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 --> 00:00:08,419 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 --> 00:00:14,154 healthcare finance leaders. Tune in wherever you get 6 00:00:14,154 --> 00:00:15,054 your podcasts. 7 00:00:15,914 --> 00:00:18,475 And don't miss the tenth annual health IT 8 00:00:18,475 --> 00:00:22,154 plus digital health plus RCM conference, happening September 9 00:00:22,154 --> 00:00:24,474 30 to 10/03/2025 10 00:00:24,474 --> 00:00:25,214 in Chicago. 11 00:00:25,755 --> 00:00:26,879 Join thousands of 12 00:00:27,279 --> 00:00:30,079 executives, engage with industry leaders, and explore the 13 00:00:30,079 --> 00:00:31,619 future of health care innovation. 14 00:00:32,320 --> 00:00:36,719 Learn more about our upcoming events at beckershospitalreview.com. 15 00:00:36,719 --> 00:00:37,539 See you there. 16 00:00:38,320 --> 00:00:40,640 This is Laura Dirdle with the Becker's Healthcare 17 00:00:40,640 --> 00:00:42,854 podcast. I'm thrilled today to be joined by 18 00:00:42,854 --> 00:00:43,755 Sameer Sethi, 19 00:00:44,295 --> 00:00:46,695 senior vice president and chief AI and insights 20 00:00:46,695 --> 00:00:49,094 officer at Hackensack Meridian Health. Sameer, it's a 21 00:00:49,094 --> 00:00:50,875 pleasure to have you on the podcast today. 22 00:00:51,094 --> 00:00:52,695 Yeah. Laura, thanks for having me. I'm really 23 00:00:52,695 --> 00:00:53,914 excited about this conversation. 24 00:00:54,590 --> 00:00:56,189 Absolutely. I'm looking forward to it as well. 25 00:00:56,189 --> 00:00:57,969 I know you're doing some really unique things 26 00:00:58,030 --> 00:00:59,869 at Hackensack Meridian, so it'll be great to 27 00:00:59,869 --> 00:01:02,270 share with our broader audience as well as 28 00:01:02,270 --> 00:01:03,789 get a sense of how you're thinking about 29 00:01:03,789 --> 00:01:05,950 the future, some of the big opportunities that 30 00:01:05,950 --> 00:01:07,884 you see ahead. But before we do that, 31 00:01:07,884 --> 00:01:09,084 I'm wondering, can you tell us a little 32 00:01:09,084 --> 00:01:11,004 bit more about Hackensack Meridian Health and what 33 00:01:11,004 --> 00:01:11,825 makes it unique? 34 00:01:12,444 --> 00:01:12,944 Absolutely. 35 00:01:13,644 --> 00:01:16,284 So, Hackensack Meridian Health is a health system 36 00:01:16,284 --> 00:01:18,284 based out in New Jersey with a total 37 00:01:18,284 --> 00:01:19,424 of 18 hospitals, 38 00:01:20,790 --> 00:01:23,369 500 plus care sites, all in New Jersey, 39 00:01:23,670 --> 00:01:25,509 and very focused on on on the state 40 00:01:25,509 --> 00:01:26,329 and providing, 41 00:01:26,709 --> 00:01:28,469 providing care to the community and the patients 42 00:01:28,469 --> 00:01:29,209 we serve. 43 00:01:29,670 --> 00:01:32,250 I function as the AI and insights officer. 44 00:01:33,349 --> 00:01:34,569 I I joined the organization, 45 00:01:36,185 --> 00:01:38,265 almost three years ago now. I started off, 46 00:01:38,664 --> 00:01:41,704 functioning as their data and analytics officer. And 47 00:01:41,704 --> 00:01:43,484 then, late last year, 48 00:01:43,864 --> 00:01:46,344 I was promoted to function as their AI 49 00:01:46,344 --> 00:01:49,469 and insights officer. The reason that is, that 50 00:01:49,469 --> 00:01:51,549 that that is unique is because, you know, 51 00:01:51,549 --> 00:01:52,290 our CEO, 52 00:01:53,069 --> 00:01:55,390 mister Garrett Bob Garrett has has put an 53 00:01:55,390 --> 00:01:56,530 emphasis on 54 00:01:56,989 --> 00:01:59,549 on AI and RPA enablement. I think the 55 00:01:59,549 --> 00:02:01,250 the push that he has made is 56 00:02:01,575 --> 00:02:03,915 so I is is, I think, very unique, 57 00:02:04,534 --> 00:02:06,055 I I think in in in the in 58 00:02:06,055 --> 00:02:08,455 various industries, but especially in health care. I 59 00:02:08,455 --> 00:02:10,555 think everyone is looking at AI and RPA 60 00:02:10,694 --> 00:02:13,834 enablement, but I think our focus is quite, 61 00:02:14,459 --> 00:02:17,180 I think, driven around, you know, what it 62 00:02:17,180 --> 00:02:19,099 does to our workforce, what it does to 63 00:02:19,099 --> 00:02:21,099 our patients, and how fast we can we 64 00:02:21,099 --> 00:02:22,939 can get there. So I think we're we 65 00:02:22,939 --> 00:02:25,340 as an organization are in addition to doing 66 00:02:25,340 --> 00:02:27,675 what other health care systems do, from an 67 00:02:27,675 --> 00:02:29,055 AI enabled perspective, 68 00:02:29,594 --> 00:02:30,895 we are doing more. 69 00:02:31,355 --> 00:02:33,855 We're we're we're scouting the market consistently. 