1 00:00:00,205 --> 00:00:00,845 - Hello everyone. 2 00:00:00,875 --> 00:00:03,325 This is Jacob Emerson with Becker's Healthcare. 3 00:00:03,465 --> 00:00:06,405 Thanks so much for tuning into our podcast today. 4 00:00:06,405 --> 00:00:08,525 We're thrilled to be joined by Amy Anderson, 5 00:00:08,585 --> 00:00:11,165 who is the Vice President of Market Development Enterprise 6 00:00:11,165 --> 00:00:12,725 and Cloud Venture at Oracle. 7 00:00:13,175 --> 00:00:15,725 Today, we're going to be discussing driving transformation 8 00:00:15,725 --> 00:00:17,125 with cloud infrastructure. 9 00:00:17,505 --> 00:00:19,365 So Amy, thank you for taking the time 10 00:00:19,365 --> 00:00:20,405 to sit down with us today. 11 00:00:20,815 --> 00:00:21,965 - Thank you. It's my pleasure. 12 00:00:22,745 --> 00:00:24,445 - And before we dive in here, Amy, I'd love 13 00:00:24,445 --> 00:00:26,445 to have you share a little bit more about yourself, 14 00:00:26,445 --> 00:00:27,605 your background in healthcare, 15 00:00:28,065 --> 00:00:29,965 and what it is that you do today at Oracle. 16 00:00:31,055 --> 00:00:32,065 - Sure. Thank you so much. 17 00:00:32,605 --> 00:00:34,545 Uh, I've been in healthcare my entire 18 00:00:34,545 --> 00:00:36,705 career, um, many decades. 19 00:00:37,485 --> 00:00:40,305 Um, currently I lead market development 20 00:00:40,365 --> 00:00:41,865 for Oracle Cloud infrastructure, 21 00:00:41,885 --> 00:00:45,545 and what that means is I'm really driving the strategy 22 00:00:45,605 --> 00:00:48,145 and implementation of our vertical, vertical 23 00:00:48,705 --> 00:00:51,465 industry specific solutions and value. 24 00:00:52,205 --> 00:00:55,585 Um, in my past, I have been a lobbyist. 25 00:00:55,895 --> 00:00:58,465 I've led strategy, I've worked in 26 00:00:59,025 --> 00:01:00,105 transformational consulting. 27 00:01:00,765 --> 00:01:03,585 Um, and for our, our purposes today, I think it's important 28 00:01:03,645 --> 00:01:06,785 to note that, um, I also led regulatory compliance 29 00:01:06,805 --> 00:01:10,025 and strategy for Kaiser Permanente in California. 30 00:01:10,845 --> 00:01:14,665 Um, and back in my early days, um, I helped 31 00:01:15,275 --> 00:01:18,985 craft the legislative language that became the HIPAA law. 32 00:01:19,125 --> 00:01:22,865 So that's something that's very important to me as we look 33 00:01:22,925 --> 00:01:27,345 to, uh, develop, you know, high value cloud solutions 34 00:01:27,925 --> 00:01:30,545 for a highly regulated industry like healthcare. 35 00:01:31,045 --> 00:01:32,265 And I'm thrilled to be here today. 36 00:01:33,385 --> 00:01:35,475 - Wonderful. Well, like I said, we're glad to have you 37 00:01:35,475 --> 00:01:36,715 with us, and thanks for taking us 38 00:01:36,715 --> 00:01:38,515 through a little bit more about your background. 39 00:01:38,745 --> 00:01:39,995 Excited to dive right in. 40 00:01:40,495 --> 00:01:41,755 So, Amy, there's been a lot 41 00:01:41,755 --> 00:01:45,235 of interest in Oracle's acquisition of Cerner last year. 42 00:01:45,905 --> 00:01:48,395 What exactly is Oracle's vision for healthcare overall 43 00:01:48,415 --> 00:01:50,355 and how do you view the Cerner acquisition 44 00:01:50,585 --> 00:01:51,595 fitting in with that? 45 00:01:52,265 --> 00:01:55,075 - Yeah. Well, let me tell you, there were a lot of, um, 46 00:01:55,495 --> 00:01:57,475 raised eyebrows and questions about, 47 00:01:57,965 --> 00:02:00,075 about Oracle buying Cerner 48 00:02:00,075 --> 00:02:02,875 because many, you know, the market really sees us 49 00:02:02,895 --> 00:02:06,555 as either a database company, a SaaS company, 50 00:02:07,095 --> 00:02:08,715 and now with the Cerner acquisition, 51 00:02:08,715 --> 00:02:09,835 they're also looking at us 52 00:02:09,855 --> 00:02:12,995 as an EHR company, but that's not correct. 