1 00:00:00,719 --> 00:00:04,000 Exciting things are happening at Becker's Healthcare. Stay 2 00:00:04,000 --> 00:00:06,240 ahead of industry trends with the new Becker's 3 00:00:06,240 --> 00:00:08,500 CFO plus Revenue Cycle podcast, 4 00:00:08,800 --> 00:00:11,119 your go to source for insights from top 5 00:00:11,119 --> 00:00:14,224 healthcare finance leaders. Tune in wherever you get 6 00:00:14,224 --> 00:00:14,964 your podcasts. 7 00:00:15,904 --> 00:00:18,464 And don't miss the tenth annual Health IT 8 00:00:18,464 --> 00:00:22,155 plus Digital Health plus RCM conference, happening September 9 00:00:22,155 --> 00:00:24,464 30 to 10/03/2025 10 00:00:24,464 --> 00:00:25,204 in Chicago. 11 00:00:25,664 --> 00:00:27,125 Join thousands of executives, 12 00:00:27,469 --> 00:00:30,429 engage with industry leaders, and explore the future 13 00:00:30,429 --> 00:00:31,570 of health care innovation. 14 00:00:32,270 --> 00:00:36,750 Learn more about our upcoming events at beckershospitalreview.com. 15 00:00:36,750 --> 00:00:37,570 See you there. 16 00:00:38,270 --> 00:00:40,429 This is Laura Dierda with the Becker's Healthcare 17 00:00:40,429 --> 00:00:42,494 podcast. I'm thrilled today to be joined by 18 00:00:42,494 --> 00:00:43,395 Omkar Kulkarni, 19 00:00:43,774 --> 00:00:46,414 vice president and chief transformation officer as well 20 00:00:46,414 --> 00:00:49,054 as chief innovation officer at Children's Hospital Los 21 00:00:49,054 --> 00:00:50,734 Angeles. Omkar, it's a pleasure to have you 22 00:00:50,734 --> 00:00:53,135 on the podcast today. Thank you for having 23 00:00:53,135 --> 00:00:53,635 me. 24 00:00:54,200 --> 00:00:55,879 Now I'm excited for our discussion. I know 25 00:00:55,879 --> 00:00:57,320 we'll be digging into some of the cool 26 00:00:57,320 --> 00:00:58,600 things you've done in the last year or 27 00:00:58,600 --> 00:01:00,519 so as well as your perspective on the 28 00:01:00,519 --> 00:01:02,119 future. But before we dive in, could you 29 00:01:02,119 --> 00:01:03,719 tell us a little bit more about Children's 30 00:01:03,719 --> 00:01:05,900 Hospital Los Angeles and what makes it unique? 31 00:01:06,534 --> 00:01:07,034 Absolutely. 32 00:01:07,974 --> 00:01:10,395 Children's Hospital Los Angeles is an amazing organization. 33 00:01:10,615 --> 00:01:12,395 We are, the largest, 34 00:01:13,015 --> 00:01:14,075 children's hospital, 35 00:01:14,454 --> 00:01:15,814 out here on the West, 36 00:01:16,215 --> 00:01:16,954 in California, 37 00:01:17,655 --> 00:01:20,234 and, we are top 10 children's hospital. 38 00:01:21,060 --> 00:01:22,439 We provide multidisciplinary 39 00:01:22,900 --> 00:01:23,400 care, 40 00:01:24,099 --> 00:01:24,599 in, 41 00:01:25,380 --> 00:01:26,760 in in various subspecialties 42 00:01:27,060 --> 00:01:28,040 across pediatrics. 43 00:01:28,659 --> 00:01:31,299 What's incredible to me about Children's Hospital Los 44 00:01:31,299 --> 00:01:34,439 Angeles is we are not only an exceptional 45 00:01:34,659 --> 00:01:35,959 organization for 46 00:01:36,525 --> 00:01:37,025 health 47 00:01:37,484 --> 00:01:40,365 care delivery. Our clinical care is some of 48 00:01:40,365 --> 00:01:41,505 the best in the country. 49 00:01:42,204 --> 00:01:44,284 And, also, we are a safety net hospital. 50 00:01:44,284 --> 00:01:44,784 So, 51 00:01:45,564 --> 00:01:47,885 we are unique in that sense in that 52 00:01:47,885 --> 00:01:50,445 we take care of the safety net in 53 00:01:50,445 --> 00:01:52,950 terms of the children of Los Angeles and 54 00:01:52,950 --> 00:01:54,170 broader Southern California, 55 00:01:55,349 --> 00:01:56,489 meaning we will, 56 00:01:56,869 --> 00:01:58,009 take care of patients 57 00:01:58,469 --> 00:02:01,269 regardless of of their insurance and their ability 58 00:02:01,269 --> 00:02:02,009 to pay. 59 00:02:02,310 --> 00:02:04,869 And that is incredibly important to me and 60 00:02:04,869 --> 00:02:06,915 and every one of the the thousands of 61 00:02:06,915 --> 00:02:08,134 people who work here. 62 00:02:08,435 --> 00:02:10,034 It is part of our mission. It is 63 00:02:10,034 --> 00:02:12,194 part of kinda who we are, and it 64 00:02:12,194 --> 00:02:13,875 makes it a fun place to work and 65 00:02:13,875 --> 00:02:15,474 and a rewarding place to work. I'll tell 66 00:02:15,474 --> 00:02:16,134 you that. 67 00:02:18,675 --> 00:02:20,834 Absolutely. That's amazing to hear. You know? And, 68 00:02:20,834 --> 00:02:23,620 certainly, what a great mission to serve children 69 00:02:23,620 --> 00:02:25,799 and promote health within the community. 