1 00:00:00,160 --> 00:00:01,919 Hello, everyone, and thank you for tuning in 2 00:00:01,919 --> 00:00:04,160 to the Becker's HealthCare podcast. We are thrilled 3 00:00:04,160 --> 00:00:06,240 to be joined on-site here at Becker's Health 4 00:00:06,240 --> 00:00:09,359 IT Digital Health RCM Conference in Chicago with 5 00:00:09,359 --> 00:00:10,259 Ajay Kapre, 6 00:00:10,639 --> 00:00:13,865 president and chief strategy officer with Elkay, and 7 00:00:13,865 --> 00:00:17,304 doctor Safar Chaudhry, senior vice president, chief digital 8 00:00:17,304 --> 00:00:19,945 officer, and chief AI and information officer with 9 00:00:19,945 --> 00:00:20,925 Seattle Children's. 10 00:00:21,464 --> 00:00:23,464 Ajay, doctor Chaudhry, thank you so much for 11 00:00:23,464 --> 00:00:24,364 being here today. 12 00:00:25,064 --> 00:00:26,984 Thanks for having us, Brian. Thank you for 13 00:00:26,984 --> 00:00:28,849 having us, Brian. And it's an honor to 14 00:00:28,849 --> 00:00:31,410 do it with doctor Chaudhry. Yeah. It's great 15 00:00:31,410 --> 00:00:33,170 to have you both here. So so let's 16 00:00:33,170 --> 00:00:34,309 get into the conversation. 17 00:00:34,770 --> 00:00:36,530 Innovation can often feel like a like a 18 00:00:36,530 --> 00:00:37,350 moving target. 19 00:00:37,649 --> 00:00:39,649 What do you think are the core elements 20 00:00:39,649 --> 00:00:41,729 that define true innovation in the health care 21 00:00:41,729 --> 00:00:43,844 IT space? So far, can we can we 22 00:00:43,844 --> 00:00:46,005 start with you? Yeah. So, certainly, the first 23 00:00:46,005 --> 00:00:48,265 thing to think about in this space is, 24 00:00:48,804 --> 00:00:50,024 are there any regulatory 25 00:00:50,405 --> 00:00:52,244 compliance issues that we need to take care 26 00:00:52,244 --> 00:00:52,744 of? 27 00:00:53,524 --> 00:00:54,265 In addition, 28 00:00:54,740 --> 00:00:56,840 there's going to be the cultural aspects 29 00:00:57,460 --> 00:00:58,359 for the organization. 30 00:00:59,219 --> 00:01:01,939 Change management is always really important when you're 31 00:01:01,939 --> 00:01:03,239 implementing new technology. 32 00:01:04,099 --> 00:01:04,599 And 33 00:01:05,140 --> 00:01:07,959 there always has to be executive level sponsorship 34 00:01:08,260 --> 00:01:09,000 and championing 35 00:01:09,459 --> 00:01:12,865 to make things actually stick. The sustainability is 36 00:01:12,865 --> 00:01:15,365 really important when thinking about innovation. 37 00:01:16,465 --> 00:01:18,545 So that that change management piece, that that 38 00:01:18,545 --> 00:01:20,805 executive buy in, I imagine, is is huge. 39 00:01:21,344 --> 00:01:22,865 Ajay, what would you add here? You know, 40 00:01:22,865 --> 00:01:24,165 I feel like true innovation, 41 00:01:24,680 --> 00:01:26,780 it needs to solve real world problems 42 00:01:27,079 --> 00:01:29,979 with scalable solutions and not just, you know, 43 00:01:30,200 --> 00:01:32,439 talking about any flashy technology or a new 44 00:01:32,439 --> 00:01:32,939 technology. 45 00:01:33,479 --> 00:01:35,640 There should be real usage of any of 46 00:01:35,640 --> 00:01:37,500 the innovation that you're leading towards. 47 00:01:38,144 --> 00:01:39,825 Especially in health care, if you look at, 48 00:01:39,825 --> 00:01:42,165 we need to simplify and not complicate 49 00:01:42,944 --> 00:01:45,665 the processes for both health care providers as 50 00:01:45,665 --> 00:01:46,724 well as the patients. 51 00:01:47,584 --> 00:01:50,384 And if we focus on patient outcomes, improving 52 00:01:50,384 --> 00:01:51,444 clinical workflows, 53 00:01:51,859 --> 00:01:53,799 I think providing the real interop 54 00:01:54,260 --> 00:01:56,340 solution, I think, you know, we can actually 55 00:01:56,340 --> 00:01:57,640 get a big wins there. 56 00:01:57,939 --> 00:02:01,060 Yeah. Some real tangible results. Right? Yes. Appreciate 57 00:02:01,060 --> 00:02:03,319 that. Doctor Chaudhary, question for you. 58 00:02:03,780 --> 00:02:05,055 From your experience, what are 59 00:02:07,055 --> 00:02:07,775 the key factors that really either enable and 60 00:02:07,775 --> 00:02:10,675 power innovation or hinder innovation in health care? 61 00:02:10,814 --> 00:02:13,134 Are there common barriers that organizations out there 62 00:02:13,134 --> 00:02:13,875 run into, 63 00:02:14,335 --> 00:02:16,495 when they're trying to to integrate new technologies 64 00:02:16,495 --> 00:02:18,510 and manage through that change as you mentioned. 