1 00:00:00,240 --> 00:00:02,580 Imagine this. You're in the heart of Chicago 2 00:00:02,639 --> 00:00:05,059 mingling with the brightest minds in health IT. 3 00:00:05,279 --> 00:00:07,839 You've arrived at the 9th annual Health IT 4 00:00:07,839 --> 00:00:11,439 plus Digital Health Plus RCM conference taking place 5 00:00:11,439 --> 00:00:14,424 October 1st through 4th at the luxurious Hyatt 6 00:00:14,424 --> 00:00:15,484 Regency Chicago. 7 00:00:15,945 --> 00:00:18,664 Picture the excitement as you collect countless business 8 00:00:18,664 --> 00:00:22,425 cards, forging invaluable connections with over 25 100 9 00:00:22,425 --> 00:00:23,884 executive level attendees. 10 00:00:24,425 --> 00:00:26,585 Feel the buzz of ideas flowing as you 11 00:00:26,585 --> 00:00:29,460 engage in meaningful conversations about the future of 12 00:00:29,460 --> 00:00:30,440 healthcare technology. 13 00:00:30,980 --> 00:00:34,200 Envision yourself attending sessions led by over 415 14 00:00:35,140 --> 00:00:36,039 elite speakers, 15 00:00:36,420 --> 00:00:39,000 gaining insights that could transform your organization. 16 00:00:39,539 --> 00:00:43,015 From digital transformation and telehealth to clinician burnout 17 00:00:43,015 --> 00:00:43,755 and cybersecurity, 18 00:00:44,615 --> 00:00:47,174 each topic is designed to spark new ideas 19 00:00:47,174 --> 00:00:49,895 and provide actionable takeaways, but it doesn't stop 20 00:00:49,895 --> 00:00:53,015 there. Imagine sitting in a packed auditorium listening 21 00:00:53,015 --> 00:00:55,210 to motivating keynotes from some of the biggest 22 00:00:55,210 --> 00:00:58,189 names in sports. Four time Super Bowl champion, 23 00:00:58,250 --> 00:00:58,990 Rob Gronkowski, 24 00:00:59,689 --> 00:01:00,189 WNBA 25 00:01:00,570 --> 00:01:02,509 champion, and author, Lisa Leslie, 26 00:01:02,890 --> 00:01:04,829 and NFL legend and ESPN 27 00:01:05,209 --> 00:01:05,709 analyst, 28 00:01:06,010 --> 00:01:08,564 Eli Manning, will be there sharing their stories 29 00:01:08,564 --> 00:01:11,525 and inspiring you to reach new heights. All 30 00:01:11,525 --> 00:01:14,244 around you, the future of health IT unfolds, 31 00:01:14,244 --> 00:01:15,784 and you're not just a spectator. 32 00:01:16,165 --> 00:01:17,784 You're an active participant. 33 00:01:18,244 --> 00:01:20,484 Don't wait. You can find the event website 34 00:01:20,484 --> 00:01:22,905 and get registered by visiting peckershospital 35 00:01:23,420 --> 00:01:26,006 review.com and clicking on the events page. That's 36 00:01:26,006 --> 00:01:27,039 the beckershospitalreview.com events page. 37 00:01:27,579 --> 00:01:28,640 This is Laura Dierda 38 00:01:29,659 --> 00:01:31,359 with the Becker's Healthcare 39 00:01:31,899 --> 00:01:33,819 podcast. I'm thrilled today to be joined by 40 00:01:33,819 --> 00:01:34,399 Steve Bethke, 41 00:01:35,179 --> 00:01:36,399 vice president of solutions develop 42 00:01:39,254 --> 00:01:41,814 a market at Mayo Clinic Platform. Steve, it's 43 00:01:41,814 --> 00:01:43,254 a pleasure to have you on the podcast 44 00:01:43,254 --> 00:01:43,754 today. 45 00:01:44,134 --> 00:01:45,515 Great to be here. Thanks. 46 00:01:45,894 --> 00:01:47,894 Now I'm really looking forward to our discussion 47 00:01:47,894 --> 00:01:50,134 because I know Mayo Clinic Platform just is 48 00:01:50,134 --> 00:01:51,894 on the forefront of so much of what's 49 00:01:51,894 --> 00:01:53,770 happening in the digital health space. 50 00:01:54,310 --> 00:01:56,790 Certainly got a lot happening with data and 51 00:01:56,790 --> 00:02:00,469 artificial intelligence and really working towards making health 52 00:02:00,469 --> 00:02:03,750 care more accessible and, more precise for patients. 53 00:02:03,750 --> 00:02:06,069 But before we dive into our discussion, can 54 00:02:06,069 --> 00:02:07,350 you tell me a little bit more about 55 00:02:07,350 --> 00:02:08,490 yourself and your background? 56 00:02:09,544 --> 00:02:10,284 Yeah. Absolutely. 