53 00:02:13,755 --> 00:02:15,245 Fundamentally, our vision 54 00:02:15,265 --> 00:02:17,845 for healthcare is really about data, right? 55 00:02:18,415 --> 00:02:21,685 Harnessing data and insights to drive clinical 56 00:02:21,685 --> 00:02:23,045 and operational excellence, 57 00:02:23,615 --> 00:02:25,755 and frankly, to reduce the total cost of care. 58 00:02:25,755 --> 00:02:28,755 There's so much inefficiency in the healthcare market, 59 00:02:29,535 --> 00:02:34,315 and healthcare data and operations are notoriously siloed, 60 00:02:35,055 --> 00:02:37,835 and frankly, EHRs were built 61 00:02:38,055 --> 00:02:40,675 as electronic filing systems for 62 00:02:40,675 --> 00:02:42,555 that siloed environment, right? 63 00:02:43,655 --> 00:02:46,145 What I like to say is our acquisition of, of Cerner, 64 00:02:46,525 --> 00:02:51,305 you know, it is not about scaling an EHR, it's really about 65 00:02:51,825 --> 00:02:56,505 creating a, an open data platform that provides access to 66 00:02:57,045 --> 00:03:01,285 the myriad types of data, structured unstructured 67 00:03:01,995 --> 00:03:05,805 data from, you know, streaming devices, imaging, 68 00:03:06,545 --> 00:03:10,525 and really taking that data and making it accessible 69 00:03:11,515 --> 00:03:16,375 and deriving, you know, insights from the data to really 70 00:03:17,055 --> 00:03:20,855 transform and innovate around clinical, operational 71 00:03:21,595 --> 00:03:23,015 and financial operations. 72 00:03:23,675 --> 00:03:28,215 And I need to say this very clearly, our open data platform 73 00:03:28,435 --> 00:03:32,575 and ecosystem will be EHR agnostic. 74 00:03:33,835 --> 00:03:35,415 It can bring their data and, 75 00:03:35,795 --> 00:03:39,415 and apply, you know, solutions, AI solutions, 76 00:03:39,415 --> 00:03:41,895 natural language processing, what have you, 77 00:03:42,475 --> 00:03:45,895 and have that data integrated into 78 00:03:46,575 --> 00:03:48,295 whatever EHR they have in their system. 79 00:03:49,925 --> 00:03:52,345 - So ultimately, Oracle's vision for healthcare is, 80 00:03:52,365 --> 00:03:54,065 is centered on data and, 81 00:03:54,065 --> 00:03:56,145 and using that data to reduce the cost of care 82 00:03:56,405 --> 00:03:58,545 and reduce those silos that you mentioned. 83 00:03:58,965 --> 00:04:00,185 Amy, in that vein, 84 00:04:00,205 --> 00:04:02,865 can you tell us a little bit more about Oracle's modern data 85 00:04:03,265 --> 00:04:05,065 platform and what that means exactly? 86 00:04:06,015 --> 00:04:09,145 - Sure. Um, well, the modern data platform is, 87 00:04:09,735 --> 00:04:10,785 I'll just walk through it. 88 00:04:10,885 --> 00:04:12,025 So why is it modern? 89 00:04:12,805 --> 00:04:17,545 Um, it's modern because we are investing in, 90 00:04:17,925 --> 00:04:20,265 we have invested billions of dollars in r 91 00:04:20,265 --> 00:04:22,785 and d so that our customers don't have to, 92 00:04:23,805 --> 00:04:28,305 and this strategy is, is industry specific. 93 00:04:28,925 --> 00:04:30,425 So we're building solutions 94 00:04:30,965 --> 00:04:33,905 and services that are prebuilt for healthcare, 95 00:04:34,365 --> 00:04:37,225 for life sciences, um, for other industries 96 00:04:37,855 --> 00:04:41,185 that include a vision service, NLP 97 00:04:42,365 --> 00:04:45,505 AI services, generative AI services. 98 00:04:45,685 --> 00:04:47,105 So that is why it's modern. 99 00:04:47,905 --> 00:04:50,445 So we have these solutions and services, 100 00:04:51,065 --> 00:04:53,485 but the data is, is our customer's data. 101 00:04:54,185 --> 00:04:58,055 Bring your own data. We will apply the services 102 00:04:58,275 --> 00:04:59,775 and solutions against those. 