70 00:02:34,395 --> 00:02:35,455 We're seeing what, 71 00:02:35,754 --> 00:02:37,675 what we need right away, what our patients 72 00:02:37,675 --> 00:02:39,995 need. So there's a very, very heavy push 73 00:02:39,995 --> 00:02:40,495 through, 74 00:02:40,795 --> 00:02:42,974 mister Garrett's sponsorship to get this done. 75 00:02:43,930 --> 00:02:45,449 That's amazing to hear. You know? And and 76 00:02:45,449 --> 00:02:46,669 really, truly 77 00:02:46,969 --> 00:02:49,050 outstanding you've got the support of, 78 00:02:49,689 --> 00:02:51,449 Bob Garrett and all those on the c 79 00:02:51,449 --> 00:02:52,830 suite to move forward, 80 00:02:54,010 --> 00:02:56,145 in really in a smart way, be able 81 00:02:56,145 --> 00:02:58,425 to use AI, use data analytics, use those 82 00:02:58,425 --> 00:02:58,925 insights 83 00:02:59,224 --> 00:03:00,905 that, in a way that you can grow 84 00:03:00,905 --> 00:03:03,004 and develop in the future. I'm curious, 85 00:03:03,385 --> 00:03:05,944 given this unique position that you're in, can 86 00:03:05,944 --> 00:03:07,544 you talk a little bit about an accomplishment 87 00:03:07,544 --> 00:03:09,064 that you're most proud of from the last 88 00:03:09,064 --> 00:03:09,965 year or so? 89 00:03:10,419 --> 00:03:11,960 Absolutely. So, you know, 90 00:03:12,419 --> 00:03:14,840 what's all what's a bit unique and also 91 00:03:14,980 --> 00:03:16,840 what led to the accomplishment 92 00:03:17,300 --> 00:03:19,060 is is a speed at which we have 93 00:03:19,060 --> 00:03:20,919 gone at this. I think that's number one. 94 00:03:21,460 --> 00:03:23,000 You know, we put 95 00:03:23,764 --> 00:03:25,064 a generative AI, 96 00:03:25,764 --> 00:03:27,145 use case in production 97 00:03:27,685 --> 00:03:30,264 within within three months, if not sooner, 98 00:03:30,965 --> 00:03:33,525 of of the, you know, the word that 99 00:03:33,525 --> 00:03:35,925 that got out with ChachiPT and others. You 100 00:03:35,925 --> 00:03:37,705 know, we we were looking at this technology 101 00:03:38,245 --> 00:03:38,745 evolve. 102 00:03:39,389 --> 00:03:41,310 It came at at us very quickly, but 103 00:03:41,310 --> 00:03:43,169 we were able to make sense of it 104 00:03:43,229 --> 00:03:45,229 and produce a use case, put that in 105 00:03:45,229 --> 00:03:46,829 production. And then now we have close to 106 00:03:46,829 --> 00:03:47,329 nine, 107 00:03:47,949 --> 00:03:49,709 use cases in production here. So I think 108 00:03:49,709 --> 00:03:51,164 I think much ahead of the market, 109 00:03:51,564 --> 00:03:54,064 and also driving value already 110 00:03:54,364 --> 00:03:55,584 within the health system. 111 00:03:55,884 --> 00:03:57,104 This helps our patients, 112 00:03:57,564 --> 00:03:59,965 it helps our our workforce, our focus has 113 00:03:59,965 --> 00:04:01,965 been around around workforce. So I think that's 114 00:04:01,965 --> 00:04:03,405 one piece of this, the speed at which 115 00:04:03,405 --> 00:04:05,324 we came at this. The other is I 116 00:04:05,324 --> 00:04:06,224 think automation. 117 00:04:06,849 --> 00:04:08,770 You know, while we while AI is new 118 00:04:08,770 --> 00:04:10,949 and everyone is, you know, running towards making, 119 00:04:11,490 --> 00:04:13,330 making sure that, you know, they drive value 120 00:04:13,330 --> 00:04:15,330 from it. You know, automation has been a 121 00:04:15,330 --> 00:04:16,949 big focus for us last year, 122 00:04:17,810 --> 00:04:19,490 and and the years before as well. But 123 00:04:19,490 --> 00:04:20,850 we were we were we were a bit 124 00:04:20,850 --> 00:04:23,625 slow at it. Generally, I think when I 125 00:04:23,625 --> 00:04:25,464 came into into the health system, we had 126 00:04:25,464 --> 00:04:27,084 20 automations in production. 127 00:04:27,544 --> 00:04:29,384 Last year, we committed to doing quite a 128 00:04:29,384 --> 00:04:31,865 bit more. And just between in the last 129 00:04:31,865 --> 00:04:33,384 two and a half years or two to 130 00:04:33,384 --> 00:04:33,779 do 131 00:04:34,339 --> 00:04:36,019 two and a half years, we've gone from 132 00:04:36,019 --> 00:04:38,819 having those 20 automations to having 80 133 00:04:38,819 --> 00:04:41,800 automations in production. You know, this varies from 134 00:04:41,860 --> 00:04:44,759 anything from, you know, using automation for, 135 00:04:45,220 --> 00:04:47,620 enrolling patients in MyChart a lot quicker. We 136 00:04:47,620 --> 00:04:49,125 have the highest and then fastest in the 137 00:04:49,125 --> 00:04:50,104 industry today. 138 00:04:50,485 --> 00:04:51,764 So what we're doing is we're taking the 139 00:04:51,764 --> 00:04:52,245 human, 140 00:04:52,964 --> 00:04:55,204 out of the the process, wherever it makes 141 00:04:55,204 --> 00:04:57,925 makes more sense. Right? Obviously, human in the 142 00:04:57,925 --> 00:04:59,925 loop is important that exists, but we are 143 00:04:59,925 --> 00:05:02,040 trying to speed things up. We have put 144 00:05:02,040 --> 00:05:04,680 use cases where we're using robotics process automation 145 00:05:04,680 --> 00:05:05,180 to, 146 00:05:05,720 --> 00:05:08,839 to enter lab results into into patient charts. 147 00:05:09,080 --> 00:05:10,600 And, obviously, there's a human in the loop 148 00:05:10,600 --> 00:05:12,120 there as well, but the person is not 149 00:05:12,120 --> 00:05:14,404 sitting there and typing it. We use this 150 00:05:14,404 --> 00:05:15,704 inform use technology 151 00:05:16,004 --> 00:05:18,004 to put in our female claims, for example, 152 00:05:18,004 --> 00:05:20,084 which were in in the numbers of thousands. 