57 00:02:11,224 --> 00:02:13,784 Early in my career, I spent time in 58 00:02:13,784 --> 00:02:16,205 technology companies, got an MBA, 59 00:02:16,585 --> 00:02:17,944 and then really picked up my head and 60 00:02:17,944 --> 00:02:19,544 said, okay. What I wanna do with my 61 00:02:19,544 --> 00:02:22,104 life and decided health care? So I spent 62 00:02:22,104 --> 00:02:22,664 my career 63 00:02:23,520 --> 00:02:24,979 most of my career in healthcare, 64 00:02:26,080 --> 00:02:29,919 really interesting problems to solve, interesting market and 65 00:02:29,919 --> 00:02:30,819 great and good. 66 00:02:31,439 --> 00:02:33,680 We spend a lot of time doing the 67 00:02:33,680 --> 00:02:34,740 things we do, 68 00:02:35,199 --> 00:02:37,300 so I'm really excited to be in healthcare 69 00:02:37,439 --> 00:02:38,824 where it matters. 70 00:02:39,604 --> 00:02:41,844 I spent some time at the enterprise as 71 00:02:41,844 --> 00:02:42,344 executive 72 00:02:42,724 --> 00:02:45,465 at GE and Optum, but really 73 00:02:45,844 --> 00:02:48,405 the last decade as an operator in private 74 00:02:48,405 --> 00:02:51,090 equity or venture capital backed growth stage companies. 75 00:02:51,469 --> 00:02:53,870 And I joined Mayo Clinic Platform about 3 76 00:02:53,870 --> 00:02:54,610 years ago 77 00:02:54,909 --> 00:02:57,090 and run the solution developer market. 78 00:02:58,349 --> 00:02:59,949 Well, that's great to hear. And, you know, 79 00:02:59,949 --> 00:03:01,949 really, it sounds like a fascinating position to 80 00:03:01,949 --> 00:03:03,969 be in. Based on your role, 81 00:03:04,715 --> 00:03:06,474 at Mayo Clinic Platform, what are some of 82 00:03:06,474 --> 00:03:08,395 the opportunities and headwinds that you have your 83 00:03:08,395 --> 00:03:09,455 eye on right now? 84 00:03:10,235 --> 00:03:11,215 It's a great question. 85 00:03:11,675 --> 00:03:13,375 At the broadest level, 86 00:03:14,074 --> 00:03:17,275 there's really an opportunity to leverage platform thinking 87 00:03:17,275 --> 00:03:20,610 and business models to drive innovation and support 88 00:03:20,610 --> 00:03:21,669 health care providers. 89 00:03:22,530 --> 00:03:25,169 So we've all seen how platforms have really 90 00:03:25,169 --> 00:03:27,729 been changing the world around us. So how 91 00:03:27,729 --> 00:03:28,949 can Mayo Clinic 92 00:03:29,409 --> 00:03:32,069 leverage platform thinking and business models 93 00:03:32,514 --> 00:03:33,814 to improve healthcare, 94 00:03:34,275 --> 00:03:35,175 to drive innovation, 95 00:03:35,875 --> 00:03:38,194 support and enhance the workflow of care teams 96 00:03:38,194 --> 00:03:40,215 and to extend the world class care 97 00:03:40,514 --> 00:03:43,634 that's already provided by Mayo Clinic to patients 98 00:03:43,634 --> 00:03:44,614 around the world. 99 00:03:45,074 --> 00:03:47,254 So that's at a high level. Now 100 00:03:48,270 --> 00:03:49,569 focusing in a bit, 101 00:03:50,430 --> 00:03:52,349 what does that mean? And so really there's 102 00:03:52,349 --> 00:03:54,449 a terrific opportunity to unlock 103 00:03:54,909 --> 00:03:57,810 and expedite innovation for solution developers 104 00:03:58,430 --> 00:04:00,770 so they can drive value and empower 105 00:04:01,229 --> 00:04:02,209 healthcare providers. 106 00:04:03,094 --> 00:04:05,254 So let me sort of step back for 107 00:04:05,254 --> 00:04:07,435 a second. What is a solution developer? 108 00:04:07,895 --> 00:04:09,115 So this could be 109 00:04:09,495 --> 00:04:11,034 a digital health company, 110 00:04:11,655 --> 00:04:12,955 a device company, 111 00:04:13,334 --> 00:04:16,714 a pharma company, really it's anyone building AI 112 00:04:16,855 --> 00:04:18,634 or data centric solutions. 113 00:04:19,919 --> 00:04:21,279 And and maybe I'll take you through an 114 00:04:21,279 --> 00:04:24,419 example of some of the challenges that solution 115 00:04:25,039 --> 00:04:26,500 developers really have. 116 00:04:27,120 --> 00:04:28,879 And and so let's say I'm a solution 117 00:04:28,879 --> 00:04:30,479 developer and I have a really good idea 118 00:04:30,479 --> 00:04:31,939 to support health care providers. 119 00:04:32,294 --> 00:04:33,995 Hey. I wanna teach a computer 120 00:04:34,375 --> 00:04:35,675 how to read an EKG 121 00:04:36,214 --> 00:04:38,954 to recognize low ejection fraction, or 122 00:04:39,414 --> 00:04:41,975 I wanna be able to predict risk of 123 00:04:41,975 --> 00:04:44,475 readmission or risk of colon cancer. 