70 00:02:26,180 --> 00:02:28,259 Now from your perspective and looking back on 71 00:02:28,259 --> 00:02:29,859 the last year or so, what are the 72 00:02:29,859 --> 00:02:31,799 accomplishments that you're most proud of? 73 00:02:33,985 --> 00:02:35,764 So we have really jumped 74 00:02:36,384 --> 00:02:38,084 two feet in into 75 00:02:38,784 --> 00:02:40,485 the world of artificial intelligence. 76 00:02:41,264 --> 00:02:42,884 We we've done many, many things, 77 00:02:43,985 --> 00:02:46,064 not just AI, but one of the things 78 00:02:46,064 --> 00:02:48,659 I'm really proud of is our approach towards, 79 00:02:50,159 --> 00:02:50,659 evaluating 80 00:02:51,280 --> 00:02:52,900 and then prioritizing 81 00:02:53,599 --> 00:02:54,340 and then, 82 00:02:54,960 --> 00:02:57,539 you know, implementing the piloting and implementing 83 00:02:58,000 --> 00:03:00,740 AI solutions here at the Children's Hospital. 84 00:03:01,275 --> 00:03:03,194 I say that because there's been in the 85 00:03:03,194 --> 00:03:05,514 industry and you know this, there's been so 86 00:03:05,514 --> 00:03:05,915 many, 87 00:03:06,314 --> 00:03:09,514 incredible new technologies that have been introduced in 88 00:03:09,514 --> 00:03:11,455 just the last, you know, year or two. 89 00:03:11,915 --> 00:03:14,235 And it can be hard for a hospital 90 00:03:14,235 --> 00:03:15,775 or a health system to, 91 00:03:16,129 --> 00:03:17,909 you know, make sense of all that, 92 00:03:18,290 --> 00:03:20,849 information and all that, you know, sometimes noise 93 00:03:20,849 --> 00:03:22,370 coming in as it relates to all these 94 00:03:22,370 --> 00:03:24,710 different amazing companies and their technologies. 95 00:03:25,250 --> 00:03:26,790 And we've done a great job, 96 00:03:27,250 --> 00:03:29,110 you know, starting with the problems 97 00:03:29,409 --> 00:03:32,224 that we're trying to solve, always problems first 98 00:03:32,525 --> 00:03:33,025 and 99 00:03:33,485 --> 00:03:35,485 using that as our guide to help us 100 00:03:35,485 --> 00:03:37,324 figure out how best we can solve the 101 00:03:37,324 --> 00:03:39,805 solution. So instead of being kind of about 102 00:03:39,805 --> 00:03:42,365 the technology, we are we've always been this 103 00:03:42,365 --> 00:03:43,985 way with from with regards to innovation, 104 00:03:44,389 --> 00:03:47,750 but especially with regards to AI. We've been 105 00:03:47,750 --> 00:03:50,330 incredibly disciplined about being problem first. 106 00:03:50,789 --> 00:03:52,090 And as a result, 107 00:03:52,469 --> 00:03:54,469 we've come up with some great, 108 00:03:55,430 --> 00:03:55,930 deployments 109 00:03:56,310 --> 00:03:57,129 of technologies 110 00:03:57,509 --> 00:04:00,009 that leverage AI and are making an impact. 111 00:04:03,004 --> 00:04:04,925 I love that. I I think it's, really 112 00:04:04,925 --> 00:04:05,745 cool to 113 00:04:06,125 --> 00:04:07,965 to know that you're looking at AI. I 114 00:04:07,965 --> 00:04:09,885 know that's something that so many different hospitals 115 00:04:09,885 --> 00:04:11,564 and health systems are trying to make sense 116 00:04:11,564 --> 00:04:13,659 of and and really figure out where the 117 00:04:13,659 --> 00:04:15,979 value is going to be. So, you know, 118 00:04:15,979 --> 00:04:18,860 when you look at, the biggest problems or 119 00:04:18,860 --> 00:04:21,339 challenges that AI is taking on, how do 120 00:04:21,339 --> 00:04:23,740 you measure its success? How are you really 121 00:04:23,740 --> 00:04:27,115 incorporating that into workflows and taking that from 122 00:04:27,115 --> 00:04:29,134 a pilot into more of a a scalable 123 00:04:29,354 --> 00:04:30,414 operation or initiative? 124 00:04:30,875 --> 00:04:32,875 They're really good really, really good question. Right? 