforce, 131 00:05:39,395 --> 00:05:42,935 - If you step back and look at it, optimizing patient flow 132 00:05:42,935 --> 00:05:45,255 through a health system has two pieces to it. 133 00:05:45,785 --> 00:05:49,175 First is optimizing the utilization of the physical asset, 134 00:05:49,175 --> 00:05:51,375 whether it's an operating room, an imaging machine, 135 00:05:51,395 --> 00:05:53,735 an infusion chair, or an inpatient bed. 136 00:05:53,955 --> 00:05:57,245 And then the second piece is optimizing the allocation 137 00:05:57,265 --> 00:06:00,445 of staff associated with that asset in patients. 138 00:06:00,445 --> 00:06:01,925 There are two distinct pieces to it. 139 00:06:02,745 --> 00:06:06,005 Now, the core concept underlying all 140 00:06:06,005 --> 00:06:09,845 of our products is the continuous balance of supply 141 00:06:09,845 --> 00:06:12,245 and demand using sophisticated math 142 00:06:12,245 --> 00:06:15,985 and AI in manufacturing, if there's an imbalance 143 00:06:15,985 --> 00:06:18,865 between supply and demand, you can easily offset it 144 00:06:18,865 --> 00:06:20,545 by just changing the inventory level. 145 00:06:20,845 --> 00:06:23,265 You either manufacture and put it to inventory 146 00:06:23,365 --> 00:06:24,585 or pull it from inventory. 147 00:06:25,075 --> 00:06:28,585 Healthcare has to balance it continuously if they don't, 148 00:06:28,585 --> 00:06:29,985 because you cannot inventory anything. 149 00:06:30,365 --> 00:06:33,425 And if you don't balance it, either a patient waits, 150 00:06:33,435 --> 00:06:34,825 which we see all too often, 151 00:06:35,205 --> 00:06:38,425 or a provider waits, which obviously is frustrating to them, 152 00:06:39,125 --> 00:06:41,345 or an expensive asset just sits idle, 153 00:06:41,595 --> 00:06:43,705 we've all seen $5 million MRI 154 00:06:43,705 --> 00:06:46,385 and CT machines sitting around with no patient in them. 155 00:06:47,045 --> 00:06:51,635 So what our solutions do is first predict the volume 156 00:06:51,855 --> 00:06:55,555 and the type of demand with a stunning level of accuracy. 157 00:06:55,655 --> 00:06:57,155 You have to predict that at a granular 158 00:06:57,155 --> 00:06:58,515 level, highly accurate. 159 00:06:59,065 --> 00:07:00,915 Then you have to understand the supply side, 160 00:07:00,915 --> 00:07:03,395 what the constraints are, facilities, staff, 161 00:07:03,545 --> 00:07:05,155 equipment rooms, et cetera. 162 00:07:05,335 --> 00:07:07,395 And then you figure out the optimal allocation 163 00:07:07,395 --> 00:07:08,435 between supply and demand 164 00:07:08,815 --> 00:07:10,875 to keep patients moving through the system. 165 00:07:11,785 --> 00:07:15,195 When we look at most staffing systems that are out there, 166 00:07:15,505 --> 00:07:18,275 they've essentially grown up over the last 20 years being 167 00:07:18,275 --> 00:07:19,355 time on attendance systems. 168 00:07:19,775 --> 00:07:22,155 That's what they were. So they kept track of 169 00:07:22,175 --> 00:07:24,435 who worked in which unit, how many hours they worked, 170 00:07:24,775 --> 00:07:27,155 was it overtime, was it bonus, double time, et cetera, 171 00:07:27,495 --> 00:07:28,715 and how they should get paid. 172 00:07:29,305 --> 00:07:31,035 This has nothing to do with optimization. 173 00:07:31,105 --> 00:07:34,435 This is a administrative payroll kind of a function. 174 00:07:34,855 --> 00:07:38,835 And so what we find is when you do the optimization, 175 00:07:38,835 --> 00:07:40,875 the way we are talking about, you can then 176 00:07:41,435 --> 00:07:44,275 construct shift schedules and rosters to meet the demand. 177 00:07:44,815 --> 00:07:47,755 And then you start making intelligent recommendations. 178 00:07:48,455 --> 00:07:51,155 Now, if you think about what burns people out 179 00:07:51,155 --> 00:07:52,955 and what, what causes frustration, 180 00:07:54,405 --> 00:07:56,295 frontline staff every day 181 00:07:56,955 --> 00:07:59,655 are highly skilled people doing menial tasks. 182 00:07:59,965 --> 00:08:02,415 They're pulling numbers, they're sending text messages, 183 00:08:02,415 --> 00:08:04,495 they're leaving voicemails, they're chasing people. 184 00:08:05,435 --> 00:08:06,935 All of this could have been automated. 185 00:08:07,475 --> 00:08:09,415 And so we help, we believe 186 00:08:09,415 --> 00:08:12,775 that if we help staff anticipate what's coming 187 00:08:12,775 --> 00:08:15,935 through prediction, reduce their cognitive overload 188 00:08:15,995 --> 00:08:18,495 by making intelligent recommendations so they don't have 189 00:08:18,495 --> 00:08:19,815 to think as hard, uh, 190 00:08:20,235 --> 00:08:22,855 and then you automate the routine tasks, 191 00:08:23,715 --> 00:08:25,615 you will free up their mind space, 192 00:08:25,665 --> 00:08:28,615 which then they can go back to doing what they love, 193 00:08:28,665 --> 00:08:30,015 which is taking care of patients. 