124 00:04:45,169 --> 00:04:46,850 What do I need to do to accomplish 125 00:04:46,850 --> 00:04:49,649 this? So there's a lot of challenges ahead 126 00:04:49,649 --> 00:04:50,389 for me. 127 00:04:50,850 --> 00:04:51,829 The first is 128 00:04:52,529 --> 00:04:54,870 I need data. I need high quality, 129 00:04:55,410 --> 00:04:55,910 comprehensive, 130 00:04:56,529 --> 00:04:57,029 representative 131 00:04:57,410 --> 00:04:59,110 data that's de identified 132 00:04:59,714 --> 00:05:01,735 and can be used to build a solution. 133 00:05:02,115 --> 00:05:04,915 I need compute data science tools in an 134 00:05:04,915 --> 00:05:07,654 environment to do the discovery and development. 135 00:05:08,355 --> 00:05:10,694 And then once I go through all that, 136 00:05:11,795 --> 00:05:14,274 and I built the model, then I need 137 00:05:14,274 --> 00:05:16,350 to validate it. How does it perform? 138 00:05:17,129 --> 00:05:17,629 Sensitivity, 139 00:05:18,009 --> 00:05:18,509 specificity, 140 00:05:18,970 --> 00:05:21,389 bias, and then you see, etcetera. 141 00:05:22,650 --> 00:05:24,449 And and once I've done that, I've taken 142 00:05:24,449 --> 00:05:26,490 a done a ton of work and taken 143 00:05:26,490 --> 00:05:29,144 a huge step forward, but, really, I've just 144 00:05:29,144 --> 00:05:29,644 begun 145 00:05:30,105 --> 00:05:32,504 because now I have to deploy my solution 146 00:05:32,504 --> 00:05:33,245 into workflow, 147 00:05:33,545 --> 00:05:36,105 which we all know is very challenging. And 148 00:05:36,105 --> 00:05:38,425 and I'm not even done yet because now 149 00:05:38,425 --> 00:05:40,444 I have to commercialize and drive adoption. 150 00:05:40,824 --> 00:05:43,819 Right? And obviously, these things are are challenging 151 00:05:44,839 --> 00:05:45,899 and it creates 152 00:05:46,919 --> 00:05:47,419 significant 153 00:05:48,279 --> 00:05:50,459 challenges for the solution developer 154 00:05:50,839 --> 00:05:53,319 moving forward. And so these are really the 155 00:05:53,319 --> 00:05:53,819 challenges 156 00:05:54,759 --> 00:05:56,300 we set out to solve. 157 00:05:56,735 --> 00:05:57,875 A little more detail, 158 00:05:58,654 --> 00:06:01,935 we have 2 programs, Mayo Clinic Platform has 159 00:06:01,935 --> 00:06:02,754 2 programs 160 00:06:03,375 --> 00:06:05,855 that allows us to meet solution developers where 161 00:06:05,855 --> 00:06:07,774 they are in their lifecycle. So first is 162 00:06:07,774 --> 00:06:08,274 Accelerate. 163 00:06:09,479 --> 00:06:12,199 Help tech start ups are really key to 164 00:06:12,199 --> 00:06:15,560 sparking innovation, so we've designed the Accelerate program 165 00:06:15,560 --> 00:06:19,019 to help early stage companies advance their solution 166 00:06:19,319 --> 00:06:21,399 and get ready to go to market. And 167 00:06:21,399 --> 00:06:24,595 then we have Solution Studio Program, which provides 168 00:06:24,654 --> 00:06:27,555 capabilities for the challenges I listed before, 169 00:06:28,095 --> 00:06:31,794 data, tools for development, validation, deployment and adoption. 170 00:06:33,214 --> 00:06:35,714 And these are really for more mature companies, 171 00:06:35,935 --> 00:06:36,435 either 172 00:06:36,910 --> 00:06:38,850 ready to go to market or 173 00:06:39,230 --> 00:06:41,089 possibly already in the market. 174 00:06:42,270 --> 00:06:44,830 So appreciate the time. These are really the 175 00:06:44,830 --> 00:06:47,790 2 programs that we can solve for reuse 176 00:06:47,790 --> 00:06:49,410 to solve for many of the challenges 177 00:06:49,790 --> 00:06:51,465 faced by solution developers 178 00:06:52,324 --> 00:06:54,345 and and are used to unlock 179 00:06:54,725 --> 00:06:55,545 and expedite 180 00:06:55,925 --> 00:06:56,425 innovation. 