1 00:00:00,640 --> 00:00:03,199 Philips is a health tech leader focused on 2 00:00:03,199 --> 00:00:06,000 innovation that improves the health and well-being of 3 00:00:06,000 --> 00:00:09,460 people. Our health care technology and informatics solutions 4 00:00:09,599 --> 00:00:12,559 help care teams diagnose, treat, and manage more 5 00:00:12,559 --> 00:00:16,244 patients with greater precision, speed, and confidence across 6 00:00:16,244 --> 00:00:19,225 the care journey. With Philips, clinicians are empowered 7 00:00:19,285 --> 00:00:21,765 with streamlined insights in the moments that matter 8 00:00:21,765 --> 00:00:24,904 for every patient. Better care for more people. 9 00:00:25,204 --> 00:00:25,704 Philips. 10 00:00:28,710 --> 00:00:31,029 This is Gracelyn Keller with the Becker's Healthcare 11 00:00:31,029 --> 00:00:33,270 Podcast, and we are live at the 9th 12 00:00:33,270 --> 00:00:36,649 annual health IT digital health and RCM conference. 13 00:00:37,109 --> 00:00:39,909 I'm joined currently by Shelly Nash, who is 14 00:00:39,909 --> 00:00:42,549 the senior vice president and global chief medical 15 00:00:42,549 --> 00:00:43,609 information officer 16 00:00:44,085 --> 00:00:45,945 at Fresenius Medical Care. 17 00:00:46,405 --> 00:00:48,564 So, Shelley, thanks for joining me this morning. 18 00:00:48,564 --> 00:00:50,164 To get us started, could you please share 19 00:00:50,164 --> 00:00:52,405 a little bit about yourself, your background, and 20 00:00:52,405 --> 00:00:54,725 your role? Sure. Thanks for having me. I'm 21 00:00:54,725 --> 00:00:56,405 happy to be here. So my name is 22 00:00:56,405 --> 00:00:58,244 Shelley Nash, and I am a physician by 23 00:00:58,244 --> 00:01:00,109 background, but I've worked worked in technology 24 00:01:00,729 --> 00:01:03,609 for over 20 years. I currently work with 25 00:01:03,609 --> 00:01:05,709 Fresenius Medical Care, which is the 26 00:01:06,010 --> 00:01:08,090 largest company in the world to supply, 27 00:01:08,569 --> 00:01:09,790 services and, 28 00:01:10,650 --> 00:01:13,209 machinery for dialysis. So we are a kidney 29 00:01:13,209 --> 00:01:14,030 care company. 30 00:01:14,435 --> 00:01:16,515 And that may sound like, you know, kidney 31 00:01:16,515 --> 00:01:19,335 is very specific, but actually kidney disease affects 32 00:01:19,475 --> 00:01:21,475 1 in 7 people in the United States, 33 00:01:21,475 --> 00:01:22,295 over 35,000,000 34 00:01:22,755 --> 00:01:24,594 people that means. So, you know, we play 35 00:01:24,594 --> 00:01:26,775 a role in providing dialysis services. 36 00:01:27,299 --> 00:01:29,700 We play a role in providing machinery for 37 00:01:29,700 --> 00:01:32,340 not just our specific dialysis centers. We have 38 00:01:32,340 --> 00:01:34,920 about 4,000 dialysis centers worldwide, 39 00:01:35,459 --> 00:01:37,079 and we provide, devices 40 00:01:37,539 --> 00:01:40,259 in about a 150 countries. So we're we're 41 00:01:40,259 --> 00:01:41,879 a very large global company. 42 00:01:42,545 --> 00:01:45,024 My background before coming to Fresenius was that 43 00:01:45,024 --> 00:01:46,084 I was a physician, 44 00:01:46,545 --> 00:01:49,204 chief medical information officer with AdventHealth 45 00:01:49,504 --> 00:01:50,164 out of 46 00:01:50,625 --> 00:01:51,125 Florida. 47 00:01:51,825 --> 00:01:53,204 I had my own practice. 48 00:01:53,504 --> 00:01:55,825 My background before becoming a CMIO was I 49 00:01:55,825 --> 00:01:56,325 worked 50 00:01:56,780 --> 00:01:59,259 in obstetrics and gynecology and then in clinical 51 00:01:59,259 --> 00:01:59,759 informatics. 