65 00:02:18,510 --> 00:02:20,349 Well, certainly, the the top of mind would 66 00:02:20,349 --> 00:02:21,330 be finances. 67 00:02:21,870 --> 00:02:23,730 Right? There's always financial constraints. 68 00:02:24,510 --> 00:02:26,590 When you're thinking about innovation, people need to 69 00:02:26,590 --> 00:02:29,490 know I agree with Ajay about simplification, 70 00:02:29,870 --> 00:02:31,170 but at the same time, 71 00:02:31,629 --> 00:02:33,125 can you afford to do it? And And 72 00:02:33,125 --> 00:02:34,564 if you do it, is it going to 73 00:02:34,564 --> 00:02:36,485 give you some sort of return? So those 74 00:02:36,485 --> 00:02:38,745 are definitely constraints. Then you've got 75 00:02:39,125 --> 00:02:40,584 the culture of your organization. 76 00:02:41,604 --> 00:02:44,485 Some organizations are open to innovation. Some are 77 00:02:44,485 --> 00:02:44,985 not. 78 00:02:45,364 --> 00:02:47,844 I'm sure you've heard the statement that we 79 00:02:47,844 --> 00:02:48,960 do it our way 80 00:02:49,920 --> 00:02:51,379 and everybody's unique. 81 00:02:51,760 --> 00:02:52,900 And they're not necessarily 82 00:02:53,520 --> 00:02:55,700 unique, but that's what they feel they are. 83 00:02:56,000 --> 00:02:56,900 And, of course, 84 00:02:57,360 --> 00:02:59,620 there is a difference between generations 85 00:02:59,920 --> 00:03:02,740 of culture within an organization that impact 86 00:03:03,375 --> 00:03:06,115 the adoption of any level of innovation. So 87 00:03:06,574 --> 00:03:09,615 an older physician like myself probably doesn't want 88 00:03:09,615 --> 00:03:12,254 to adopt new things, whereas a Gen z 89 00:03:12,254 --> 00:03:12,754 physician 90 00:03:13,294 --> 00:03:15,375 grew up that way. They were digital to 91 00:03:15,375 --> 00:03:16,435 start with and 92 00:03:16,840 --> 00:03:19,479 we'll adopt those things. The the other thing 93 00:03:19,479 --> 00:03:21,419 is when you're setting this up, 94 00:03:22,280 --> 00:03:23,879 you've got to make sure that, as I 95 00:03:23,879 --> 00:03:26,379 said before, the highest level of buy in. 96 00:03:26,519 --> 00:03:29,000 Mhmm. So if you are the innovation champion, 97 00:03:29,000 --> 00:03:30,219 let's say it's me, 98 00:03:30,844 --> 00:03:32,925 I would then have to champion that. I'd 99 00:03:32,925 --> 00:03:34,944 all have to also do the good communication 100 00:03:35,165 --> 00:03:37,025 around it. So communication is also 101 00:03:37,405 --> 00:03:39,425 the you know, why are we doing this? 102 00:03:39,564 --> 00:03:41,405 Right. I always like to say, what problem 103 00:03:41,405 --> 00:03:43,004 are we really trying to solve with the 104 00:03:43,004 --> 00:03:43,504 innovation? 105 00:03:43,980 --> 00:03:45,580 Or are we just trying to buy another 106 00:03:45,580 --> 00:03:47,659 shiny toy? And if we have a shiny 107 00:03:47,659 --> 00:03:49,580 toy, is that is that just gonna be 108 00:03:49,580 --> 00:03:51,260 the flavor of the month? Right. Or is 109 00:03:51,260 --> 00:03:53,340 it gonna be something that truly drives the 110 00:03:53,340 --> 00:03:56,080 most important thing, which is patient outcomes? 111 00:03:56,735 --> 00:03:58,735 So that's that's what we're gonna focus on. 112 00:03:58,735 --> 00:04:00,094 Yeah. And and so far, I would never 113 00:04:00,094 --> 00:04:02,094 describe you as an older physician. So I 114 00:04:02,094 --> 00:04:04,335 I I appreciate the the humor there, but 115 00:04:04,335 --> 00:04:06,415 let's dig dig deeper into sort of the 116 00:04:06,415 --> 00:04:08,655 the the the cultural component here and, of 117 00:04:08,655 --> 00:04:11,879 course, that that that champion that executive champion. 118 00:04:12,180 --> 00:04:13,780 Ajay, can can you talk about sort of 119 00:04:13,780 --> 00:04:16,259 what role leadership plays in fostering an innovative 120 00:04:16,259 --> 00:04:18,899 culture within health care and and what leaders 121 00:04:18,899 --> 00:04:20,980 can do to really sustain that innovation and 122 00:04:20,980 --> 00:04:23,204 continue to encourage it? I think to start 123 00:04:23,204 --> 00:04:24,904 with and, you know, I agree with Zafar, 124 00:04:25,365 --> 00:04:27,044 everything he said. But, you know, to start 125 00:04:27,044 --> 00:04:27,544 with, 126 00:04:28,245 --> 00:04:30,805 anything you want to actually have innovation, you 127 00:04:30,805 --> 00:04:32,664 need to actually set that culture. 