181 00:06:57,925 --> 00:06:59,764 That's fantastic to hear. And, you know, I 182 00:06:59,764 --> 00:07:02,745 can imagine that many of our listeners appreciate 183 00:07:03,389 --> 00:07:05,149 how much of a challenge it is to 184 00:07:05,149 --> 00:07:05,649 really 185 00:07:05,949 --> 00:07:08,189 stand up programs like that, have the high 186 00:07:08,189 --> 00:07:10,209 quality data that you were talking about, 187 00:07:10,830 --> 00:07:13,089 and really build into the workflows, 188 00:07:14,110 --> 00:07:16,850 everything that needs to be there to successfully, 189 00:07:18,095 --> 00:07:20,915 commercialize the company and then drive the adoption 190 00:07:20,975 --> 00:07:23,294 across the system wide. And, you know, I 191 00:07:23,294 --> 00:07:24,675 can imagine the technology 192 00:07:24,975 --> 00:07:27,555 piece of it is, one challenge, but then, 193 00:07:27,935 --> 00:07:30,110 the people piece of it is another. When 194 00:07:30,110 --> 00:07:31,710 you look at some of the different ways 195 00:07:31,710 --> 00:07:33,330 that you've been able to, 196 00:07:33,710 --> 00:07:36,370 you know, really tackle the challenges, whether it's 197 00:07:36,589 --> 00:07:39,470 on the data side or, you know, really 198 00:07:39,470 --> 00:07:42,270 getting people into that space where, you know, 199 00:07:42,270 --> 00:07:45,764 they're adopting the new technologies or or new 200 00:07:46,245 --> 00:07:46,745 functions, 201 00:07:47,125 --> 00:07:49,205 that need to occur in order to make 202 00:07:49,205 --> 00:07:51,685 sure that your projects are successful. How do 203 00:07:51,685 --> 00:07:53,285 you do that and and really have that 204 00:07:53,285 --> 00:07:54,264 culture of innovation 205 00:07:54,805 --> 00:07:56,905 across the board with Mayo Clinic Platform? 206 00:07:58,259 --> 00:07:59,220 Yeah. That's great. 207 00:07:59,779 --> 00:08:02,500 We we work with and so Mayo Clinic 208 00:08:02,500 --> 00:08:03,720 Platform connects 209 00:08:04,259 --> 00:08:05,879 then the solution developers 210 00:08:06,660 --> 00:08:08,279 to the health care providers. 211 00:08:08,660 --> 00:08:09,879 And we really provide 212 00:08:10,419 --> 00:08:12,500 value in a number of ways. 1, as 213 00:08:12,500 --> 00:08:15,264 we just talked about, the technology, the data, 214 00:08:16,524 --> 00:08:19,645 and capabilities that the solution developer needs, but 215 00:08:19,645 --> 00:08:21,964 then we make the connection to the healthcare 216 00:08:21,964 --> 00:08:22,464 provider. 217 00:08:23,404 --> 00:08:24,225 And so 218 00:08:24,845 --> 00:08:27,040 what we will do is actually go through 219 00:08:27,040 --> 00:08:27,779 a qualification 220 00:08:28,240 --> 00:08:28,740 process 221 00:08:29,360 --> 00:08:32,160 with the solution developer. And you can really 222 00:08:32,160 --> 00:08:33,620 think about this as 223 00:08:34,160 --> 00:08:34,660 transparency, 224 00:08:35,279 --> 00:08:36,179 providing transparency 225 00:08:36,480 --> 00:08:37,920 to the health care provider. And we can 226 00:08:37,920 --> 00:08:40,340 talk more about what this is. 227 00:08:40,799 --> 00:08:43,245 But you can think about it as a 228 00:08:43,245 --> 00:08:44,304 nutrition label 229 00:08:44,605 --> 00:08:47,585 that provides this transparency to the healthcare providers. 230 00:08:48,205 --> 00:08:51,345 And then we also have deploy capabilities 231 00:08:52,365 --> 00:08:54,365 and we mentioned that before. But it's a 232 00:08:54,365 --> 00:08:54,865 common 233 00:08:55,169 --> 00:08:57,409 technology. You can think about it as sort 234 00:08:57,409 --> 00:08:58,070 of endpoint 235 00:08:58,529 --> 00:09:01,409 last mile connectivity into the EMR for those 236 00:09:01,409 --> 00:09:01,909 workloads. 237 00:09:03,250 --> 00:09:03,990 So once 238 00:09:05,330 --> 00:09:08,389 a solution developer is on the Solution Studio 239 00:09:08,529 --> 00:09:09,029 program, 240 00:09:09,745 --> 00:09:12,725 They have the deploy capabilities, which is common 241 00:09:13,024 --> 00:09:13,524 technology 242 00:09:13,985 --> 00:09:14,485 infrastructure 243 00:09:14,945 --> 00:09:16,165 and they have qualification, 244 00:09:16,785 --> 00:09:19,845 which is provides transparency to healthcare providers. 245 00:09:20,785 --> 00:09:23,504 And these things are really important then to 246 00:09:23,504 --> 00:09:24,830 drive adoption determinations? 247 00:09:32,970 --> 00:09:33,790 What is the 248 00:09:37,555 --> 00:09:38,134 the determinations? 249 00:09:38,754 --> 00:09:41,095 What is the performance of the solution? 250 00:09:41,435 --> 00:09:41,935 And 251 00:09:42,274 --> 00:09:43,415 then I can also 252 00:09:45,075 --> 00:09:47,254 connect in with common infrastructure 253 00:09:47,555 --> 00:09:50,615 of Deploy. So these are two really valuable 254 00:09:50,754 --> 00:09:51,254 capabilities 255 00:09:51,715 --> 00:09:52,215 that 256 00:09:52,779 --> 00:09:53,600 we provide 257 00:09:53,980 --> 00:09:56,799 to solution developers that then drive adoption 258 00:09:57,419 --> 00:09:58,720 or ease adoption 259 00:09:59,019 --> 00:10:00,000 into the health 260 00:10:00,460 --> 00:10:02,320 health care provider side of the market. 