1 00:00:00,880 --> 00:00:03,139 Welcome, everyone, to the Becker's Healthcare Podcast. 2 00:00:03,520 --> 00:00:05,919 I'm Laura Dirda, Vice President, Editor in Chief 3 00:00:05,919 --> 00:00:07,759 here at Becker's Healthcare, and I'm thrilled today 4 00:00:07,759 --> 00:00:09,939 to be joined by Sudipto Srivastava, 5 00:00:10,559 --> 00:00:13,299 the Chief Data and Analytics Officer at Montefiore 6 00:00:13,439 --> 00:00:14,179 Health System. 7 00:00:14,695 --> 00:00:15,974 Sudipto, it's a pleasure to have you on 8 00:00:15,974 --> 00:00:17,035 the podcast today. 9 00:00:18,054 --> 00:00:19,894 Thanks. It's great to be here. Big fan 10 00:00:19,894 --> 00:00:22,635 of Becker. So, so excited, for this opportunity, 11 00:00:22,774 --> 00:00:23,274 Laura. 12 00:00:23,814 --> 00:00:25,894 Absolutely. And we're big fans of yours and 13 00:00:25,894 --> 00:00:28,339 everything that you're doing at Montefiore Health System 14 00:00:28,339 --> 00:00:29,940 as well. I think it's such an interesting 15 00:00:29,940 --> 00:00:32,259 time in health care, and we're certainly excited 16 00:00:32,259 --> 00:00:33,159 for our conversation. 17 00:00:34,020 --> 00:00:35,960 Indeed. Yeah. It is very exciting. 18 00:00:36,979 --> 00:00:38,979 Absolutely. Well, I know we'll talk about a 19 00:00:38,979 --> 00:00:41,299 good many things in thinking about technology and 20 00:00:41,299 --> 00:00:43,424 data and AI and more. But before we 21 00:00:43,424 --> 00:00:45,585 do, can you introduce yourself and tell us 22 00:00:45,585 --> 00:00:47,445 a little bit more about the health system? 23 00:00:48,385 --> 00:00:48,885 Absolutely. 24 00:00:49,424 --> 00:00:51,445 And, actually, even before I do that, 25 00:00:51,745 --> 00:00:53,905 you know, because this is an audience that's 26 00:00:53,905 --> 00:00:56,065 near and dear to me, my, other colleagues 27 00:00:56,065 --> 00:00:58,420 in health care and and tech who are 28 00:00:58,420 --> 00:01:00,740 trying to solve big problems. I wanna maybe 29 00:01:00,740 --> 00:01:03,719 start with, a couple of hypothesis that as 30 00:01:03,780 --> 00:01:05,859 we're going through our discussion today, Laura, I 31 00:01:05,859 --> 00:01:07,859 just want, the audience to keep in the 32 00:01:07,859 --> 00:01:09,159 back of their minds. 33 00:01:09,700 --> 00:01:10,599 Number one, 34 00:01:11,564 --> 00:01:13,885 do you think that we have solved all 35 00:01:13,885 --> 00:01:15,584 of our problems in health care? 36 00:01:16,685 --> 00:01:17,744 And number two, 37 00:01:19,325 --> 00:01:21,165 given all those sort of focus on AI 38 00:01:21,165 --> 00:01:23,405 and things like that, but how would you 39 00:01:23,405 --> 00:01:24,625 change work 40 00:01:25,459 --> 00:01:27,780 if you had access to several really smart 41 00:01:27,780 --> 00:01:30,039 PhDs who are working for you? Of course, 42 00:01:30,420 --> 00:01:33,219 I'll be with a little contact with little 43 00:01:33,219 --> 00:01:35,619 context for operational and cultural context that you 44 00:01:35,619 --> 00:01:38,099 work in, like these, you know, AI tools 45 00:01:38,099 --> 00:01:39,539 can do that. But just how would you 46 00:01:39,539 --> 00:01:40,034 change? 47 00:01:40,355 --> 00:01:42,115 And I want the the the audience to 48 00:01:42,115 --> 00:01:43,555 keep that as a frame in the back 49 00:01:43,555 --> 00:01:44,915 of their minds because, you know, we'll be 50 00:01:44,915 --> 00:01:47,015 talking a lot about it. And I think 51 00:01:47,075 --> 00:01:49,174 as we have the conversation, it might, 52 00:01:49,515 --> 00:01:51,255 you know, prompt some thoughts and ideas 53 00:01:53,000 --> 00:01:54,600 that in their in their own heads, which 54 00:01:54,600 --> 00:01:56,859 is, of course, the goal of this discussion. 55 00:01:58,120 --> 00:01:59,719 Anyway, so with that said, you know, just 56 00:01:59,719 --> 00:02:01,240 to let me tell a little about, you 57 00:02:01,240 --> 00:02:03,980 know, our organization and myself, you know, Montefiore 58 00:02:04,040 --> 00:02:05,659 Health System, Montefiore Einstein, 59 00:02:06,334 --> 00:02:08,735 is a 13 hospital health system, covers the 60 00:02:08,735 --> 00:02:11,395 New York City, Bronx, Westchester, Hudson Valley area. 61 00:02:11,614 --> 00:02:13,074 About 7,500,000 62 00:02:13,134 --> 00:02:17,055 encounters in a year, about 36, 38, 7,000 63 00:02:17,055 --> 00:02:17,555 employees. 64 00:02:18,014 --> 00:02:20,495 We also are an academic medical center, in 65 00:02:20,495 --> 00:02:22,439 the Albert Einstein School of Medicine. 66 00:02:22,900 --> 00:02:25,459 And the, the interesting fact that some of 67 00:02:25,459 --> 00:02:27,400 your audience may or may not know is 68 00:02:27,459 --> 00:02:29,479 that we have a $0 69 00:02:29,939 --> 00:02:31,159 MD student tuition, 70 00:02:31,780 --> 00:02:33,879 because this was made possible by, 71 00:02:35,415 --> 00:02:38,955 doctor Ruth Gottesman who announced in February 2024 72 00:02:39,014 --> 00:02:41,735 that all current and future medical students will 73 00:02:41,735 --> 00:02:43,915 have their tuition waived in perpetuity 74 00:02:44,615 --> 00:02:47,590 through a billion dollar donation. So that's something 75 00:02:47,590 --> 00:02:48,650 that is fascinating, 76 00:02:48,950 --> 00:02:51,210 and we love, sort of sharing that back. 77 00:02:51,510 --> 00:02:53,349 As for me, you know, my title is 78 00:02:53,349 --> 00:02:54,569 VP data analytics, 79 00:02:54,870 --> 00:02:56,469 and my role includes, 80 00:02:56,870 --> 00:02:57,930 oversight for 81 00:02:58,389 --> 00:02:59,930 data analytics, organizational 82 00:03:00,230 --> 00:03:00,730 reporting, 83 00:03:01,175 --> 00:03:04,455 AI governance, and also research IT, partnering with 84 00:03:04,455 --> 00:03:05,514 our sort of school 85 00:03:06,134 --> 00:03:06,794 of medicine. 