194 00:08:30,395 --> 00:08:32,295 And so that is what we believe is the core. 195 00:08:33,315 --> 00:08:37,655 - So, so in the ideal situation, a much, much greater fit 196 00:08:37,655 --> 00:08:39,335 of supply and demand and, 197 00:08:39,355 --> 00:08:43,135 and a lot of taking the logistics, at least the, the out 198 00:08:43,135 --> 00:08:46,055 of the, the paper, the logistics, the guessing logistics 199 00:08:46,055 --> 00:08:48,615 and so forth so that nurses, physicians, 200 00:08:48,615 --> 00:08:50,815 clinicians can spend more time just taking care 201 00:08:50,815 --> 00:08:52,255 of patients versus worrying 202 00:08:52,355 --> 00:08:54,655 so much about is black time being used as it not being used 203 00:08:54,655 --> 00:08:56,330 as this person showing up and they're not showing up? 204 00:08:56,465 --> 00:08:57,605 How are we turning over operating 205 00:08:57,605 --> 00:08:58,845 rooms and, and everything else? 206 00:08:59,835 --> 00:09:04,045 Talk to us now about how AI is gonna sort of help 207 00:09:04,045 --> 00:09:05,525 to revolutionize this. 208 00:09:05,935 --> 00:09:07,845 There, there's lots of concerns from people. 209 00:09:08,385 --> 00:09:09,725 Is AI gonna take away jobs? 210 00:09:10,105 --> 00:09:14,245 Is it going to replace human jobs or, or, or, 211 00:09:14,385 --> 00:09:16,885 or get, get rid of roles. 212 00:09:17,085 --> 00:09:19,245 I mean, we've seen some of this automation in some places 213 00:09:19,335 --> 00:09:21,245 where, you know, you go to your bank 214 00:09:21,265 --> 00:09:23,565 and there used to be a teller and now it's an ATM, 215 00:09:23,565 --> 00:09:25,045 and of course we've all going to love that, 216 00:09:25,425 --> 00:09:28,005 but people are still concerned about is this gonna hurt jobs 217 00:09:28,145 --> 00:09:29,445 and is this gonna take away jobs? 218 00:09:30,545 --> 00:09:34,285 How do you get buy-in from overburdened frontline staff to 219 00:09:34,385 --> 00:09:38,205 to, to try and implement some of this technology 220 00:09:39,235 --> 00:09:41,125 when some technology that they work with 221 00:09:41,715 --> 00:09:43,245 creates more harm than help? 222 00:09:43,265 --> 00:09:44,325 You talked about the EMR, and 223 00:09:44,325 --> 00:09:45,605 obviously we're not living without the EMRs. 224 00:09:45,805 --> 00:09:47,125 EMRs have been extremely helpful, 225 00:09:47,665 --> 00:09:49,565 but they have added a level of burden 226 00:09:50,035 --> 00:09:52,045 that people didn't expect and exactly. 227 00:09:52,045 --> 00:09:53,045 You talked about people coming home, 228 00:09:53,045 --> 00:09:54,525 you talked about pajama time, people being at 229 00:09:54,525 --> 00:09:55,645 home, working in those things. 230 00:09:56,195 --> 00:10:00,165 What mindset shift has to occur for staff to buy into, 231 00:10:00,165 --> 00:10:02,765 to feel like AI is helping versus adding more 232 00:10:02,765 --> 00:10:04,045 burdens or taking away jobs? 233 00:10:04,465 --> 00:10:08,125 How do you sort of get positive clinician buy-in 234 00:10:08,465 --> 00:10:10,765 to new technology and AI driven technology? 235 00:10:12,025 --> 00:10:14,445 - The first thing is, it's important to be realistic 236 00:10:14,625 --> 00:10:17,965 and not over promise what AI can do for the frontline. 237 00:10:18,585 --> 00:10:22,125 The way we think about it is it's augmented intelligence. 238 00:10:22,155 --> 00:10:23,605 It's not artificial intelligence 239 00:10:23,605 --> 00:10:24,965 that replaces the human being. 240 00:10:25,545 --> 00:10:28,845 It just gives them a set of recommendations 241 00:10:28,845 --> 00:10:32,755 that are intelligent and that they can think about 242 00:10:32,975 --> 00:10:34,835 and perhaps consider making. 243 00:10:35,695 --> 00:10:38,235 So in our view, the frontline has, 244 00:10:38,335 --> 00:10:40,675 has the final mile of decision making. 