153 00:05:20,084 --> 00:05:21,925 And if a person were to do it, 154 00:05:21,925 --> 00:05:22,904 it would take us, 155 00:05:23,444 --> 00:05:25,365 I believe the estimate was four months to 156 00:05:25,365 --> 00:05:26,485 do it. And we did it in two 157 00:05:26,485 --> 00:05:29,579 days overnight. Robots just just kept working. So 158 00:05:29,579 --> 00:05:32,060 I think the accomplishments have been many, but 159 00:05:32,060 --> 00:05:34,939 I think it usually is focused on bringing 160 00:05:34,939 --> 00:05:37,180 the the tech as fast as possible to 161 00:05:37,180 --> 00:05:40,220 bear, to drive value. And then I think 162 00:05:40,220 --> 00:05:42,620 also continuing on the fundamentals of things like 163 00:05:42,620 --> 00:05:45,485 robotics process automation. I'm happy to go through, 164 00:05:45,485 --> 00:05:46,925 you know, one or two use case that 165 00:05:46,925 --> 00:05:48,524 I'm really proud of, but in general, that's 166 00:05:48,524 --> 00:05:49,185 the principle. 167 00:05:50,365 --> 00:05:51,805 That's amazing to hear. And I I love 168 00:05:51,805 --> 00:05:54,044 that overall strategy of trying to find those 169 00:05:54,044 --> 00:05:55,724 right use cases or ways that you can 170 00:05:55,724 --> 00:05:58,305 use the robot effectively and and use automation 171 00:05:58,365 --> 00:06:00,759 as well as AI to boost especially the 172 00:06:00,759 --> 00:06:02,439 workforce as I know that's a huge, huge 173 00:06:02,439 --> 00:06:04,600 challenge for so many hospitals and health systems 174 00:06:04,600 --> 00:06:07,000 across the country. And I definitely am interested 175 00:06:07,000 --> 00:06:09,000 in zeroing in on some of those, use 176 00:06:09,000 --> 00:06:09,500 cases, 177 00:06:09,879 --> 00:06:11,160 that you find most, 178 00:06:11,834 --> 00:06:14,074 most helpful or or beneficial. I I think 179 00:06:14,074 --> 00:06:15,295 it's really cool to have, 180 00:06:15,675 --> 00:06:18,894 grown that automation from 20 to a 80 181 00:06:18,954 --> 00:06:21,274 in production so quickly, and and, clearly, the 182 00:06:21,274 --> 00:06:23,610 culture is, is able to do that. So 183 00:06:23,689 --> 00:06:24,969 I'm curious if you're able to dial in 184 00:06:24,969 --> 00:06:26,169 on some of the things you're most proud 185 00:06:26,169 --> 00:06:28,009 of there. I think, would love to hear 186 00:06:28,009 --> 00:06:30,329 more about that. Yeah. Absolutely. I I'll talk 187 00:06:30,329 --> 00:06:31,789 about, you know, something that's 188 00:06:32,250 --> 00:06:35,129 that I think is is evolving today, and 189 00:06:35,129 --> 00:06:36,810 and and it stays on top of our 190 00:06:36,810 --> 00:06:38,509 mind or and on our minds. 191 00:06:39,154 --> 00:06:41,254 You know, almost a year ago, 192 00:06:41,875 --> 00:06:43,814 if not a bit more, you know, we 193 00:06:44,115 --> 00:06:46,295 launched our use case where we were using 194 00:06:46,675 --> 00:06:50,214 generative AI to summarize a clinical note. 195 00:06:50,754 --> 00:06:52,800 This is so so think about how, you 196 00:06:52,800 --> 00:06:54,639 know, when you and I go into a 197 00:06:54,639 --> 00:06:57,439 physician office, generally, a physician is obviously being 198 00:06:57,439 --> 00:06:58,819 present at the same time, 199 00:06:59,120 --> 00:07:01,379 you know, trying to read on the screen 200 00:07:01,439 --> 00:07:03,599 information about you. Now this is the patient 201 00:07:03,599 --> 00:07:05,519 chart. It has your lab values. It has 202 00:07:05,519 --> 00:07:07,714 what, you know, what was discussed last time 203 00:07:07,714 --> 00:07:09,714 you were there and discussed the conditions that 204 00:07:09,714 --> 00:07:11,875 you had. And it's quite a bit, you 205 00:07:11,875 --> 00:07:12,615 know, we have 206 00:07:12,995 --> 00:07:15,474 a lot of information that that that physicians 207 00:07:15,474 --> 00:07:16,854 and clinicians in general, 208 00:07:17,314 --> 00:07:19,235 you know, gather about the about you as 209 00:07:19,235 --> 00:07:21,350 a patient in there. What we did was 210 00:07:21,350 --> 00:07:24,069 we made it easier for the clinicians to 211 00:07:24,069 --> 00:07:26,810 consume that information by summarizing all that. 212 00:07:27,509 --> 00:07:29,589 Our first version of that was just a 213 00:07:29,589 --> 00:07:30,490 general summary. 214 00:07:30,949 --> 00:07:32,949 We then when when we put it in 215 00:07:32,949 --> 00:07:33,449 production, 216 00:07:34,069 --> 00:07:36,485 we realized that that the that the clinicians 217 00:07:36,485 --> 00:07:37,464 were looking for, 218 00:07:38,485 --> 00:07:41,444 summarization by specialty. So then we selected nine 219 00:07:41,444 --> 00:07:41,944 specialties, 220 00:07:42,485 --> 00:07:44,805 and the intention there was that, what a 221 00:07:44,805 --> 00:07:46,805 primary care physician wants to see in a 222 00:07:46,805 --> 00:07:49,125 summary is different from somebody in oncology or 223 00:07:49,125 --> 00:07:49,625 cardiology. 