86 00:03:07,894 --> 00:03:10,055 And then as we sort of think of 87 00:03:10,055 --> 00:03:11,995 roles, titles, and what we, 88 00:03:12,375 --> 00:03:14,074 a lot what we'd like to 89 00:03:15,280 --> 00:03:17,699 pivot on within our organization is 90 00:03:18,159 --> 00:03:20,239 that we have made a conscious decision not 91 00:03:20,239 --> 00:03:23,680 to create a separate, like, say, czar for 92 00:03:23,680 --> 00:03:25,919 AI or anything else. And, again, there's nothing 93 00:03:25,919 --> 00:03:27,840 wrong with organizations that are doing it, but 94 00:03:27,840 --> 00:03:29,219 our philosophy is that 95 00:03:29,599 --> 00:03:30,819 AI and tech is 96 00:03:31,275 --> 00:03:32,094 everyone's responsibility. 97 00:03:33,034 --> 00:03:34,555 And we find that this frees up our 98 00:03:34,555 --> 00:03:36,254 staff and docs to explore things 99 00:03:36,955 --> 00:03:39,694 from their unique vantage unique vantage point. 100 00:03:40,235 --> 00:03:41,455 Now, of course, we have guardrails, 101 00:03:42,074 --> 00:03:44,314 and but we wanna be deliberate in not 102 00:03:44,314 --> 00:03:46,094 taking and making AI 103 00:03:46,810 --> 00:03:48,030 an individual's response. 104 00:03:49,530 --> 00:03:51,129 Well, that makes a ton of sense. And, 105 00:03:51,129 --> 00:03:52,409 you know, thank you so much for that 106 00:03:52,409 --> 00:03:55,129 explanation. It's, so fascinating to see the different 107 00:03:55,129 --> 00:03:58,030 perspectives that health systems are taking as technology 108 00:03:58,090 --> 00:03:59,949 and AI move so quickly. And 109 00:04:00,250 --> 00:04:02,724 I I love the idea that it's everyone's 110 00:04:02,784 --> 00:04:05,745 responsibility that you want everyone from their seat, 111 00:04:05,905 --> 00:04:08,245 to to take that unique vantage point and 112 00:04:08,465 --> 00:04:10,465 really figure out how they can apply it 113 00:04:10,465 --> 00:04:12,965 within their own roles and workflows and, 114 00:04:13,344 --> 00:04:15,830 get the best results possible. So that that's, 115 00:04:16,230 --> 00:04:17,769 really cool to hear about. Exactly. 116 00:04:18,790 --> 00:04:20,230 When you think about the last year or 117 00:04:20,230 --> 00:04:22,310 so, what was the most most important initiative 118 00:04:22,310 --> 00:04:23,509 that you led? What did you do, and 119 00:04:23,509 --> 00:04:24,410 what were the results? 120 00:04:25,509 --> 00:04:26,410 Yeah. Well, 121 00:04:27,285 --> 00:04:29,845 you know, plenty with, like, 37,000 122 00:04:29,845 --> 00:04:30,345 employees, 123 00:04:31,045 --> 00:04:33,764 thinking and working every day, smart bunch of 124 00:04:33,764 --> 00:04:35,845 clinicians and staff and nurses that we have. 125 00:04:35,845 --> 00:04:38,245 So lots, I guess, you know, in terms 126 00:04:38,245 --> 00:04:40,485 of this conversation, I'll pick up a few 127 00:04:40,485 --> 00:04:41,465 to talk about. 128 00:04:42,730 --> 00:04:44,569 And, of course, as with every self respecting 129 00:04:44,569 --> 00:04:47,550 health system, you know, we launched, Ambient Voice 130 00:04:47,610 --> 00:04:48,270 AI solutions. 131 00:04:48,810 --> 00:04:50,350 You know, so we have over 132 00:04:51,050 --> 00:04:52,110 550, 133 00:04:52,569 --> 00:04:55,129 clinicians enrolled in that, you know, covering areas 134 00:04:55,129 --> 00:04:57,925 such as primary care, medical and surgical specialties, 135 00:04:57,985 --> 00:05:00,245 and we have an ongoing demand 136 00:05:01,025 --> 00:05:04,245 of additional departments that want to use, ambient 137 00:05:04,305 --> 00:05:04,805 scribes. 138 00:05:05,665 --> 00:05:08,225 We have a very successful implementation there. We 139 00:05:08,225 --> 00:05:11,185 have over 48% high u utilizers. You know, 140 00:05:11,185 --> 00:05:12,004 these are folks 141 00:05:12,509 --> 00:05:13,729 that who are using, 142 00:05:14,269 --> 00:05:16,829 scribes more than 50% of the times in 143 00:05:16,829 --> 00:05:18,669 their sort of visit and over 50% of 144 00:05:18,669 --> 00:05:19,410 their visits. 145 00:05:19,870 --> 00:05:21,169 So we've had about, 146 00:05:21,470 --> 00:05:23,149 like, over 300,000 147 00:05:23,149 --> 00:05:23,649 encounters, 148 00:05:24,944 --> 00:05:27,345 and, you know, these things have continues to 149 00:05:27,345 --> 00:05:29,425 grow. And, you know, back to the question 150 00:05:29,425 --> 00:05:31,185 that we sort of prompted the audience to 151 00:05:31,185 --> 00:05:33,345 think of is, you know, think of, you 152 00:05:33,345 --> 00:05:35,685 know, have you solved all problems in health? 153 00:05:35,745 --> 00:05:37,824 And I think Ambient Scribe becomes a very 154 00:05:37,824 --> 00:05:39,125 interesting one because 155 00:05:39,879 --> 00:05:41,420 this was a problem that 156 00:05:41,800 --> 00:05:43,500 we like, over the last 157 00:05:44,040 --> 00:05:46,680 few decades, we kinda created for our doctors 158 00:05:46,680 --> 00:05:49,720 and nurses where documentation burden sort of, kept 159 00:05:49,720 --> 00:05:51,800 growing. And here we have a technology solution 160 00:05:51,800 --> 00:05:54,225 that allows them to, you know, solve that 161 00:05:54,225 --> 00:05:56,084 problem, that that classical 162 00:05:56,704 --> 00:05:58,625 pajama time that they were sort of all 163 00:05:58,625 --> 00:06:00,384 giving. And you've done many of podcasts with 164 00:06:00,384 --> 00:06:02,824 Becker's, and articles around that. So I want 165 00:06:02,824 --> 00:06:04,544 to report the audience with it. But, you 166 00:06:04,544 --> 00:06:07,589 know, here we have is a huge problem 167 00:06:07,589 --> 00:06:09,830 that now we that we can try to 168 00:06:09,830 --> 00:06:11,370 solve with, with tech. 169 00:06:12,230 --> 00:06:14,410 Continuing with, you know, our other initiatives, 170 00:06:15,029 --> 00:06:17,449 you know, we also launched our AI governance 171 00:06:17,509 --> 00:06:20,149 framework and our AI policy for the entire 172 00:06:20,149 --> 00:06:22,170 health system to guide how things go. 173 00:06:22,764 --> 00:06:24,604 You know? And we've had our evolution in 174 00:06:24,604 --> 00:06:27,164 that. Last year, when we started, we launched 175 00:06:27,164 --> 00:06:29,004 what we call governance one point o. We 176 00:06:29,004 --> 00:06:31,004 learned from their lessons. The starting of this 177 00:06:31,004 --> 00:06:33,245 year, we launched governance