128 00:04:33,125 --> 00:04:36,000 Culture plays a very important role. And with 129 00:04:36,000 --> 00:04:37,379 culture comes collaboration. 130 00:04:38,160 --> 00:04:40,160 You need to listen more. You need to 131 00:04:40,160 --> 00:04:42,240 hear more, talk more to people. What are 132 00:04:42,240 --> 00:04:44,800 the real market problems out there? What can 133 00:04:44,800 --> 00:04:47,039 I do to solve those? At the end 134 00:04:47,039 --> 00:04:49,039 of the day, we are in healthcare IT. 135 00:04:49,039 --> 00:04:50,579 We're here to serve patients 136 00:04:51,095 --> 00:04:52,154 and patient care. 137 00:04:52,694 --> 00:04:54,535 And if you look at it, you know, 138 00:04:54,535 --> 00:04:55,435 it is really 139 00:04:56,214 --> 00:04:59,354 80% is people, 15% is process, 140 00:04:59,735 --> 00:05:00,954 5% is technology. 141 00:05:01,574 --> 00:05:03,414 And if you think that way and if 142 00:05:03,414 --> 00:05:05,574 you put culture as your main thing, align 143 00:05:05,574 --> 00:05:06,314 with people 144 00:05:06,829 --> 00:05:08,050 or even with partners, 145 00:05:08,589 --> 00:05:10,350 you know, health system partner with who you 146 00:05:10,350 --> 00:05:11,009 are developing 147 00:05:11,470 --> 00:05:12,610 a innovative idea, 148 00:05:13,230 --> 00:05:15,389 it all comes down to that culture plus 149 00:05:15,389 --> 00:05:16,610 collaboration together. 150 00:05:17,149 --> 00:05:19,470 I'll also give an example here. You know? 151 00:05:19,470 --> 00:05:21,685 And these this line is not from me. 152 00:05:21,685 --> 00:05:23,925 This is from Judy Faulkner, which says that, 153 00:05:23,925 --> 00:05:24,584 you know, 154 00:05:24,884 --> 00:05:26,185 if you wanna go fast, 155 00:05:26,644 --> 00:05:29,605 go alone. If you're gonna go far, go 156 00:05:29,605 --> 00:05:30,105 together. 157 00:05:31,045 --> 00:05:33,045 Go as a team. So the team plays 158 00:05:33,045 --> 00:05:35,350 a very important role when it when you're 159 00:05:35,350 --> 00:05:37,509 talking about any innovation or you want to 160 00:05:37,509 --> 00:05:38,170 bring it, 161 00:05:38,710 --> 00:05:40,550 everyone wants to bring an idea very fast 162 00:05:40,550 --> 00:05:42,310 to the market, but I feel like one 163 00:05:42,310 --> 00:05:44,310 has to vet it properly. What are you 164 00:05:44,310 --> 00:05:46,389 trying to solve? Is the market ready for 165 00:05:46,389 --> 00:05:49,029 that idea to adopt? Adoption of the idea 166 00:05:49,029 --> 00:05:51,925 is much, much more bigger than just going 167 00:05:52,384 --> 00:05:54,305 as going as a shiny object just at 168 00:05:54,305 --> 00:05:56,785 the start. Right. Right. And that shiny object 169 00:05:56,785 --> 00:05:58,704 thing. If you're if you're focusing on the 170 00:05:58,704 --> 00:06:01,024 people and the culture, it's gonna prevent the 171 00:06:01,024 --> 00:06:03,185 shiny object syndrome. Right? If you're if you're 172 00:06:03,185 --> 00:06:04,865 actually thinking about the teams and the people. 173 00:06:04,865 --> 00:06:05,189 Yep. 174 00:06:05,670 --> 00:06:07,050 Yeah. Appreciate that. So, 175 00:06:07,990 --> 00:06:10,230 Zafar, can you can you also just elaborate 176 00:06:10,230 --> 00:06:11,990 on how you think about this? So I'm 177 00:06:11,990 --> 00:06:12,810 gonna add 178 00:06:13,509 --> 00:06:15,769 obviously, I've said before you need an executive 179 00:06:15,910 --> 00:06:16,410 sponsor, 180 00:06:17,029 --> 00:06:19,189 but whoever that person is, that person has 181 00:06:19,189 --> 00:06:20,170 to have a vision. 182 00:06:20,735 --> 00:06:22,975 Right? I always tell people that if you 183 00:06:22,975 --> 00:06:25,134 have a really big vision and you get 184 00:06:25,134 --> 00:06:27,055 50% of the way there, you've done really 185 00:06:27,055 --> 00:06:27,555 well. 186 00:06:28,095 --> 00:06:30,435 So you somebody's got to show the organization 187 00:06:30,735 --> 00:06:32,675 what blue sky thinking looks like 188 00:06:32,975 --> 00:06:34,975 and then that person has to be a, 189 00:06:34,975 --> 00:06:37,269 has to stick around and then has to 190 00:06:37,269 --> 00:06:38,569 actually drive through 191 00:06:38,949 --> 00:06:41,589 whatever innovation needs to be driven through. So 192 00:06:41,589 --> 00:06:43,589 you may then be classified as a change 193 00:06:43,589 --> 00:06:44,089 agent. 194 00:06:44,550 --> 00:06:46,470 You may not be very popular in your 195 00:06:46,470 --> 00:06:47,769 organization, but 196 00:06:48,245 --> 00:06:50,404 you probably were hired to do that. And 197 00:06:50,404 --> 00:06:52,105 so I think that's really important. 