224 00:07:49,979 --> 00:07:51,439 Right. So we created 225 00:07:51,819 --> 00:07:54,160 we then start to tailor these summaries 226 00:07:54,620 --> 00:07:56,560 by specialty and that 227 00:07:57,099 --> 00:07:58,160 we got a lot more 228 00:07:58,620 --> 00:08:01,419 attraction and value from it. We then went 229 00:08:01,419 --> 00:08:02,479 into now summarizing 230 00:08:02,860 --> 00:08:03,759 lab values 231 00:08:04,544 --> 00:08:06,785 into this this clinical note because the clinician 232 00:08:06,785 --> 00:08:08,305 said, I would like to see lab values 233 00:08:08,305 --> 00:08:09,664 in there as well. So I don't have 234 00:08:09,664 --> 00:08:11,264 to go and look for it. So this 235 00:08:11,264 --> 00:08:13,104 is an example of a use case and 236 00:08:13,104 --> 00:08:15,985 even our strategy around doing this. Obviously, there's 237 00:08:15,985 --> 00:08:17,904 a lot of governance around putting in team 238 00:08:17,904 --> 00:08:19,845 production, and we abide by those things. 239 00:08:20,520 --> 00:08:22,779 I believe we have the best AI 240 00:08:23,639 --> 00:08:25,819 governance safety framework in place. 241 00:08:27,080 --> 00:08:28,759 But what we try very hard to do 242 00:08:28,759 --> 00:08:30,520 and then we this is where we push 243 00:08:30,520 --> 00:08:32,759 the business, the clinicians, and everyone in the 244 00:08:32,759 --> 00:08:34,615 world to put something out there as fast 245 00:08:34,615 --> 00:08:36,615 as possible, as long as it passes through 246 00:08:36,615 --> 00:08:39,415 the safety checks. Right. But then we iterate 247 00:08:39,415 --> 00:08:41,915 over time. That's been a pretty big accomplishment 248 00:08:42,295 --> 00:08:42,955 for us. 249 00:08:43,495 --> 00:08:45,335 As I mentioned, you know, we did this 250 00:08:45,335 --> 00:08:48,055 right right after this technology started to become 251 00:08:48,055 --> 00:08:49,940 available to us. We put something out there, 252 00:08:49,940 --> 00:08:51,779 and it's evolved and grown bigger and bigger 253 00:08:51,779 --> 00:08:53,300 and bigger, and we are really proud of 254 00:08:53,300 --> 00:08:53,800 that. 255 00:08:54,500 --> 00:08:56,340 That's really cool to hear. And, definitely, as 256 00:08:56,340 --> 00:08:58,500 you mentioned, something to be extremely proud of 257 00:08:58,500 --> 00:09:00,340 knowing all the work and effort that goes 258 00:09:00,340 --> 00:09:02,820 into it. It can be extremely complex to 259 00:09:02,820 --> 00:09:05,084 put together on the technology side, but on 260 00:09:05,084 --> 00:09:06,764 the people side too and just make sure 261 00:09:06,764 --> 00:09:09,485 that everyone, is comfortable with these changes and 262 00:09:09,485 --> 00:09:11,164 then, being able to do them quickly, as 263 00:09:11,164 --> 00:09:12,684 you mentioned, in order to get the best 264 00:09:12,684 --> 00:09:14,524 results. One thing as well, when you look 265 00:09:14,524 --> 00:09:15,964 into the future, where do you see some 266 00:09:15,964 --> 00:09:17,264 of the big growth opportunities 267 00:09:17,644 --> 00:09:19,960 over the next twelve months or so? Yeah. 268 00:09:19,960 --> 00:09:21,220 I think, 269 00:09:21,799 --> 00:09:23,960 the biggest opportunity that I am seeing is 270 00:09:23,960 --> 00:09:26,600 is how do we start to glue these 271 00:09:26,600 --> 00:09:30,200 different technologies together? Right? And, you know, that's 272 00:09:30,200 --> 00:09:31,720 a bit of a challenge. But I think 273 00:09:31,720 --> 00:09:34,220 to me, that's a growth opportunity today. 274 00:09:35,345 --> 00:09:36,125 You know, while, 275 00:09:36,584 --> 00:09:39,225 you know, the industry in general thinks of 276 00:09:39,225 --> 00:09:41,304 AI as it's as a separate thing, when 277 00:09:41,304 --> 00:09:42,924 in fact, that is not the case. 278 00:09:43,544 --> 00:09:45,245 AI, if if it were to exist, 279 00:09:46,904 --> 00:09:50,110 separately, would will not drive value. It has 280 00:09:50,110 --> 00:09:52,769 to work with other technologies and people. 281 00:09:53,149 --> 00:09:55,470 It has to be embedded into the right 282 00:09:55,470 --> 00:09:58,110 workforce so that capability is delivered at the 283 00:09:58,110 --> 00:10:00,750 right time to the right person in the 284 00:10:00,750 --> 00:10:01,490 right way. 285 00:10:01,964 --> 00:10:04,225 So in my mind, that is the opportunity 286 00:10:04,284 --> 00:10:06,464 today is where we're taking AI 287 00:10:07,804 --> 00:10:09,264 as as as a conversation 288 00:10:09,804 --> 00:10:13,084 and but also but then embedding it embedding 289 00:10:13,084 --> 00:10:15,184 it into what what our workforce 290 00:10:15,725 --> 00:10:17,039 do day to day. 291 00:10:17,679 --> 00:10:19,699 You know, that's a that's a growth opportunity 292 00:10:19,839 --> 00:10:21,279 we have, and, you know, we are really 293 00:10:21,279 --> 00:10:23,699 focused on that. We have, you know, folks 294 00:10:23,839 --> 00:10:26,820 that that that abide by, you know, concepts 295 00:10:26,879 --> 00:10:28,899 of human factor engineering. This