two point o. And 178 00:06:33,245 --> 00:06:36,240 we're already thinking about governance three point o. 179 00:06:36,319 --> 00:06:38,000 And if your audience is saying, well, what's 180 00:06:38,000 --> 00:06:40,339 the difference between each of these? I think, 181 00:06:41,000 --> 00:06:43,060 you know, as we went through our phases, 182 00:06:43,519 --> 00:06:45,620 we started thinking of AI governance 183 00:06:46,240 --> 00:06:46,899 in terms 184 00:06:47,360 --> 00:06:49,360 of quick decision making because we were facing 185 00:06:49,360 --> 00:06:51,205 a lot of volume of requests that are 186 00:06:51,205 --> 00:06:52,024 coming in. 187 00:06:52,324 --> 00:06:54,665 And then as we were able to stabilize 188 00:06:54,725 --> 00:06:56,964 that, we realized that we needed, you know, 189 00:06:56,964 --> 00:06:59,685 significant input in governance two point o from 190 00:06:59,685 --> 00:07:01,225 all walks of our 191 00:07:01,845 --> 00:07:04,490 ecosystem. You know, of course, the clinical teams, 192 00:07:04,490 --> 00:07:06,970 the nursing teams, as well as people in 193 00:07:06,970 --> 00:07:07,949 finance and 194 00:07:08,329 --> 00:07:11,449 legal and privacy and cyber and so on. 195 00:07:11,449 --> 00:07:14,029 So that is the combination of our governance 196 00:07:14,089 --> 00:07:16,329 two point o. And then, you know, we're 197 00:07:16,329 --> 00:07:16,829 seeing 198 00:07:17,294 --> 00:07:20,334 how even this process can be improved given 199 00:07:20,334 --> 00:07:22,574 the new volume of request that we're getting 200 00:07:22,574 --> 00:07:24,654 on AI, and we're starting to think of 201 00:07:24,654 --> 00:07:26,254 governance sort of three point o. So it's 202 00:07:26,254 --> 00:07:28,814 a very, you know, deliberate iterative process, and, 203 00:07:28,814 --> 00:07:30,629 you know, we're really sort of proud of 204 00:07:30,629 --> 00:07:32,389 what we've done. You know, we've, 205 00:07:33,350 --> 00:07:34,169 looked at 206 00:07:34,629 --> 00:07:37,430 over, like, 80 like, we've launched over 80 207 00:07:37,430 --> 00:07:38,310 some solutions. We have, 208 00:07:39,110 --> 00:07:39,610 several, 209 00:07:40,149 --> 00:07:42,089 close to a 100 more in the pipeline 210 00:07:42,470 --> 00:07:45,115 and covers the entire gamut of, like, radiology 211 00:07:45,115 --> 00:07:48,615 and acute care, cardiology, revenue cycle, patient access, 212 00:07:49,714 --> 00:07:52,194 GI, IT security, nursing, just to sort of, 213 00:07:52,194 --> 00:07:53,254 you know, name a few. 214 00:07:54,115 --> 00:07:56,435 Now with that sort of said, we also 215 00:07:56,435 --> 00:07:57,175 feel that 216 00:07:58,009 --> 00:08:00,569 the most important initiatives are also the ones 217 00:08:00,569 --> 00:08:02,829 where we have deep partnerships with our business. 218 00:08:03,050 --> 00:08:04,729 So in this area, we've done a lot 219 00:08:04,729 --> 00:08:06,889 of work in our with our population health 220 00:08:06,889 --> 00:08:09,310 teams and within our care management organization, 221 00:08:09,850 --> 00:08:11,955 you know, when when it comes to having 222 00:08:11,955 --> 00:08:12,935 data on 223 00:08:13,314 --> 00:08:15,795 care gap closures, having data on where they 224 00:08:15,875 --> 00:08:17,555 how are they're they're doing with their heat 225 00:08:17,555 --> 00:08:19,634 is measures. On the clinical side, you know, 226 00:08:19,634 --> 00:08:20,615 we've, started 227 00:08:21,475 --> 00:08:23,955 auto tagging of sort of cancer types using 228 00:08:23,955 --> 00:08:26,675 GenAI tools, like the bio clinical BERTs sort 229 00:08:26,675 --> 00:08:26,754 of, 230 00:08:27,580 --> 00:08:28,080 capabilities. 231 00:08:28,620 --> 00:08:30,939 On the research side, we actually entered last 232 00:08:30,939 --> 00:08:33,600 year into a partnership with Dandelion Health. 233 00:08:33,980 --> 00:08:36,860 You know? And there's details written up about 234 00:08:36,860 --> 00:08:39,759 it, but, essentially, you know, we will 235 00:08:40,085 --> 00:08:42,164 partner we are part of a consortium of, 236 00:08:42,884 --> 00:08:45,225 four other health systems around the country 237 00:08:45,605 --> 00:08:47,625 which are offering de identified data 238 00:08:48,565 --> 00:08:50,264 to, you know, test out, 239 00:08:51,445 --> 00:08:53,144 AI tools, AI algorithms, 240 00:08:54,080 --> 00:08:56,560 advanced research, all in a safety and invite 241 00:08:56,560 --> 00:08:58,560 sort of framework. So we're very proud of 242 00:08:58,560 --> 00:08:59,540 that sort of partnership. 243 00:09:00,080 --> 00:09:01,519 And that's just to name a few. You 244 00:09:01,519 --> 00:09:02,180 know? I'm, 245 00:09:02,560 --> 00:09:04,240 of course, not talking about, you know, things 246 00:09:04,240 --> 00:09:05,840 that we did with our pharmacy. We have 247 00:09:05,840 --> 00:09:08,320 a strong one Amazon One Medical partnership and 248 00:09:08,320 --> 00:09:09,995 so on. But I'll I'll I'll shut up 249 00:09:09,995 --> 00:09:12,154 for now, and hopefully that gives you a 250 00:09:12,154 --> 00:09:13,514 little bit of a perspective of, 251 00:09:14,475 --> 00:09:15,535 what we've been doing. 252 00:09:16,875 --> 00:09:19,355 Absolutely. That's incredible. I mean, you know, to 253 00:09:19,355 --> 00:09:21,835 have so many different AI solutions in the 254 00:09:21,835 --> 00:09:23,610 pipeline close to a 100 is, 255 00:09:24,250 --> 00:09:26,889 really, really a huge accomplishment right now. And 256 00:09:26,889 --> 00:09:30,089 I, appreciate you talking through, you know, whether, 257 00:09:30,730 --> 00:09:32,970 the governance process, that structure. I know a 258 00:09:32,970 --> 00:09:35,049 lot of health systems and leaders that I 259 00:09:35,049 --> 00:09:37,209 talk to, that's a sticking point for them, 260 00:09:37,209 --> 00:09:39,274 trying to figure out how they're incorporating 261 00:09:39,735 --> 00:09:42,134 AI smartly into that governance process to make 262 00:09:42,134 --> 00:09:44,454 sure they're not missing anything, but also not 263 00:09:44,454 --> 00:09:46,774 reinventing the wheel and keeping the aspects of 264 00:09:46,774 --> 00:09:47,274 governance 265 00:09:47,575 --> 00:09:49,894 in place that have worked across the board. 