1 00:00:00,285 --> 00:00:02,615 - This is Laura Dedo with the Becker's Healthcare Podcast. 2 00:00:03,115 --> 00:00:05,215 I'm thrilled today to be joined by Dr. Alan Weiss, 3 00:00:05,365 --> 00:00:07,735 vice President and Chief Medical Information Officer at 4 00:00:07,735 --> 00:00:09,855 BayCare Health System, Dr. Weiss, it's a pleasure 5 00:00:09,855 --> 00:00:10,975 to have you on the podcast today. 6 00:00:11,645 --> 00:00:12,665 - Thanks for having me. 7 00:00:13,475 --> 00:00:14,855 - Now, I know we have a lot to talk about. 8 00:00:14,855 --> 00:00:16,735 There's so much happening and changing in healthcare, 9 00:00:16,875 --> 00:00:18,415 and certainly I'm excited to learn more about 10 00:00:18,415 --> 00:00:20,655 what you're planning for BayCare in the next year. 11 00:00:20,755 --> 00:00:22,375 But before we dive into those questions, 12 00:00:22,435 --> 00:00:23,455 can you tell me a little bit more 13 00:00:23,455 --> 00:00:24,615 about yourself and your background? 14 00:00:26,025 --> 00:00:28,675 - Sure. So I have a, sort 15 00:00:28,675 --> 00:00:30,275 of a different background than a lot 16 00:00:30,275 --> 00:00:31,315 of people in my position. 17 00:00:31,395 --> 00:00:34,395 I, I actually have a computer science undergraduate degree. 18 00:00:34,395 --> 00:00:35,435 It's actually computer science 19 00:00:35,435 --> 00:00:38,595 and philosophy from, uh, the University of Michigan. 20 00:00:38,975 --> 00:00:40,355 And went 21 00:00:40,375 --> 00:00:44,115 and did work in the pharmaceutical, uh, industry, 22 00:00:44,465 --> 00:00:47,915 basically helping to create databases for drug approvals 23 00:00:47,935 --> 00:00:50,355 and analyze those databases for the FDA 24 00:00:51,015 --> 00:00:52,355 and for medical journals. 25 00:00:52,775 --> 00:00:57,025 And after I worked there for several years, I turned around 26 00:00:57,025 --> 00:00:59,825 and got an MBA with a focus both in healthcare management 27 00:00:59,825 --> 00:01:01,265 and the management of information systems. 28 00:01:01,885 --> 00:01:05,265 And finally, um, got so interested in medicine 29 00:01:05,265 --> 00:01:07,625 through working in the pharmaceutical industry 30 00:01:07,625 --> 00:01:09,985 that I decided to, to take the plunge. 31 00:01:10,025 --> 00:01:12,625 I became a, went to medical school, did my, uh, 32 00:01:12,905 --> 00:01:15,385 residency in internal medicine at the Johns Hopkins Bayview 33 00:01:15,385 --> 00:01:19,985 Medical Center, and returned to, um, Cleveland, Ohio, 34 00:01:19,985 --> 00:01:22,385 which is where I'm from, to work at the Cleveland Clinic 35 00:01:22,405 --> 00:01:23,425 for about 10 years. 36 00:01:24,545 --> 00:01:26,065 I was a practicing physician there, 37 00:01:26,085 --> 00:01:27,865 but I also helped out with informatics. 38 00:01:28,105 --> 00:01:30,345 I had, uh, worked in business informatics. 39 00:01:30,385 --> 00:01:32,905 I had a, a number of different positions in addition to 40 00:01:33,565 --> 00:01:36,905 seeing patients, I was also teaching both medical students 41 00:01:36,925 --> 00:01:40,145 and residents and, uh, doing a, and, 42 00:01:40,165 --> 00:01:41,985 and I was the ward attending as well. 43 00:01:42,125 --> 00:01:42,985 So a lot of 44 00:01:42,985 --> 00:01:44,185 different things that I did at the Cleveland Clinic. 45 00:01:44,205 --> 00:01:46,745 It was a lot of fun and, and certainly a, a growth career. 