is, 296 00:10:30,125 --> 00:10:32,945 the the in in some words, industrial engineering, 297 00:10:33,404 --> 00:10:33,884 where, 298 00:10:34,365 --> 00:10:36,044 technology is looked at as a part of 299 00:10:36,044 --> 00:10:39,004 the process versus a technology alone. Right? And 300 00:10:39,004 --> 00:10:40,845 and embedding that into a process. So I 301 00:10:40,845 --> 00:10:42,940 think that's the, to me, that's the growth 302 00:10:42,940 --> 00:10:45,899 opportunity for everyone, including us. I think we 303 00:10:45,899 --> 00:10:47,500 are doing really well, but we can do 304 00:10:47,500 --> 00:10:51,259 better where we are embedding different techno embedding 305 00:10:51,259 --> 00:10:52,860 AI into the into into, 306 00:10:53,580 --> 00:10:55,980 into a process, but then also bringing different 307 00:10:55,980 --> 00:10:57,200 technologies together. 308 00:10:58,575 --> 00:10:59,134 You know, 309 00:10:59,695 --> 00:11:01,615 if you we keep hearing about, you know, 310 00:11:01,615 --> 00:11:03,455 and I'm digressing here a bit, but we 311 00:11:03,455 --> 00:11:06,254 keep hearing about agentic AI. You know? And 312 00:11:06,254 --> 00:11:08,414 agentic AI is a lot of things. But 313 00:11:08,414 --> 00:11:11,054 to me, the biggest value there is that 314 00:11:11,054 --> 00:11:12,355 it is an orchestration 315 00:11:12,735 --> 00:11:13,235 of 316 00:11:13,589 --> 00:11:17,190 of robotics process automation and and three different 317 00:11:17,190 --> 00:11:19,269 AIs and a few other capabilities, all that 318 00:11:19,269 --> 00:11:21,669 put together. So it works at a command 319 00:11:21,669 --> 00:11:23,429 line. It works at a command to say 320 00:11:23,429 --> 00:11:25,269 when a patient says, I need to go 321 00:11:25,269 --> 00:11:27,375 to the doctor, so make me an appointment 322 00:11:27,514 --> 00:11:29,855 and make sure that I have car service, 323 00:11:30,475 --> 00:11:31,995 available for me. And then when I get 324 00:11:31,995 --> 00:11:34,394 there, you know, there's a wheelchair there. That 325 00:11:34,394 --> 00:11:36,495 is a command. And that's a command line. 326 00:11:36,554 --> 00:11:38,875 Right? And I'm using the word command line 327 00:11:38,875 --> 00:11:41,090 as a as a nontechnical term here. And 328 00:11:41,090 --> 00:11:41,590 then 329 00:11:42,210 --> 00:11:46,050 and then agents take that command and do 330 00:11:46,050 --> 00:11:47,730 five different things. And that's what I'm talking 331 00:11:47,730 --> 00:11:50,850 about bringing three to five different technologies together, 332 00:11:50,850 --> 00:11:53,970 AI, RPA, digital, whatever you have, whatever is 333 00:11:53,970 --> 00:11:55,904 required to do it, maybe even a robot 334 00:11:55,904 --> 00:11:57,745 making a phone call into a real person 335 00:11:57,745 --> 00:11:59,904 having conversation and saying, you know, this person 336 00:11:59,904 --> 00:12:01,684 this person is coming in for this appointment 337 00:12:01,745 --> 00:12:03,584 at this time. Please make sure you have 338 00:12:03,584 --> 00:12:05,664 a wheelchair available. All that has to come 339 00:12:05,664 --> 00:12:08,304 together. So that's the biggest opportunity, which is 340 00:12:08,304 --> 00:12:10,084 being able to tailor all that together. 341 00:12:11,070 --> 00:12:12,829 I love that. It seems like such a 342 00:12:12,829 --> 00:12:14,429 a simple thing, yet I know nothing is 343 00:12:14,429 --> 00:12:15,169 ever simple, 344 00:12:15,709 --> 00:12:17,409 when it comes to this type of transformation. 345 00:12:17,629 --> 00:12:19,870 And and certainly, those little things make a 346 00:12:19,870 --> 00:12:21,709 big difference when you're looking at the patient 347 00:12:21,709 --> 00:12:24,014 care journey, the experience, but then to how 348 00:12:24,014 --> 00:12:26,415 things are operating, at the hospital and in 349 00:12:26,415 --> 00:12:29,055 clinics and really, you know, how teams are 350 00:12:29,055 --> 00:12:30,434 working together most effectively. 351 00:12:30,975 --> 00:12:32,815 A lot of opportunity, it seems like, with 352 00:12:32,815 --> 00:12:34,595 AI, especially in the technologies, 353 00:12:35,215 --> 00:12:37,509 as we've been talking about. But I'm curious, 354 00:12:37,509 --> 00:12:39,690 what are the big challenges that you're anticipating 355 00:12:39,750 --> 00:12:40,409 as well? 356 00:12:40,870 --> 00:12:43,269 Yeah. You know, our challenge is, I think, 357 00:12:43,990 --> 00:12:44,649 the our 358 00:12:45,110 --> 00:12:47,289 which is a blessing in disguise, but, 359 00:12:47,750 --> 00:12:50,009 it's it's the pipeline. You know, we have 360 00:12:50,230 --> 00:12:51,210 a close to 361 00:12:51,815 --> 00:12:54,774 300 use cases that are waiting to be 362 00:12:54,774 --> 00:12:57,254 looked at, waiting to be worked on, waiting 363 00:12:57,254 --> 00:12:59,495 to be developed, waiting to be deployed, waiting 364 00:12:59,495 --> 00:13:00,235 to be evaluated. 