198 00:06:52,645 --> 00:06:54,964 I agree with the collaboration piece. You have 199 00:06:54,964 --> 00:06:56,504 to bring people on a journey, 200 00:06:57,285 --> 00:06:59,524 and you have to show certainly clinicians, you 201 00:06:59,524 --> 00:07:00,904 have to show them the why. 202 00:07:01,819 --> 00:07:04,000 Right? Why are we doing this initiative 203 00:07:04,620 --> 00:07:06,620 versus we should just do it because it 204 00:07:06,620 --> 00:07:09,500 makes us look good. That's really important. People 205 00:07:09,500 --> 00:07:11,360 need to be able to understand the narrative. 206 00:07:11,500 --> 00:07:13,040 So telling a story 207 00:07:13,660 --> 00:07:14,399 and communicating 208 00:07:14,699 --> 00:07:16,639 that story is also really important, 209 00:07:17,334 --> 00:07:18,794 in the process, in my opinion. 210 00:07:19,095 --> 00:07:20,774 And can you elaborate too on sort of 211 00:07:20,855 --> 00:07:22,694 you mentioned sort of you need somebody to 212 00:07:22,694 --> 00:07:24,475 come to the table and bring that vision, 213 00:07:25,654 --> 00:07:27,495 but you also mentioned that might not be 214 00:07:27,495 --> 00:07:30,134 very popular necessarily sometimes. I guess, how you 215 00:07:30,214 --> 00:07:32,154 how do you stay resilient and optimistic 216 00:07:32,639 --> 00:07:34,479 and not fall into any sort of cynical 217 00:07:34,479 --> 00:07:36,240 thinking when you're trying to be that vision 218 00:07:36,240 --> 00:07:37,779 for the for the organization? 219 00:07:38,160 --> 00:07:40,079 So I suppose it it really it really 220 00:07:40,079 --> 00:07:43,519 boils down to the individual's personality. But I 221 00:07:43,519 --> 00:07:44,894 always say to people that, 222 00:07:45,615 --> 00:07:47,535 working in health care is is like a 223 00:07:47,535 --> 00:07:49,535 marriage. Right? There's more rough times than good 224 00:07:49,535 --> 00:07:51,535 times. But if you make it to 7 225 00:07:51,535 --> 00:07:52,834 years, it's happy days. 226 00:07:53,375 --> 00:07:55,615 And I've been in this for 38 years, 227 00:07:55,615 --> 00:07:57,794 so it's probably a really bad marriage. But 228 00:07:58,769 --> 00:08:02,209 you've got to always reset your clock. Right? 229 00:08:02,209 --> 00:08:03,970 We're all running I would say in health 230 00:08:03,970 --> 00:08:06,769 care now, most leaders are running on more 231 00:08:06,769 --> 00:08:09,089 like half empty versus half full because of 232 00:08:09,089 --> 00:08:10,470 all the changes and 233 00:08:10,930 --> 00:08:13,089 the the costs and, like, everything that's causing 234 00:08:13,089 --> 00:08:16,404 issues. But you've got to find yourself back 235 00:08:16,404 --> 00:08:18,485 to why you do the work. So it's 236 00:08:18,485 --> 00:08:20,264 easy in pediatrics because 237 00:08:21,045 --> 00:08:22,805 coming to work every day knowing that you're 238 00:08:22,805 --> 00:08:25,365 helping kids is a easy mission Mhmm. To 239 00:08:25,365 --> 00:08:28,004 follow. Some aren't as easy. But in health 240 00:08:28,004 --> 00:08:29,920 care in general, you're not in health care 241 00:08:29,920 --> 00:08:32,080 if you don't wanna help people. Right. So 242 00:08:32,080 --> 00:08:34,100 you have to bring yourself back 243 00:08:34,639 --> 00:08:35,860 to that true north 244 00:08:36,160 --> 00:08:38,799 probably every week. And once you do that, 245 00:08:38,799 --> 00:08:41,379 then you remain that champion of change 246 00:08:41,840 --> 00:08:44,179 if if you want to do something differently. 247 00:08:44,894 --> 00:08:47,075 Right? So the question I ask people is, 248 00:08:47,295 --> 00:08:48,735 do you wanna do more of the same 249 00:08:48,735 --> 00:08:51,215 every day, or do you wanna do something 250 00:08:51,215 --> 00:08:52,514 that actually will 251 00:08:52,975 --> 00:08:55,134 allow us to stand out or you as 252 00:08:55,134 --> 00:08:57,055 an individual to stand out or as a 253 00:08:57,055 --> 00:08:57,555 team 254 00:08:57,950 --> 00:08:58,850 to stand out. 255 00:08:59,230 --> 00:09:00,990 It's hard to get there, but you have 256 00:09:00,990 --> 00:09:02,129 to keep that focus. 257 00:09:02,830 --> 00:09:03,730 There's a mindset. 