125 00:04:32,875 --> 00:04:35,294 So every single one of our projects that 126 00:04:35,435 --> 00:04:36,414 we do in innovation, 127 00:04:37,834 --> 00:04:40,254 especially those that leverage artificial intelligence, 128 00:04:41,435 --> 00:04:43,399 we are carefully looking at, 129 00:04:44,019 --> 00:04:46,339 you know, pre and post data. Pre data 130 00:04:46,339 --> 00:04:48,740 meaning what is what is the metric that's 131 00:04:48,740 --> 00:04:50,360 going to evaluate the 132 00:04:50,980 --> 00:04:52,920 the efficacy of a specific process? 133 00:04:53,900 --> 00:04:55,860 You know, how effective is it before you 134 00:04:55,860 --> 00:04:57,000 introduce the technology 135 00:04:57,514 --> 00:05:00,334 and then carefully evaluating, you know, post 136 00:05:00,634 --> 00:05:01,454 AI deployment. 137 00:05:01,834 --> 00:05:04,235 How is that how is that process been 138 00:05:04,235 --> 00:05:04,735 improved? 139 00:05:05,915 --> 00:05:08,954 Often it is a productivity measure. Often it's 140 00:05:08,954 --> 00:05:12,074 a financial measure, clinical measure as we think 141 00:05:12,074 --> 00:05:12,574 about 142 00:05:13,620 --> 00:05:15,379 different ways in which the AI can be 143 00:05:15,379 --> 00:05:18,100 used, but being really concrete about what the 144 00:05:18,100 --> 00:05:20,500 baseline data is and what the improvement is. 145 00:05:20,500 --> 00:05:22,500 I know that sounds simple. It's basic kinda 146 00:05:22,500 --> 00:05:23,939 innovation one zero one, but it's been a 147 00:05:23,939 --> 00:05:25,160 really key part of 148 00:05:25,534 --> 00:05:28,115 of the process for us. We've also introduced 149 00:05:28,495 --> 00:05:30,814 in all of our AI projects this kind 150 00:05:30,814 --> 00:05:31,875 of phase zero 151 00:05:32,254 --> 00:05:33,714 in which we are 152 00:05:34,175 --> 00:05:34,675 validating 153 00:05:35,055 --> 00:05:36,754 and testing the models, 154 00:05:38,175 --> 00:05:40,334 using our own data before it actually goes 155 00:05:40,334 --> 00:05:43,149 live to patients or staff depending on the 156 00:05:43,149 --> 00:05:45,729 use case. So we are evaluating 157 00:05:46,110 --> 00:05:47,009 these technologies, 158 00:05:48,269 --> 00:05:49,969 leveraging retrospective data, 159 00:05:51,469 --> 00:05:52,610 you know, in a really 160 00:05:54,274 --> 00:05:55,095 in a really 161 00:05:55,634 --> 00:05:58,115 controlled manner to really make sure we're comfortable 162 00:05:58,115 --> 00:06:00,375 with the output of the product before we 163 00:06:00,675 --> 00:06:02,055 make it available to 164 00:06:02,435 --> 00:06:04,354 end users who will ultimately be using it. 165 00:06:04,354 --> 00:06:06,694 So that that approach of kind of incorporating 166 00:06:06,834 --> 00:06:09,050 this kind of pre pilot phase zero, whatever 167 00:06:09,050 --> 00:06:11,529 you wanna call it, is really helpful to 168 00:06:11,529 --> 00:06:12,670 help us really understand, 169 00:06:13,770 --> 00:06:16,330 and and make sure these the tools are 170 00:06:16,330 --> 00:06:18,410 are really delivering on what what the promise 171 00:06:18,410 --> 00:06:20,970 is before we introduce them to to real 172 00:06:20,970 --> 00:06:21,470 workflows. 173 00:06:24,625 --> 00:06:27,185 That's really helpful context to understand. Thank you 174 00:06:27,185 --> 00:06:28,865 so much for digging a little bit deeper 175 00:06:28,865 --> 00:06:30,785 in there for us. Now when you look 176 00:06:30,785 --> 00:06:32,625 into the future, where are you thinking about 177 00:06:32,625 --> 00:06:34,884 the biggest opportunities for growth and development, 178 00:06:35,264 --> 00:06:36,085 for your team? 179 00:06:38,879 --> 00:06:41,199 So there's a few areas that are interesting. 180 00:06:41,199 --> 00:06:42,740 Right? So I think, 181 00:06:44,240 --> 00:06:44,740 within 182 00:06:45,920 --> 00:06:47,439 within the space of 183 00:06:48,319 --> 00:06:50,805 one of the most exciting things about artificial 184 00:06:50,805 --> 00:06:52,884 intelligence, let's start there. And I can answer 185 00:06:52,884 --> 00:06:55,444 broadly about things that are, you know, technology 186 00:06:55,444 --> 00:06:57,524 in general. But with regards to AI, one 187 00:06:57,524 --> 00:06:59,285 of the things that appeals to me the 188 00:06:59,285 --> 00:06:59,785 most 189 00:07:00,245 --> 00:07:03,029 is there are many ways that you know, 190 