365 00:13:01,254 --> 00:13:03,115 So it's, you know, our our organization, 366 00:13:03,735 --> 00:13:05,674 you know, is very excited about, 367 00:13:05,990 --> 00:13:08,069 you know, what the potential of what these 368 00:13:08,069 --> 00:13:11,049 technologies, you know, bring to them. And and 369 00:13:11,509 --> 00:13:13,610 the I think the time and space 370 00:13:14,230 --> 00:13:15,769 to actually do this right, 371 00:13:16,309 --> 00:13:18,309 is really about this is no longer for 372 00:13:18,309 --> 00:13:19,049 us about 373 00:13:19,375 --> 00:13:21,535 running after or looking at the the shiny 374 00:13:21,535 --> 00:13:24,575 toy. Right? In addition to, you know, this 375 00:13:24,575 --> 00:13:27,055 thinking about, you know, these use cases as 376 00:13:27,055 --> 00:13:29,555 being a good idea, it's also about ROI. 377 00:13:29,855 --> 00:13:32,095 Right? How do we make sure we capture 378 00:13:32,095 --> 00:13:35,050 that information? And, unfortunately, that's not how people 379 00:13:35,050 --> 00:13:37,129 are thinking about today about about AI today. 380 00:13:37,129 --> 00:13:38,750 People want to do AI. But 381 00:13:39,050 --> 00:13:41,290 when we have those conversations about, you know, 382 00:13:41,290 --> 00:13:42,889 what you know, how do you how will 383 00:13:42,889 --> 00:13:44,330 you drive value from it? And how do 384 00:13:44,330 --> 00:13:46,009 we make sure it it impacts the bottom 385 00:13:46,009 --> 00:13:47,690 line? And bottom line could be financials, could 386 00:13:47,690 --> 00:13:50,110 be patient experience, could be work for experience. 387 00:13:50,595 --> 00:13:52,115 Those those take a lot of time. I'm 388 00:13:52,115 --> 00:13:53,634 not saying people aren't ready to have that 389 00:13:53,634 --> 00:13:54,134 conversation, 390 00:13:54,674 --> 00:13:57,475 but exercising those, I think those steps as 391 00:13:57,475 --> 00:13:59,174 a part of our governance process, 392 00:13:59,794 --> 00:14:01,714 is is is a is a challenge for 393 00:14:01,714 --> 00:14:03,174 us. There's a large demand, 394 00:14:03,679 --> 00:14:05,620 and we have to cater to that demand. 395 00:14:06,559 --> 00:14:08,559 And it's, you know, it it requires times. 396 00:14:08,559 --> 00:14:09,860 It requires resources. 397 00:14:10,399 --> 00:14:12,319 That's a big challenge. These are all great 398 00:14:12,319 --> 00:14:14,240 ideas. We just have to pick the right 399 00:14:14,240 --> 00:14:15,919 ideas to work on because we can't work 400 00:14:15,919 --> 00:14:16,815 on all of them. 401 00:14:17,695 --> 00:14:19,554 That's such a great point. And I know, 402 00:14:19,615 --> 00:14:22,495 as you mentioned, having so many ideas coming 403 00:14:22,495 --> 00:14:23,634 in and so much, 404 00:14:24,335 --> 00:14:24,835 possibilities, 405 00:14:25,375 --> 00:14:28,254 and and then truly understanding the benefits, the 406 00:14:28,254 --> 00:14:30,335 different, you know, return that you can get 407 00:14:30,335 --> 00:14:32,580 from these, what should be prior prioritize is 408 00:14:32,660 --> 00:14:35,059 key. When looking at that governance structure, I'm 409 00:14:35,059 --> 00:14:37,059 wondering if we can, dig just one bit 410 00:14:37,059 --> 00:14:39,480 deeper there. I know a lot of, again, 411 00:14:39,620 --> 00:14:41,460 hospital and health systems are trying to figure 412 00:14:41,460 --> 00:14:43,160 out where to do this right and understand 413 00:14:43,460 --> 00:14:45,240 what they need in order to develop 414 00:14:45,700 --> 00:14:47,559 a strong and and meaningful governance 415 00:14:48,044 --> 00:14:49,345 process for especially, 416 00:14:50,044 --> 00:14:51,264 AI driven projects. 417 00:14:51,725 --> 00:14:53,725 What did you do at Hackensack Meridian, and 418 00:14:53,725 --> 00:14:55,964 what have you found really effective? If there's 419 00:14:55,964 --> 00:14:58,284 anything that you've changed or tweaked, that you 420 00:14:58,284 --> 00:14:59,725 found didn't work, I'd just love to hear 421 00:14:59,725 --> 00:15:01,804 your perspective on that briefly before we wrap 422 00:15:01,804 --> 00:15:04,460 up here. Yeah. I think the biggest piece 423 00:15:04,460 --> 00:15:06,460 that, you know, just looking back now in 424 00:15:06,460 --> 00:15:08,460 our journey for approximately three years or, you 425 00:15:08,460 --> 00:15:10,320 know, my journey at three years at Hackensack, 426 00:15:11,019 --> 00:15:12,700 you know, I think we've done a lot 427 00:15:12,700 --> 00:15:14,559 of great and lot of right things. 428 00:15:15,375 --> 00:15:17,134 Having said that, I think it's fair to 429 00:15:17,134 --> 00:15:18,175 say that, you know, we could have done 430 00:15:18,175 --> 00:15:20,095 a lot of things better as well. One 431 00:15:20,095 --> 00:15:20,835 thing that 432 00:15:21,215 --> 00:15:22,915 continuously comes to mind, 433 00:15:23,774 --> 00:15:26,754 you know, is is education. Right. I think 434 00:15:26,815 --> 00:15:27,955 educating people 435 00:15:28,509 --> 00:15:29,889 on this technology 436 00:15:30,190 --> 00:15:32,350 is something that I think us as an 437 00:15:32,350 --> 00:15:35,949 industry have haven't thought about or acted on 438 00:15:35,949 --> 00:15:37,809 as much as we should have. Right? 