258 00:09:04,110 --> 00:09:05,970 I also say that it also involves, 259 00:09:06,350 --> 00:09:07,009 you know, 260 00:09:07,389 --> 00:09:08,610 probably a lot of drinking 261 00:09:09,950 --> 00:09:12,764 and a lots of pizza. But there's usually 262 00:09:12,764 --> 00:09:14,524 a time when you have to ground yourself 263 00:09:14,524 --> 00:09:15,024 back. 264 00:09:15,404 --> 00:09:17,985 That's usually on a weekly basis. Yeah. Absolutely. 265 00:09:18,205 --> 00:09:19,565 Pizza's always great. Yeah. 266 00:09:20,284 --> 00:09:20,784 So 267 00:09:21,085 --> 00:09:22,924 LK has really been at the the forefront 268 00:09:22,924 --> 00:09:24,304 of connectivity and interoperability 269 00:09:25,004 --> 00:09:25,620 for years. 270 00:09:26,179 --> 00:09:28,740 I'm wondering if you can share some specific 271 00:09:28,740 --> 00:09:31,299 examples, doctor Chaudhry, of your your collaboration with 272 00:09:31,299 --> 00:09:33,620 LK at Seattle Children's and and what what 273 00:09:33,620 --> 00:09:35,539 that's yielded. So let's go back to the 274 00:09:35,539 --> 00:09:37,700 earlier part of the conversation when I spoke 275 00:09:37,700 --> 00:09:39,700 about, well, what problem are we trying to 276 00:09:39,700 --> 00:09:42,304 solve? So what's really interesting about us is 277 00:09:42,304 --> 00:09:44,384 at the time, we were trying to do 278 00:09:44,384 --> 00:09:45,845 a CERNAT epic migration 279 00:09:46,464 --> 00:09:47,605 in the middle of a pandemic. 280 00:09:48,225 --> 00:09:51,504 And I bumped into AJ at a CHIME 281 00:09:51,504 --> 00:09:54,225 conference, and we started talking about, well, I 282 00:09:54,225 --> 00:09:56,360 have a problem. And the problem I had 283 00:09:56,360 --> 00:09:56,860 is 284 00:09:57,160 --> 00:09:58,299 when you ask a physician, 285 00:09:58,679 --> 00:10:00,360 you know, what do you want to do 286 00:10:00,360 --> 00:10:03,080 with your historical data? The answer is always 287 00:10:03,080 --> 00:10:04,919 going to be, I want it all. And 288 00:10:04,919 --> 00:10:07,485 in pediatrics, depending on what state you're in, 289 00:10:07,644 --> 00:10:09,404 sometimes you have to keep 30 years' worth 290 00:10:09,404 --> 00:10:10,065 of data. 291 00:10:10,524 --> 00:10:12,125 And at the moment in time when we 292 00:10:12,125 --> 00:10:13,964 were thinking about this conversion and we had 293 00:10:13,964 --> 00:10:16,125 been on Cerner for 17 years, that was 294 00:10:16,125 --> 00:10:17,584 17 years of data 295 00:10:17,964 --> 00:10:19,964 that I had no clue on how to 296 00:10:19,964 --> 00:10:20,464 convert, 297 00:10:21,164 --> 00:10:23,539 where to put it, and how to make 298 00:10:23,559 --> 00:10:26,159 it accessible in the format that clinicians would 299 00:10:26,159 --> 00:10:28,240 want to consume it. Right? Because there's a 300 00:10:28,240 --> 00:10:30,179 big difference between here's your data 301 00:10:30,720 --> 00:10:32,480 versus here's your data, and you actually can 302 00:10:32,480 --> 00:10:34,720 do something with that data. So this is 303 00:10:34,720 --> 00:10:36,735 how we sort of started our journey in 304 00:10:36,735 --> 00:10:39,294 partnership with Elkay in terms of we have 305 00:10:39,294 --> 00:10:40,115 a data problem. 306 00:10:41,454 --> 00:10:43,855 Rather not move it all into Epic because 307 00:10:43,855 --> 00:10:45,315 that way, a really big database. 308 00:10:45,934 --> 00:10:48,514 And can you give us ideas and engineering 309 00:10:48,654 --> 00:10:51,269 skills to help us out of this particular 310 00:10:51,730 --> 00:10:53,090 problem? So it goes back to what I'm 311 00:10:53,090 --> 00:10:54,629 saying. We had a problem to solve. 312 00:10:55,250 --> 00:10:57,730 They're the data engineers. Well, that's what AJ 313 00:10:57,730 --> 00:10:58,789 told me at the time. 314 00:10:59,250 --> 00:11:01,250 And so we said, here's a problem for 315 00:11:01,250 --> 00:11:03,169 you to solve. But I'll let AJ tell 316 00:11:03,169 --> 00:11:04,309 the rest of that story. 317 00:11:04,745 --> 00:11:06,264 Yeah. I'll tell the rest of the story 318 00:11:06,264 --> 00:11:08,424 is really when I met Zafar first time, 319 00:11:08,424 --> 00:11:08,924 he 320 00:11:09,304 --> 00:11:11,225 he told me that, you know, you better 321 00:11:11,225 --> 00:11:12,125 do a good job. 322 00:11:12,504 --> 00:11:13,865 And I said, what if we do a 323 00:11:13,865 --> 00:11:15,304 good job? He said, I'll go to Becker's, 324 00:11:15,304 --> 00:11:16,825 and I'll tell them how good you guys 325 00:11:16,825 --> 00:11:17,325 are. 326 00:11:17,779 --> 00:11:19,139 And I said, what if we don't do 327 00:11:19,139 --> 00:11:20,340 a good job? He said, I'll go to 328 00:11:20,340 --> 00:11:21,860 Becker's, and I'll tell them how bad you 329 00:11:21,860 --> 00:11:22,360 are. 330 00:11:22,740 --> 00:11:25,220 So it all summarizes pretty well. But, you 331 00:11:25,220 --> 00:11:27,379 know, the opportunity came in, and I think 332 00:11:27,379 --> 00:11:30,340 we work very closely with the clinicians, with 333 00:11:30,340 --> 00:11:33,080 their even physicians, understanding their workflow. 