00:07:03,029 --> 00:07:03,529 organizations 191 00:07:04,550 --> 00:07:05,289 and hospitals 192 00:07:05,669 --> 00:07:06,889 specifically like ours 193 00:07:07,349 --> 00:07:09,689 could build our own AI solutions 194 00:07:10,069 --> 00:07:13,289 in a safe and and, you know, efficacious 195 00:07:13,509 --> 00:07:14,009 way 196 00:07:14,310 --> 00:07:16,475 without expanding a ton of resources. Right? That 197 00:07:16,475 --> 00:07:18,714 may not have been possible a decade ago 198 00:07:18,714 --> 00:07:20,795 as we thought about other technologies that you've 199 00:07:20,795 --> 00:07:23,274 been the hospital wanna build. But with AI, 200 00:07:23,274 --> 00:07:25,115 there's a lot of opportunities for us to 201 00:07:25,115 --> 00:07:25,615 build 202 00:07:25,915 --> 00:07:26,814 small, simple 203 00:07:27,194 --> 00:07:29,930 tools. You know, nothing that's gonna commercialize and 204 00:07:29,930 --> 00:07:32,250 be massive, but something that solves a real 205 00:07:32,250 --> 00:07:35,230 problem for us here, either clinically or administratively 206 00:07:35,370 --> 00:07:37,529 or in our research enterprise or our teaching 207 00:07:37,529 --> 00:07:38,029 enterprise, 208 00:07:38,330 --> 00:07:40,509 something that solves a problem that we can 209 00:07:40,730 --> 00:07:42,830 build in house and perhaps 210 00:07:43,795 --> 00:07:45,074 even get to a place in the next 211 00:07:45,074 --> 00:07:47,475 few years where, you know, people who aren't 212 00:07:47,475 --> 00:07:49,574 kind of computer scientists could even 213 00:07:50,115 --> 00:07:52,915 stand up simple solutions that could either work 214 00:07:52,915 --> 00:07:54,595 for their own workflows or for their team 215 00:07:54,595 --> 00:07:56,915 or department. So this whole world of, 216 00:07:57,314 --> 00:07:58,055 you know, 217 00:07:58,620 --> 00:08:00,080 build within AI 218 00:08:00,540 --> 00:08:02,699 is really interesting for us as we think 219 00:08:02,699 --> 00:08:05,280 about solutions that we can build in house, 220 00:08:05,900 --> 00:08:08,080 in partnership with some of our key stakeholders. 221 00:08:09,100 --> 00:08:11,040 But then the broader piece, I think, 222 00:08:12,220 --> 00:08:13,360 for me is 223 00:08:14,194 --> 00:08:15,875 I think we're getting to a place where 224 00:08:15,875 --> 00:08:17,235 where a lot of this technology, a lot 225 00:08:17,235 --> 00:08:18,774 of which is enabled by AI, 226 00:08:19,235 --> 00:08:21,654 is enabling us to 227 00:08:22,675 --> 00:08:25,414 optimize the the output of our, 228 00:08:26,194 --> 00:08:27,014 of our workforce, 229 00:08:27,319 --> 00:08:29,160 which is so crucial. Right? So by that, 230 00:08:29,160 --> 00:08:31,399 it could be that we're improving productivity as 231 00:08:31,399 --> 00:08:33,179 some of our administrative team members. 232 00:08:33,559 --> 00:08:35,799 We could be making we could be helping 233 00:08:35,799 --> 00:08:36,539 our clinicians, 234 00:08:37,799 --> 00:08:40,485 make better, you know, even even better 235 00:08:41,044 --> 00:08:44,184 decisions based on intelligence and and data. 236 00:08:45,284 --> 00:08:47,845 We we could be enabling for care to 237 00:08:47,845 --> 00:08:48,985 be delivered faster 238 00:08:49,524 --> 00:08:52,325 or or improving access so that more people 239 00:08:52,325 --> 00:08:55,169 can access the the clinical care they require. 240 00:08:55,169 --> 00:08:57,589 So I'm just really excited about that element 241 00:08:57,649 --> 00:08:58,709 of where we're headed. 242 00:08:59,409 --> 00:09:01,169 It's not all gonna be AI. Some of 243 00:09:01,169 --> 00:09:03,009 it it can be in it can involve 244 00:09:03,009 --> 00:09:05,490 a variety of different technology modalities, but I 245 00:09:05,490 --> 00:09:07,089 think we're getting to a place. We've been 246 00:09:07,089 --> 00:09:08,370 on this road for a while, but we're 247 00:09:08,370 --> 00:09:10,665 getting to a place where, you know, the 248 00:09:10,665 --> 00:09:14,184 demands of our kind of primary service areas 249 00:09:14,184 --> 00:09:16,445 individually are our population essentially. 