266 00:09:50,214 --> 00:09:52,149 So it seems like you know, being able 267 00:09:52,149 --> 00:09:54,070 to move quickly is important, but obviously you 268 00:09:54,070 --> 00:09:55,990 want to mitigate the risks and make sure 269 00:09:55,990 --> 00:09:57,830 you're not moving too quickly and finding that 270 00:09:57,830 --> 00:09:58,570 right balance, 271 00:09:59,029 --> 00:10:00,649 is critical, it seems like. 272 00:10:01,029 --> 00:10:04,855 Indeed. Ashley Inkumsah: Absolutely. Well, I'm curious, you 273 00:10:04,855 --> 00:10:06,534 know, kind of building upon all of these 274 00:10:06,534 --> 00:10:08,534 things that you've been talking about, these different 275 00:10:08,534 --> 00:10:11,834 AI applications and really incorporating that into, 276 00:10:12,214 --> 00:10:14,794 the the daily workflows for your team members, 277 00:10:14,934 --> 00:10:16,134 what do you see as being some of 278 00:10:16,134 --> 00:10:18,134 the big priorities and headwinds that you're focused 279 00:10:18,134 --> 00:10:19,914 on for the rest of this year? 280 00:10:21,470 --> 00:10:22,210 Oh, yeah. 281 00:10:23,070 --> 00:10:24,029 Well, I think, 282 00:10:24,509 --> 00:10:26,370 from a when it comes to priorities, 283 00:10:27,149 --> 00:10:28,990 you know, we to the point that I 284 00:10:28,990 --> 00:10:30,830 made earlier, we really wanna align with our 285 00:10:30,830 --> 00:10:33,710 business and clinical teams in, you know, exploring 286 00:10:33,710 --> 00:10:34,929 the problems that 287 00:10:35,865 --> 00:10:37,225 they face day to day and how it 288 00:10:37,225 --> 00:10:39,625 can be all through tech, through AI, and 289 00:10:39,625 --> 00:10:41,544 and other tools. And in that, you know, 290 00:10:41,544 --> 00:10:43,865 there are certain areas that have popped up, 291 00:10:44,264 --> 00:10:45,804 big in that space. 292 00:10:46,504 --> 00:10:48,745 You know, many of your our our colleagues 293 00:10:48,745 --> 00:10:51,549 here who are listening in will have been 294 00:10:51,610 --> 00:10:52,990 thinking about rev cycle. 295 00:10:53,449 --> 00:10:55,949 And, you know, we see a huge opportunity 296 00:10:56,089 --> 00:10:58,829 in revenue cycle, whether it's in terms of, 297 00:10:59,850 --> 00:11:02,429 you know, denials management, prior authorization, 298 00:11:02,809 --> 00:11:05,389 you know, other sort of functional areas where, 299 00:11:05,449 --> 00:11:07,894 you know, know, we have a huge opportunity 300 00:11:08,995 --> 00:11:12,035 to work better, to have better throughput, get 301 00:11:12,035 --> 00:11:14,274 better outputs, you know, as we partner with 302 00:11:14,274 --> 00:11:15,555 our, health, 303 00:11:15,955 --> 00:11:18,835 payers as well. Supply chain is another huge 304 00:11:18,835 --> 00:11:19,335 area. 305 00:11:20,049 --> 00:11:21,509 You know, if you think about, 306 00:11:21,889 --> 00:11:24,690 you know and most health systems, you know, 307 00:11:24,690 --> 00:11:27,649 supply chain is a significant significant probably number 308 00:11:27,649 --> 00:11:29,190 two or number three when it comes 309 00:11:29,809 --> 00:11:31,970 to the amount of cost and revenue that 310 00:11:31,970 --> 00:11:33,684 they sort of have to handle. 311 00:11:34,225 --> 00:11:37,204 And, you know, they look at contracts. 312 00:11:37,584 --> 00:11:39,264 There's a lot of information that they have 313 00:11:39,264 --> 00:11:41,105 to extract. You know, they have so many 314 00:11:41,105 --> 00:11:43,284 different vendors looking across the different 315 00:11:44,065 --> 00:11:46,225 vendor landscape. You know, I kinda always say 316 00:11:46,225 --> 00:11:48,320 it's, you you know, they're buying pencils to 317 00:11:48,320 --> 00:11:49,139 MRI machines. 318 00:11:50,000 --> 00:11:53,120 So, you know, have using AI in a 319 00:11:53,120 --> 00:11:54,419 thoughtful manner there 320 00:11:55,200 --> 00:11:55,940 is huge. 321 00:11:56,320 --> 00:11:58,720 HR is another area, you know, from a 322 00:11:58,720 --> 00:12:00,634 business perspective, you know, because we get a 323 00:12:00,634 --> 00:12:02,794 lot of internal questions around basic things like, 324 00:12:02,794 --> 00:12:04,955 you know, what's the vacation policy, how it's 325 00:12:04,955 --> 00:12:05,455 happening, 326 00:12:05,834 --> 00:12:07,355 what are the rules around x, y, and 327 00:12:07,355 --> 00:12:07,855 z 328 00:12:08,475 --> 00:12:09,754 that we get a lot of sort of 329 00:12:09,754 --> 00:12:10,975 staffing separate question. 330 00:12:11,830 --> 00:12:14,230 On the clinical side, you know, there's a 331 00:12:14,230 --> 00:12:16,809 a ton that we're thinking of in diabetes 332 00:12:16,870 --> 00:12:17,929 management outreach 333 00:12:18,470 --> 00:12:20,490 and population health care gap closures 334 00:12:20,870 --> 00:12:22,789 in our sort of surgical areas. You know, 335 00:12:22,789 --> 00:12:24,389 we do so much in our sort of 336 00:12:24,389 --> 00:12:25,289 peri ops 337 00:12:25,625 --> 00:12:29,004 space, with that. So, you know, all those 338 00:12:29,544 --> 00:12:31,725 are active exploration and discovery 339 00:12:32,904 --> 00:12:35,725 and sometimes even some deeper that's happening. And 340 00:12:35,945 --> 00:12:38,524 finally, from a tech perspective, from a priorities 341 00:12:38,745 --> 00:12:40,845 point of view, you know, we're looking at 342 00:12:41,549 --> 00:12:42,210 conversational AI 343 00:12:42,669 --> 00:12:45,409 because, you know, that allows our nurses 344 00:12:45,710 --> 00:12:47,970 and sort of front desk staff to, 345 00:12:48,269 --> 00:12:50,509 you know, focus on the higher acuity sort 346 00:12:50,509 --> 00:12:52,029 of, you know, patients. And so we're looking 347 00:12:52,029 --> 00:12:54,450 into sort of implementing tools in that space. 