334 00:11:33,824 --> 00:11:35,345 See, I think, you know, one is data 335 00:11:35,345 --> 00:11:37,044 and then understanding the data 336 00:11:37,584 --> 00:11:40,944 going towards enterprise data management, archiving piece into 337 00:11:40,944 --> 00:11:43,284 it is important what we are doing here. 338 00:11:43,985 --> 00:11:45,284 But more than that, 339 00:11:46,370 --> 00:11:48,769 if you look at it, a children's hospital, 340 00:11:48,769 --> 00:11:51,190 sometimes the workflow is different than an academic 341 00:11:51,330 --> 00:11:53,490 hospital, then it is different than an ID 342 00:11:53,490 --> 00:11:55,490 and big ID and hospital. So you've got 343 00:11:55,490 --> 00:11:57,570 to understand that. You've got to actually work 344 00:11:57,570 --> 00:11:58,230 with them. 345 00:11:58,824 --> 00:12:01,945 Because if you are archiving any existing data, 346 00:12:01,945 --> 00:12:04,824 if the usage is there or informatics for 347 00:12:04,824 --> 00:12:06,584 physicians to go back and look at some 348 00:12:06,584 --> 00:12:09,304 of the old legacy data, then actually you 349 00:12:09,304 --> 00:12:10,764 can see the real value 350 00:12:11,220 --> 00:12:12,199 of that solution. 351 00:12:12,659 --> 00:12:15,059 And I think Seattle Children also helped us 352 00:12:15,059 --> 00:12:17,959 giving feedback, which we incorporated in our solution 353 00:12:18,179 --> 00:12:20,179 to make it more stronger and go towards 354 00:12:20,179 --> 00:12:21,720 the direction where we are today. 355 00:12:22,100 --> 00:12:24,195 So I I also wanna say thank you 356 00:12:24,195 --> 00:12:26,754 to Seattle Children and doctor Zafar Chaudhry in 357 00:12:26,754 --> 00:12:28,914 partnering with us on this. Yeah. That that 358 00:12:28,995 --> 00:12:30,695 that's really fascinating that that collaboration, 359 00:12:31,154 --> 00:12:33,475 you took feedback from Seattle Children's too. Is 360 00:12:33,475 --> 00:12:35,815 that do you think that's essential for for 361 00:12:35,875 --> 00:12:37,975 a partner like yours to be open to 362 00:12:38,519 --> 00:12:41,340 adjusting and iterating based on your partner's feedback? 363 00:12:41,560 --> 00:12:44,440 I think feedback from any partner is extremely 364 00:12:44,440 --> 00:12:46,440 important because, you know, you also have to 365 00:12:46,440 --> 00:12:48,519 see from their side what are they trying 366 00:12:48,519 --> 00:12:49,580 to actually achieve. 367 00:12:50,040 --> 00:12:51,754 You have a solution which you want to 368 00:12:51,754 --> 00:12:53,355 actually take it to the places. And if 369 00:12:53,355 --> 00:12:55,615 you wanna make that differentiator in the market, 370 00:12:56,154 --> 00:12:58,875 that collaboration, listening to them, you know, we 371 00:12:58,875 --> 00:13:01,595 made numerous trips to Seattle Children just to 372 00:13:01,595 --> 00:13:03,754 sit in a room, understand, do a whiteboard 373 00:13:03,754 --> 00:13:06,154 session. What next can we actually do on 374 00:13:06,154 --> 00:13:07,429 that? In fact, 375 00:13:07,889 --> 00:13:11,009 even after our product was deployed, everything was 376 00:13:11,009 --> 00:13:12,850 live, we still went back and looked at 377 00:13:12,850 --> 00:13:14,450 it. What else can we do it? Because 378 00:13:14,450 --> 00:13:16,129 that's the only way you can make your 379 00:13:16,129 --> 00:13:17,269 product more richer. 380 00:13:17,809 --> 00:13:20,210 And, these are some complex things that we 381 00:13:20,210 --> 00:13:21,350 solve here at Elkay. 382 00:13:22,075 --> 00:13:22,575 Interoperability 383 00:13:22,955 --> 00:13:25,754 is out there and it's not everyone who 384 00:13:25,754 --> 00:13:27,695 can do it. You know, today, 385 00:13:28,554 --> 00:13:30,235 among all the things that we are doing 386 00:13:30,235 --> 00:13:33,195 now, even Commonwealth, we have the platform that 387 00:13:33,195 --> 00:13:34,654 is going to support Commonwealth. 