250 00:09:16,904 --> 00:09:18,684 The health care demands of our populations 251 00:09:19,384 --> 00:09:21,545 just continue to exceed what our workforce can 252 00:09:21,545 --> 00:09:23,829 deliver, which is relating to all these access 253 00:09:23,829 --> 00:09:26,149 issues, but it's also relating to workforce issues 254 00:09:26,149 --> 00:09:28,970 relates to burnout and it relates to experience. 255 00:09:29,509 --> 00:09:31,589 And I'm really hopeful that we can design 256 00:09:31,589 --> 00:09:32,970 and prioritize solutions 257 00:09:33,589 --> 00:09:36,434 with technology and AI specifically in the next, 258 00:09:36,595 --> 00:09:38,995 you know, few years, if not sooner, they 259 00:09:38,995 --> 00:09:40,754 can really they can really make an impact 260 00:09:40,754 --> 00:09:43,095 on both those things. Let's increase patient access. 261 00:09:43,235 --> 00:09:44,855 Let's give patients answers, 262 00:09:45,315 --> 00:09:47,475 good high quality answers to what they're looking 263 00:09:47,475 --> 00:09:49,095 for, you know, sooner, 264 00:09:50,269 --> 00:09:51,970 and let's enable our clinicians 265 00:09:52,669 --> 00:09:54,129 to, you know, 266 00:09:54,750 --> 00:09:57,870 have assistance and help so they can really 267 00:09:57,870 --> 00:10:00,189 focus on what they got into medicine for, 268 00:10:00,189 --> 00:10:02,350 which is to to help save lives and 269 00:10:02,350 --> 00:10:03,490 to help treat people. 270 00:10:04,115 --> 00:10:05,875 And, you know, and and at the same 271 00:10:05,875 --> 00:10:07,975 token, let's help our health systems, 272 00:10:08,514 --> 00:10:11,394 you know, do the administrative work required to, 273 00:10:11,394 --> 00:10:13,714 you know, keep our doors open. So I 274 00:10:13,714 --> 00:10:16,054 I think there's this trifecta that's that's 275 00:10:16,434 --> 00:10:18,274 really close, and we're we're getting close to 276 00:10:18,274 --> 00:10:19,575 kind of figuring it out. 277 00:10:21,450 --> 00:10:23,309 That is amazing to hear. And what 278 00:10:23,690 --> 00:10:25,769 a cool future that you have painted for 279 00:10:25,769 --> 00:10:27,690 us in terms of being able to utilize 280 00:10:27,690 --> 00:10:30,410 and leverage AI better in a more specific 281 00:10:30,410 --> 00:10:33,294 basis and and having the teams and expertise 282 00:10:33,514 --> 00:10:35,375 available, as well as the technology 283 00:10:35,995 --> 00:10:38,714 to really improve health care and the outcomes 284 00:10:38,714 --> 00:10:41,294 of of patients and populations across the country. 285 00:10:41,434 --> 00:10:43,034 I'm curious when you look at that and 286 00:10:43,034 --> 00:10:45,450 and knowing that the technology is coming, how 287 00:10:45,450 --> 00:10:48,250 do you, really build your teams or educate 288 00:10:48,250 --> 00:10:50,889 your current, workforce to make sure that they're 289 00:10:50,889 --> 00:10:53,610 ready for that, for that future and for 290 00:10:53,610 --> 00:10:55,370 a time when, you know, AI can be 291 00:10:55,370 --> 00:10:57,710 used in such a a more sophisticated way? 292 00:10:59,674 --> 00:11:02,095 So really, it's a it's a really important 293 00:11:02,235 --> 00:11:04,475 part of the innovation process, which is kind 294 00:11:04,475 --> 00:11:06,154 of tilling the earth in a sense. Right? 295 00:11:06,154 --> 00:11:08,815 Getting the the soil ready for the future. 296 00:11:09,595 --> 00:11:11,250 The soil and as you describe it in 297 00:11:11,250 --> 00:11:13,649 this analogy would basically be our workforce and 298 00:11:13,649 --> 00:11:15,409 and included in that is not just our 299 00:11:15,409 --> 00:11:17,089 workforce, but our patients and families. Right? How 300 00:11:17,089 --> 00:11:19,169 do we enable people to to get comfortable 301 00:11:19,169 --> 00:11:21,329 with this? So a lot of it is 302 00:11:21,329 --> 00:11:25,009 exposure. So exposing them, exposing our our our 303 00:11:25,009 --> 00:11:27,584 staff, our clinicians to what's happening in the 304 00:11:27,584 --> 00:11:30,384 industry. Like, what are other examples of children's 305 00:11:30,384 --> 00:11:31,764 hospitals who have proven 306 00:11:32,225 --> 00:11:35,105 value using certain new innovative technologies, whether it's 307 00:11:35,105 --> 00:11:37,584 AI or digital health or virtual care? What 308 00:11:37,584 --> 00:11:39,745 are examples? What are