1 00:00:00,080 --> 00:00:02,319 Hi, everyone. This is Lucas Voss with Becker's 2 00:00:02,319 --> 00:00:03,759 Healthcare. Thanks so much for tuning in to 3 00:00:03,759 --> 00:00:06,480 the Becker's Healthcare podcast series. It's fantastic to 4 00:00:06,480 --> 00:00:08,960 have you. Today, we're talking about what surgical 5 00:00:08,960 --> 00:00:10,500 readiness means for ASCs 6 00:00:10,800 --> 00:00:13,359 in an AI driven era. And I'm so 7 00:00:13,359 --> 00:00:16,004 excited to welcome doctor Christian Paian, CEO and 8 00:00:16,004 --> 00:00:18,885 cofounder of Revel AI Health. Doctor Paeyon, thanks 9 00:00:18,885 --> 00:00:20,004 so much for being here today. It's great 10 00:00:20,004 --> 00:00:20,744 to have you. 11 00:00:21,204 --> 00:00:22,724 Great to be here and to be talking 12 00:00:22,724 --> 00:00:23,524 about this. 13 00:00:23,925 --> 00:00:26,404 Definitely an AI forward world as as you 14 00:00:26,404 --> 00:00:28,344 said. So I'm glad to hear you. Absolutely. 15 00:00:28,730 --> 00:00:30,329 And I love that I have you on, 16 00:00:30,329 --> 00:00:31,769 and I do wanna give you a chance 17 00:00:31,769 --> 00:00:33,689 to introduce yourself to our audience because you 18 00:00:33,689 --> 00:00:34,350 have a 19 00:00:34,729 --> 00:00:37,289 a position as an innovator, but also as 20 00:00:37,289 --> 00:00:38,429 a surgeon yourself. 21 00:00:38,809 --> 00:00:40,649 So if you could just introduce yourself and 22 00:00:40,649 --> 00:00:42,329 tell us a little bit about your background 23 00:00:42,329 --> 00:00:44,804 and your work in health care. Absolutely. So 24 00:00:44,804 --> 00:00:47,765 Christian Payan, I'm a CEO, cofounder of Revel 25 00:00:47,765 --> 00:00:49,765 AI Health. The other hat I wear is 26 00:00:49,765 --> 00:00:52,325 I am a practicing orthopedic trauma surgeon at 27 00:00:52,325 --> 00:00:54,725 Duke University School of Medicine where I'm on 28 00:00:54,725 --> 00:00:55,225 faculty. 29 00:00:55,924 --> 00:00:57,924 I'm also on faculty at the Margolis Institute 30 00:00:57,924 --> 00:00:58,984 for Health Policy. 31 00:00:59,310 --> 00:01:01,789 A lot of my focus is on care 32 00:01:01,789 --> 00:01:02,289 transformation, 33 00:01:02,750 --> 00:01:05,390 value based care, and trying to understand how 34 00:01:05,390 --> 00:01:07,310 tech enabled services are going to change the 35 00:01:07,310 --> 00:01:09,469 way that we deliver health care. So I 36 00:01:09,469 --> 00:01:10,530 do a lot of things, 37 00:01:10,829 --> 00:01:12,430 but at the at the cross section of 38 00:01:12,430 --> 00:01:14,689 everything I do is this idea of delivering 39 00:01:14,805 --> 00:01:17,125 better care that's value based and seeing where 40 00:01:17,125 --> 00:01:18,504 technology plays a role. 41 00:01:19,125 --> 00:01:21,204 Yeah. Absolutely. And and you know this yourself. 42 00:01:21,204 --> 00:01:23,204 Right? We see a lot more higher acuity 43 00:01:23,204 --> 00:01:23,704 cases 44 00:01:24,484 --> 00:01:25,305 for organizations, 45 00:01:26,084 --> 00:01:28,165 but we're also seeing them operate with a 46 00:01:28,165 --> 00:01:31,479 lot leaner teams, which doesn't necessarily correlate. 