52 00:02:00,219 --> 00:02:02,459 So I really always felt like technology could 53 00:02:02,459 --> 00:02:05,019 really improve the care of patients and improve 54 00:02:05,019 --> 00:02:08,239 the experience for providers, doctors, nurses as well. 55 00:02:09,044 --> 00:02:11,685 Wonderful. Well, thanks for being here. And speaking 56 00:02:11,685 --> 00:02:14,504 of technology, we're gonna start our conversation today 57 00:02:14,805 --> 00:02:17,944 talking about AI adoption. So this is exploding 58 00:02:18,004 --> 00:02:19,764 right now in health care. And in your 59 00:02:19,764 --> 00:02:21,864 view, what is the most significant or promising 60 00:02:21,924 --> 00:02:24,030 application of AI right now? And how is 61 00:02:24,030 --> 00:02:26,770 this informing your organization's innovation strategy? 62 00:02:27,389 --> 00:02:29,229 Yeah. I don't think you can read an 63 00:02:29,229 --> 00:02:31,229 article online or go to a conference or 64 00:02:31,229 --> 00:02:32,909 talk to someone in health care, especially health 65 00:02:32,909 --> 00:02:35,169 care technology without AI coming up. Right? 66 00:02:36,105 --> 00:02:37,944 AI, you know, has been used for a 67 00:02:37,944 --> 00:02:39,805 while in the form of machine learning. 68 00:02:40,264 --> 00:02:42,905 But I think now with large language models, 69 00:02:42,905 --> 00:02:43,645 with ChatGPT, 70 00:02:43,944 --> 00:02:45,724 it's it's really, as you said, exploding. 71 00:02:46,344 --> 00:02:47,944 I think it can really play a place 72 00:02:47,944 --> 00:02:48,925 in health care, 73 00:02:49,400 --> 00:02:52,199 in frontline health care, even when we start 74 00:02:52,199 --> 00:02:54,620 using it to decrease what we'll call administrative 75 00:02:54,840 --> 00:02:57,020 burden. So doctors, nurses, 76 00:02:58,520 --> 00:03:00,680 front desk folks do so much work every 77 00:03:00,680 --> 00:03:02,840 day that could be done much easier by 78 00:03:02,840 --> 00:03:03,340 technology. 79 00:03:03,875 --> 00:03:04,194 So, for example, 80 00:03:05,155 --> 00:03:06,694 the ability to summarize 81 00:03:06,995 --> 00:03:09,155 information from a chart for someone who's doing 82 00:03:09,155 --> 00:03:10,775 billing. Right? The ability 83 00:03:11,715 --> 00:03:14,675 to answer simple questions around policies and procedures. 84 00:03:14,675 --> 00:03:16,854 We're doing some work around that. So 85 00:03:17,340 --> 00:03:19,180 I know there's vendors who are doing work 86 00:03:19,180 --> 00:03:23,099 around, using AI for answering emails that doctors 87 00:03:23,099 --> 00:03:25,019 get because they spend over half their time, 88 00:03:25,180 --> 00:03:28,139 the literature shows, answering emails to patients and 89 00:03:28,139 --> 00:03:30,379 doing those types of things. We're focusing more 90 00:03:30,379 --> 00:03:31,199 on administrative 91 00:03:31,500 --> 00:03:32,000 work 92 00:03:32,585 --> 00:03:33,724 to make the life 93 00:03:34,264 --> 00:03:36,105 of humans easier. Right? So, you know, we 94 00:03:36,105 --> 00:03:37,405 always talk about in medicine, 95 00:03:37,865 --> 00:03:39,465 people working at the top of their license, 96 00:03:39,465 --> 00:03:40,825 but it's not just that. If we can 97 00:03:40,825 --> 00:03:42,825 really take away some of those, I don't 98 00:03:42,825 --> 00:03:44,985 wanna say mundane, but they are mundane tasks 99 00:03:44,985 --> 00:03:47,224 of looking through, you know, screen after screen 100 00:03:47,224 --> 00:03:48,300 and having summarizations. 101 00:03:48,759 --> 00:03:50,439 I think that's the first place we'll go. 102 00:03:50,439 --> 00:03:52,360 I do think we'll we'll move into things 103 00:03:52,360 --> 00:03:54,539 like and we are doing that now, predictions. 