papers? What are studies 309 00:11:39,745 --> 00:11:40,644 that have been done? 310 00:11:40,980 --> 00:11:43,139 Building that evidence base is really crucial. That's 311 00:11:43,139 --> 00:11:44,839 how medicine is you know, that's 312 00:11:45,139 --> 00:11:46,659 how medicine is really 313 00:11:47,220 --> 00:11:49,379 medicine in general has advanced over, you know, 314 00:11:49,379 --> 00:11:51,860 hundreds of years, which is someone discovers something 315 00:11:51,860 --> 00:11:54,019 new, they generate evidence around it, and they 316 00:11:54,019 --> 00:11:56,355 disseminate that to their peers, and that then 317 00:11:56,355 --> 00:11:58,915 builds and moves everybody forward. It's not it's 318 00:11:58,915 --> 00:12:00,835 not all that different as we think about, 319 00:12:00,835 --> 00:12:03,075 you know, technology adoption. If we that's what 320 00:12:03,075 --> 00:12:04,514 I do. Right? We we try to find 321 00:12:04,514 --> 00:12:05,174 and surface, 322 00:12:05,715 --> 00:12:07,955 including through your own organization and all the 323 00:12:07,955 --> 00:12:09,715 great work that you you surface. Right? There's 324 00:12:09,715 --> 00:12:10,294 a great, 325 00:12:10,660 --> 00:12:12,779 you know, Becker's article about this that someone 326 00:12:12,779 --> 00:12:14,620 else is doing, sending it to different people 327 00:12:14,620 --> 00:12:16,860 who I imagine are gonna be part of 328 00:12:16,860 --> 00:12:19,340 that, you know, team that's gonna help us 329 00:12:19,340 --> 00:12:20,960 do it in the future at our hospital 330 00:12:21,259 --> 00:12:24,044 that those little elements of exposure are key. 331 00:12:24,284 --> 00:12:27,184 The other is really picking the right problems. 332 00:12:27,245 --> 00:12:29,245 Right? So we wanna make sure that we're 333 00:12:29,245 --> 00:12:30,924 picking the problems that are gonna be most 334 00:12:30,924 --> 00:12:31,424 impactful. 335 00:12:31,964 --> 00:12:33,804 And as we do so, making sure that 336 00:12:33,804 --> 00:12:35,565 the people who we are going to include 337 00:12:35,565 --> 00:12:37,825 in the process or people like you described 338 00:12:38,125 --> 00:12:39,664 who are ready for that change. 339 00:12:40,000 --> 00:12:42,000 And so, you know, that is helpful. We've 340 00:12:42,000 --> 00:12:44,259 got an amazing, our chief data officer, 341 00:12:44,960 --> 00:12:47,279 has chief enterprise data officer has has a, 342 00:12:47,279 --> 00:12:49,059 you know, an analytics program 343 00:12:49,360 --> 00:12:52,019 that he has, got people across the organization 344 00:12:52,080 --> 00:12:53,680 kind of doing. So there's some actual hard 345 00:12:53,680 --> 00:12:54,899 skills that we've got, 346 00:12:55,565 --> 00:12:58,144 people learning as it relates to intelligence, data, 347 00:12:58,605 --> 00:12:59,745 analytics, AI. 348 00:13:00,125 --> 00:13:02,544 So there there's there's both, you know, didactic 349 00:13:02,605 --> 00:13:03,585 learning, exposure, 350 00:13:03,965 --> 00:13:05,644 and then just change management that are, I 351 00:13:05,644 --> 00:13:07,884 think, all key to getting that workforce and 352 00:13:07,884 --> 00:13:10,544 community ready for the changes that are ahead. 353 00:13:13,110 --> 00:13:15,350 Got it. That's, amazing to hear. And, you 354 00:13:15,350 --> 00:13:17,029 know, I I really love that analogy as 355 00:13:17,029 --> 00:13:19,029 you talked about, you know, building the soil 356 00:13:19,029 --> 00:13:20,549 and getting it ready for the future. And, 357 00:13:20,549 --> 00:13:22,710 certainly, it takes a lot of time, effort, 358 00:13:22,710 --> 00:13:24,549 energy on the technology as well as the 359 00:13:24,549 --> 00:13:26,330 people side, but truly, truly, 360 00:13:26,705 --> 00:13:27,825 with great outcomes, 361 00:13:28,304 --> 00:13:30,785 as the potential rewards. So that's awesome to 362 00:13:30,785 --> 00:13:32,865 hear. I know we've talked a lot about 363 00:13:32,865 --> 00:13:34,705 some of the opportunities and the cool things 364 00:13:34,705 --> 00:13:35,605 that could come, 365 00:13:36,065 --> 00:13:38,304 from the technology side of health care, especially 366 00:13:38,304 --> 00:13:40,245 AI, but I'm curious from your perspective, 367 00:13:40,610 --> 00:13:41,889 what are some of the challenges you have 368 00:13:41,889 --> 00:13:43,170 your eye on as well? What do you 369 00:13:43,170 --> 00:13:46,450 see as being, potential headwinds or things you'll 370 00:13:46,450 --> 00:13:48,050 have to overcome in the future to to 371 00:13:48,050 --> 00:13:49,350 reach this ideal state? 