47 00:01:31,939 --> 00:01:34,340 When you look ahead five years, how do 48 00:01:34,340 --> 00:01:37,379 you define surgical readiness right now? And where 49 00:01:37,379 --> 00:01:39,479 does clinical AI meaningfully 50 00:01:39,859 --> 00:01:41,640 change that equation for you? 51 00:01:42,224 --> 00:01:44,944 I I think that today, we're defining surgical 52 00:01:44,944 --> 00:01:45,444 readiness 53 00:01:45,825 --> 00:01:47,344 mostly at the point of care. We're saying 54 00:01:47,344 --> 00:01:50,064 is the patient medically cleared? Is the OR 55 00:01:50,064 --> 00:01:51,504 set up? That we got our vendors in 56 00:01:51,504 --> 00:01:53,844 place. That's that's great. All of those 57 00:01:54,420 --> 00:01:56,500 aspects of care are necessary, but in my 58 00:01:56,500 --> 00:01:59,400 opinion, it's it's insufficient. Right? The patient expectations 59 00:01:59,540 --> 00:02:00,280 are changing. 60 00:02:00,739 --> 00:02:02,980 Five years from now, surgical readiness should really 61 00:02:02,980 --> 00:02:04,040 mean the entire 62 00:02:04,500 --> 00:02:05,000 perioperative 63 00:02:05,379 --> 00:02:07,560 arc, that entire experience is orchestrated 64 00:02:08,020 --> 00:02:09,879 from the time that a patient is scheduled 65 00:02:09,939 --> 00:02:11,055 through through the recovery milestones 66 00:02:11,594 --> 00:02:14,094 after they leave the hospital or the ambulatory 67 00:02:14,155 --> 00:02:15,055 surgery center. 68 00:02:15,675 --> 00:02:17,754 And where I think AI is really going 69 00:02:17,754 --> 00:02:20,414 to help improve this arc 70 00:02:20,794 --> 00:02:21,935 of surgical readiness 71 00:02:22,520 --> 00:02:24,840 is at any point in that journey that 72 00:02:24,840 --> 00:02:25,979 you need good communication 73 00:02:26,439 --> 00:02:28,139 and context around your patient. 74 00:02:28,759 --> 00:02:30,379 There's so much administrative 75 00:02:30,840 --> 00:02:33,019 work and labor that goes into 76 00:02:33,560 --> 00:02:35,560 the process of getting a patient ready for 77 00:02:35,560 --> 00:02:36,060 surgery. 78 00:02:36,519 --> 00:02:38,835 And then really with technology 79 00:02:39,135 --> 00:02:40,754 that is placed smartly 80 00:02:41,215 --> 00:02:43,694 in a way to engage with patients and 81 00:02:43,694 --> 00:02:46,175 offload staff from having to make those touch 82 00:02:46,175 --> 00:02:49,215 points, but they can also surface those issues 83 00:02:49,215 --> 00:02:51,135 to the clinical team ahead of time, we 84 00:02:51,135 --> 00:02:52,354 can make a big difference. 85 00:02:53,090 --> 00:02:54,689 I think what's really going to change five 86 00:02:54,689 --> 00:02:56,930 years from now for ambulatory surgery centers is, 87 00:02:56,930 --> 00:02:58,449 yeah, we're going to be doing more of 88 00:02:58,449 --> 00:03:01,110 these high acuity cases in the outpatient setting, 89 00:03:01,169 --> 00:03:02,849 and that means we're going to need more 90 00:03:02,849 --> 00:03:05,090 contextual information to make sure that we're doing 91 00:03:05,090 --> 00:03:07,294 it safely. And AI is going to play 92 00:03:07,294 --> 00:03:09,294 a big role in extracting that information from 93 00:03:09,294 --> 00:03:11,875 the chart and making sure that the information 94 00:03:11,935 --> 00:03:14,175 gets communicated to the clinical team in a 95 00:03:14,175 --> 00:03:16,334 way that's simple for them to understand, and 96 00:03:16,334 --> 00:03:18,349 most importantly, to the patient so so that 97 00:03:18,349 --> 00:03:20,669 they understand their expectations and that so nothing 98 00:03:20,669 --> 00:03:22,349 falls through the gaps the way it might 99 00:03:22,349 --> 00:03:25,009 today in what is a more fragmented system. 