46 00:01:47,625 --> 00:01:50,825 I, I ended up moving from, uh, the Cleveland Clinic 47 00:01:50,925 --> 00:01:55,305 to Los Angeles where I was the, uh, the physician in charge 48 00:01:55,645 --> 00:01:58,985 of their epic rollout on the inpatient side. 49 00:01:59,005 --> 00:02:00,545 And I, that goes back a ways, 50 00:02:00,645 --> 00:02:03,865 but spent several years there helping them develop their 51 00:02:03,865 --> 00:02:08,305 epic implementation before moving on to Memorial Hermann at, 52 00:02:08,485 --> 00:02:11,305 uh, or in Houston, Texas, which is where my wife is from. 53 00:02:11,885 --> 00:02:13,585 And we spent about five years there 54 00:02:14,085 --> 00:02:16,585 as their ambulatory Chief Medical Information Officer 55 00:02:17,015 --> 00:02:20,065 working on a variety of different EHRs, 56 00:02:20,455 --> 00:02:23,585 including GE centricity, uh, eClinical works, 57 00:02:23,925 --> 00:02:26,305 and, uh, also Cerner while I was there. 58 00:02:26,485 --> 00:02:29,505 And I had a very interesting time there. 59 00:02:29,525 --> 00:02:31,865 It was very interesting, tried to figure out 60 00:02:31,865 --> 00:02:35,465 how we could encode, uh, quality into the, the EHR and, 61 00:02:35,465 --> 00:02:37,225 and also help out with efficiency issues. 62 00:02:37,805 --> 00:02:40,865 Uh, I, five years ago, I, I moved here to Tampa, Florida, 63 00:02:40,865 --> 00:02:43,825 which is, uh, you know, where I'm, where I'm located now. 64 00:02:44,345 --> 00:02:46,225 I, I'm the, the Chief Medical Information Officer 65 00:02:46,245 --> 00:02:48,105 for the BayCare Health System here. 66 00:02:48,605 --> 00:02:50,185 And, uh, BayCare is the largest 67 00:02:50,185 --> 00:02:51,625 healthcare provider in Tampa. 68 00:02:52,005 --> 00:02:56,905 And we, um, uh, we like to say the qualities are true north, 69 00:02:56,965 --> 00:02:59,260 and, uh, that's essentially my background. 70 00:03:00,605 --> 00:03:01,815 - Well, that's fantastic to hear 71 00:03:01,815 --> 00:03:03,855 and what amazing experiences you've had throughout your 72 00:03:03,855 --> 00:03:06,215 career, whether your early career, um, you know, 73 00:03:06,435 --> 00:03:08,935 in computer science, in, in doing, um, 74 00:03:08,935 --> 00:03:10,495 several different aspects of healthcare 75 00:03:10,515 --> 00:03:13,735 and then jumping into, um, you know, practicing medicine 76 00:03:13,735 --> 00:03:14,975 and being in so many different places. 77 00:03:15,115 --> 00:03:18,255 And, and then too, um, heading up on the medical side, 78 00:03:18,415 --> 00:03:19,455 an EHR rollout. 79 00:03:19,535 --> 00:03:22,375 I can imagine you've just seen so many things, um, coming 80 00:03:22,375 --> 00:03:24,975 through the system and now looking ahead, you know, 81 00:03:25,375 --> 00:03:28,175 a completely different healthcare system, um, is evolving. 82 00:03:28,355 --> 00:03:30,535 So I'm excited to hear about that. 83 00:03:32,495 --> 00:03:33,695 - Absolutely. It's, it's, it's been 84 00:03:34,215 --> 00:03:35,895 a really amazing experience. 85 00:03:36,255 --> 00:03:38,095 I, I've, and, uh, you know, 86 00:03:38,095 --> 00:03:39,855 sometimes I could say it hasn't been as much fun 87 00:03:39,855 --> 00:03:42,655 as it sounds, but it, it's been certainly a, 88 00:03:42,775 --> 00:03:45,015 a very interesting learning experience as, 89 00:03:45,015 --> 00:03:46,575 as I've gone from different healthcare systems 90 00:03:46,835 --> 00:03:49,535 and had different varieties of, uh, projects 91 00:03:49,535 --> 00:03:51,775 and experiences throughout the course of my career. 