103 00:05:00,145 --> 00:05:03,335 We'll help you develop algorithms. 104 00:05:03,675 --> 00:05:07,735 We have a host of incredible partners like NVIDIA 105 00:05:07,755 --> 00:05:10,855 and Cohere, um, that we can leverage 106 00:05:10,855 --> 00:05:13,895 and our customers can leverage to, you know, 107 00:05:13,995 --> 00:05:18,095 get quicker results and, and, and, and impact. 108 00:05:19,075 --> 00:05:21,975 And the platform, of course, this is the OCI platform. 109 00:05:22,475 --> 00:05:25,055 It is, it is, um, envisioned 110 00:05:25,055 --> 00:05:29,825 to be an innovation ecosystem of solutions 111 00:05:29,825 --> 00:05:31,105 that run on OCI. 112 00:05:31,125 --> 00:05:34,825 So that can include analytics and genomics. 113 00:05:35,085 --> 00:05:36,785 Um, and, and so that 114 00:05:37,585 --> 00:05:40,625 platform play is really exciting for us, 115 00:05:41,005 --> 00:05:44,975 but it is also the environment in which we'll provide that, 116 00:05:45,005 --> 00:05:46,815 that environment for innovation 117 00:05:46,835 --> 00:05:48,855 so our customers can innovate within it. 118 00:05:49,155 --> 00:05:52,215 But we also are working closely 119 00:05:52,365 --> 00:05:55,415 with our customers on specific use cases. 120 00:05:56,475 --> 00:05:59,745 Um, that can be, you know, I think add value 121 00:05:59,745 --> 00:06:01,185 to the market more broadly, 122 00:06:02,125 --> 00:06:05,905 and those, those solutions will be accessible to, to other 123 00:06:06,745 --> 00:06:10,465 customers who bring their data that will be protected, um, 124 00:06:10,685 --> 00:06:12,905 and sequestered for their own purposes. 125 00:06:13,285 --> 00:06:17,025 And getting back to why this is important to me, I think 126 00:06:17,025 --> 00:06:21,545 that, um, that security particularly in, in the healthcare 127 00:06:21,545 --> 00:06:25,675 and life sciences field is so paramount so 128 00:06:25,675 --> 00:06:28,955 that we have an innovation environment that 129 00:06:29,695 --> 00:06:31,915 builds in the types of regulations 130 00:06:31,915 --> 00:06:35,355 and policies, um, specifically around security. 131 00:06:36,495 --> 00:06:38,065 - Yeah. So Amy mean, it sounds like then you, 132 00:06:38,065 --> 00:06:39,305 you are making those research 133 00:06:39,305 --> 00:06:40,745 and development investments so 134 00:06:40,745 --> 00:06:42,865 that your customers do not have to, it's 135 00:06:42,865 --> 00:06:44,145 so interesting to hear you talk about this. 136 00:06:44,685 --> 00:06:48,065 You, you mentioned specific use cases for this technology, 137 00:06:48,325 --> 00:06:50,865 and a top concern that we hear from payers often 138 00:06:51,045 --> 00:06:52,305 is fraud detection. 139 00:06:52,645 --> 00:06:54,625 So based off everything we've just talked about, 140 00:06:54,685 --> 00:06:55,985 can you talk a little bit more about 141 00:06:56,125 --> 00:06:58,905 how new technology can really help in this space? 142 00:06:59,535 --> 00:07:00,585 - Yeah, absolutely. I'm 143 00:07:00,585 --> 00:07:02,385 so glad you asked about fraud detection 144 00:07:02,385 --> 00:07:07,145 because fraudulent claims against payers are estimated in 145 00:07:07,145 --> 00:07:08,865 the billions of dollars annually. 146 00:07:09,845 --> 00:07:13,145 And the work that we're doing with our customers 147 00:07:13,925 --> 00:07:17,665 around fraud detection, you know, a, a percentage 148 00:07:17,665 --> 00:07:20,625 or two in improvement could 149 00:07:21,175 --> 00:07:24,185 save the entire healthcare system, billions of dollars. 150 00:07:24,605 --> 00:07:28,985 And, and that, and that translates into expanding access 151 00:07:29,045 --> 00:07:30,425 to care, improving quality. 