261 00:10:03,500 --> 00:10:05,259 That's fascinating to hear. And thank you so 262 00:10:05,259 --> 00:10:07,585 much for digging one bit deeper. Now I'm 263 00:10:07,585 --> 00:10:09,424 wondering, how are you thinking about growth and 264 00:10:09,424 --> 00:10:11,904 adding value to the organization all overall? Where 265 00:10:11,904 --> 00:10:13,205 do you see things headed? 266 00:10:14,304 --> 00:10:15,904 Yeah. This is great. So you can think 267 00:10:15,904 --> 00:10:18,225 about Mayo Clinic platform as a 3 sided 268 00:10:18,225 --> 00:10:20,789 marketplace, and I mentioned some of the sides 269 00:10:20,870 --> 00:10:24,549 already solution developer and healthcare provider, but at 270 00:10:24,549 --> 00:10:26,089 the base is data. 271 00:10:26,709 --> 00:10:29,289 So we've created Mayo Clinic Platform Connect, 272 00:10:29,750 --> 00:10:32,309 which is a federated network of the world's 273 00:10:32,309 --> 00:10:36,095 leading medical centers enabling access to globally diverse 274 00:10:36,394 --> 00:10:39,434 eIdentified data. So this is very real. We've 275 00:10:39,434 --> 00:10:40,254 signed partnerships 276 00:10:40,634 --> 00:10:41,615 and are implementing 277 00:10:42,235 --> 00:10:45,134 with 8 of the world's leading health systems 278 00:10:45,195 --> 00:10:46,495 across 3 continents. 279 00:10:47,669 --> 00:10:48,970 We have Mercyhealth 280 00:10:49,350 --> 00:10:51,129 in UC Davis in 281 00:10:51,509 --> 00:10:52,090 the US, 282 00:10:52,629 --> 00:10:53,529 Albert Einstein 283 00:10:53,909 --> 00:10:56,809 in Brazil, University Health Network in Canada, 284 00:10:57,269 --> 00:10:59,909 Chiba Medical Center in Israel, Singh Health in 285 00:10:59,909 --> 00:11:03,134 Singapore, and Seoul National University in Seoul. 286 00:11:04,095 --> 00:11:07,054 So that is the base, you know, one 287 00:11:07,054 --> 00:11:07,554 side 288 00:11:08,095 --> 00:11:10,995 that provides data and that's again hugely important. 289 00:11:11,615 --> 00:11:13,294 The other two sides and we've talked a 290 00:11:13,294 --> 00:11:15,235 little bit about this is the connection 291 00:11:15,615 --> 00:11:17,774 between the solution developers on one side and 292 00:11:17,774 --> 00:11:19,669 the health care providers on the other. 293 00:11:20,049 --> 00:11:23,970 Obviously, healthcare providers are well healthcare providers and 294 00:11:23,970 --> 00:11:26,389 again solution developers are on the other side 295 00:11:26,929 --> 00:11:30,850 are digital health companies, device companies, pharma, anyone 296 00:11:30,850 --> 00:11:33,029 building AI or data centric solutions. 297 00:11:34,434 --> 00:11:36,455 And really, Mayo Clinic platform 298 00:11:37,554 --> 00:11:40,134 continues to grow each side of this marketplace, 299 00:11:40,914 --> 00:11:44,534 connect partners and data, solution developers building innovative 300 00:11:44,674 --> 00:11:45,174 solutions 301 00:11:45,554 --> 00:11:48,720 and health care providers leveraging those solutions. And 302 00:11:48,720 --> 00:11:50,899 then you really see the flywheel 303 00:11:51,360 --> 00:11:52,340 network effect 304 00:11:52,799 --> 00:11:54,340 start to come into play. 305 00:11:55,040 --> 00:11:57,700 Access to broad data drives innovation 306 00:11:58,080 --> 00:12:01,139 with solution developers, which drives value 307 00:12:02,654 --> 00:12:04,274 the health care provider side. 308 00:12:05,215 --> 00:12:06,894 That's great to hear. And, you know, that 309 00:12:06,894 --> 00:12:08,975 firewall can be so important and valuable once 310 00:12:08,975 --> 00:12:11,455 you have it going. But for organizations that 311 00:12:11,455 --> 00:12:13,634 are still at the early stages of developing 312 00:12:13,695 --> 00:12:15,629 a platform like this or or trying to 313 00:12:15,629 --> 00:12:16,529 get their organizations 314 00:12:17,070 --> 00:12:17,570 to, 315 00:12:18,909 --> 00:12:21,250 turn that corner to have that data to 316 00:12:21,309 --> 00:12:22,690 provide access overall, 317 00:12:23,149 --> 00:12:24,589 what's kind of the first step? What do 318 00:12:24,589 --> 00:12:26,450 you need to do, initially 319 00:12:26,990 --> 00:12:29,169 in order to make sure you've got 320 00:12:29,514 --> 00:12:31,595 that data, you've got the right investments in 321 00:12:31,595 --> 00:12:34,634 place to achieve that data and then move 322 00:12:34,634 --> 00:12:35,615 forward from there. 