92 00:03:52,815 --> 00:03:55,095 - Absolutely. Well, you know, now looking ahead, 93 00:03:55,165 --> 00:03:57,255 what are some of the biggest issues that you're following, 94 00:03:57,435 --> 00:03:59,015 taking you into the next 12 months? 95 00:03:59,075 --> 00:04:00,655 Um, what's kind of top of mind for you? 96 00:04:02,215 --> 00:04:04,785 - Well, what's always top of mind for me 97 00:04:05,365 --> 00:04:07,145 is the electronic health record 98 00:04:07,725 --> 00:04:10,385 and how we can try to make it better than 99 00:04:10,385 --> 00:04:11,505 what it currently is. 100 00:04:11,625 --> 00:04:15,465 I mean, it's, it's always an optimization adventure for us. 101 00:04:15,525 --> 00:04:18,185 And, and for us, it comes down to how, 102 00:04:18,205 --> 00:04:20,025 how can we collect the data 103 00:04:20,045 --> 00:04:23,105 that's more clinically appropriate, more, more clinically 104 00:04:23,705 --> 00:04:26,505 accurate, and serve it up to the physicians in a way 105 00:04:26,505 --> 00:04:28,865 that allows them to make better healthcare decisions. 106 00:04:29,485 --> 00:04:34,305 It also involves figuring out how we can help our, our, uh, 107 00:04:34,405 --> 00:04:38,505 entire team write documents in an easier way, organize them 108 00:04:38,565 --> 00:04:39,905 so you can find them easier. 109 00:04:40,685 --> 00:04:42,705 And, and the, the same with orders. 110 00:04:43,005 --> 00:04:45,865 Um, you know, how, how do you make it easier for, for people 111 00:04:45,865 --> 00:04:47,265 to find the orders that are needed 112 00:04:47,325 --> 00:04:50,745 and then display the orders in a concise, um, 113 00:04:51,075 --> 00:04:54,105 consistent manner so that people can carry them out in, 114 00:04:54,105 --> 00:04:55,105 in a way that makes sense. 115 00:04:55,855 --> 00:04:59,325 Part of those optimization efforts also involve ways 116 00:04:59,425 --> 00:05:01,805 of trying to embed evidence-based medicine, 117 00:05:01,915 --> 00:05:03,605 into the work that people are doing. 118 00:05:04,265 --> 00:05:06,645 And, uh, also to help us. 119 00:05:06,785 --> 00:05:09,645 And as like, like other healthcare systems, we're trying 120 00:05:09,645 --> 00:05:11,885 to do a care transformation project where 121 00:05:12,425 --> 00:05:15,885 we both reduced the cost of healthcare 122 00:05:16,185 --> 00:05:18,205 and improved the efficiency. 123 00:05:18,385 --> 00:05:20,925 So a lot of different projects out there, A lot of, uh, 124 00:05:21,645 --> 00:05:24,965 interesting projects on the EHR front in, in addition to 125 00:05:24,965 --> 00:05:28,525 that, I, I tell you, we certainly are working very 126 00:05:28,805 --> 00:05:31,405 diligently on, uh, a number of AI initiatives, 127 00:05:31,405 --> 00:05:33,245 and I can give more details on that later on. 128 00:05:33,705 --> 00:05:35,805 Um, trying to, to figure out how we, we, 129 00:05:35,955 --> 00:05:38,925 like many other healthcare systems, uh, are, are trying to, 130 00:05:38,985 --> 00:05:41,965 to, uh, uh, you know, address what is now a, 131 00:05:42,045 --> 00:05:45,005 a very transformative type of technology in healthcare. 132 00:05:45,625 --> 00:05:48,365 Um, I would finally say that that certainly part 133 00:05:48,605 --> 00:05:50,005 of our efficiency issues, part 134 00:05:50,005 --> 00:05:52,085 of our EHR issues involve our nurses. 