100 00:03:25,709 --> 00:03:27,389 I do wanna follow-up on this really quickly 101 00:03:27,389 --> 00:03:28,830 because I it feels like it's a very 102 00:03:28,830 --> 00:03:30,669 personal issue for you, I feel like, because 103 00:03:30,669 --> 00:03:32,594 you know both sides. Is that correct? And 104 00:03:32,675 --> 00:03:34,194 and why is that such why is it 105 00:03:34,194 --> 00:03:36,115 so important to you personally from from your 106 00:03:36,115 --> 00:03:37,415 position where you're at? 107 00:03:37,955 --> 00:03:40,354 Absolutely. I am, like you said, kind of 108 00:03:40,354 --> 00:03:42,034 working on both sides of the coin here. 109 00:03:42,034 --> 00:03:43,715 I'm I'm thinking about how we as a 110 00:03:43,715 --> 00:03:46,009 health system at Duke can strategically 111 00:03:46,389 --> 00:03:47,990 shift a lot of our cases to the 112 00:03:47,990 --> 00:03:50,550 outpatient setting, including some of our fracture cases 113 00:03:50,550 --> 00:03:52,709 that we've traditionally thought of as needing to 114 00:03:52,709 --> 00:03:54,469 be done in the hospital. And I wanna 115 00:03:54,469 --> 00:03:55,909 make sure that the experience is good for 116 00:03:55,909 --> 00:03:56,490 our patients, 117 00:03:56,949 --> 00:03:59,844 and that this this shift happens safely. Now 118 00:03:59,844 --> 00:04:02,645 the other side, right, wearing my entrepreneurial hat, 119 00:04:02,645 --> 00:04:03,865 I work with hospitals 120 00:04:04,245 --> 00:04:05,865 and health systems and organizations 121 00:04:06,564 --> 00:04:09,685 that are at all different levels of technical 122 00:04:09,685 --> 00:04:11,224 readiness or clinical 123 00:04:11,889 --> 00:04:12,709 protocol readiness. 124 00:04:13,250 --> 00:04:14,930 So for me, it's it's really trying to 125 00:04:14,930 --> 00:04:17,810 bridge that idea of what we're doing in 126 00:04:17,810 --> 00:04:21,250 an academic medical center as everything evolves to 127 00:04:21,250 --> 00:04:24,209 the outpatient setting while trying to understand how 128 00:04:24,209 --> 00:04:27,509 you can embed technology into the patient experience 129 00:04:27,694 --> 00:04:29,314 and the clinical infrastructure 130 00:04:30,014 --> 00:04:31,774 to make it a lot easier. So, yeah, 131 00:04:31,774 --> 00:04:34,095 for me, it's definitely, I think, an issue 132 00:04:34,095 --> 00:04:36,014 that's really personal because I want my patients 133 00:04:36,014 --> 00:04:37,555 as a surgeon have a good experience. 134 00:04:38,334 --> 00:04:40,514 And then from an infrastructure perspective, 135 00:04:40,894 --> 00:04:42,974 I'm hoping that we can build something that 136 00:04:42,974 --> 00:04:46,189 is scalable and really changes the experience for 137 00:04:46,189 --> 00:04:47,569 patients to be less fragmented 138 00:04:48,029 --> 00:04:51,230 and for organizations that are honestly, in many 139 00:04:51,230 --> 00:04:54,129 ways, struggling, right, with labor needs and constraints, 140 00:04:54,910 --> 00:04:56,110 to be able to do this in a 141 00:04:56,110 --> 00:04:58,334 in a way that's automated and allows staff 142 00:04:58,334 --> 00:05:00,175 to spend more time on patients and less 143 00:05:00,175 --> 00:05:00,834 on paperwork. 