323 00:12:36,634 --> 00:12:38,954 Perfect. Yeah. This is this is really the 324 00:12:38,954 --> 00:12:39,454 generation 325 00:12:39,914 --> 00:12:42,574 of the 2 programs Mayo Clinic Platform, 326 00:12:43,970 --> 00:12:44,949 has created, 327 00:12:45,329 --> 00:12:48,049 right? So we're doing the hard work Mayo 328 00:12:48,049 --> 00:12:50,069 Clinic Platform is doing the hard work 329 00:12:50,610 --> 00:12:52,949 of creating that 3 sided 330 00:12:54,289 --> 00:12:56,949 marketplace. So we're going off and creating 331 00:12:57,490 --> 00:13:00,745 this data asset and the tools and technologies 332 00:13:01,125 --> 00:13:04,024 that solution developers and health care providers need 333 00:13:04,485 --> 00:13:06,024 to create and adopt 334 00:13:06,884 --> 00:13:10,665 innovative solutions. So as a solution developer, 335 00:13:11,509 --> 00:13:14,070 I now have access to 2 programs. If 336 00:13:14,070 --> 00:13:16,789 I'm an early stage solution developer and I 337 00:13:16,789 --> 00:13:18,089 really have a good idea, 338 00:13:18,470 --> 00:13:19,289 maybe I've 339 00:13:20,950 --> 00:13:22,330 had some initial 340 00:13:23,190 --> 00:13:25,049 funding, seed, etcetera, 341 00:13:25,524 --> 00:13:28,084 but I'm really early stage, then I can 342 00:13:28,084 --> 00:13:30,424 get access to Mayo Clinic Platform Accelerate. 343 00:13:30,884 --> 00:13:31,784 And that's fundamentally 344 00:13:32,325 --> 00:13:33,384 access to 345 00:13:34,164 --> 00:13:35,144 our product, 346 00:13:35,524 --> 00:13:39,144 Mayo Clinic Platform Discover that allows access to 347 00:13:39,205 --> 00:13:41,740 the compute and data that we talked about. 348 00:13:41,740 --> 00:13:45,339 So these companies can get on early stage 349 00:13:45,339 --> 00:13:47,500 companies can get on, get access to that 350 00:13:47,500 --> 00:13:50,240 data and start creating their MVP. 351 00:13:50,620 --> 00:13:53,200 We also support them with technical, clinical 352 00:13:54,804 --> 00:13:56,584 and administrative resources to 353 00:13:56,884 --> 00:13:59,304 help them think through the problem. So that's 354 00:13:59,684 --> 00:14:01,625 Accelerate and where they can start. 355 00:14:02,245 --> 00:14:04,424 If the solution developer is more mature, hey, 356 00:14:04,424 --> 00:14:04,504 I have a product, I have a solution, 357 00:14:04,504 --> 00:14:05,705 I understand what I want to do, then 358 00:14:20,264 --> 00:14:22,904 you know, those important capabilities and then access 359 00:14:22,904 --> 00:14:23,965 the healthcare provider. 360 00:14:24,345 --> 00:14:26,845 So we've really tried to create programs 361 00:14:27,625 --> 00:14:30,345 inside of Mayo Clinic platform that will meet 362 00:14:30,345 --> 00:14:31,644 the solution developers 363 00:14:32,504 --> 00:14:34,125 where they are in their lifecycle. 364 00:14:35,620 --> 00:14:37,779 That's, you know, really cool to hear and 365 00:14:37,779 --> 00:14:40,019 and definitely seems like a great opportunity to 366 00:14:40,019 --> 00:14:41,459 take advantage of some of the work, like 367 00:14:41,459 --> 00:14:43,459 you mentioned, that Mayo Clinic platform has done 368 00:14:43,459 --> 00:14:46,600 and really incorporate that into something meaningful for 369 00:14:46,820 --> 00:14:49,240 health systems across the country and worldwide. 370 00:14:49,940 --> 00:14:52,304 Now I'm wondering, you know, we talked a 371 00:14:52,304 --> 00:14:53,745 little bit about some of the different things 372 00:14:53,745 --> 00:14:55,904 that are important. Is there any other risks 373 00:14:55,904 --> 00:14:57,904 or investments that you see worth making this 374 00:14:57,904 --> 00:14:59,745 year, especially knowing that for a lot of 375 00:14:59,745 --> 00:15:01,664 hospitals and health systems, they still have tight 376 00:15:01,664 --> 00:15:02,164 margins, 377 00:15:02,465 --> 00:15:05,159 budgets are still, you know, somewhat challenging. So 378 00:15:05,159 --> 00:15:07,019 if they're limited in some of their options, 379 00:15:07,399 --> 00:15:09,320 what do you think is still something that 380 00:15:09,320 --> 00:15:10,759 they need to do or risk they need 381 00:15:10,759 --> 00:15:12,440 to take in order to, 382 00:15:12,840 --> 00:15:15,100 set themselves up for success going forward? 