135 00:05:52,745 --> 00:05:55,245 We are very deeply involved with trying to figure out 136 00:05:55,245 --> 00:05:56,805 how we make nurses more efficient, 137 00:05:57,265 --> 00:05:59,565 and, uh, once again, it's, it's all about trying 138 00:05:59,565 --> 00:06:01,765 to figure out how to display information 139 00:06:01,865 --> 00:06:04,605 for our nurses in a better way, cut down on the tasks 140 00:06:04,675 --> 00:06:07,645 that they have and improve the work that they do. 141 00:06:07,845 --> 00:06:10,045 I mean, so it's a lot of, a lot of effort all throughout. 142 00:06:12,275 --> 00:06:14,375 - That's amazing to hear, and certainly so important, 143 00:06:14,515 --> 00:06:16,775 as you said, in looking at the current environment, 144 00:06:16,775 --> 00:06:18,775 making sure that, you know, 145 00:06:18,775 --> 00:06:20,615 you're leveraging technology in the EHR 146 00:06:20,615 --> 00:06:22,535 to optimize everything you can, um, 147 00:06:22,715 --> 00:06:24,415 to support the workforce in, 148 00:06:24,475 --> 00:06:27,175 in operational efficiency while also cutting costs 149 00:06:27,175 --> 00:06:29,495 where it makes sense and being more efficient 150 00:06:29,495 --> 00:06:30,495 and effective in that way. 151 00:06:31,235 --> 00:06:33,495 And, and I appreciate you sharing all these examples 152 00:06:33,495 --> 00:06:36,135 because I think it's certainly, um, you know, 153 00:06:36,875 --> 00:06:38,895 so many different projects can come across your desk, 154 00:06:38,955 --> 00:06:40,815 and yet they all kind of seem 155 00:06:40,815 --> 00:06:43,015 to dovetail into having the same mission or, 156 00:06:43,015 --> 00:06:45,415 or driving forward the, a similar strategy 157 00:06:45,415 --> 00:06:46,855 and mission throughout the health system. 158 00:06:48,395 --> 00:06:49,605 - Exactly, exactly. 159 00:06:50,765 --> 00:06:53,505 - So, um, given everything we just talked about, 160 00:06:53,735 --> 00:06:56,105 what are some of the things you're most excited about right 161 00:06:56,105 --> 00:06:57,105 now and what makes you nervous? 162 00:06:59,845 --> 00:07:03,495 - True. Um, I, I'm, I'm very excited, um, 163 00:07:04,145 --> 00:07:05,935 about the promise of ai. 164 00:07:06,295 --> 00:07:09,175 I, I, I think there's just so much that you could be doing 165 00:07:09,175 --> 00:07:10,175 with AI right now. 166 00:07:10,335 --> 00:07:13,375 I, I, I, I'm, I'm very excited by, uh, 167 00:07:13,635 --> 00:07:15,575 by its potential and possibility. 168 00:07:16,155 --> 00:07:18,175 Um, we are in the process of doing some 169 00:07:18,175 --> 00:07:21,535 of the ambient listening, uh, pilots right now and, 170 00:07:21,715 --> 00:07:23,735 and trying to figure out how we're gonna approach this. 171 00:07:23,995 --> 00:07:26,455 Uh, we're having lots of discussions about 172 00:07:26,635 --> 00:07:28,935 how you use generative AI in medicine. 173 00:07:29,145 --> 00:07:31,735 Those are just a couple of of things that, that excite me 174 00:07:31,735 --> 00:07:33,095 and make me very interested. 175 00:07:33,335 --> 00:07:34,815 I mean, I, it's fascinating to me. 176 00:07:35,355 --> 00:07:39,735 Um, I get, uh, very excited just by the efficiency of 177 00:07:39,735 --> 00:07:41,295 what we can do with the EHR. 178 00:07:41,955 --> 00:07:43,615 One of the things that we're doing is, 179 00:07:43,615 --> 00:07:47,935 another example is we're automating tasks using the EHR. 180 00:07:47,995 --> 00:07:50,975 So we are literally taking millions of things 181 00:07:50,975 --> 00:07:54,135 that physicians and their staff would be doing, 182 00:07:54,435 --> 00:07:58,615 and we are instead, um, pushing that into the EHR 183 00:07:58,675 --> 00:08:00,615 and letting it be done automatically. 