152 00:07:30,685 --> 00:07:33,665 So all of the things that we all want to do, right? 153 00:07:34,715 --> 00:07:37,975 And let me just be clear that we are, we are working 154 00:07:38,365 --> 00:07:42,055 with our customers around these key business challenges, 155 00:07:42,635 --> 00:07:45,735 and we're doing so with the modern data platform, 156 00:07:46,155 --> 00:07:47,855 but foundationally, all 157 00:07:47,855 --> 00:07:51,295 of this occurs within the Oracle Cloud infrastructure 158 00:07:51,445 --> 00:07:54,935 that is our foundational ecosystem for innovation. 159 00:07:55,875 --> 00:07:59,295 And let me just also say that our, our proposition 160 00:07:59,645 --> 00:08:01,255 with the Oracle Cloud infrastructure 161 00:08:01,515 --> 00:08:04,575 and the modern data platform is really to partner 162 00:08:04,765 --> 00:08:09,015 with the customers around core use cases and, 163 00:08:09,075 --> 00:08:13,735 and solutions, bring in other partners who can, 164 00:08:13,915 --> 00:08:18,575 can provide those industry specific services like Nvidia, 165 00:08:18,885 --> 00:08:23,495 like cohere in the, um, AI and generative AI space. 166 00:08:24,435 --> 00:08:27,935 But also we are, we are stocking the shelves 167 00:08:28,765 --> 00:08:31,415 with key solutions that are, uh, 168 00:08:31,435 --> 00:08:34,095 and partners that are specific to those industries. 169 00:08:34,555 --> 00:08:37,335 So I would ask, you know, just keep your, 170 00:08:37,525 --> 00:08:39,855 keep your eye on the ball as we continue 171 00:08:39,855 --> 00:08:42,375 to roll out additional partnerships, um, 172 00:08:42,485 --> 00:08:46,135 that will make the Oracle cloud infrastructure 173 00:08:46,825 --> 00:08:50,655 truly an innovation ecosystem as it relates to fraud, 174 00:08:50,875 --> 00:08:51,975 uh, detection. 175 00:08:52,435 --> 00:08:55,055 Um, our approach to the problem is, 176 00:08:55,305 --> 00:08:57,445 is really bringing together all that data. 177 00:08:57,945 --> 00:09:02,045 We then, you know, look at, um, you know, 178 00:09:02,045 --> 00:09:04,045 really applying kind of data science 179 00:09:04,105 --> 00:09:07,205 and AI services, um, to bring 180 00:09:08,485 --> 00:09:10,845 insights into claims and risk stratification 181 00:09:10,895 --> 00:09:13,165 where we can predict, um, 182 00:09:13,345 --> 00:09:18,205 and recommend, um, optimized actions on, on case management. 183 00:09:18,985 --> 00:09:21,605 And this is all being done again, 184 00:09:21,745 --> 00:09:26,685 inside the Oracle cloud infrastructure, um, that is managed 185 00:09:26,865 --> 00:09:31,285 by a, a specific policy and role-based access management. 186 00:09:31,285 --> 00:09:33,885 So the data go governance is secure, 187 00:09:34,625 --> 00:09:37,565 and we prebuilt all these functions 188 00:09:38,105 --> 00:09:41,125 and services to ensure, you know, security 189 00:09:41,985 --> 00:09:45,685 and in compliance with any new, uh, policies 190 00:09:45,685 --> 00:09:47,405 or regulations that that roll out. 191 00:09:47,425 --> 00:09:50,125 So we're very excited about what we can do. 192 00:09:50,295 --> 00:09:51,565 We're not doing this alone. 193 00:09:51,945 --> 00:09:54,325 It takes working with our customers 194 00:09:54,785 --> 00:09:56,045 who bring their own data. 195 00:09:56,305 --> 00:10:00,285 So we can do this in a, you know, with, with real world, um, 196 00:10:01,005 --> 00:10:02,885 examples and partners. 197 00:10:03,655 --> 00:10:05,905 - Yeah, absolutely. And it sounds like getting a, hold on, 198 00:10:05,925 --> 00:10:09,425 on fraud detection really could save billions annually, 199 00:10:09,445 --> 00:10:11,985 not just for payers, but for members as well. 200 00:10:12,605 --> 00:10:13,625 Um, and, and we know, 201 00:10:13,625 --> 00:10:16,505 we've heard payers consistently talk over the last few years 202 00:10:16,505 --> 00:10:19,265 about using AI within their fraud detection spaces. 