439 00:15:38,350 --> 00:15:38,850 People 440 00:15:39,870 --> 00:15:42,049 have a sense of what AI is. 441 00:15:42,644 --> 00:15:44,664 People don't know how 442 00:15:45,044 --> 00:15:45,865 best to 443 00:15:46,404 --> 00:15:47,144 use it 444 00:15:47,445 --> 00:15:47,945 correctly. 445 00:15:48,804 --> 00:15:50,324 You know, as a result of that, this 446 00:15:50,324 --> 00:15:52,245 technology ends up, you know, getting a lot 447 00:15:52,245 --> 00:15:53,704 of bad rap at times 448 00:15:54,004 --> 00:15:55,865 when, in fact, in my opinion, 449 00:15:56,245 --> 00:15:57,865 it's not used correctly. 450 00:15:58,379 --> 00:15:59,980 To explain this, I'll use example of, you 451 00:15:59,980 --> 00:16:01,179 know, the the likes of, 452 00:16:01,660 --> 00:16:03,740 you know, chat GBT or the generative AI 453 00:16:03,740 --> 00:16:06,559 capability. Right? I consistently have folks, 454 00:16:07,500 --> 00:16:08,000 looking 455 00:16:08,379 --> 00:16:10,399 for answers from such technologies, 456 00:16:11,565 --> 00:16:14,125 that are that I think this technology cannot 457 00:16:14,125 --> 00:16:16,065 answer. So they think of this as 458 00:16:16,365 --> 00:16:19,245 one place for everything that solves, you know, 459 00:16:19,245 --> 00:16:21,585 world hunger. Right? When that's not the case, 460 00:16:21,804 --> 00:16:24,045 you know, I the the analogy that I 461 00:16:24,045 --> 00:16:25,840 have used is, you know, the likes of 462 00:16:25,840 --> 00:16:28,660 chat could be Gemini or it could be, 463 00:16:28,879 --> 00:16:29,540 you know, 464 00:16:29,920 --> 00:16:30,420 chat. 465 00:16:31,360 --> 00:16:34,399 So it's it's like the high fructose corn 466 00:16:34,399 --> 00:16:35,460 syrup or sweeteners. 467 00:16:35,920 --> 00:16:37,860 The reason I call it that is because 468 00:16:38,125 --> 00:16:40,605 it does the job. It's really sweet, but 469 00:16:40,605 --> 00:16:42,605 it may not be good for everyone or 470 00:16:42,605 --> 00:16:44,925 all use cases. So when a clinician is 471 00:16:44,925 --> 00:16:47,884 going in and typing a use case question 472 00:16:47,884 --> 00:16:49,985 in there that is very clinically focused 473 00:16:50,309 --> 00:16:52,549 and demanding a accurate response. And when the 474 00:16:52,549 --> 00:16:55,110 clinician doesn't get it, you know, this technology 475 00:16:55,110 --> 00:16:56,090 gets bad rap. 476 00:16:56,789 --> 00:16:57,289 We 477 00:16:57,830 --> 00:17:00,250 educate our our clinicians internally 478 00:17:00,710 --> 00:17:03,129 to find ways to ask the question correctly. 479 00:17:03,774 --> 00:17:05,694 We actually build a use we we built 480 00:17:05,694 --> 00:17:08,255 this capability where we use this technology called 481 00:17:08,255 --> 00:17:09,634 RAG, r a g, 482 00:17:10,335 --> 00:17:12,255 which sits on top of these generative AI 483 00:17:12,255 --> 00:17:12,755 capabilities. 484 00:17:13,134 --> 00:17:14,654 So it provides a better answer, but I 485 00:17:14,654 --> 00:17:16,414 think it all comes with education. The point 486 00:17:16,414 --> 00:17:18,009 I'm trying to make is that I think 487 00:17:18,009 --> 00:17:20,589 we have ran fast at especially this generative 488 00:17:20,650 --> 00:17:21,309 AI technology, 489 00:17:21,929 --> 00:17:22,990 and folks are, 490 00:17:23,769 --> 00:17:25,769 are not educated. It just, you know, if 491 00:17:25,769 --> 00:17:27,210 if I had to go back, which is 492 00:17:27,210 --> 00:17:28,210 which no one can, 493 00:17:28,650 --> 00:17:30,910 I would say, you know, let's in parallel 494 00:17:31,049 --> 00:17:32,429 invest enough in educating 495 00:17:33,065 --> 00:17:34,904 the public and our workforce on what this 496 00:17:34,904 --> 00:17:36,424 is and what this isn't and how it 497 00:17:36,424 --> 00:17:37,244 should be used? 498 00:17:38,505 --> 00:17:40,345 As we work on building this technology, I 499 00:17:40,345 --> 00:17:42,444 think we all ran at building these technologies. 500 00:17:42,904 --> 00:17:45,944 And then we we we didn't invest as 501 00:17:45,944 --> 00:17:48,839 much in educating our masses around what this 502 00:17:48,839 --> 00:17:50,200 is and what this isn't and how this 503 00:17:50,200 --> 00:17:51,259 is useful to you. 504 00:17:52,759 --> 00:17:54,519 That's such an excellent point. I I really 505 00:17:54,519 --> 00:17:56,680 appreciate your perspective on this. And, certainly, I 506 00:17:56,680 --> 00:17:58,759 can imagine some efforts to to try to 507 00:17:58,759 --> 00:18:01,255 do that now, but still, you know, having 508 00:18:01,255 --> 00:18:03,255 it from the beginning, it sounds like it 509 00:18:03,255 --> 00:18:05,515 is really beneficial or would have been beneficial. 