372 00:13:50,690 --> 00:13:51,750 So I think 373 00:13:52,210 --> 00:13:54,690 what's exciting is the technology is being developed 374 00:13:54,690 --> 00:13:56,995 so quickly. The challenge is that 375 00:13:57,535 --> 00:13:59,795 unless you have really 376 00:14:00,894 --> 00:14:01,795 high performing, 377 00:14:02,254 --> 00:14:02,754 consistent 378 00:14:03,055 --> 00:14:05,154 and somewhat sometimes standardized processes, 379 00:14:06,575 --> 00:14:07,634 across your organizations, 380 00:14:08,254 --> 00:14:09,955 if you don't have those in place, 381 00:14:11,429 --> 00:14:11,929 putting 382 00:14:12,269 --> 00:14:12,769 a 383 00:14:13,110 --> 00:14:16,409 a nice, exciting new technology on top of 384 00:14:16,789 --> 00:14:18,710 the current state is just not going to 385 00:14:18,710 --> 00:14:19,909 it's not going to be great. It's not 386 00:14:19,909 --> 00:14:21,750 going to work well. It's really complicated to 387 00:14:21,750 --> 00:14:23,750 do. And especially as we think about the 388 00:14:23,750 --> 00:14:26,475 new technologies coming out now, they really rely 389 00:14:26,535 --> 00:14:27,355 on having 390 00:14:28,134 --> 00:14:30,394 strong core operational processes. 391 00:14:30,774 --> 00:14:32,295 And so as we think about it, I 392 00:14:32,295 --> 00:14:34,394 mean, we all we all in our organizations 393 00:14:34,535 --> 00:14:35,514 have varying, 394 00:14:36,215 --> 00:14:37,595 you know, levels of 395 00:14:38,070 --> 00:14:38,570 process, 396 00:14:39,110 --> 00:14:41,750 you know, cleanup to do. But that's a 397 00:14:41,750 --> 00:14:43,830 key part of, I think, the success is 398 00:14:43,830 --> 00:14:44,730 making sure 399 00:14:45,269 --> 00:14:47,290 that that the the processes 400 00:14:48,070 --> 00:14:51,049 that that, you know, they're underneath all these 401 00:14:51,375 --> 00:14:52,595 exciting new technologies 402 00:14:53,294 --> 00:14:54,115 that they're 403 00:14:54,415 --> 00:14:55,634 as highly 404 00:14:56,095 --> 00:14:58,335 functional as they can be. So that when 405 00:14:58,335 --> 00:14:59,634 you layer on the technology, 406 00:15:00,495 --> 00:15:02,575 you are you're doing so in a way 407 00:15:02,575 --> 00:15:05,075 that is optimizing the value of that technology. 408 00:15:05,970 --> 00:15:07,669 So that's one. The other 409 00:15:08,049 --> 00:15:10,230 is and it goes to your previous question. 410 00:15:10,690 --> 00:15:12,230 I still think there is 411 00:15:12,690 --> 00:15:13,589 a sizable 412 00:15:14,610 --> 00:15:16,929 change management element that we need to navigate. 413 00:15:16,929 --> 00:15:19,169 And it's not just around do we trust 414 00:15:19,169 --> 00:15:22,504 AI? But I think people generally any technology 415 00:15:23,125 --> 00:15:25,365 it changing from their current workflow to a 416 00:15:25,365 --> 00:15:26,105 new workflow, 417 00:15:26,644 --> 00:15:31,144 unless it's really not, you know, noticeable change. 418 00:15:31,684 --> 00:15:34,240 Change for people, especially in our industry, is 419 00:15:34,240 --> 00:15:36,960 not easy. And and we need to really 420 00:15:36,960 --> 00:15:38,740 think about, you know, some of the core 421 00:15:39,120 --> 00:15:41,600 core basics of change management as we think 422 00:15:41,600 --> 00:15:42,100 about, 423 00:15:42,559 --> 00:15:44,259 how we're going to, you know, 424 00:15:44,639 --> 00:15:46,980 get the maximum value out of these innovations. 425 00:15:50,325 --> 00:15:53,524 That is absolutely crucial and definitely being able 426 00:15:53,524 --> 00:15:55,205 to double click and and zero in on 427 00:15:55,205 --> 00:15:57,225 those spaces where there could be 428 00:15:57,524 --> 00:16:00,565 additional challenges or or ways that, success could 429 00:16:00,565 --> 00:16:02,245 be hindered. It makes a lot of sense 430 00:16:02,245 --> 00:16:04,930 and then truly moving forward in an optimized 431 00:16:04,930 --> 00:16:07,330 fashion. Before we wrap up here, I'm curious. 