144 00:05:01,615 --> 00:05:03,774 You mentioned something really important, which is the 145 00:05:03,774 --> 00:05:05,615 technical readiness piece. And this is one of 146 00:05:05,615 --> 00:05:07,615 my favorite topics to talk about because we 147 00:05:07,615 --> 00:05:09,875 saw so much of this in 2025. 148 00:05:10,014 --> 00:05:11,474 There's a ton of AI pilots. 149 00:05:11,935 --> 00:05:14,790 All every organization wants to do it. Right? 150 00:05:14,790 --> 00:05:16,870 They start projects, and then they sort of 151 00:05:16,870 --> 00:05:19,829 fade. There's very few examples of sustained impact. 152 00:05:19,829 --> 00:05:22,709 We're seeing some, but very few across the 153 00:05:22,709 --> 00:05:24,889 nation right now, especially for ASCs. 154 00:05:25,669 --> 00:05:27,829 For ASCs today, what are some of those 155 00:05:27,829 --> 00:05:30,354 AI use cases, with clinical AI use cases 156 00:05:30,354 --> 00:05:32,935 that you're looking to that are actually delivering 157 00:05:32,995 --> 00:05:33,495 value, 158 00:05:34,035 --> 00:05:36,675 and what separates those from the pilots that 159 00:05:36,675 --> 00:05:37,415 don't scale? 160 00:05:38,115 --> 00:05:40,194 You're absolutely right. I mean, there's this gold 161 00:05:40,194 --> 00:05:42,454 rush of use cases and pilots, and 162 00:05:42,834 --> 00:05:45,800 the pilots that become platforms are few and 163 00:05:45,800 --> 00:05:46,699 far in between. 164 00:05:47,160 --> 00:05:49,800 I think that in the ASC space, there 165 00:05:49,800 --> 00:05:52,220 are a lot of labor challenges right now. 166 00:05:52,279 --> 00:05:55,100 So people aren't necessarily looking for technology 167 00:05:55,639 --> 00:05:58,555 to ping their clinicians with more decision support 168 00:05:58,555 --> 00:06:00,475 at the point of care. Where I think 169 00:06:00,475 --> 00:06:02,634 sustainable innovation is going to happen from a 170 00:06:02,634 --> 00:06:05,535 clinical AI perspective in the ambulatory surgery center 171 00:06:05,754 --> 00:06:08,495 is around patient communication and engagement automation 172 00:06:09,355 --> 00:06:12,095 and trying to help ambulatory surgery centers 173 00:06:12,449 --> 00:06:15,589 prepare for this era of asynchronous longitudinal 174 00:06:16,370 --> 00:06:19,009 quality data. And I'm really talking about patient 175 00:06:19,009 --> 00:06:20,229 reported outcome measures. 176 00:06:20,610 --> 00:06:23,169 I think that we were somewhat fortunate in 177 00:06:23,169 --> 00:06:25,110 the final rule that got passed by CMS 178 00:06:25,169 --> 00:06:28,644 to not have information transfer and Pro PM 179 00:06:28,704 --> 00:06:31,745 be launched onto ambulatory surgery centers, but that's 180 00:06:31,745 --> 00:06:34,564 coming. Every single model that's come from CMS 181 00:06:34,944 --> 00:06:37,425 is asking us to report on how our 182 00:06:37,425 --> 00:06:40,224 patients are doing around their procedure, and that's 183 00:06:40,224 --> 00:06:42,199 a ton of labor costs. I think this 184 00:06:42,199 --> 00:06:43,720 is a place where clinically I is going 185 00:06:43,720 --> 00:06:45,560 to make a big difference by automating these 186 00:06:45,560 --> 00:06:46,300 touch points, 187 00:06:46,600 --> 00:06:47,580 pushing that information 188 00:06:48,199 --> 00:06:51,959 into the electronic health record, surfacing it to 189 00:06:51,959 --> 00:06:54,485 clinicians so that they can have better a 190 00:06:54,485 --> 00:06:56,645 better idea of how their patients are doing 191 00:06:56,645 --> 00:06:57,464 after procedures. 