510 00:18:05,974 --> 00:18:07,335 Yeah. It's not late. I mean, we're, you 511 00:18:07,335 --> 00:18:09,335 know, we're we're now charging at this at 512 00:18:09,335 --> 00:18:12,134 Hackensack where, you know, we have more people 513 00:18:12,134 --> 00:18:13,815 involved than ever. You know, I'll give you 514 00:18:13,815 --> 00:18:16,509 an example of our governance team. When we 515 00:18:16,509 --> 00:18:18,990 started AI governance, it was, you know, it 516 00:18:18,990 --> 00:18:19,470 was, 517 00:18:19,789 --> 00:18:21,630 we we we it we had a total 518 00:18:21,630 --> 00:18:22,849 of 13 domains 519 00:18:23,230 --> 00:18:25,549 that evaluated all these use cases, and it 520 00:18:25,549 --> 00:18:28,690 was 13 people. Today, it's over 26. 521 00:18:29,154 --> 00:18:30,454 Right? So we have doubled. 522 00:18:30,994 --> 00:18:33,654 We have better engagement from our leadership, 523 00:18:34,275 --> 00:18:36,674 which is our executive leadership team on which 524 00:18:36,674 --> 00:18:38,134 use cases to work on, 525 00:18:38,595 --> 00:18:40,035 in in in the past. I'm not saying 526 00:18:40,035 --> 00:18:41,875 that wasn't there, but they are more present. 527 00:18:41,875 --> 00:18:44,019 They're more talking about this. They're demanding and 528 00:18:44,019 --> 00:18:45,700 saying, why should we do this? So I 529 00:18:45,700 --> 00:18:47,619 think it all came from learning. So I 530 00:18:47,619 --> 00:18:49,779 think it's not too late. We're, you know, 531 00:18:49,940 --> 00:18:52,500 you know, Hackensack is is obviously very keen 532 00:18:52,500 --> 00:18:54,420 in making sure we get this right. Other 533 00:18:54,420 --> 00:18:56,259 organizations are doing this as well. So it's 534 00:18:56,420 --> 00:18:58,440 I I say better late than never. 535 00:18:59,714 --> 00:19:02,595 Absolutely. Absolutely. I I love that. Now, before 536 00:19:02,595 --> 00:19:04,674 we wrap up, one more question. What is 537 00:19:04,674 --> 00:19:06,194 the number one thing that you're doing right 538 00:19:06,194 --> 00:19:08,115 now to set the organization up for long 539 00:19:08,115 --> 00:19:08,855 term success? 540 00:19:10,035 --> 00:19:10,515 I think, 541 00:19:11,230 --> 00:19:14,190 it's it's about being very I'm asking the 542 00:19:14,190 --> 00:19:16,529 organization to be open to ideas. 543 00:19:17,149 --> 00:19:17,649 Right. 544 00:19:18,509 --> 00:19:19,970 There is no bad idea, 545 00:19:20,349 --> 00:19:21,409 but it requires, 546 00:19:22,509 --> 00:19:24,974 you know, attention from people. So I think 547 00:19:24,974 --> 00:19:27,454 what I am asking the organization is is 548 00:19:27,454 --> 00:19:30,414 is is open your door, listen to, you 549 00:19:30,414 --> 00:19:31,875 know, how this technology 550 00:19:32,174 --> 00:19:34,494 can help you, you know, come to us 551 00:19:34,494 --> 00:19:36,815 with ideas that you have come to us 552 00:19:36,815 --> 00:19:38,434 with ideas that you are hearing. 553 00:19:39,130 --> 00:19:40,429 And I think we should 554 00:19:40,890 --> 00:19:43,289 problem solve around what is the best thing 555 00:19:43,289 --> 00:19:44,349 to do for you, 556 00:19:44,730 --> 00:19:48,009 that that I think sentiment existed. It's not 557 00:19:48,009 --> 00:19:49,549 fair. It's not something that, 558 00:19:50,089 --> 00:19:52,970 that didn't exist, but it's it needs to 559 00:19:52,970 --> 00:19:54,190 be hyperscaled. 560 00:19:54,805 --> 00:19:57,605 Right? This is new tech, and there's some 561 00:19:57,605 --> 00:19:59,684 great ideas out there. There are companies that 562 00:19:59,684 --> 00:20:00,904 are doing it really well. 563 00:20:01,365 --> 00:20:03,605 There's it. So I I think what what 564 00:20:03,605 --> 00:20:04,345 I am 565 00:20:04,724 --> 00:20:08,025 telling them is is this AI is not 566 00:20:09,130 --> 00:20:10,430 a similar problem, 567 00:20:10,890 --> 00:20:13,230 or similar initiative. This is an organizational 568 00:20:13,609 --> 00:20:16,029 initiative. So keep your ears open. 569 00:20:16,730 --> 00:20:18,569 Speak to us about this. We will tell 570 00:20:18,569 --> 00:20:19,710 you let's collaborate. 571 00:20:20,345 --> 00:20:22,585 Right? And and and get to a place 572 00:20:22,585 --> 00:20:25,545 where either we decide to do this level 573 00:20:25,545 --> 00:20:27,945 of AI enablement in your in your in 574 00:20:27,945 --> 00:20:29,704 your team and in your department, or we 575 00:20:29,704 --> 00:20:30,904 decide not to do it at that point 576 00:20:30,904 --> 00:20:32,345 and move on to the next use case. 577 00:20:32,345 --> 00:20:34,505 But I think it's all about being open 578 00:20:34,505 --> 00:20:35,884 to what AI is, 579 00:20:36,390 --> 00:20:38,789 realizing where that where it it drives value 580 00:20:38,789 --> 00:20:39,690 and where it doesn't. 581 00:20:40,950 --> 00:20:43,750 Absolutely. I I really appreciate that. Sameer, thank 582 00:20:43,750 --> 00:20:44,950 you so much for joining us on the 583 00:20:44,950 --> 00:20:46,950 podcast today. This has been such a valuable 584 00:20:46,950 --> 00:20:48,630 discussion, and I look forward to connecting with 585 00:20:48,630 --> 00:20:50,940 you again soon. Yeah. Likewise, Zor. Thank you 586 00:20:50,940 --> 00:20:52,779 so much for the opportunity. Really excited to 587 00:20:52,779 --> 00:20:53,679 talk to you again.