245 00:10:41,055 --> 00:10:43,155 So we prescribe intelligent recommendations, 246 00:10:43,575 --> 00:10:46,915 but we expect that the frontline has got clinical context, 247 00:10:47,225 --> 00:10:49,035 patient context, provider context, 248 00:10:49,465 --> 00:10:51,635 that they should make the final override 249 00:10:51,695 --> 00:10:53,195 or go no-go decision on it. 250 00:10:53,575 --> 00:10:55,835 The black box should not make the decision for them. 251 00:10:56,455 --> 00:10:57,835 So the way we think about it is, 252 00:10:57,985 --> 00:11:00,115 imagine the navigation system in your car. 253 00:11:00,585 --> 00:11:04,235 It's constantly suggesting an intelligent route to get 254 00:11:04,255 --> 00:11:05,715 to your destination faster, 255 00:11:06,535 --> 00:11:09,835 but you as the driver can always override it based 256 00:11:09,835 --> 00:11:10,955 on your unique knowledge. 257 00:11:11,375 --> 00:11:15,635 If it's late at night on the freeway in a not so great part 258 00:11:15,635 --> 00:11:17,715 of town, and it tells you, Hey, get off the freeway 259 00:11:17,775 --> 00:11:20,115 and you can say five minutes, you might say, yeah, 260 00:11:20,175 --> 00:11:21,355 no, I don't want to get off the freeway. 261 00:11:21,925 --> 00:11:24,595 Right? So you've applied the last minute judgment 262 00:11:24,945 --> 00:11:26,035 that overrides it. 263 00:11:26,265 --> 00:11:27,795 What does the navigation system do? 264 00:11:27,895 --> 00:11:29,235 It reacts to that and says, fine, 265 00:11:29,255 --> 00:11:31,395 and it suggests the next best route. 266 00:11:31,695 --> 00:11:33,555 And you can constantly override it 267 00:11:33,645 --> 00:11:36,875 until you think it's got a good idea, uh, and you follow it. 268 00:11:37,055 --> 00:11:40,475 So what happens over time is the frontline gains confidence 269 00:11:40,705 --> 00:11:42,835 that the recommendations are actually intelligent 270 00:11:43,295 --> 00:11:45,515 and they start relying on it more and more. 271 00:11:45,695 --> 00:11:48,675 And it starts to feel natural, just like we all do 272 00:11:48,675 --> 00:11:51,275 with Netflix recommendations when it recommends movies 273 00:11:51,335 --> 00:11:53,525 to us, it turns out it's pretty accurate. 274 00:11:53,745 --> 00:11:56,285 Or Amazon recommends things for us to buy 275 00:11:56,745 --> 00:11:58,645 or on navigation systems, as I said, right? 276 00:11:58,825 --> 00:12:00,125 So the same clinicians 277 00:12:00,125 --> 00:12:03,325 and providers who are unwilling 278 00:12:03,325 --> 00:12:06,165 to accept an AI recommendation at the end of the day, 279 00:12:06,265 --> 00:12:07,965 get into the their cars and drive home 280 00:12:07,965 --> 00:12:10,125 and happily accept all the navigation 281 00:12:10,125 --> 00:12:11,245 system recommendations. 282 00:12:11,265 --> 00:12:14,245 And so we just have to, uh, make sure we do that. 283 00:12:14,745 --> 00:12:17,205 The other thing we have to do is not pretend 284 00:12:17,205 --> 00:12:18,565 to have expertise we don't have. 285 00:12:19,345 --> 00:12:22,685 So when we make operational recommendations, we don't try 286 00:12:22,685 --> 00:12:25,205 and make clinical recommendations where we are trying 287 00:12:25,205 --> 00:12:27,965 to out dock the docs where we pretend 288 00:12:27,965 --> 00:12:29,005 to have clinical judgment 289 00:12:29,005 --> 00:12:30,725 that exceeds theirs because we don't. 290 00:12:31,185 --> 00:12:34,325 So we are very clear that we've got operational expertise, 291 00:12:34,535 --> 00:12:36,725 we'll make excellent operational recommendations 292 00:12:37,185 --> 00:12:40,125 and leave the clinical judgment to the people who know best. 293 00:12:41,885 --> 00:12:43,315 - Thank you. It's a, it's a fascinating 294 00:12:43,315 --> 00:12:44,995 and brilliant perspective as to how to look at this 295 00:12:45,015 --> 00:12:46,835 and compare it to the sort of navigation system, 296 00:12:46,835 --> 00:12:49,315 Netflix suggestions, the Amazon suggestions, right? 297 00:12:49,455 --> 00:12:50,875 We get that, the choices and ideas, 298 00:12:51,015 --> 00:12:52,235 and then we decide, are we 299 00:12:52,235 --> 00:12:53,355 doing this or we're not doing that. 300 00:12:53,355 --> 00:12:54,675 Exactly. And I think that's a, 301 00:12:54,755 --> 00:12:55,875 a brilliant way to look at it. 302 00:12:55,875 --> 00:12:57,835 And all those things, as you know, have gotten 303 00:12:57,895 --> 00:12:59,675 so good at making those suggestions. 304 00:13:00,015 --> 00:13:01,275 So they're easy to make a choice. 305 00:13:01,415 --> 00:13:03,035 I'm gonna continue on my route, I'm gonna take the 306 00:13:03,035 --> 00:13:04,675 suggestion, but there's not so much 307 00:13:05,195 --> 00:13:07,875 internal fighting over trying to figure out what am I doing? 