184 00:08:01,035 --> 00:08:02,495 That's improving reimbursement, 185 00:08:02,565 --> 00:08:04,655 it's improving quality, it's improving safety. 186 00:08:05,155 --> 00:08:06,895 So we're very excited about that kind of work. 187 00:08:06,925 --> 00:08:08,215 It's really, it's, it's fantastic. 188 00:08:09,365 --> 00:08:13,465 Um, so I'm, I'm very, very excited by all of these things. 189 00:08:13,685 --> 00:08:15,425 The things that that scare me. 190 00:08:15,765 --> 00:08:17,825 Um, I get a little scared by AI 191 00:08:17,825 --> 00:08:19,585 and I, I'm probably not the only one. 192 00:08:19,585 --> 00:08:22,665 There's, there's all kinds of biases that AI has been known 193 00:08:22,665 --> 00:08:23,745 to have, and, 194 00:08:23,745 --> 00:08:25,825 and I I would tell you that, that one of the things 195 00:08:25,825 --> 00:08:28,825 that we are finding is that, uh, some of the AI 196 00:08:29,545 --> 00:08:32,025 companies out there that say that they're doing AI 197 00:08:32,565 --> 00:08:35,665 are probably not doing AI as much as they're doing, um, 198 00:08:35,815 --> 00:08:40,025 some advanced logic, you know, AI by itself of a, a system 199 00:08:40,025 --> 00:08:43,545 that learns on its own is, uh, well, we're, 200 00:08:43,545 --> 00:08:46,745 we're just finding that a lot of, uh, the companies 201 00:08:46,745 --> 00:08:48,865 that are saying they're doing AI really aren't, 202 00:08:49,205 --> 00:08:53,425 and we're not having universal success in the ai We're 203 00:08:53,425 --> 00:08:57,845 finding that there's a lot of, of times when the, um, 204 00:08:58,265 --> 00:09:01,245 the, the AI isn't quite performing as 205 00:09:01,265 --> 00:09:02,725 to the metrics that we've created. 206 00:09:03,735 --> 00:09:06,355 So I, I'm, I'm worried about those, those kinds of, 207 00:09:06,375 --> 00:09:07,875 of efforts that, that are out there. 208 00:09:07,915 --> 00:09:09,395 I, I think they're certainly worth pursuing, 209 00:09:09,695 --> 00:09:12,875 but they're worth pursuing with the same kind of diligence 210 00:09:13,185 --> 00:09:16,515 that we should have or any kind of healthcare system 211 00:09:16,895 --> 00:09:18,235 or any kind of application. 212 00:09:18,455 --> 00:09:21,035 Uh, making sure that we understand the implications 213 00:09:21,035 --> 00:09:23,275 of the system before we get into 'em, and, 214 00:09:23,275 --> 00:09:25,235 and that we make sure that we we're, we're, uh, 215 00:09:25,595 --> 00:09:27,755 approaching them with the, the, the right due diligence 216 00:09:27,855 --> 00:09:29,595 by our is, uh, colleagues. 217 00:09:30,015 --> 00:09:33,355 So I, I, what scares me is, is in some ways 218 00:09:33,465 --> 00:09:34,475 what also excites me. 219 00:09:35,595 --> 00:09:36,885 - Yeah, that's such a great point. 220 00:09:36,945 --> 00:09:39,085 And certainly looking at artificial intelligence, 221 00:09:39,155 --> 00:09:41,325 it's such in early stages right now, 222 00:09:41,325 --> 00:09:43,285 especially within the healthcare spaces and, 223 00:09:43,305 --> 00:09:46,205 and applications that could really make a big difference 224 00:09:46,205 --> 00:09:48,805 both clinically and operationally from your perspective. 