388 00:13:35,179 --> 00:13:37,819 So we're we're really trying to solve real 389 00:13:37,819 --> 00:13:39,440 complex problems out there 390 00:13:39,980 --> 00:13:42,379 around interoperability. Yeah. Yeah. But I wanna move 391 00:13:42,379 --> 00:13:44,699 now to a a final question thinking here 392 00:13:44,699 --> 00:13:46,620 because we're talking about data and, of course, 393 00:13:46,620 --> 00:13:47,679 the rise of AI, 394 00:13:48,235 --> 00:13:50,315 and and machine learning and these various solutions 395 00:13:50,315 --> 00:13:53,035 that are coming coming to the fore. Data 396 00:13:53,035 --> 00:13:55,115 is just essential for the effectiveness of the 397 00:13:55,195 --> 00:13:56,975 of these programs and these this technology. 398 00:13:57,514 --> 00:13:58,955 I and so so my question then, what 399 00:13:58,955 --> 00:14:01,355 steps should organizations take to ensure their data 400 00:14:01,355 --> 00:14:02,575 is reliable, accurate, 401 00:14:02,940 --> 00:14:05,899 and ready for for these advanced technologies? Doctor 402 00:14:05,899 --> 00:14:07,660 Choudhary, do you wanna begin on this question? 403 00:14:07,660 --> 00:14:10,000 So you always have to start with governance. 404 00:14:10,700 --> 00:14:13,179 Right? Data governance is really important in this 405 00:14:13,179 --> 00:14:13,679 space, 406 00:14:14,059 --> 00:14:16,879 and many organizations don't focus enough time. 407 00:14:17,404 --> 00:14:19,644 And and data governance not just in the 408 00:14:19,644 --> 00:14:20,465 IT realm 409 00:14:20,845 --> 00:14:22,384 but with multidisciplinary 410 00:14:23,004 --> 00:14:24,065 teams. Right? 411 00:14:24,445 --> 00:14:26,605 I I can say data is correct and 412 00:14:26,605 --> 00:14:28,625 a physician might tell me that data's incorrect. 413 00:14:29,004 --> 00:14:30,929 So you need to include all of 414 00:14:31,250 --> 00:14:32,389 these stakeholders 415 00:14:32,850 --> 00:14:34,549 in your data governance group. 416 00:14:34,929 --> 00:14:36,690 The other thing to look at is, well, 417 00:14:36,690 --> 00:14:38,289 what is the quality of the data that 418 00:14:38,289 --> 00:14:39,269 you actually hold? 419 00:14:39,730 --> 00:14:42,049 Right? So we've talked about data warehouses in 420 00:14:42,049 --> 00:14:42,710 the past 421 00:14:43,089 --> 00:14:44,549 when it comes to analytics. 422 00:14:44,934 --> 00:14:48,215 Now there's data lakes and data oceans and 423 00:14:48,215 --> 00:14:49,754 probably now a data sea. 424 00:14:50,134 --> 00:14:51,575 And really what you're looking at when you 425 00:14:51,575 --> 00:14:53,115 talk about AI is 426 00:14:53,575 --> 00:14:56,615 what are you pointing that machine learning to, 427 00:14:56,615 --> 00:14:58,535 right? Are you pointing it to your data 428 00:14:58,535 --> 00:14:58,980 warehouse, 429 00:14:59,539 --> 00:15:01,720 which is probably a very small language model? 430 00:15:01,940 --> 00:15:03,699 Are you pointing it to a very large 431 00:15:03,699 --> 00:15:06,100 language model? Because in our case we have 432 00:15:06,100 --> 00:15:08,339 17 years' worth of Cerner data. That's a 433 00:15:08,339 --> 00:15:10,500 much bigger pool than just a year's worth 434 00:15:10,500 --> 00:15:11,159 of data. 435 00:15:11,585 --> 00:15:13,904 So you've got to validate the quality of 436 00:15:13,904 --> 00:15:15,205 the data that you have 437 00:15:15,745 --> 00:15:18,565 when you are trying to make clinical decisions. 438 00:15:19,264 --> 00:15:20,945 Once all that has been done by the 439 00:15:20,945 --> 00:15:23,524 IT team in collaboration with your clinicians, 440 00:15:24,149 --> 00:15:26,649 then you need a team of like minded 441 00:15:26,870 --> 00:15:29,429 clinical people who are now going to then 442 00:15:29,429 --> 00:15:29,929 test. 443 00:15:30,470 --> 00:15:32,070 Lots of testing has to happen. So when 444 00:15:32,070 --> 00:15:34,009 we did our archive project with Elkay, 445 00:15:35,029 --> 00:15:37,129 we ended up on version 14 446 00:15:38,524 --> 00:15:39,745 of what we actually 447 00:15:40,125 --> 00:15:40,625 launched. 448 00:15:41,245 --> 00:15:42,705 Took 14 iterations 449 00:15:43,085 --> 00:15:44,225 for us to test, 450 00:15:44,605 --> 00:15:45,105 review, 451 00:15:45,725 --> 00:15:47,504 satisfy a group of individuals, 452 00:15:48,285 --> 00:15:49,424 and it's all contextually 453 00:15:49,725 --> 00:15:52,065 mapped because that's the other important thing. Right? 