348 00:12:54,745 --> 00:12:57,144 And we're also, you know, starting to look 349 00:12:57,144 --> 00:12:59,144 deeper into the partnerships that we already have 350 00:12:59,144 --> 00:13:00,825 with our sort of vendors. I mean, you 351 00:13:00,825 --> 00:13:01,325 know, 352 00:13:02,105 --> 00:13:04,425 we of course, it's the we use Epic 353 00:13:04,425 --> 00:13:06,985 as our EMR, and Epic has been, you 354 00:13:06,985 --> 00:13:10,205 know, pretty amazing in terms of, exposing tools 355 00:13:11,039 --> 00:13:13,220 in the space of AI and productivity, 356 00:13:13,519 --> 00:13:14,580 and we're actively, 357 00:13:15,039 --> 00:13:17,120 looking at those. We have about 10 or 358 00:13:17,120 --> 00:13:19,120 12 act in in our pipeline that are 359 00:13:19,120 --> 00:13:21,200 going some many of them are live in 360 00:13:21,200 --> 00:13:23,120 use right now. Many are about to sort 361 00:13:23,120 --> 00:13:24,559 of go live, and we have a longer 362 00:13:24,559 --> 00:13:26,444 sort of road map of how we switch 363 00:13:26,444 --> 00:13:29,324 those capabilities on. And it doesn't just stop 364 00:13:29,324 --> 00:13:31,324 with our EMR systems. You know, we're looking 365 00:13:31,324 --> 00:13:33,245 at our operational systems. You know, we use 366 00:13:33,245 --> 00:13:33,745 ServiceNow. 367 00:13:34,284 --> 00:13:36,464 What can we use there to increase efficiency 368 00:13:36,524 --> 00:13:39,245 and respond better to our customer requests? You 369 00:13:39,245 --> 00:13:39,985 know, Workday. 370 00:13:40,450 --> 00:13:42,230 We went through that implementation, 371 00:13:42,610 --> 00:13:44,850 and Workday itself has tools. And as you 372 00:13:44,850 --> 00:13:47,029 as you look at our at our application 373 00:13:47,169 --> 00:13:48,230 landscape, every 374 00:13:48,769 --> 00:13:51,169 vendor is trying to sort of build build 375 00:13:51,169 --> 00:13:53,649 tools in for added efficiency, cost savings, and 376 00:13:53,649 --> 00:13:55,464 so on. So, you know, those would be 377 00:13:55,464 --> 00:13:56,584 sort of the a little bit of a 378 00:13:56,584 --> 00:13:58,845 smattering of the priorities that we're looking at. 379 00:13:59,704 --> 00:14:01,804 I think you asked about headwinds as well. 380 00:14:02,264 --> 00:14:05,225 So, well, there there are plenty, and your 381 00:14:05,225 --> 00:14:05,945 audience is, 382 00:14:06,664 --> 00:14:08,184 is no stranger to those. 383 00:14:08,504 --> 00:14:09,964 You know, I like to say that 384 00:14:11,040 --> 00:14:12,399 health care likes to go through, 385 00:14:13,360 --> 00:14:15,279 not likes to. It just goes through feast 386 00:14:15,279 --> 00:14:17,279 and famine cycles, you know, when it comes 387 00:14:17,279 --> 00:14:19,360 to funding and so on. So, you know, 388 00:14:19,360 --> 00:14:22,080 as we look at 2026 and 2027, 389 00:14:22,080 --> 00:14:24,639 the the macro environments will kind of force 390 00:14:24,639 --> 00:14:25,279 us to, 391 00:14:26,024 --> 00:14:28,284 focus a lot on the cost savings. 392 00:14:29,225 --> 00:14:31,884 You know, the other part will be filtering, 393 00:14:32,184 --> 00:14:34,845 you know, signal from the noise. You know? 394 00:14:35,865 --> 00:14:37,164 Health care is embracing, 395 00:14:37,544 --> 00:14:38,044 unlike 396 00:14:38,889 --> 00:14:41,389 like many or similar to other industry, 397 00:14:42,089 --> 00:14:43,529 but I think you need to health care 398 00:14:43,529 --> 00:14:45,629 now is we are embracing, 399 00:14:47,049 --> 00:14:48,809 AI at a faster pace. You know, the 400 00:14:48,809 --> 00:14:50,970 interest is there both the leadership level, the 401 00:14:50,970 --> 00:14:53,115 clinical level, the nursing level to do that. 402 00:14:53,434 --> 00:14:55,034 And then how do you filter out the 403 00:14:55,034 --> 00:14:57,274 signal from the noise? What is worth investing 404 00:14:57,274 --> 00:14:59,294 in? What is not worth investing in? 405 00:14:59,754 --> 00:15:02,315 The other headwinds are around protecting our data 406 00:15:02,315 --> 00:15:04,095 and our information, you know, because, 407 00:15:04,394 --> 00:15:06,634 I mean, of all the big bold ideas 408 00:15:06,634 --> 00:15:08,315 that we have, we have to be mindful 409 00:15:08,315 --> 00:15:10,070 that, you know, we are we are guard 410 00:15:10,149 --> 00:15:11,830 you know, we have to protect our patients' 411 00:15:11,830 --> 00:15:12,649 set of data. 412 00:15:14,309 --> 00:15:17,049 You know, we there there's always a potential 413 00:15:17,110 --> 00:15:19,110 for breaches, so we partner very closely with 414 00:15:19,110 --> 00:15:20,250 our, you know, cybersecurity 415 00:15:20,709 --> 00:15:21,209 teams. 416 00:15:22,544 --> 00:15:25,024 Especially with AI. There's new aspects of data 417 00:15:25,024 --> 00:15:26,404 come that come in, which is, 418 00:15:26,945 --> 00:15:28,384 you know, what is the vendor doing with 419 00:15:28,384 --> 00:15:30,485 your data? How are they training this? 420 00:15:31,745 --> 00:15:32,644 Partner with, 421 00:15:33,545 --> 00:15:34,965 you know, the large LLMs. 422 00:15:35,370 --> 00:15:37,769 You know, what is going on in terms 423 00:15:37,769 --> 00:15:39,289 of the safety of our data? What kind 424 00:15:39,289 --> 00:15:41,049 of agreements we need to have there? So 425 00:15:41,049 --> 00:15:43,049 those are, like, going to be I mean, 426 00:15:43,049 --> 00:15:44,809 they've always been challenges for us, but I 427 00:15:44,809 --> 00:15:46,509 think they will continue to be challenges. 