225 00:09:48,925 --> 00:09:50,845 I, I know you talked a little bit about, um, some 226 00:09:50,845 --> 00:09:52,525 of the challenges, whether it's the biases 227 00:09:52,745 --> 00:09:54,765 and then, you know, jumping into, um, 228 00:09:54,765 --> 00:09:57,805 the AI not exactly doing, um, what was anticipated 229 00:09:57,825 --> 00:09:59,645 or having the results that were anticipated. 230 00:10:00,505 --> 00:10:03,685 How do you, uh, really work with your team on that, um, 231 00:10:03,865 --> 00:10:06,365 you know, who maybe don't necessarily understand the 232 00:10:06,365 --> 00:10:07,605 technology, but are skeptical 233 00:10:07,785 --> 00:10:10,045 and are seeing some of these challenges as validating that 234 00:10:10,345 --> 00:10:13,925 and, and thinking that, you know, potentially, um, having, 235 00:10:14,285 --> 00:10:16,925 creating more questions than answers amongst team members. 236 00:10:17,105 --> 00:10:18,645 Um, is that something you're seeing 237 00:10:18,705 --> 00:10:20,765 or have people been pretty quick to embrace the change 238 00:10:20,785 --> 00:10:23,125 and understanding of the process on, you know, 239 00:10:23,125 --> 00:10:25,325 incorporating new technology into the healthcare space? 240 00:10:26,345 --> 00:10:27,595 - Yeah, the, the, the problem is, 241 00:10:27,595 --> 00:10:29,675 and I think this, this is a 242 00:10:30,395 --> 00:10:33,155 a a probably a fundamental aspect of the excitement 243 00:10:33,155 --> 00:10:35,475 that we get about new technology is that the, 244 00:10:35,475 --> 00:10:37,595 the new technology is so fascinating. 245 00:10:37,625 --> 00:10:40,995 It's so interesting. And you, you read the examples of 246 00:10:41,025 --> 00:10:43,635 what AI can do and let's face it chat. 247 00:10:43,755 --> 00:10:45,115 GPT is, it's, it's cool. 248 00:10:45,305 --> 00:10:48,475 There's a lot of just really interesting things 249 00:10:48,625 --> 00:10:51,555 that generative AI can do, and it, 250 00:10:51,555 --> 00:10:54,115 and it, it certainly has captured our imaginations. 251 00:10:54,215 --> 00:10:55,515 And, you know, 252 00:10:55,905 --> 00:10:59,115 when we start thinking about the administrative overhead 253 00:10:59,145 --> 00:11:03,355 that is so, uh, problemsome for people 254 00:11:03,855 --> 00:11:08,355 inside of medicine, the, the opportunities to have an AI 255 00:11:08,735 --> 00:11:11,995 to help address the issues is just amazing. 256 00:11:12,095 --> 00:11:14,635 So I, I, I think there's, there's lots of great excitement. 257 00:11:14,815 --> 00:11:18,395 The the problem is that there's also a lack of understanding 258 00:11:19,265 --> 00:11:21,485 and that lack of understanding and knowledge is one 259 00:11:21,485 --> 00:11:22,925 of the things we face on regular basis. 260 00:11:23,665 --> 00:11:26,845 For instance, I mean, I, I tell you, when you start to look 261 00:11:27,625 --> 00:11:32,165 at, at ai, you know, we, we have, we have, um, execs 262 00:11:32,225 --> 00:11:34,645 and we have users who come up to me 263 00:11:34,645 --> 00:11:38,605 and say, well, we need AI to solve, you know, to help us. 264 00:11:39,185 --> 00:11:42,605 And I, I guess the, the issue that always comes up is 265 00:11:42,605 --> 00:11:46,125 what we, we need to do is, is to understand what the nature 266 00:11:46,225 --> 00:11:49,205 of the problem is around whatever issue there is that they, 267 00:11:49,355 --> 00:11:52,565 they they want AI for, and then decide whether 268 00:11:52,565 --> 00:11:56,845 or not AI is the right approach to help address the issue. 