308 00:13:07,935 --> 00:13:09,675 We sort of react to it very naturally 309 00:13:11,225 --> 00:13:14,755 from other applications, previous AI 310 00:13:14,895 --> 00:13:18,915 and analytics implementation line, what, you know, in, in 311 00:13:18,915 --> 00:13:21,155 regarding what have you learned 312 00:13:21,615 --> 00:13:23,835 or what have we all learned in healthcare from previous 313 00:13:23,865 --> 00:13:25,235 efforts in AI 314 00:13:25,335 --> 00:13:27,195 and analytics implementations in healthcare 315 00:13:27,505 --> 00:13:29,475 regarding things like stakeholder engagement. 316 00:13:29,475 --> 00:13:31,595 How, how much will the stakeholder actually use it? 317 00:13:31,595 --> 00:13:32,995 We all, we all are familiar with, 318 00:13:33,215 --> 00:13:35,355 you guys have done this brilliant job of making the software 319 00:13:35,375 --> 00:13:37,275 and, and, and wing toss on the system 320 00:13:37,275 --> 00:13:38,395 that people actually use, 321 00:13:38,695 --> 00:13:39,875 but we're all familiar with lots 322 00:13:39,875 --> 00:13:40,875 of systems people have bought 323 00:13:41,095 --> 00:13:42,675 and they use by 1% of the workforce, 324 00:13:42,675 --> 00:13:45,115 or you only use, you know, 10% 325 00:13:45,115 --> 00:13:46,635 of the applicability and so forth. 326 00:13:47,025 --> 00:13:49,635 What have we learned about stakeholder engagement culture 327 00:13:49,735 --> 00:13:52,115 and change management that could be applied now 328 00:13:52,255 --> 00:13:55,155 to health systems to make them better users of AI 329 00:13:55,155 --> 00:13:56,235 and better users of systems? 330 00:13:58,025 --> 00:14:00,985 - I think the first thing is that senior leadership has 331 00:14:00,985 --> 00:14:03,345 to buy in into one simple fact. 332 00:14:04,395 --> 00:14:09,095 The operational complexity of healthcare has gone up by 10 x 333 00:14:09,095 --> 00:14:11,655 or a hundred x in the last 10 or 15 years, 334 00:14:12,515 --> 00:14:16,095 but the operational practices have not kept up with 335 00:14:16,095 --> 00:14:17,535 that growth of complexity. 336 00:14:17,845 --> 00:14:19,935 They still pull dashboards from EHRs. 337 00:14:19,935 --> 00:14:21,535 They manually do the best they can. 338 00:14:22,085 --> 00:14:25,055 This is just not gonna be good enough on a go forward basis. 339 00:14:25,435 --> 00:14:27,615 So senior leadership has to accept that concept. 340 00:14:28,365 --> 00:14:32,055 Then they have to be committed to exploring the art 341 00:14:32,055 --> 00:14:35,975 of the possible to just start to understand the level 342 00:14:35,995 --> 00:14:38,655 of sophistication that's inside things. 343 00:14:38,655 --> 00:14:40,855 We take for granted the yield management 344 00:14:40,855 --> 00:14:42,495 and airlines, how they fill planes 345 00:14:42,915 --> 00:14:45,295 or other com operationally complex environments 346 00:14:45,635 --> 00:14:47,295 and how it might be applied to healthcare. 347 00:14:47,865 --> 00:14:49,095 Could you just step back for a moment 348 00:14:49,155 --> 00:14:53,605 and imagine what would happen if airlines assign seats 349 00:14:53,625 --> 00:14:56,805 to passengers the way health systems assign appointments 350 00:14:56,805 --> 00:14:58,125 to patients, right? 351 00:14:58,505 --> 00:15:01,645 Or if airlines allocated pilots 352 00:15:01,645 --> 00:15:06,165 and aircraft to routes the way health system assign ORs 353 00:15:06,165 --> 00:15:08,765 to surgeons or service lines, that would just, 354 00:15:08,825 --> 00:15:11,445 it would just be permanently gridlocked. 355 00:15:11,785 --> 00:15:13,725 And we can see what happens once in a while. 356 00:15:13,725 --> 00:15:16,125 There's a big storm or a software outage 357 00:15:16,315 --> 00:15:19,045 that throws airline operations outta whack for two days, 358 00:15:19,465 --> 00:15:21,605 and it's the news, it's everywhere. 359 00:15:22,435 --> 00:15:24,215 The reality is health systems are operating in 360 00:15:24,215 --> 00:15:25,495 that state pretty much every day. 361 00:15:25,645 --> 00:15:28,175 They're at the edge of capacity, uh, 362 00:15:28,315 --> 00:15:30,495 and they're making operational decisions manually. 363 00:15:30,875 --> 00:15:33,455 So they are almost operating in that manner every day. 364 00:15:33,475 --> 00:15:36,575 So the first thing is you need change the senior leadership 365 00:15:36,955 --> 00:15:40,935 to buy into the complexity and it takes different tools 366 00:15:41,035 --> 00:15:43,215 and then the mindset to explore the art of the possible. 367 00:15:43,755 --> 00:15:47,175 Second is everybody talks about change management 368 00:15:47,175 --> 00:15:49,735 and it's very important, but here's the interesting thing. 