192 00:06:58,085 --> 00:07:01,125 And maybe most importantly and not often highlighted, 193 00:07:01,125 --> 00:07:01,944 I think, 194 00:07:03,045 --> 00:07:05,045 improving the patient experience, making it so that 195 00:07:05,045 --> 00:07:07,285 patients feel like they have an always on 196 00:07:07,285 --> 00:07:09,729 conversational assistant that can explain to them why 197 00:07:09,729 --> 00:07:12,289 they're filling out another form, why they've gotta 198 00:07:12,289 --> 00:07:14,289 fax three or four things to their primary 199 00:07:14,289 --> 00:07:16,129 care doctor. And I think that if we 200 00:07:16,129 --> 00:07:19,169 can deploy those kinds of use cases, we'll 201 00:07:19,169 --> 00:07:19,909 see scalable 202 00:07:20,289 --> 00:07:23,625 and lasting technology in the implementation of clinical 203 00:07:23,625 --> 00:07:24,685 AI for ASCs. 204 00:07:25,544 --> 00:07:28,024 You mentioned my favorite f word, the facts. 205 00:07:28,024 --> 00:07:30,824 It's still being mentioned in 2026 206 00:07:30,824 --> 00:07:32,985 in podcasts, so make sure that you know 207 00:07:32,985 --> 00:07:34,879 what a facts is. If you don't, you 208 00:07:34,879 --> 00:07:35,379 probably 209 00:07:36,159 --> 00:07:38,819 you talked about you talked about scalability here. 210 00:07:38,959 --> 00:07:41,699 What's that one factor for you personally 211 00:07:42,319 --> 00:07:45,060 that's most important for organizations to scale? 212 00:07:45,439 --> 00:07:46,419 Workflow integration. 213 00:07:46,895 --> 00:07:50,014 You you have to integrate and understand the 214 00:07:50,014 --> 00:07:52,995 clinician and the patient's perspective inside and out. 215 00:07:53,615 --> 00:07:55,455 If you and we've seen this. Right? We've 216 00:07:55,455 --> 00:07:57,615 we've deployed technology in the past at Revel 217 00:07:57,615 --> 00:08:00,035 AI that didn't take into account 218 00:08:01,149 --> 00:08:02,930 the change management that's required, 219 00:08:03,310 --> 00:08:04,370 the deep understanding 220 00:08:04,829 --> 00:08:05,810 of the workflow. 221 00:08:06,829 --> 00:08:09,250 I think that if we can find those 222 00:08:09,470 --> 00:08:11,709 use cases that honestly, at first, will not 223 00:08:11,709 --> 00:08:13,629 feel like they're scalable because you've gotta get 224 00:08:13,629 --> 00:08:15,229 in the trenches. You have to speak to 225 00:08:15,229 --> 00:08:15,729 nurses. 226 00:08:16,055 --> 00:08:18,295 You have to secret shop and live the 227 00:08:18,295 --> 00:08:20,855 experience of surgical readiness as a patient, and 228 00:08:20,855 --> 00:08:23,254 then see where technology can embed in a 229 00:08:23,254 --> 00:08:25,895 way that's going to remove friction and not 230 00:08:25,895 --> 00:08:28,235 add it over and over and over again 231 00:08:28,535 --> 00:08:29,035 throughout 232 00:08:29,889 --> 00:08:32,129 a region and then the country for this 233 00:08:32,129 --> 00:08:34,389 setting of care in ambulatory surgery centers. 234 00:08:35,250 --> 00:08:36,049 I will say, 235 00:08:36,529 --> 00:08:38,690 you know, there is something else that's very 236 00:08:38,690 --> 00:08:39,990 important. It's interoperability. 