269 00:11:57,325 --> 00:12:01,205 I mean, AI is a tool like many other tools that we have. 270 00:12:01,765 --> 00:12:03,445 I tell you that most of the AI 271 00:12:03,445 --> 00:12:05,245 that we've looked at is a very expensive tool, 272 00:12:05,825 --> 00:12:10,685 and that expense, you know, can, can help inhibit the notion 273 00:12:10,685 --> 00:12:13,765 of it being adopted or, um, by our organization. 274 00:12:14,165 --> 00:12:15,285 I think we have to be very careful. 275 00:12:15,505 --> 00:12:19,645 Um, when I start to talk to users about all of the issues 276 00:12:19,645 --> 00:12:24,245 that are out there, there's, um, there's almost a hesitancy 277 00:12:24,265 --> 00:12:26,805 for me to actually make those kinds of statements. 278 00:12:27,185 --> 00:12:29,405 You know, there's so many people that just want 279 00:12:29,645 --> 00:12:34,285 to plow ahead without thinking about the, uh, the dangers 280 00:12:34,285 --> 00:12:35,365 and the issues that are out there. 281 00:12:35,485 --> 00:12:38,805 I think we, we have to approach AI with caution, 282 00:12:39,395 --> 00:12:42,765 with some notion that we have to, you know, make sure 283 00:12:42,765 --> 00:12:44,485 that it's proven and we have to make sure 284 00:12:44,485 --> 00:12:47,765 that there are very defined metrics for its use 285 00:12:48,345 --> 00:12:52,125 before we, uh, before and, and as we adopt. 286 00:12:53,405 --> 00:12:54,465 - That's such a great point. 287 00:12:54,465 --> 00:12:56,865 Thank you so much for sharing just your thought process 288 00:12:56,875 --> 00:12:59,505 there, and especially how other clinicians are, 289 00:12:59,505 --> 00:13:02,425 are viewing AI and, and technology integration in general. 290 00:13:03,125 --> 00:13:05,225 Now, I know we've talked about a lot 291 00:13:05,225 --> 00:13:07,065 of different changes within the healthcare space 292 00:13:07,125 --> 00:13:09,345 and how it's evolving so rapidly. 293 00:13:10,055 --> 00:13:11,065 What do you think is going 294 00:13:11,065 --> 00:13:13,225 to be the most effective thing healthcares will need 295 00:13:13,285 --> 00:13:15,465 to be successful over the next two to three years? 296 00:13:15,535 --> 00:13:17,465 What should leaders do and understand, 297 00:13:17,605 --> 00:13:19,945 and what will they need to do, um, to make sure 298 00:13:19,945 --> 00:13:21,425 that their organizations are successful? 299 00:13:23,725 --> 00:13:28,665 - So, I, I would tell you that, that when I start to talk 300 00:13:28,685 --> 00:13:33,185 to my colleagues, uh, around the, the, uh, 301 00:13:33,205 --> 00:13:34,985 the country, a lot 302 00:13:34,985 --> 00:13:37,545 of them are facing the same kind of things that we're facing. 303 00:13:37,975 --> 00:13:40,585 There's, um, uh, revenue challenges, 304 00:13:41,575 --> 00:13:44,315 and I, I think a lot of healthcare organizations 305 00:13:45,825 --> 00:13:48,875 have since, uh, since Covid, they, they've, 306 00:13:48,875 --> 00:13:52,475 they've really had to, um, rethink of 307 00:13:52,695 --> 00:13:55,515 how they can reduce costs, improve quality, 308 00:13:55,615 --> 00:14:00,195 and do so in a way that, uh, can, can somehow promise all 309 00:14:00,195 --> 00:14:01,195 of this at a lower cost. 310 00:14:01,435 --> 00:14:04,955 I think that those, those issues are paramount to a lot 311 00:14:04,955 --> 00:14:06,155 of the organizations and, 312 00:14:06,155 --> 00:14:08,665 and a lot of people, uh, I, 313 00:14:08,785 --> 00:14:13,185 I do think there's gonna be a continual, uh, focus on 314 00:14:13,565 --> 00:14:17,265 how do we improve the quality of the work that we provide. 