104 00:03:54,680 --> 00:03:55,180 So 105 00:03:55,479 --> 00:03:58,039 having AI be able to look through the 106 00:03:58,039 --> 00:03:59,560 chart in a way that a human could, 107 00:03:59,560 --> 00:04:01,584 but in a faster way with AI so 108 00:04:01,584 --> 00:04:04,145 that they can come to conclusions and predict 109 00:04:04,145 --> 00:04:06,224 outcomes and really improve the care of patients 110 00:04:06,224 --> 00:04:07,044 in that way. 111 00:04:07,905 --> 00:04:10,564 And shifting gears just slightly to data. 112 00:04:11,185 --> 00:04:13,905 Currently, healthcare leaders are managing greater volumes of 113 00:04:13,905 --> 00:04:16,544 data and more devices across a growing number 114 00:04:16,544 --> 00:04:19,080 of care settings and populations. This is a 115 00:04:19,080 --> 00:04:21,480 complex environment that we find ourselves in. So 116 00:04:21,480 --> 00:04:24,060 what clinical data integration tools or practices 117 00:04:24,519 --> 00:04:27,080 are you seeing drive improvements in patient outcomes? 118 00:04:27,080 --> 00:04:29,019 And I'd love to hear a specific example. 119 00:04:29,524 --> 00:04:31,845 Yeah. Yeah. So you're right. I mean, we 120 00:04:31,845 --> 00:04:35,064 have over 200 clinical applications that our clinicians 121 00:04:35,125 --> 00:04:36,904 use every day. And if you think of 122 00:04:37,044 --> 00:04:39,524 every hospital or every unit on a hospital 123 00:04:39,524 --> 00:04:41,365 or every doctor's office, and in my case, 124 00:04:41,365 --> 00:04:44,024 every dialysis center as its own little 125 00:04:44,560 --> 00:04:46,959 company. Right? So someone, let's say the manager 126 00:04:46,959 --> 00:04:48,959 is the CEO of the clinic. Every day, 127 00:04:48,959 --> 00:04:51,120 there are so many different applications and places 128 00:04:51,120 --> 00:04:52,479 they need to look. Right? They need to 129 00:04:52,479 --> 00:04:54,399 look to see who hasn't showed up, what 130 00:04:54,399 --> 00:04:56,479 patients are missing. Have there been any adverse 131 00:04:56,479 --> 00:04:56,979 events? 132 00:04:57,295 --> 00:04:59,134 You know? What's going on with their billing? 133 00:04:59,134 --> 00:05:00,495 Have they not got bills out and they 134 00:05:00,495 --> 00:05:01,775 need to do that to keep the lights 135 00:05:01,775 --> 00:05:03,855 on? So one thing we did with all 136 00:05:03,855 --> 00:05:04,995 these hundreds of applications, 137 00:05:05,375 --> 00:05:07,535 because our users were telling us, you know, 138 00:05:07,535 --> 00:05:09,759 we have to go to 5,000 dashboards. We've 139 00:05:09,899 --> 00:05:11,322 got all these dashboards. We need to check 140 00:05:11,322 --> 00:05:12,745 what's going on with so we created kind 141 00:05:12,745 --> 00:05:12,826 of a we call it daily hub. So 142 00:05:12,826 --> 00:05:12,891 one place which integrated information from dashboards. It 143 00:05:12,891 --> 00:05:14,860 doesn't have the dashboard, but we created something 144 00:05:14,860 --> 00:05:15,360 that 145 00:05:21,435 --> 00:05:24,074 told our users, our clinic managers, and we've 146 00:05:24,074 --> 00:05:26,154 rolled it out for clinicians as well. What 147 00:05:26,154 --> 00:05:27,355 do you need to look at? And we 148 00:05:27,355 --> 00:05:29,115 we, you know, we did something simple, and 149 00:05:29,115 --> 00:05:31,194 you'll see EHR vendors do this as well 150 00:05:31,194 --> 00:05:33,675 with green, yellow, red. So if there's a 151 00:05:33,675 --> 00:05:36,550 new adverse event that happened, safety issue, it's 152 00:05:36,550 --> 00:05:38,150 red. And they come in right away. They 153 00:05:38,150 --> 00:05:39,509 just look at the list and they see 154 00:05:39,509 --> 00:05:41,670 green, yellow, red. And then we just link 155 00:05:41,670 --> 00:05:43,830 them through this hub, it's called it's called 156 00:05:43,830 --> 00:05:45,509 their daily hub because it's their first place 157 00:05:45,509 --> 00:05:47,384 they go every morning. Click that and it 158 00:05:47,384 --> 00:05:48,585 gets them to go see what they need 159 00:05:48,585 --> 00:05:50,824 to go to to review. So we did 160 00:05:50,824 --> 00:05:52,425 integration kind of at a high level, but 161 00:05:52,425 --> 00:05:53,645 it's been very successful. 