369 00:15:50,355 --> 00:15:52,455 The frontline wants to do the right thing. 370 00:15:53,005 --> 00:15:55,255 They want to take care of patients, they want 371 00:15:55,255 --> 00:15:56,855 to do it in a safe and effective manner. 372 00:15:57,115 --> 00:15:59,175 So you know how to fight the frontline 373 00:15:59,875 --> 00:16:01,375 to do something they don't want to do. 374 00:16:01,375 --> 00:16:02,495 That's when change management 375 00:16:02,495 --> 00:16:04,095 and you're trying to persuade someone 376 00:16:04,115 --> 00:16:05,815 to do something they don't want to do. 377 00:16:06,485 --> 00:16:09,775 They want to do this, they just need better tools to do it. 378 00:16:10,155 --> 00:16:13,535 So if you can persuade them that what we are providing 379 00:16:14,385 --> 00:16:16,565 is easy, it's intuitive, 380 00:16:17,185 --> 00:16:18,805 and they can do the right thing all the time, 381 00:16:19,225 --> 00:16:21,885 it soon becomes in their enlightened self-interest 382 00:16:21,885 --> 00:16:24,605 to use the tools, you're now not trying to fool them 383 00:16:24,625 --> 00:16:27,165 or persuade them or cajole them or threaten them to use it. 384 00:16:27,555 --> 00:16:29,125 They just find it's easier 385 00:16:29,305 --> 00:16:31,565 to do the right thing quickly all the time. 386 00:16:32,175 --> 00:16:34,685 Think about it, nobody from Uber came to my house 387 00:16:35,185 --> 00:16:38,605 to apply change management psychology to me, to convince me 388 00:16:38,605 --> 00:16:39,925 to start using the Uber app. 389 00:16:40,465 --> 00:16:43,725 It is just the simply the best way to go from point A 390 00:16:43,725 --> 00:16:44,845 to point B at short notice. 391 00:16:45,125 --> 00:16:48,765 I therefore use it. There was no Uber change management, uh, 392 00:16:48,765 --> 00:16:50,205 school that they had to run for me. 393 00:16:50,545 --> 00:16:53,245 So that's what we aspire to do with our tools. 394 00:16:53,555 --> 00:16:54,845 Make it easy and intuitive 395 00:16:54,865 --> 00:16:56,245 to do the right thing all the time. 396 00:16:57,755 --> 00:17:01,015 - No, and it's, and it's so critical that ease of usability 397 00:17:01,835 --> 00:17:03,935 so people can, can start to plug in 398 00:17:03,935 --> 00:17:06,815 and use it without feeling like there's incredible learning 399 00:17:06,815 --> 00:17:08,495 curve or incredible challenges to it. 400 00:17:09,035 --> 00:17:10,975 To, to, to making it useful 401 00:17:11,035 --> 00:17:13,895 and not having to go through an incredible amount 402 00:17:13,895 --> 00:17:16,175 of change management, but actually easy to use. 403 00:17:16,175 --> 00:17:18,215 You start to adopt it, you start to use it and, 404 00:17:18,215 --> 00:17:20,735 and you love it and it makes sense to do the right thing. 405 00:17:21,215 --> 00:17:22,455 I I love that perspective. 406 00:17:23,235 --> 00:17:26,135 One of things that's being talked about right now, just to, 407 00:17:26,195 --> 00:17:27,655 to take it to one further 408 00:17:28,355 --> 00:17:30,335 diving into the workforce issue on this, 409 00:17:30,715 --> 00:17:33,575 is there's a tremendous amount of clinician burnout. 410 00:17:34,115 --> 00:17:36,135 You know, different articles talk about, there's a, 411 00:17:36,255 --> 00:17:40,415 a recent article journal of general internal medicine report 412 00:17:40,415 --> 00:17:43,135 that shows 50% of all healthcare professionals are, 413 00:17:43,135 --> 00:17:44,255 are burnt out some way 414 00:17:44,255 --> 00:17:46,295 or another are, are at least facing burnout. 415 00:17:47,395 --> 00:17:51,125 How can technology positively impacts staff burnout versus 416 00:17:51,125 --> 00:17:53,605 being another burden on top of, of people 417 00:17:53,745 --> 00:17:55,485 or just sort of operationally, 418 00:17:56,225 --> 00:17:58,445 but aside from sort of improving operational metrics, 419 00:17:58,955 --> 00:18:00,325 helping us deal with supply 420 00:18:00,325 --> 00:18:02,845 and demand, how can it actually help sort 421 00:18:02,845 --> 00:18:04,845 of clinician burnout and, 422 00:18:04,845 --> 00:18:07,725 and positively impact the human situation? 423 00:18:08,885 --> 00:18:11,355 - Let's think about all the things that cause stress. 424 00:18:12,385 --> 00:18:13,875 Operating at the edge 425 00:18:13,875 --> 00:18:17,115 of capacity every single day is exhausting. 426 00:18:17,625 --> 00:18:20,955 Imagine if you had to drive in rush hour traffic nonstop 427 00:18:20,955 --> 00:18:23,275 for eight to 10 hours every single day, right? 