315 00:14:17,725 --> 00:14:19,465 Uh, I'm just seeing that more 316 00:14:19,465 --> 00:14:21,265 and more often as, as I talk to people, 317 00:14:21,715 --> 00:14:24,465 those quality initiatives are becoming, well, 318 00:14:25,015 --> 00:14:28,825 it's not like they weren't, you know, prevalent beforehand, 319 00:14:29,045 --> 00:14:31,385 but they're, they're becoming even more important 320 00:14:31,565 --> 00:14:33,425 and the use of the EHR 321 00:14:33,445 --> 00:14:36,345 and other clinical tools to help in the process 322 00:14:36,405 --> 00:14:38,225 of delivering care, it's becoming more 323 00:14:38,225 --> 00:14:40,705 and more, um, you know, more 324 00:14:40,705 --> 00:14:42,505 and more of a project, more of a learning issue. 325 00:14:42,605 --> 00:14:44,865 So I, I think that's something that, that you'll see more 326 00:14:44,865 --> 00:14:45,945 of as time goes on. 327 00:14:46,685 --> 00:14:48,385 Um, I would also say, 328 00:14:50,005 --> 00:14:53,495 and when I, I, I start to, to think about the, um, 329 00:14:53,755 --> 00:14:57,495 the issues and projects that people start to, to work on, I, 330 00:14:57,775 --> 00:15:00,215 I do think that we are going to see more 331 00:15:00,215 --> 00:15:03,135 and more integration across the healthcare system 332 00:15:03,135 --> 00:15:05,415 and the healthcare environment that, that integration, 333 00:15:05,805 --> 00:15:10,335 what I mean by that is, is more ways of integrating data 334 00:15:11,155 --> 00:15:14,055 and operations, uh, about patients 335 00:15:14,315 --> 00:15:15,735 and making it into a more 336 00:15:15,735 --> 00:15:17,895 wholesome approach to patient care. 337 00:15:18,295 --> 00:15:20,895 I think we're gonna find that the data that patients have 338 00:15:20,915 --> 00:15:23,615 and collect on their everyday lives are gonna start 339 00:15:23,615 --> 00:15:25,975 to impact the way that we treat patients. 340 00:15:26,275 --> 00:15:28,695 Uh, I think you're gonna see more wearables in the system. 341 00:15:29,255 --> 00:15:31,415 I think you're gonna see patients have reported outcomes 342 00:15:32,045 --> 00:15:35,735 will start to drive the, the way we, we, uh, handle care. 343 00:15:36,195 --> 00:15:37,775 So I, I think that's all there. 344 00:15:38,155 --> 00:15:41,775 Um, I, I would also tell you that digital transformation 345 00:15:42,295 --> 00:15:44,455 continues to be an issue that we start to work on so 346 00:15:44,455 --> 00:15:46,655 that a lot of different facilities 347 00:15:46,655 --> 00:15:48,775 that we have within the healthcare system, 348 00:15:49,215 --> 00:15:51,615 I think are gonna be, be produced 349 00:15:51,795 --> 00:15:55,615 or will be evaluated in such a way that, uh, they'll, 350 00:15:55,615 --> 00:15:57,175 they'll move to digital tools. 351 00:15:59,035 --> 00:16:00,215 - That's fascinating to hear. 352 00:16:00,315 --> 00:16:01,335 Dr. Weiss, thank you so much 353 00:16:01,335 --> 00:16:02,615 for joining us on the podcast today. 354 00:16:02,645 --> 00:16:04,975 This has been such a fun and fascinating conversation, 355 00:16:04,995 --> 00:16:06,975 and I look forward to connecting with you again soon. 356 00:16:07,515 --> 00:16:08,895 - Sounds good. 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