432 00:16:07,330 --> 00:16:08,850 What is the number one thing that you're 433 00:16:08,850 --> 00:16:11,170 doing right now to set up Children's Hospital 434 00:16:11,170 --> 00:16:13,110 Los Angeles for long term success? 435 00:16:15,824 --> 00:16:18,704 I think one thing, and and it can't 436 00:16:18,784 --> 00:16:20,464 it's not a me. It's a we. Right? 437 00:16:20,464 --> 00:16:22,245 This is not there's no 438 00:16:22,625 --> 00:16:24,464 there's no unique thing that I do. I 439 00:16:24,464 --> 00:16:26,784 I I help lead, but there's a team 440 00:16:26,784 --> 00:16:27,684 that does this. 441 00:16:28,544 --> 00:16:31,649 We we've we've established, I think, a really 442 00:16:31,649 --> 00:16:33,990 great process around technology 443 00:16:34,450 --> 00:16:34,950 evaluation. 444 00:16:35,570 --> 00:16:37,730 And it's not just looking at kind of 445 00:16:37,730 --> 00:16:39,649 vendors and solutions that are out there, but 446 00:16:39,649 --> 00:16:40,549 what we do 447 00:16:40,929 --> 00:16:43,429 is we kind of understand the current process, 448 00:16:43,730 --> 00:16:44,230 determine, 449 00:16:44,795 --> 00:16:46,394 you know, is that process in a place 450 00:16:46,394 --> 00:16:48,955 where we feel like it's ready for for 451 00:16:48,955 --> 00:16:49,455 innovation? 452 00:16:50,075 --> 00:16:51,055 And if it is, 453 00:16:51,514 --> 00:16:53,595 you know, what are the core problems that 454 00:16:53,595 --> 00:16:55,434 we're trying to solve? And then we, you 455 00:16:55,434 --> 00:16:56,095 know, we 456 00:16:56,809 --> 00:16:59,049 work with stakeholders to figure out what are 457 00:16:59,049 --> 00:17:01,049 within those problems, what are the most important 458 00:17:01,049 --> 00:17:02,409 problems and what are the ones that are 459 00:17:02,409 --> 00:17:04,809 gonna result in an ROI. And then we 460 00:17:04,809 --> 00:17:07,789 go find innovative technologies that solve those problems 461 00:17:07,929 --> 00:17:09,309 and building that robust, 462 00:17:10,345 --> 00:17:11,245 you know, toolkit 463 00:17:11,785 --> 00:17:12,845 pathway around, 464 00:17:13,384 --> 00:17:16,265 you know, identifying innovation solutions, I think is 465 00:17:16,265 --> 00:17:17,325 a really key 466 00:17:18,025 --> 00:17:20,025 important discipline, especially as I said at the 467 00:17:20,025 --> 00:17:21,485 very beginning of this conversation. 468 00:17:22,184 --> 00:17:24,585 There's so many amazing solutions out there that 469 00:17:24,585 --> 00:17:26,820 it can be really easy to get distracted 470 00:17:27,119 --> 00:17:29,440 by, you know, the the next kind of 471 00:17:29,440 --> 00:17:30,900 great thing that you get pitched. 472 00:17:31,200 --> 00:17:33,920 And so having the discipline around looking at 473 00:17:33,920 --> 00:17:37,059 the process, looking at readiness, looking at problem, 474 00:17:37,200 --> 00:17:38,099 you know, prioritization, 475 00:17:38,960 --> 00:17:41,779 it's really key as we think about the 476 00:17:42,075 --> 00:17:43,694 the ultimate goal, which is 477 00:17:44,075 --> 00:17:46,474 picking a handful of projects that we think 478 00:17:46,474 --> 00:17:48,875 are gonna deliver the maximum value across our 479 00:17:48,875 --> 00:17:51,134 organization with the maximum amount of adoption. 480 00:17:51,514 --> 00:17:53,514 So I think we've been able to put 481 00:17:53,514 --> 00:17:55,034 that process out there, and I think that 482 00:17:55,034 --> 00:17:55,534 process 483 00:17:55,900 --> 00:17:57,339 is really gonna help us. 484 00:17:57,660 --> 00:17:59,179 It is it is already helping us, but 485 00:17:59,179 --> 00:18:00,299 I think it will help us in the 486 00:18:00,299 --> 00:18:02,779 future continue to make disciplined decisions as it 487 00:18:02,779 --> 00:18:03,679 relates to innovation. 488 00:18:04,940 --> 00:18:06,380 I love that. Omkar, thank you so much 489 00:18:06,380 --> 00:18:07,980 for joining us in the podcast today. This 490 00:18:07,980 --> 00:18:09,980 has been a really fantastic discussion, and I 491 00:18:09,980 --> 00:18:11,714 look forward to connecting with you again soon. 492 00:18:13,075 --> 00:18:14,454 Thank you for having me.