237 00:08:40,529 --> 00:08:41,669 And I think that 238 00:08:42,054 --> 00:08:44,215 a common theme that I'm seeing at in 239 00:08:44,215 --> 00:08:46,634 outpatient surgery centers is there's information 240 00:08:47,014 --> 00:08:49,415 living there on one system of record, and 241 00:08:49,415 --> 00:08:52,535 then there's information living everywhere else, and patients 242 00:08:52,535 --> 00:08:53,595 are trying to 243 00:08:53,975 --> 00:08:54,955 compile it. 244 00:08:55,370 --> 00:08:56,190 Ambulatory surgery centers 245 00:08:56,570 --> 00:08:57,949 are struggling to 246 00:08:58,409 --> 00:08:59,789 synthesize all that information. 247 00:09:00,329 --> 00:09:02,490 And so as I talk about scalability with 248 00:09:02,490 --> 00:09:05,949 workflow integration, it's gotta be paired with access 249 00:09:06,089 --> 00:09:08,730 to the system of record and allowing for 250 00:09:08,730 --> 00:09:11,695 a gintech systems and AI to contextualize this 251 00:09:11,695 --> 00:09:12,995 information and make it meaningful. 252 00:09:14,174 --> 00:09:15,695 To be able to do that, you've touched 253 00:09:15,695 --> 00:09:18,095 on it earlier in the conversation, you need 254 00:09:18,095 --> 00:09:20,195 data, and you need good data. 255 00:09:20,975 --> 00:09:22,894 Yeah. Yeah. We talk about, you know, quality 256 00:09:22,894 --> 00:09:25,379 reporting, and and it's sort of a this 257 00:09:25,379 --> 00:09:27,220 this compliance exercise that a lot of folks 258 00:09:27,220 --> 00:09:28,899 are talking about, but it's also a leading 259 00:09:28,899 --> 00:09:31,720 indicator for readiness for a lot of organizations. 260 00:09:32,740 --> 00:09:35,299 How does AI shift quality data from that 261 00:09:35,299 --> 00:09:35,799 retrospective 262 00:09:36,274 --> 00:09:39,174 reporting piece to then real time clinical insight 263 00:09:39,394 --> 00:09:41,735 in specifically the perioperative setting? 264 00:09:42,274 --> 00:09:44,355 I think that this has been a missed 265 00:09:44,355 --> 00:09:46,514 opportunity for a long time. Right? To your 266 00:09:46,514 --> 00:09:50,355 point, we've thought of quality reporting as a 267 00:09:50,355 --> 00:09:52,169 checklist, something we've gotta get off our 268 00:09:52,970 --> 00:09:55,370 our plate. Where I think AI is going 269 00:09:55,370 --> 00:09:56,809 to make a difference you know, this is 270 00:09:56,809 --> 00:09:58,649 still a checklist. Right? We've gotta get it 271 00:09:58,649 --> 00:10:01,049 done. But let AI do a lot of 272 00:10:01,049 --> 00:10:04,509 that chart abstraction, the submission to CMS, which 273 00:10:05,054 --> 00:10:07,774 traditionally has been a really laborious and, 274 00:10:08,174 --> 00:10:10,115 administratively burdensome task. 275 00:10:10,654 --> 00:10:12,195 And then let organizations, 276 00:10:12,815 --> 00:10:16,034 people, shift their attention from collecting these measures 277 00:10:16,495 --> 00:10:19,615 to understanding through continuous collection what those measures 278 00:10:19,615 --> 00:10:23,009 mean. Right? Start using patient reported outcome measures 279 00:10:23,230 --> 00:10:25,410 or your ED visit rate at your ASC 280 00:10:26,029 --> 00:10:26,529 to 281 00:10:26,910 --> 00:10:28,210 fuel care transformation. 