383 00:15:16,360 --> 00:15:18,884 Yeah. And so one one risk or challenge 384 00:15:18,884 --> 00:15:21,304 for them for health care providers is understanding 385 00:15:21,445 --> 00:15:22,424 all the solutions 386 00:15:22,884 --> 00:15:23,384 available 387 00:15:23,684 --> 00:15:24,345 to them. 388 00:15:24,725 --> 00:15:26,184 There there is a cacophony 389 00:15:27,365 --> 00:15:29,764 of solutions and they're bombarded. And as you 390 00:15:29,764 --> 00:15:30,264 said, 391 00:15:30,659 --> 00:15:32,980 they're under a great deal of pressure around 392 00:15:32,980 --> 00:15:33,480 margin, 393 00:15:34,019 --> 00:15:35,700 and they want to provide the best care 394 00:15:35,700 --> 00:15:37,480 they can for their patients. So 395 00:15:37,860 --> 00:15:39,399 how does the health care provider 396 00:15:40,259 --> 00:15:40,759 understand 397 00:15:41,700 --> 00:15:44,579 what these solutions are? Hey, AI is this 398 00:15:44,579 --> 00:15:45,079 incredible 399 00:15:45,504 --> 00:15:48,164 thing that's coming that can support healthcare providers, 400 00:15:49,184 --> 00:15:52,384 enable care teams, etcetera. But as a healthcare 401 00:15:52,384 --> 00:15:52,884 provider, 402 00:15:53,345 --> 00:15:55,524 I'm working on my day to day 403 00:15:56,225 --> 00:15:57,764 and I'm really 404 00:15:58,210 --> 00:15:58,710 battling, 405 00:15:59,730 --> 00:16:00,789 how do I understand 406 00:16:02,370 --> 00:16:04,850 what's real, what's not, what's going to provide 407 00:16:04,850 --> 00:16:07,830 value. And that's and to solve that problem, 408 00:16:08,289 --> 00:16:09,029 that's where, 409 00:16:10,129 --> 00:16:12,004 Mayo Clinic Platform really comes 410 00:16:12,705 --> 00:16:15,764 in inside the solution studio program includes 411 00:16:16,625 --> 00:16:17,285 a qualification 412 00:16:17,904 --> 00:16:18,965 process. So 413 00:16:19,345 --> 00:16:20,565 as we go through, 414 00:16:21,024 --> 00:16:21,764 we evaluate 415 00:16:22,144 --> 00:16:24,245 these solutions so we can provide transparency 416 00:16:24,705 --> 00:16:25,684 to end users. 417 00:16:26,250 --> 00:16:27,769 Again, you can think about this as a 418 00:16:27,769 --> 00:16:28,830 nutrition label 419 00:16:29,210 --> 00:16:31,370 so that the end users then can make 420 00:16:31,370 --> 00:16:32,590 informed decisions. 421 00:16:33,370 --> 00:16:34,029 The qualification 422 00:16:34,410 --> 00:16:34,910 process 423 00:16:35,290 --> 00:16:38,730 includes evaluation from teams of physicians, data scientists 424 00:16:38,730 --> 00:16:39,914 and AI experts. 425 00:16:40,475 --> 00:16:42,254 They look at a number of the criteria, 426 00:16:42,475 --> 00:16:43,615 for example, how 427 00:16:44,235 --> 00:16:47,355 does this solution perform mathematically, what's the evidence 428 00:16:47,355 --> 00:16:48,014 of claims, 429 00:16:48,394 --> 00:16:48,894 etcetera. 430 00:16:49,355 --> 00:16:50,014 And so 431 00:16:50,315 --> 00:16:53,579 given more information and transparency, health care providers 432 00:16:53,639 --> 00:16:55,659 can then make informed decisions, 433 00:16:57,799 --> 00:16:59,820 and adding this layer of transparency 434 00:17:00,200 --> 00:17:01,740 reduces the risk. Again, 435 00:17:02,600 --> 00:17:03,740 health care providers 436 00:17:04,200 --> 00:17:06,619 want to take advantage of all this innovation 437 00:17:07,319 --> 00:17:07,686 that's taking place in the market, but sorting 438 00:17:07,686 --> 00:17:08,835 through and understanding really what's going to 439 00:17:19,394 --> 00:17:19,894 Solution 440 00:17:20,274 --> 00:17:22,914 Studio, we provide them transparency so they can 441 00:17:22,914 --> 00:17:24,054 make better decisions. 