428 00:18:23,275 --> 00:18:24,715 We get away with rush hour traffic 429 00:18:24,715 --> 00:18:27,315 because an hour in each direction and we call it a day. 430 00:18:27,575 --> 00:18:30,635 But the, the frontline staff is living in rush hour 431 00:18:30,635 --> 00:18:32,875 conditions where everything is a crisis 432 00:18:33,015 --> 00:18:34,075 and everything comes at them. 433 00:18:34,415 --> 00:18:38,035 So that's one source of, uh, exhaustion that comes in. 434 00:18:39,115 --> 00:18:41,595 Spending a large chunk of your day doing routine 435 00:18:42,155 --> 00:18:44,315 mundane tasks that are way beyond your skilled 436 00:18:44,995 --> 00:18:46,715 licensed level is frustrating. 437 00:18:47,375 --> 00:18:49,035 And yet we force our frontline 438 00:18:49,055 --> 00:18:50,955 to do a lot of mundane things. 439 00:18:51,335 --> 00:18:54,195 And here they are highly qualified nurses and caregivers 440 00:18:54,455 --> 00:18:57,315 and we are forcing them to pull data from spreadsheets 441 00:18:57,315 --> 00:18:58,355 and cut and paste into things. 442 00:18:59,835 --> 00:19:03,295 Having the staff feel overwhelmed all the time where 443 00:19:03,805 --> 00:19:08,295 they're reacting to issues one at a time, somehow getting 444 00:19:08,295 --> 00:19:11,015 through it only to have the next issue and the next issue 445 00:19:11,015 --> 00:19:14,095 and the next issue come at, come at them like a tsunami. 446 00:19:14,605 --> 00:19:17,095 They somehow power through it, get through the day, 447 00:19:17,635 --> 00:19:19,655 and then like groundhog data will happen again tomorrow. 448 00:19:20,085 --> 00:19:23,575 That is stressful. Imagine if they could anticipate the 449 00:19:23,575 --> 00:19:25,215 issues, prepare for it in advance 450 00:19:25,595 --> 00:19:27,375 and not have to deal with it, right? 451 00:19:27,375 --> 00:19:28,935 Just think about going through life. 452 00:19:28,955 --> 00:19:30,375 If everything was a surprise to you, 453 00:19:30,645 --> 00:19:33,215 life would be a lot more stressful than if you could plan 454 00:19:33,235 --> 00:19:35,815 what's happening today, tomorrow, next week, next month. 455 00:19:36,155 --> 00:19:39,335 And then finally, they are forced to make decisions 456 00:19:39,765 --> 00:19:42,015 that are not just minor decisions. 457 00:19:42,015 --> 00:19:44,495 They impact a patient's health, maybe their life, 458 00:19:44,995 --> 00:19:47,295 and they don't have all the information at their fingertips. 459 00:19:47,295 --> 00:19:49,015 They don't have access to everything they need. 460 00:19:49,275 --> 00:19:51,415 And that creates anxiety that I am, 461 00:19:51,415 --> 00:19:52,575 I sure I'm doing the right thing. 462 00:19:52,955 --> 00:19:55,295 And, and so we've got many things 463 00:19:55,295 --> 00:19:59,975 that create the perfect storm from the manual tasks 464 00:20:00,195 --> 00:20:02,615 to the being overwhelmed to, you know, 465 00:20:02,615 --> 00:20:04,375 not having all the information at your fingertips 466 00:20:04,485 --> 00:20:06,095 that causes the, the stress. 467 00:20:06,155 --> 00:20:10,375 And we think that our approach to it can, uh, uh, you know, 468 00:20:10,375 --> 00:20:11,695 can solve many of the problems. 469 00:20:11,695 --> 00:20:14,335 Obviously we can't solve every problem in front of them, 470 00:20:14,355 --> 00:20:16,135 but we can do a lot to alleviate, 471 00:20:16,135 --> 00:20:17,655 alleviate the stress in the burnout. 472 00:20:19,075 --> 00:20:20,855 - But, but your point on this concept 473 00:20:20,955 --> 00:20:23,655 of living in a relatively constant fire trail, 474 00:20:23,755 --> 00:20:25,615 and it's not always the case, but it's, 475 00:20:25,615 --> 00:20:27,655 but it's a lot the case reminds you of 476 00:20:27,655 --> 00:20:29,055 where when travel goes wrong 477 00:20:29,395 --> 00:20:30,695 and how stressed out the staff 478 00:20:30,695 --> 00:20:31,895 is 'cause travel has gone wrong. 479 00:20:32,055 --> 00:20:33,455 'cause they're dealing with every single person trying 480 00:20:33,455 --> 00:20:35,095 to change and figure out what flight to get on, 481 00:20:35,395 --> 00:20:37,615 and they don't necessarily have all the logistics to do it. 482 00:20:37,615 --> 00:20:39,655 Well, is is the situation you're talking about, 483 00:20:39,655 --> 00:20:41,975 that stress level is very constant in, 484 00:20:41,975 --> 00:20:42,975 in large health systems. 