282 00:10:28,750 --> 00:10:30,990 I think that's where clinical AI is going 283 00:10:30,990 --> 00:10:32,990 to really embed and make a difference. It's 284 00:10:32,990 --> 00:10:34,450 gonna automate that 285 00:10:34,824 --> 00:10:35,324 piece 286 00:10:35,664 --> 00:10:36,164 of 287 00:10:36,504 --> 00:10:38,264 of the puzzle for us that to date 288 00:10:38,264 --> 00:10:40,664 has been a headache, and instead, make it 289 00:10:40,664 --> 00:10:42,824 a place that we can focus our attention 290 00:10:42,824 --> 00:10:45,804 to improve patient experience, to improve clinical outcomes, 291 00:10:46,024 --> 00:10:49,440 and hopefully to shift staff effort away from 292 00:10:49,440 --> 00:10:52,399 repetitive tasks that are administrative in nature and 293 00:10:52,399 --> 00:10:55,759 instead towards revenue generating activity and activity that 294 00:10:55,759 --> 00:10:57,839 is improving, again, the patient experience and the 295 00:10:57,839 --> 00:10:59,860 clinical experience. That's that's where I see, 296 00:11:00,480 --> 00:11:02,584 really a lot of change coming 297 00:11:03,044 --> 00:11:04,245 soon if we can if we can get 298 00:11:04,245 --> 00:11:04,824 it right. 299 00:11:05,365 --> 00:11:08,024 And it'll it enables organizations to be proactive. 300 00:11:08,245 --> 00:11:10,565 It enables organizations to look to the future 301 00:11:10,565 --> 00:11:13,365 instead of always running behind, so to speak. 302 00:11:13,365 --> 00:11:15,704 And and speaking of that, specifically, 303 00:11:17,250 --> 00:11:19,809 for ASC leaders who want to be AI 304 00:11:19,809 --> 00:11:22,290 ready, who want to do this right, rather 305 00:11:22,290 --> 00:11:24,529 than being AI reactive and reacting to all 306 00:11:24,529 --> 00:11:26,790 of these trends too late, quite frankly, 307 00:11:27,330 --> 00:11:29,730 what priorities should they focus on over the 308 00:11:29,730 --> 00:11:31,664 next twelve to twenty four months to support 309 00:11:31,664 --> 00:11:34,404 that safe, scalable adoption that we've touched on? 310 00:11:34,784 --> 00:11:36,884 You you, hinted at this. I think 311 00:11:37,264 --> 00:11:39,664 we have to shift from being reactive to 312 00:11:39,664 --> 00:11:40,164 proactive. 313 00:11:40,705 --> 00:11:43,024 We can't wait until the penalties kick in. 314 00:11:43,024 --> 00:11:45,105 We have to recognize the signals from the 315 00:11:45,105 --> 00:11:46,304 regulatory bodies, 316 00:11:47,000 --> 00:11:49,000 from, you know, what our own sort of 317 00:11:49,000 --> 00:11:50,919 bottom lines are telling us. And I think 318 00:11:50,919 --> 00:11:53,320 that there are really three priorities ASCs should 319 00:11:53,320 --> 00:11:55,320 look for, over the next twelve to twenty 320 00:11:55,320 --> 00:11:57,720 four months. One, get your data in order 321 00:11:57,720 --> 00:11:59,480 or at least understand where the gaps are 322 00:11:59,480 --> 00:12:01,304 in your data. Are you on one system 323 00:12:01,304 --> 00:12:02,684 of record? Are you processing 324 00:12:03,225 --> 00:12:05,485 EHR information from multiple providers? 325 00:12:05,865 --> 00:12:07,464 How are you gonna take that data and 326 00:12:07,464 --> 00:12:09,944 organize it in a way that provides context 327 00:12:09,944 --> 00:12:12,264 to your patients, improves your outcomes, and lets 328 00:12:12,264 --> 00:12:14,745 you be ready for those inevitable quality reporting 329 00:12:14,745 --> 00:12:16,169 measures that are coming your way? 330 00:12:16,649 --> 00:12:19,129 Start thinking about workflows, right, that you want 331 00:12:19,129 --> 00:12:19,789 to augment, 332 00:12:20,570 --> 00:12:23,289 or replace, and think about how technology is 333 00:12:23,289 --> 00:12:25,309 going to play a role in that workflow, 334 00:12:26,009 --> 00:12:26,509 transformation. 