428 00:15:47,129 --> 00:15:48,750 And finally, just, you know, 429 00:15:49,164 --> 00:15:50,764 the other headwind is, like, we have to 430 00:15:50,764 --> 00:15:52,605 go be steady in in the storm. I 431 00:15:52,605 --> 00:15:54,144 think there's so much 432 00:15:54,924 --> 00:15:56,625 news, media, articles 433 00:15:57,245 --> 00:15:59,644 that's coming out. All the things about the 434 00:15:59,644 --> 00:16:01,644 glorious things that AI can do and all 435 00:16:01,644 --> 00:16:03,404 the mistakes that it can do and all 436 00:16:03,404 --> 00:16:04,065 the doom, 437 00:16:04,949 --> 00:16:07,110 that it can cause or all the amazing 438 00:16:07,110 --> 00:16:09,750 things it can do. So staying true to 439 00:16:09,750 --> 00:16:10,409 our mission 440 00:16:11,110 --> 00:16:13,909 and aligning with the needs of our staff, 441 00:16:13,909 --> 00:16:14,889 doctors, and nurses, 442 00:16:15,350 --> 00:16:17,110 that will be a big sort of headwind 443 00:16:17,110 --> 00:16:19,315 that we have to manage as well. Anyway, 444 00:16:19,315 --> 00:16:20,294 I said a lot, 445 00:16:20,914 --> 00:16:22,914 but that's, that's what we're sort of tackling 446 00:16:22,914 --> 00:16:23,574 right now. 447 00:16:24,674 --> 00:16:27,074 Yeah. Absolutely. I mean, you know, it's a 448 00:16:27,074 --> 00:16:29,475 huge space and and certainly a lot of 449 00:16:29,475 --> 00:16:30,595 challenges out there, 450 00:16:31,009 --> 00:16:32,850 across the board. And so, you know, when 451 00:16:32,850 --> 00:16:33,830 you're looking at, 452 00:16:34,370 --> 00:16:35,190 the opportunities 453 00:16:35,809 --> 00:16:39,330 out there, I I think, so many possible 454 00:16:39,330 --> 00:16:41,570 partnerships you could have, new companies coming up 455 00:16:41,570 --> 00:16:43,409 every day as well as, like you mentioned, 456 00:16:43,409 --> 00:16:44,629 you know, existing, 457 00:16:45,455 --> 00:16:47,715 partners coming out with new AI applications 458 00:16:48,095 --> 00:16:51,295 in ways to ideally increase efficiencies and and 459 00:16:51,295 --> 00:16:54,975 become, more critical within your daily workflows. So 460 00:16:54,975 --> 00:16:57,875 I'm curious when you're evaluating all the opportunities 461 00:16:58,014 --> 00:17:00,980 out there and and trying to bring, your 462 00:17:00,980 --> 00:17:03,139 your teams along, and especially in health care, 463 00:17:03,139 --> 00:17:04,440 you know, there can be some, 464 00:17:04,820 --> 00:17:07,299 resistance to change in in certain ways. How 465 00:17:07,299 --> 00:17:09,619 do you, kind of bridge that gap and 466 00:17:09,619 --> 00:17:12,099 really make sure you're, one, selecting the right 467 00:17:12,099 --> 00:17:13,394 things, and then, two, 468 00:17:13,955 --> 00:17:15,955 putting your team in the position to actually 469 00:17:15,955 --> 00:17:17,394 use it so, you know, these, 470 00:17:18,035 --> 00:17:20,115 new applications that you're bringing in or or 471 00:17:20,115 --> 00:17:21,015 working through 472 00:17:21,315 --> 00:17:22,375 aren't left dormant, 473 00:17:22,835 --> 00:17:24,295 you know, a year from now. 474 00:17:25,980 --> 00:17:27,440 Yeah. No. I think, you know 475 00:17:27,819 --> 00:17:30,460 and this is where all '37, thirty eight 476 00:17:30,460 --> 00:17:32,539 thousand employees, you know, have a role to 477 00:17:32,539 --> 00:17:33,039 play. 478 00:17:33,420 --> 00:17:33,920 And, 479 00:17:34,460 --> 00:17:36,940 you know, there are many aspects that go 480 00:17:36,940 --> 00:17:37,440 in. 481 00:17:37,819 --> 00:17:39,200 One, we don't wanna 482 00:17:39,500 --> 00:17:40,000 force 483 00:17:40,299 --> 00:17:40,960 AI down 484 00:17:41,975 --> 00:17:44,775 any sort of, particular area. You know, there 485 00:17:44,775 --> 00:17:48,055 has to be a conversation and understanding of 486 00:17:48,055 --> 00:17:50,375 what it does, what it doesn't do. There's 487 00:17:50,375 --> 00:17:51,015 a lot of, 488 00:17:51,654 --> 00:17:53,734 training and coaching that goes in there in 489 00:17:53,734 --> 00:17:56,455 terms of what is the value of that, 490 00:17:56,455 --> 00:17:59,890 you know, talking and being actually honest about 491 00:18:00,029 --> 00:18:02,349 some of the skepticism that people have. And 492 00:18:02,349 --> 00:18:03,950 that is a journey. And sometimes you take 493 00:18:03,950 --> 00:18:05,730 two steps forward and one step backward. 494 00:18:06,029 --> 00:18:08,269 You know, when it comes to, you know, 495 00:18:08,269 --> 00:18:08,769 people 496 00:18:09,070 --> 00:18:10,690 in teams who may be genuinely, 497 00:18:11,244 --> 00:18:14,204 you know, nervous and anxious about the quality 498 00:18:14,204 --> 00:18:15,424 of the tools, the, 499 00:18:15,804 --> 00:18:17,964 stability of these tools, the accuracy of these 500 00:18:17,964 --> 00:18:19,964 tools. So, you know, so we have to 501 00:18:19,964 --> 00:18:20,464 definitely 502 00:18:21,325 --> 00:18:23,424 sort of do that. We also, 503 00:18:23,724 --> 00:18:26,169 you know, have certain measurements. So we haven't 504 00:18:26,169 --> 00:18:28,649 talked a lot about, the control towers and 505 00:18:28,649 --> 00:18:31,210 the control centers that we have to overall 506 00:18:31,210 --> 00:18:33,289 monitor the use of AI. And not just 507 00:18:33,289 --> 00:18:36,089 monitoring from a performance drift other perspective, but 508 00:18:36,089 --> 00:18:39,005 also from a, hey. Did it meet the 509 00:18:39,005 --> 00:18:41,345 hypothesis that you had going into it? 510 00:18:41,964 --> 00:18:43,884 Because if you think about it, you know, 511 00:18:43,884 --> 00:18:46,365 many large organizations like ours and especially in 512 00:18:46,365 --> 00:18:47,025 health care, 513 00:18:47,444 --> 00:18:48,684 you know, I like to say that we're 514 00:18:48,684 --> 00:18:50,605 really good at addition, but not good at 515 00:18:50,605 --> 00:18:51,105 subtraction. 516 00:18:51,404 --> 00:18:52,470 And And let me tell you what I 517 00:18:52,470 --> 00:18:54,070 mean by that. What I mean is we're 518 00:18:54,070 --> 00:18:56,170 really good at adding more and more 519 00:18:56,789 --> 00:18:59,029 solutions and tech to it, but we're not 520 00:18:59,029 --> 00:19:00,410 as deliberate about 521 00:19:00,789 --> 00:19:03,269 subtracting it and taking them away. So we've 522 00:19:03,269 --> 00:19:05,609 been very conscious in terms of 523 00:19:06,205 --> 00:19:08,465 our approach to tech and AI 524 00:19:09,005 --> 00:19:11,105 is as we work through our governance process, 525 00:19:12,525 --> 00:19:15,105 we will go back to solutions and say, 526 00:19:15,325 --> 00:19:17,565 you have you know, when you launch a 527 00:19:17,565 --> 00:19:20,144 solution and when AI governance approved it, 528 00:19:20,559 --> 00:19:22,799 the hypothesis was it was going to do 529 00:19:22,799 --> 00:19:25,279 x, you know, x number of patient encounters 530 00:19:25,279 --> 00:19:28,240 and improve win productivity or maybe some dollar 531 00:19:28,240 --> 00:19:31,200 threshold or numbers or volume thresholds or something 532 00:19:31,200 --> 00:19:32,019 something something. 