485 00:20:43,115 --> 00:20:46,135 And so your point on how can we make that more planned, 486 00:20:46,325 --> 00:20:49,285 more, more systematic, a a little bit less stress, 487 00:20:49,365 --> 00:20:52,205 a little bit less fire drills goes a long way in terms 488 00:20:52,205 --> 00:20:53,765 of making just the environment easier 489 00:20:53,905 --> 00:20:55,565 to work in? , you're 490 00:20:55,565 --> 00:20:56,565 - Exactly right, Scott. 491 00:20:56,565 --> 00:20:58,405 They, they call it, uh, airlines, call it iop, 492 00:20:58,475 --> 00:20:59,645 irregular operations. 493 00:21:00,145 --> 00:21:01,805 So when, uh, there's a storm in Chicago 494 00:21:01,985 --> 00:21:04,645 and 2000 people have missed their connecting flights 495 00:21:04,645 --> 00:21:05,925 and you need to rebook them, 496 00:21:06,275 --> 00:21:09,005 there's a whole different method that comes into play 497 00:21:09,255 --> 00:21:11,685 where the airline is in IOP mode, 498 00:21:11,685 --> 00:21:13,165 where they're in irregular operations 499 00:21:13,545 --> 00:21:16,285 and their goal is to get out of IO into regular operations 500 00:21:16,285 --> 00:21:17,285 as quickly as they can. 501 00:21:17,905 --> 00:21:19,325 And your point's exactly right, 502 00:21:19,325 --> 00:21:23,165 health systems are often operating always in IOP mode, 503 00:21:23,225 --> 00:21:25,125 and that's what, uh, is stressful. 504 00:21:26,235 --> 00:21:27,685 - That sounds exactly right. 505 00:21:28,705 --> 00:21:29,925 You and a colleague, 506 00:21:29,955 --> 00:21:32,285 co-authored the book on hospital operations, 507 00:21:32,805 --> 00:21:34,605 a brilliant book on Better Healthcare 508 00:21:34,605 --> 00:21:37,325 through math is I think the title of, I've got that right. 509 00:21:37,625 --> 00:21:39,085 Is it, is that right? That's right. 510 00:21:39,785 --> 00:21:41,045 In in the year ahead, 511 00:21:41,955 --> 00:21:43,845 what do you anticipate will be the biggest, 512 00:21:44,025 --> 00:21:46,005 the single biggest challenge that 513 00:21:46,005 --> 00:21:48,645 that hospital executive teams and leadership teams face? 514 00:21:49,025 --> 00:21:51,445 And, and, and how can leaders stay ahead of that now? 515 00:21:51,445 --> 00:21:52,805 What, what are the biggest challenges 516 00:21:52,865 --> 00:21:53,805 or the biggest challenge that 517 00:21:53,805 --> 00:21:54,725 operations teams are gonna face? 518 00:21:55,395 --> 00:21:56,965 - Yeah, so staying on the operational side, 519 00:21:56,965 --> 00:21:58,725 because obviously clinical, there's a whole bunch of things. 520 00:21:58,985 --> 00:22:00,325 We are not expert on the clinical, 521 00:22:00,745 --> 00:22:03,925 but if I think about the single biggest challenge from an 522 00:22:03,925 --> 00:22:07,525 operational perspective for health system leaders is 523 00:22:07,545 --> 00:22:10,525 to do more with the existing assets 524 00:22:10,665 --> 00:22:13,965 and the existing staff that are already in place now, right? 525 00:22:14,345 --> 00:22:17,725 In the past, health systems could simply build their way 526 00:22:17,725 --> 00:22:18,805 out of operational problems. 527 00:22:18,955 --> 00:22:20,725 When they ran into operational problems, 528 00:22:20,915 --> 00:22:23,485 they constructed more hospitals, put in more ORs, 529 00:22:23,505 --> 00:22:24,645 put in more inpatient units, 530 00:22:25,015 --> 00:22:27,285 built ambulatory facilities, they kept building. 531 00:22:28,205 --> 00:22:31,985 Now they are under enormous pressure from many directions. 532 00:22:32,365 --> 00:22:34,785 Demand is going up. We've got a aging population, 533 00:22:34,855 --> 00:22:37,945 more chronic illnesses, reimbursement levels are down, 534 00:22:38,595 --> 00:22:41,385 input costs, particularly labor are rising like crazy. 535 00:22:41,645 --> 00:22:44,225 So that makes it, uh, that makes it particularly hard. 536 00:22:45,005 --> 00:22:46,545 And the result of all 537 00:22:46,545 --> 00:22:48,865 of these forces is the financial performance 538 00:22:48,865 --> 00:22:52,345 of most health systems has deteriorated right now. 539 00:22:52,345 --> 00:22:53,585 Therefore, they have to do more with less. 540 00:22:53,845 --> 00:22:56,585 If you look at asset utilization broadly 541 00:22:57,465 --> 00:22:58,585 measured in healthcare, 542 00:22:59,245 --> 00:23:02,505 it lags every other asset intensive service 543 00:23:02,905 --> 00:23:03,945 business by a lot. 544 00:23:04,405 --> 00:23:05,785 Now, some of it's not controllable. 545 00:23:06,115 --> 00:23:07,945 Other service businesses can operate 546 00:23:07,945 --> 00:23:09,145 24 hours around the clock. 547 00:23:09,275 --> 00:23:12,545 Healthcare essentially is at best a 12 hour operation. 548 00:23:12,545 --> 00:23:14,825 It's a 7:00 AM to 7:00 PM kind of operation. 