335 00:12:27,209 --> 00:12:29,129 And then I think the third thing that 336 00:12:29,129 --> 00:12:30,809 ASCs need to think about is defining their 337 00:12:30,809 --> 00:12:33,355 culture. A culture of iteration and innovation is 338 00:12:33,355 --> 00:12:35,595 going to be extremely important. There's so many 339 00:12:35,595 --> 00:12:37,915 cases that are coming towards ASCs. It's like 340 00:12:37,915 --> 00:12:39,835 a good problem to have. But if you're 341 00:12:39,835 --> 00:12:40,495 not careful, 342 00:12:41,355 --> 00:12:43,215 this case mix that's going to 343 00:12:43,519 --> 00:12:44,879 all of a sudden show up at your 344 00:12:44,879 --> 00:12:47,120 facility could really change your workflows in a 345 00:12:47,120 --> 00:12:48,799 way that you're not ready for, affect your 346 00:12:48,799 --> 00:12:50,399 bottom line, and I think that could be 347 00:12:50,399 --> 00:12:52,399 a a really big problem. And with those 348 00:12:52,399 --> 00:12:54,559 three things in mind, what ASC leaders should 349 00:12:54,559 --> 00:12:56,639 start to be doing now as well as 350 00:12:56,639 --> 00:12:58,455 over the next twelve to twenty four months 351 00:12:58,535 --> 00:13:01,174 is identify your partners and and start to 352 00:13:01,174 --> 00:13:02,634 iterate with them before, 353 00:13:03,095 --> 00:13:06,134 you know, a percentage of your reimbursement is 354 00:13:06,134 --> 00:13:07,575 on the line so that you have that 355 00:13:07,575 --> 00:13:09,735 chance to iterate, to change your workflow, to 356 00:13:09,735 --> 00:13:11,095 get your data in order so that when 357 00:13:11,095 --> 00:13:13,014 the stakes are real, you're not playing catch 358 00:13:13,014 --> 00:13:15,279 up. Right? So those would be my recommendations. 359 00:13:15,340 --> 00:13:17,259 Right? Like, be at the cutting edge of 360 00:13:17,259 --> 00:13:18,000 this stuff. 361 00:13:18,700 --> 00:13:21,259 Find use cases that you can silo and 362 00:13:21,259 --> 00:13:23,580 innovate and partner on, and then prepare for 363 00:13:23,580 --> 00:13:25,419 the future instead of just reacting to the 364 00:13:25,419 --> 00:13:25,919 present. 365 00:13:26,365 --> 00:13:27,884 Doctor Pan, it's so great to have you. 366 00:13:27,884 --> 00:13:29,165 Thanks so much for taking some time for 367 00:13:29,165 --> 00:13:30,205 us. We'll have to come back and do 368 00:13:30,205 --> 00:13:32,205 an episode on partnership. I feel like that 369 00:13:32,205 --> 00:13:34,545 warrants its own, its own episode. 370 00:13:36,365 --> 00:13:38,445 Agreed. Yeah. They're bad partners. Like, you know, 371 00:13:38,445 --> 00:13:40,205 you gotta know how to vet a partner. 372 00:13:40,205 --> 00:13:41,024 That is true. 373 00:13:41,570 --> 00:13:43,009 Doctor Pan, again, thank you so much for 374 00:13:43,009 --> 00:13:44,450 being here today, and we also want to 375 00:13:44,450 --> 00:13:46,769 thank our podcast sponsor, Revel AI Health. You 376 00:13:46,769 --> 00:13:48,370 can tune in to more podcasts from Becker's 377 00:13:48,370 --> 00:13:52,870 Healthcare by visiting our podcast page at beckershospitalreview.com.