533 00:19:32,734 --> 00:19:34,654 Is it doing that? And let's be very 534 00:19:34,654 --> 00:19:37,315 honest to measure if it's doing that. And 535 00:19:38,015 --> 00:19:38,994 if it isn't, 536 00:19:39,375 --> 00:19:41,055 let's take it out. Let's take it out 537 00:19:41,055 --> 00:19:41,875 of our ecosystem 538 00:19:42,414 --> 00:19:44,575 and do that. And trust me, these are 539 00:19:44,575 --> 00:19:46,589 not easy conversations to have. 540 00:19:47,150 --> 00:19:49,069 But that is a framework that is needed 541 00:19:49,069 --> 00:19:51,230 so that, you know, two years, three years 542 00:19:51,230 --> 00:19:53,710 down the line, we're not taking on so 543 00:19:53,710 --> 00:19:54,769 much tech debt 544 00:19:55,150 --> 00:19:57,390 that we have to, you know, have a 545 00:19:57,390 --> 00:19:59,970 separate exercise to unwind all all of that. 546 00:20:00,345 --> 00:20:01,484 Does that make sense? 547 00:20:02,265 --> 00:20:04,505 Yeah. That's so helpful to understand how you're 548 00:20:04,505 --> 00:20:06,265 thinking about these things and, you know, really 549 00:20:06,265 --> 00:20:07,964 truly trying to avoid that, 550 00:20:08,424 --> 00:20:10,044 technical debt for sure. 551 00:20:10,345 --> 00:20:12,105 I'm curious, you know, when looking ahead, what 552 00:20:12,105 --> 00:20:13,544 do you think the hardest thing you'll have 553 00:20:13,544 --> 00:20:15,244 to do in the coming year will be? 554 00:20:16,519 --> 00:20:17,240 Yeah. I think, 555 00:20:18,919 --> 00:20:20,839 and again, this is something maybe your audience 556 00:20:20,839 --> 00:20:22,220 can appreciate as well, 557 00:20:23,079 --> 00:20:25,980 especially if it's, in a large health system 558 00:20:26,039 --> 00:20:28,359 like ours with an academic medical center as 559 00:20:28,359 --> 00:20:31,275 well, is just picking the right problems to 560 00:20:31,275 --> 00:20:33,115 solve. You know, I like to joke with 561 00:20:33,115 --> 00:20:34,875 my not joke, but at least have a 562 00:20:34,875 --> 00:20:37,275 conversation with my stakeholder team and my leadership 563 00:20:37,275 --> 00:20:37,775 is 564 00:20:38,714 --> 00:20:40,734 we have a 100 problems to solve, 565 00:20:41,275 --> 00:20:43,755 but the funding and resources to do 17 566 00:20:43,755 --> 00:20:44,414 of them. 567 00:20:45,440 --> 00:20:47,519 And then how do we do that? So 568 00:20:47,599 --> 00:20:49,539 and it is very hard because, 569 00:20:50,160 --> 00:20:52,480 you know, when someone comes in and says, 570 00:20:52,480 --> 00:20:54,019 this is going to help me 571 00:20:54,480 --> 00:20:54,980 detect 572 00:20:55,519 --> 00:20:56,740 a particular disease 573 00:20:57,605 --> 00:20:59,765 three days earlier, five days earlier, or this 574 00:20:59,765 --> 00:21:02,164 will have a clinical impact on someone who 575 00:21:02,164 --> 00:21:05,045 is working with diabetes, or here's a cost 576 00:21:05,045 --> 00:21:07,845 saving or split. It is very hard to 577 00:21:07,845 --> 00:21:10,085 make those decisions to pick those 17 or 578 00:21:10,085 --> 00:21:11,464 20 out of the 100, 579 00:21:12,420 --> 00:21:13,860 But we have to because we don't have 580 00:21:13,860 --> 00:21:14,920 unlimited resources. 581 00:21:15,539 --> 00:21:16,920 So allocating our funds 582 00:21:17,460 --> 00:21:20,019 wisely in that area, investing in the right 583 00:21:20,019 --> 00:21:22,340 things where we see the right quote unquote 584 00:21:22,340 --> 00:21:24,360 me. I'm doing air quotes right now ROI 585 00:21:24,420 --> 00:21:27,105 because ROI is defined very differently for every 586 00:21:27,105 --> 00:21:29,025 organization. So I'm looking at it from a 587 00:21:29,025 --> 00:21:30,865 purely DARS perspective. Some, 588 00:21:31,184 --> 00:21:33,105 identify other factors. You know, we, of course, 589 00:21:33,105 --> 00:21:35,204 have our framework for that. But 590 00:21:35,664 --> 00:21:37,585 it really will be how do we pick 591 00:21:37,585 --> 00:21:39,365 the right problems to solve. 592 00:21:40,019 --> 00:21:41,700 And to the question that I asked, sort 593 00:21:41,700 --> 00:21:43,940 of your audience to think through is, you 594 00:21:43,940 --> 00:21:46,100 know, do we feel that we have solved 595 00:21:46,100 --> 00:21:47,779 all our problems? So as we look at 596 00:21:47,779 --> 00:21:49,539 our health systems, what is the biggest one? 597 00:21:49,539 --> 00:21:51,539 Is access big? Is reaching out to a 598 00:21:51,539 --> 00:21:53,240 certain patient population big? 599 00:21:53,595 --> 00:21:56,234 Is, looking at the high acuity patients, you 600 00:21:56,234 --> 00:21:57,835 know, who may have a lung nodule that 601 00:21:57,835 --> 00:21:58,335 goes 602 00:21:58,714 --> 00:22:00,714 undiagnosed for a period of time to get 603 00:22:00,714 --> 00:22:02,954 a referral appointment back? Like, so there's so 604 00:22:02,954 --> 00:22:04,474 many of them, but just picking the right 605 00:22:04,474 --> 00:22:05,454 problems, I think, 606 00:22:05,950 --> 00:22:07,950 that has been always a challenge. But I 607 00:22:07,950 --> 00:22:10,350 think especially with the supercharged environment of tech 608 00:22:10,350 --> 00:22:11,410 that we're in right now, 609 00:22:11,789 --> 00:22:13,710 that I feel will be a pretty hard 610 00:22:13,710 --> 00:22:14,190 thing, 611 00:22:15,150 --> 00:22:17,250 for this year and many years to come. 612 00:22:19,345 --> 00:22:21,365 That makes a lot of sense. And certainly, 613 00:22:21,825 --> 00:22:24,144 you know, having that strong process, as you 614 00:22:24,144 --> 00:22:24,964 mentioned earlier, 615 00:22:25,265 --> 00:22:27,424 can make a big difference in in keeping 616 00:22:27,424 --> 00:22:27,924 things, 617 00:22:28,704 --> 00:22:31,345 you know, relatively focused in on what's most 618 00:22:31,345 --> 00:22:33,470 important for the health system, tying back to 619 00:22:33,470 --> 00:22:35,309 the mission and vision of where you wanna 620 00:22:35,309 --> 00:22:37,710 go. Before we wrap up here, I wanna 621 00:22:37,710 --> 00:22:39,549 talk about growth too. Where do you see 622 00:22:39,549 --> 00:22:42,029 some of the best opportunities for organizational growth 623 00:22:42,029 --> 00:22:42,769 in the future? 