549 00:23:15,005 --> 00:23:16,745 So by definition, if you are perfect, 550 00:23:17,085 --> 00:23:18,465 you can be 50% utilized. 551 00:23:18,805 --> 00:23:21,905 So that's, uh, you know, a starting point that's, 552 00:23:21,905 --> 00:23:24,465 that's difficult, but they can do much better. 553 00:23:25,125 --> 00:23:28,145 And if you looked at what is the value at stake, 554 00:23:28,155 --> 00:23:29,905 there are 5,000 hospitals in this country. 555 00:23:30,765 --> 00:23:31,825 On average, they have three 556 00:23:31,925 --> 00:23:35,265 or $400 million in assets, not counting real estate. 557 00:23:35,325 --> 00:23:36,825 So an or is 10 558 00:23:36,825 --> 00:23:39,465 or $15 million, an imaging machine is three or $4 million. 559 00:23:39,615 --> 00:23:41,305 Inpatient units are expensive. 560 00:23:41,595 --> 00:23:45,565 Three or $400 million per hospital across 5,000 hospitals 561 00:23:46,305 --> 00:23:48,285 is $2 trillion of assets. 562 00:23:49,105 --> 00:23:51,485 If you unlock 10 points of productivity, 563 00:23:52,145 --> 00:23:54,845 you can pump $200 billion of value 564 00:23:55,625 --> 00:23:58,325 per year into this country's healthcare system, right? 565 00:23:58,755 --> 00:24:01,565 That means it's 30 or 40 million per hospital, which is 566 00:24:02,285 --> 00:24:03,445 straight bottom line effects. 567 00:24:04,325 --> 00:24:07,385 And if you did that, it's a boost to the bottom line. 568 00:24:07,565 --> 00:24:10,025 But more importantly, it has the ability 569 00:24:10,125 --> 00:24:12,865 to serve patients more effectively, more access, 570 00:24:12,865 --> 00:24:15,665 better service, faster throughput, less wait time. 571 00:24:15,965 --> 00:24:17,825 And so the value at stake is enormous. 572 00:24:18,005 --> 00:24:21,585 And that's kind of our sole focus on what we're trying 573 00:24:21,585 --> 00:24:23,065 to deliver to our customers every day. 574 00:24:24,555 --> 00:24:25,655 - No, thank you for that. 575 00:24:25,895 --> 00:24:27,975 I mean, uh, unlocking that value in those assets 576 00:24:27,975 --> 00:24:30,535 that are already there versus building more assets, 577 00:24:30,955 --> 00:24:32,615 you know, and, and, and tying it back 578 00:24:32,675 --> 00:24:35,055 to the patient, into the workforce. 579 00:24:35,445 --> 00:24:39,095 This critical concept of reducing burnout 580 00:24:39,755 --> 00:24:40,775 by making life 581 00:24:41,035 --> 00:24:43,415 and work a little bit more manageable by, 582 00:24:43,435 --> 00:24:46,015 by having better predictability, better analytics, 583 00:24:46,675 --> 00:24:50,215 better recommendations on how to, how to manage operations 584 00:24:50,275 --> 00:24:53,815 or, or, or, or better tools is so important. 585 00:24:54,345 --> 00:24:56,415 Mohan, as always, I want to thank you 586 00:24:56,415 --> 00:24:58,055 for taking the time to visit with you. 587 00:24:58,675 --> 00:25:01,215 To me, I always learn a lot when I speak to you 588 00:25:01,315 --> 00:25:05,015 and your leadership about sort of hospital operations and, 589 00:25:05,075 --> 00:25:07,615 and how, you know, the supply demand, 590 00:25:07,635 --> 00:25:10,295 the logistics can be better managed and, 591 00:25:10,295 --> 00:25:12,695 and how you're doing that at 5,000 plus operating rooms, 592 00:25:12,815 --> 00:25:14,215 hundreds and hundreds of infusion 593 00:25:14,215 --> 00:25:15,455 centers and, and a lot more. 594 00:25:15,985 --> 00:25:18,775 Thank you for joining us on this discussion, sort 595 00:25:18,775 --> 00:25:21,535 of AI in the workforce, empowering staff 596 00:25:21,555 --> 00:25:22,575 and systems to thrive. 597 00:25:23,195 --> 00:25:25,775 So, so important to, to make things more predictable, 598 00:25:25,775 --> 00:25:28,095 getting outta what you call this IROC concept, 599 00:25:28,245 --> 00:25:31,575 this a regular operations concept of a constant fire drill, 600 00:25:31,575 --> 00:25:34,215 which causes so much, so much stress and so much burnout. 601 00:25:34,805 --> 00:25:37,175 Moan, thank you very much for, for visiting. Thank you, 602 00:25:37,355 --> 00:25:38,655 - God, great to chat with you as always. 603 00:25:38,665 --> 00:25:39,665 Thank you. 604 00:25:40,445 --> 00:25:42,775 - Well, thanks again to our listeners for tuning in today. 605 00:25:43,355 --> 00:25:44,895 I'd also like to thank Lean Toss 606 00:25:44,895 --> 00:25:46,015 for sponsoring this episode. 607 00:25:46,555 --> 00:25:49,015 You can tune into more podcasts from Becker's Healthcare 608 00:25:49,235 --> 00:25:52,575 by visiting our podcast page at becker's podcast.com.