454 00:15:52,379 --> 00:15:53,899 I don't want to be a physician that 455 00:15:53,899 --> 00:15:55,200 has data in system 456 00:15:55,660 --> 00:15:57,259 a, and then I go to system b, 457 00:15:57,259 --> 00:15:59,100 and then I have to find that data 458 00:15:59,100 --> 00:16:01,660 all over again. I want all those data 459 00:16:01,660 --> 00:16:03,600 points to be contextually linked 460 00:16:03,980 --> 00:16:05,440 so that at a click of a button, 461 00:16:05,795 --> 00:16:09,075 I can take action on data. Because when 462 00:16:09,075 --> 00:16:11,254 you think about the average outpatient visit, 463 00:16:12,195 --> 00:16:14,835 takes 8 minutes. In 8 minutes, you've got 464 00:16:14,835 --> 00:16:15,894 to talk to the patient, 465 00:16:16,274 --> 00:16:18,115 find all the data you need about that 466 00:16:18,115 --> 00:16:20,535 patient, then make an informed decision 467 00:16:20,929 --> 00:16:22,789 on what to do next with that patient. 468 00:16:22,850 --> 00:16:24,549 That is not a lot of time. 469 00:16:24,929 --> 00:16:26,309 So our job 470 00:16:26,850 --> 00:16:27,509 at MIND 471 00:16:27,970 --> 00:16:28,470 versus 472 00:16:29,009 --> 00:16:30,769 our partners is to make sure that that 473 00:16:30,769 --> 00:16:32,309 data is clean, available, 474 00:16:33,304 --> 00:16:34,284 valid, usable, 475 00:16:34,664 --> 00:16:36,584 at the right place, at the right time, 476 00:16:36,584 --> 00:16:38,504 at the point of care. Yeah. Thank you 477 00:16:38,504 --> 00:16:40,424 so much, doctor Chaudhry. Ajay, what would you 478 00:16:40,424 --> 00:16:42,264 add to to that? I think, you know, 479 00:16:42,264 --> 00:16:44,024 just to add to what doctor Zafar said. 480 00:16:44,024 --> 00:16:45,625 I mean, it it all comes down to 481 00:16:45,625 --> 00:16:47,699 the source of the data, quality of the 482 00:16:47,699 --> 00:16:49,799 data, and reliability of the data. 483 00:16:50,259 --> 00:16:52,659 If you have that good reliable data, that 484 00:16:52,659 --> 00:16:55,620 becomes like a fuel. Or any AI application 485 00:16:55,620 --> 00:16:58,179 or machine learning applications to really perform what 486 00:16:58,179 --> 00:16:59,399 they are supposed to. 487 00:17:00,485 --> 00:17:02,245 If at the start of the source of 488 00:17:02,245 --> 00:17:04,744 the data itself is not good enough, 489 00:17:05,045 --> 00:17:07,605 then you cannot actually get that end result 490 00:17:07,605 --> 00:17:08,585 with all these 491 00:17:08,884 --> 00:17:10,744 great tools which are available today. 492 00:17:11,605 --> 00:17:13,204 In order to get there, you need to 493 00:17:13,204 --> 00:17:14,664 have a very good interoperability 494 00:17:15,480 --> 00:17:17,640 platform. You need to actually make sure the 495 00:17:17,640 --> 00:17:19,799 validation of the product or validation of the 496 00:17:19,799 --> 00:17:21,099 data is done correctly. 497 00:17:21,799 --> 00:17:24,679 An organization need to put some focus on 498 00:17:24,679 --> 00:17:27,240 it, put some area of expertise in it, 499 00:17:27,240 --> 00:17:29,559 also partner with the right people there who 500 00:17:29,559 --> 00:17:30,940 can help you get there. 501 00:17:31,294 --> 00:17:33,875 Because all these big investment that you're doing, 502 00:17:34,095 --> 00:17:34,595 if 503 00:17:35,214 --> 00:17:37,134 the reliability of the data is not there, 504 00:17:37,134 --> 00:17:38,275 you'll end up actually 505 00:17:38,654 --> 00:17:40,654 getting not the result that you're looking for 506 00:17:40,654 --> 00:17:43,214 in long term. Yeah. It's crucial that that 507 00:17:43,214 --> 00:17:45,375 you have it. Yeah. It's the Absolutely. Excellent. 508 00:17:45,375 --> 00:17:45,809 Well, 509 00:17:46,210 --> 00:17:47,650 this really was a pleasure to to walk 510 00:17:47,650 --> 00:17:49,410 through this conversation with both of you, Ajay, 511 00:17:49,410 --> 00:17:51,650 and and doctor Chaudhry. Truly appreciate you taking 512 00:17:51,650 --> 00:17:52,309 the time. 513 00:17:52,769 --> 00:17:54,930 I also, of course, wanna thank LK for 514 00:17:54,930 --> 00:17:56,390 sponsoring today's conversation. 515 00:17:56,930 --> 00:17:58,930 To our listeners, thank you for joining us, 516 00:17:58,930 --> 00:18:00,450 and please be sure to check out other 517 00:18:00,450 --> 00:18:02,875 Becker's podcasts. Have a wonderful rest of your 518 00:18:02,875 --> 00:18:04,394 day. And gentlemen, I hope you enjoy the 519 00:18:04,394 --> 00:18:06,815 conference. Thank you so much. Thank you.