624 00:22:44,670 --> 00:22:46,849 Yeah. Well, that's a fascinating question. 625 00:22:48,255 --> 00:22:50,674 You know, if if I have to pick 626 00:22:51,615 --> 00:22:52,115 maybe 627 00:22:52,654 --> 00:22:53,154 one, 628 00:22:55,055 --> 00:22:56,275 I would say it's 629 00:22:56,734 --> 00:23:00,035 I see a unique opportunity in redefining 630 00:23:00,494 --> 00:23:01,555 the way we work. 631 00:23:03,179 --> 00:23:04,619 And, you know, and to those in the 632 00:23:04,619 --> 00:23:07,019 audience, you know, who are either rolling their 633 00:23:07,019 --> 00:23:09,099 eyes because every consultant walking to the door 634 00:23:09,099 --> 00:23:10,880 right now is using these big words, 635 00:23:11,419 --> 00:23:11,919 but 636 00:23:12,940 --> 00:23:15,419 I think there is a huge opportunity there. 637 00:23:15,419 --> 00:23:15,919 So 638 00:23:16,265 --> 00:23:18,585 maybe just let me share a story, a 639 00:23:18,585 --> 00:23:19,144 small one. 640 00:23:20,265 --> 00:23:22,345 So I was speaking recently to someone who 641 00:23:22,345 --> 00:23:25,625 is in ER radiology and also teaches radiology 642 00:23:25,625 --> 00:23:26,125 residents. 643 00:23:26,745 --> 00:23:28,745 And what they've been observing, they said, was 644 00:23:28,745 --> 00:23:31,589 that first year residents in radiology are catching 645 00:23:31,589 --> 00:23:33,509 up quite fast with their third year or 646 00:23:33,509 --> 00:23:34,809 even fourth year colleagues. 647 00:23:35,269 --> 00:23:37,609 And their hypothesis, again, not proven, 648 00:23:37,990 --> 00:23:40,069 was that this is due to AI because 649 00:23:40,069 --> 00:23:42,549 a lot of first year residents are adept 650 00:23:42,549 --> 00:23:44,650 at AI and are using it different ways. 651 00:23:45,045 --> 00:23:47,384 And then the discussion evolved into 652 00:23:48,644 --> 00:23:50,644 what can be done to further expand the 653 00:23:50,644 --> 00:23:52,644 scope and scale of what is taught to 654 00:23:52,644 --> 00:23:53,144 residents 655 00:23:54,005 --> 00:23:56,565 using now, perhaps AI as a tool. So 656 00:23:56,565 --> 00:23:58,424 now I'm not clinical, so I'm paraphrasing 657 00:23:58,965 --> 00:24:01,599 some of what they said. But can AI 658 00:24:02,059 --> 00:24:03,359 be used to expose 659 00:24:04,539 --> 00:24:07,740 radiology residents to other business fields that they 660 00:24:07,740 --> 00:24:10,460 interact with? Many earlier so much earlier. So 661 00:24:10,460 --> 00:24:13,180 that instead of looking at certain things from 662 00:24:13,180 --> 00:24:14,799 a very silo lens of radiology, 663 00:24:15,184 --> 00:24:16,464 they can look at it from a lens 664 00:24:16,464 --> 00:24:18,304 that a cardiologist would look at or a 665 00:24:18,304 --> 00:24:21,025 neurologist would look at. So now doctors in 666 00:24:21,025 --> 00:24:23,265 the audience may say, well, that's a cockamamie 667 00:24:23,265 --> 00:24:24,944 idea, but which is why I'm, you know, 668 00:24:24,944 --> 00:24:25,444 paraphrasing 669 00:24:25,984 --> 00:24:27,505 someone else, you know, who is way more 670 00:24:27,505 --> 00:24:29,285 intelligent than than I am in the clinical 671 00:24:30,359 --> 00:24:31,799 sphere. But I give that as a as 672 00:24:31,799 --> 00:24:33,099 an example to say, 673 00:24:33,400 --> 00:24:33,900 now 674 00:24:34,680 --> 00:24:35,180 imagine 675 00:24:36,839 --> 00:24:40,359 your processes, your workflows, the things that you 676 00:24:40,359 --> 00:24:43,900 do, whether it's operations or clinical or nursing, 677 00:24:44,984 --> 00:24:46,285 or call centers, 678 00:24:46,664 --> 00:24:49,484 supply chain or population health. Pick an area. 679 00:24:49,545 --> 00:24:51,005 Look upstream and downstream. 680 00:24:51,545 --> 00:24:53,785 Are there ways that we can redefine things 681 00:24:53,785 --> 00:24:55,565 a little bit? I think we have a 682 00:24:55,705 --> 00:24:56,845 once in a 683 00:24:57,609 --> 00:24:59,929 long time opportunity to be able to do 684 00:24:59,929 --> 00:25:01,849 that because we now have the tech tools, 685 00:25:01,849 --> 00:25:04,889 the AI tools, the capability, the desire, the 686 00:25:04,889 --> 00:25:07,369 capital required for it, the funding needed for 687 00:25:07,369 --> 00:25:09,769 it, the leadership and the board level interest 688 00:25:09,769 --> 00:25:11,795 in that, that it will be a missed 689 00:25:11,795 --> 00:25:13,474 opportunity if we don't do that from an 690 00:25:13,474 --> 00:25:15,795 organizational growth perspective. And this won't be a 691 00:25:15,795 --> 00:25:18,055 one year effort. This might be multiyear efforts 692 00:25:18,195 --> 00:25:19,095 and so on, 693 00:25:19,714 --> 00:25:20,214 but 694 00:25:20,994 --> 00:25:22,855 it allows us to focus on that. 695 00:25:24,019 --> 00:25:25,940 Yeah. Yeah. Definitely. I I think that makes 696 00:25:25,940 --> 00:25:27,140 a lot of sense. And, you know, it's 697 00:25:27,140 --> 00:25:28,919 really helpful to have that type of, 698 00:25:29,539 --> 00:25:31,079 focus in and then understanding 699 00:25:31,380 --> 00:25:33,539 where, you know, you're going from here. So 700 00:25:33,539 --> 00:25:36,019 I appreciate it. Sudipto, thank you so much 701 00:25:36,019 --> 00:25:37,619 for joining us on the podcast today. This 702 00:25:37,619 --> 00:25:39,815 has been a fun conversation. I'm really kind 703 00:25:39,815 --> 00:25:41,894 of focused, and I appreciate your time and 704 00:25:41,894 --> 00:25:43,894 energy on it and look forward to continuing 705 00:25:43,894 --> 00:25:46,535 the conversation soon. This was fascinating. Laura, I 706 00:25:46,535 --> 00:25:48,295 love your podcast, and I'm glad that we 707 00:25:48,295 --> 00:25:49,835 had an opportunity to discuss.