442 00:17:25,569 --> 00:17:27,089 Thank you so much for going through that. 443 00:17:27,089 --> 00:17:28,789 I think, you know, it's always so powerful 444 00:17:28,929 --> 00:17:31,329 to have that type of clarity in a 445 00:17:31,329 --> 00:17:33,730 world where you're getting bombarded by so many 446 00:17:33,730 --> 00:17:36,369 different pitches and offers, and there's a lot 447 00:17:36,369 --> 00:17:38,369 of information out there. Things are changing so 448 00:17:38,369 --> 00:17:41,704 rapidly. It seems like a really great benefit 449 00:17:41,704 --> 00:17:43,544 to have that type of clarity in in 450 00:17:43,544 --> 00:17:45,704 cutting through some of the noise. Now before 451 00:17:45,704 --> 00:17:46,924 we wrap up our conversation, 452 00:17:47,224 --> 00:17:47,964 I'm wondering, 453 00:17:48,345 --> 00:17:50,105 would you talk to some of the best 454 00:17:50,105 --> 00:17:52,024 opportunities you see for growth in the future 455 00:17:52,024 --> 00:17:52,524 overall? 456 00:17:53,019 --> 00:17:54,619 What's really some of the things that you 457 00:17:54,619 --> 00:17:56,779 see coming down the pipe that are really 458 00:17:56,779 --> 00:17:57,759 exciting for you? 459 00:17:58,940 --> 00:18:00,960 Yes. So this is really the 460 00:18:01,339 --> 00:18:02,319 power, the 461 00:18:02,779 --> 00:18:05,839 joy of Mayo Clinic Platform model. 462 00:18:06,835 --> 00:18:10,215 The Mayo Clinic Platform builds programs and capabilities 463 00:18:10,995 --> 00:18:13,394 that we offer to solution developers, so they 464 00:18:13,394 --> 00:18:14,535 can drive innovation 465 00:18:15,154 --> 00:18:16,775 that supports healthcare providers. 466 00:18:17,235 --> 00:18:18,215 We empower 467 00:18:19,119 --> 00:18:21,940 and seek to empower all the brilliant innovators 468 00:18:22,559 --> 00:18:24,099 to do just that, innovate, 469 00:18:24,559 --> 00:18:27,779 right? And so, it's actually working. We're seeing 470 00:18:28,000 --> 00:18:30,259 solutions that are broad reaching 471 00:18:30,720 --> 00:18:34,125 from image based cancer detection and 472 00:18:34,505 --> 00:18:37,005 ambient listening to population 473 00:18:37,305 --> 00:18:38,285 health to 474 00:18:38,585 --> 00:18:40,285 administrative tasks like scheduling 475 00:18:40,664 --> 00:18:41,805 and task management. 476 00:18:42,265 --> 00:18:44,365 And so when you really think about this, 477 00:18:44,984 --> 00:18:45,484 solutions 478 00:18:46,184 --> 00:18:46,765 can help 479 00:18:47,730 --> 00:18:51,029 practitioners more quickly identify the most critical patients, 480 00:18:51,730 --> 00:18:53,589 prioritizing them for care. 481 00:18:54,369 --> 00:18:56,710 Solutions can automate or simplify 482 00:18:57,009 --> 00:18:59,109 administrative tasks, reducing burnout, 483 00:18:59,664 --> 00:19:02,325 allowing care teams to focus on decision making 484 00:19:02,384 --> 00:19:04,085 in the human element of care. 485 00:19:04,704 --> 00:19:05,445 They can 486 00:19:06,065 --> 00:19:09,125 treat more patients with the same resources, increasing 487 00:19:09,184 --> 00:19:09,684 capacity, 488 00:19:10,065 --> 00:19:12,484 enabling more time for patient care. 489 00:19:14,019 --> 00:19:15,320 And really simply 490 00:19:15,859 --> 00:19:18,920 they can help providers improve quality and 491 00:19:19,299 --> 00:19:20,279 decrease cost. 492 00:19:21,700 --> 00:19:24,740 So the Mayo Clinic platform and Accelerate and 493 00:19:24,740 --> 00:19:28,545 Solution Studios programs really provide these key capabilities 494 00:19:28,845 --> 00:19:29,585 and connections 495 00:19:30,445 --> 00:19:33,825 that allow solution developers then to unlock innovation 496 00:19:34,445 --> 00:19:35,424 that will benefit 497 00:19:35,805 --> 00:19:37,904 health care providers and, of course, 498 00:19:38,205 --> 00:19:39,585 most importantly, patients. 499 00:19:40,720 --> 00:19:42,240 Well, Steve, thank you so much for joining 500 00:19:42,240 --> 00:19:44,000 us on the podcast today. This has been 501 00:19:44,000 --> 00:19:46,079 such a fun conversation. I learned a lot, 502 00:19:46,079 --> 00:19:47,440 and I look forward to connecting with you 503 00:19:47,440 --> 00:19:49,119 again soon and seeing you at our health 504 00:19:49,119 --> 00:19:51,519 IT digital health at revenue cycle conference in 505 00:19:51,519 --> 00:19:52,019 October. 506 00:19:52,799 --> 00:19:54,179 Look forward to being there.