203 00:10:20,165 --> 00:10:22,585 It, it's no surprise everyone's talking about ai, 204 00:10:23,365 --> 00:10:25,505 - So it's really the same problem 205 00:10:26,365 --> 00:10:28,545 across payers and providers. 206 00:10:28,605 --> 00:10:33,055 So on the provider side, you know, there is a real desire 207 00:10:33,595 --> 00:10:36,855 to improve, um, revenue cycle management 208 00:10:37,285 --> 00:10:40,175 because of, as you mentioned, the implications 209 00:10:40,395 --> 00:10:42,975 for clinicians, uh, improving quality of care, 210 00:10:44,095 --> 00:10:47,175 easing the burden on patients and improving outcomes. 211 00:10:48,115 --> 00:10:50,935 And one of those challenges is really in prior 212 00:10:50,935 --> 00:10:52,415 authorization, right? 213 00:10:52,595 --> 00:10:57,015 So prior authorization is a massive challenge on the 214 00:10:57,215 --> 00:11:00,415 provider side, but we hear from our customers on the payer 215 00:11:00,525 --> 00:11:04,415 side that they would like to have ways to improve 216 00:11:04,415 --> 00:11:06,575 that process, that that is fraught 217 00:11:06,575 --> 00:11:08,655 with manual processes faxing. 218 00:11:09,315 --> 00:11:12,375 So we really envision, uh, 219 00:11:12,375 --> 00:11:16,575 working within the OCI environment to bring together 220 00:11:17,275 --> 00:11:20,055 the payer and the provider side to come up with, you know, 221 00:11:20,055 --> 00:11:23,775 prior authorization, uh, solutions that, that, 222 00:11:24,005 --> 00:11:26,135 that can really, um, transform 223 00:11:26,565 --> 00:11:28,855 that whole continuum across payer provider. 224 00:11:29,645 --> 00:11:30,655 - Yeah, absolutely. 225 00:11:30,715 --> 00:11:32,575 And Amy, to your point, through our reporting, 226 00:11:32,575 --> 00:11:34,095 we have seen large health systems 227 00:11:34,195 --> 00:11:36,295 and payers begin to start these, 228 00:11:36,295 --> 00:11:37,775 these AI powered partnerships 229 00:11:37,775 --> 00:11:39,375 around prior authorization in different 230 00:11:39,375 --> 00:11:40,455 parts of the country. 231 00:11:41,115 --> 00:11:44,175 Um, but you, you brought up generative AI specifically, Amy, 232 00:11:44,435 --> 00:11:46,335 so I have to ask, what is Oracle's 233 00:11:46,775 --> 00:11:48,055 strategy in this growing field? 234 00:11:48,925 --> 00:11:50,935 - Well, there's a I think there's a lot 235 00:11:50,935 --> 00:11:53,095 of confusion about what generative AI is. 236 00:11:53,465 --> 00:11:54,605 Um, uh, 237 00:11:54,785 --> 00:11:59,745 but put simply, I think our sol our strategy related 238 00:11:59,885 --> 00:12:03,025 to generative AI is pretty simple. 239 00:12:03,615 --> 00:12:05,905 It's about using high powered computing 240 00:12:06,285 --> 00:12:08,465 and the modern data platform together 241 00:12:09,535 --> 00:12:11,545 with generative ai. 242 00:12:12,285 --> 00:12:17,065 So if you think about chat GPT, right, very powerful. 243 00:12:18,125 --> 00:12:21,425 But I will say that that approach is a generalized approach. 244 00:12:21,695 --> 00:12:25,265 It's looking at the AI not specific 245 00:12:25,365 --> 00:12:26,625 to a particular industry. 246 00:12:27,205 --> 00:12:32,185 And that has challenges, I think, ethically with, you know, 247 00:12:32,285 --> 00:12:36,145 how it's applied in a healthcare specific environment. 248 00:12:36,875 --> 00:12:39,325 What differentiates Oracle, um, 249 00:12:39,425 --> 00:12:42,365 and frankly our partnership with Cohere is 250 00:12:42,365 --> 00:12:45,085 that we're bringing industry-based solutions 251 00:12:45,425 --> 00:12:46,525 for generative ai. 252 00:12:46,995 --> 00:12:50,765 This is part of what I mentioned earlier about pre-building 253 00:12:51,805 --> 00:12:52,885 services and solutions, 254 00:12:53,505 --> 00:12:55,085 but it's really important to know 255 00:12:55,085 --> 00:12:58,645 that we are taking an industry specific approach towards 256 00:12:58,645 --> 00:12:59,725 generative ai. 257 00:13:00,265 --> 00:13:03,445 And that makes, I truly believe that that is 258 00:13:03,445 --> 00:13:04,765 what is gonna be the most meaningful 259 00:13:04,765 --> 00:13:07,365 and impactful, um, approach 260 00:13:07,545 --> 00:13:10,165 for our customers in healthcare and life sciences. 261 00:13:10,745 --> 00:13:14,845 And because we have this industry specific approach, 262 00:13:15,585 --> 00:13:18,485 our customers, when they bring their sequestered data 263 00:13:18,625 --> 00:13:21,565 to our platform, um, it is protected. 264 00:13:21,865 --> 00:13:26,165 It is protected in the context of the particular use. 265 00:13:26,665 --> 00:13:28,645 So if it's, if it's a clinical trial 266 00:13:28,985 --> 00:13:33,805 or if it's in, in, um, sort of the claim space, um, 267 00:13:34,585 --> 00:13:36,005 all of those, uh, 268 00:13:36,165 --> 00:13:39,645 requirements are built into those industry 269 00:13:39,965 --> 00:13:41,085 specific, uh, solutions. 270 00:13:41,955 --> 00:13:44,815 And I can't emphasize this enough, it's, 271 00:13:44,885 --> 00:13:46,015 it's incredibly important 272 00:13:46,015 --> 00:13:47,975 because it, it means that we can work 273 00:13:47,975 --> 00:13:51,575 with our customer's data and ensure that it's protected. 274 00:13:52,195 --> 00:13:53,775 So the Oracle Cloud platform 275 00:13:54,155 --> 00:13:57,095 and managed services are prebuilt functions 276 00:13:57,095 --> 00:14:01,015 and services that are enshrined with the security 277 00:14:01,205 --> 00:14:03,695 that is specific for the particular use case. 278 00:14:04,065 --> 00:14:05,975 These will be pre-trained models. 279 00:14:07,085 --> 00:14:08,905 And I know this sounds kind of simple, 280 00:14:09,085 --> 00:14:12,785 but you bring your own data to use these pre-trained models. 281 00:14:13,645 --> 00:14:18,545 And from, from the real data that our customers bring, 282 00:14:18,645 --> 00:14:21,305 that's how we're going to drive, uh, innovation 283 00:14:21,565 --> 00:14:25,665 and transformation, um, that can be replicable 284 00:14:25,925 --> 00:14:29,545 and scalable, um, beyond the individual customer. 285 00:14:29,965 --> 00:14:33,745 Uh, but our hope is within the OCI Oracle cloud 286 00:14:33,745 --> 00:14:36,745 infrastructure environment, we will develop 287 00:14:37,435 --> 00:14:41,185 meaningful solutions that can have a bigger impact 288 00:14:41,885 --> 00:14:45,465 on the market beyond one customer here or there. 289 00:14:46,335 --> 00:14:48,825 - Wonderful. Well, Amy, thank you so, so much 290 00:14:48,965 --> 00:14:52,365 for taking the time to be with us on the podcast today. 291 00:14:52,995 --> 00:14:54,405 It's been a pleasure speaking with you 292 00:14:54,465 --> 00:14:56,925 and hearing a little bit more about Oracle's vision 293 00:14:57,025 --> 00:15:00,445 for healthcare, for your customers and for AI technologies. 294 00:15:00,905 --> 00:15:01,965 We really appreciate it. 295 00:15:02,415 --> 00:15:04,885 - Thank you so much. - I'd also like 296 00:15:04,885 --> 00:15:07,005 to thank our podcast sponsor Oracle. 297 00:15:07,385 --> 00:15:09,805 You can tune into more podcast from Becker's Healthcare 298 00:15:10,105 --> 00:15:12,965 by visiting our podcast page at becker's hospital 299 00:15:12,965 --> 00:15:13,965 review.com.