162 00:05:54,185 --> 00:05:56,045 We've seen a decrease in 163 00:05:56,585 --> 00:05:58,585 days for billing to go out because they've 164 00:05:58,585 --> 00:06:00,185 been able to find that. We've seen some 165 00:06:00,185 --> 00:06:00,925 even increased 166 00:06:01,769 --> 00:06:04,810 ability of filling open slots. So we've really 167 00:06:04,810 --> 00:06:05,849 done a lot of work on that. And 168 00:06:05,849 --> 00:06:06,970 I think that's kind of the way to 169 00:06:06,970 --> 00:06:08,810 go. It's gonna be really difficult to get 170 00:06:08,810 --> 00:06:10,970 rid of all of the applications hospitals and 171 00:06:10,970 --> 00:06:13,449 doctors offices use, even though everyone's trying to 172 00:06:13,449 --> 00:06:15,529 align them. So really trying to create tools 173 00:06:15,529 --> 00:06:16,095 that make 174 00:06:16,654 --> 00:06:18,175 people aware of what they need to look 175 00:06:18,175 --> 00:06:19,875 at, I think are is really important. 176 00:06:21,134 --> 00:06:21,634 And 177 00:06:22,014 --> 00:06:25,855 how can healthcare organizations better support our IC 178 00:06:25,855 --> 00:06:27,935 and our clinical teams as they carry out 179 00:06:27,935 --> 00:06:30,069 these innovation efforts? And do you know of 180 00:06:30,069 --> 00:06:32,170 any common pitfalls that you've seen here? 181 00:06:32,629 --> 00:06:34,790 Yeah. I I think that what happens sometimes 182 00:06:34,790 --> 00:06:36,790 in large health systems having worked for 1 183 00:06:36,790 --> 00:06:37,610 for 10 years, 184 00:06:38,069 --> 00:06:39,990 or in companies is that, you know, you 185 00:06:39,990 --> 00:06:41,830 have folks that get ideas and they may 186 00:06:41,830 --> 00:06:42,970 be in the c suite, 187 00:06:43,444 --> 00:06:45,605 and they don't include the IT teams either 188 00:06:45,605 --> 00:06:47,925 early enough or the clinical IT teams early 189 00:06:47,925 --> 00:06:50,084 enough. So I think it's important to if 190 00:06:50,084 --> 00:06:51,524 you come up with an idea for something 191 00:06:51,524 --> 00:06:52,644 you wanna do, and I was in a 192 00:06:52,644 --> 00:06:55,204 session yesterday where a CMIO said, you know, 193 00:06:55,204 --> 00:06:58,245 often the clinical IT folks aren't pulled until 194 00:06:58,245 --> 00:07:00,939 later. So So making sure that, you know, 195 00:07:00,939 --> 00:07:03,980 you don't start projects without having everyone having 196 00:07:03,980 --> 00:07:05,420 a seat at the table. And I'm not 197 00:07:05,420 --> 00:07:06,860 saying everyone has to make the decision, of 198 00:07:06,860 --> 00:07:08,459 course, and maybe the CEO who makes the 199 00:07:08,459 --> 00:07:11,180 decision, but including everyone in the discussions early 200 00:07:11,180 --> 00:07:12,860 because they may have a viewpoint that you 201 00:07:12,860 --> 00:07:14,475 didn't think of. You know, people on the 202 00:07:14,475 --> 00:07:16,795 front lines really might understand the workflow, so 203 00:07:16,795 --> 00:07:17,855 you don't wanna create 204 00:07:18,155 --> 00:07:19,835 tools that you think are going to work 205 00:07:19,835 --> 00:07:21,835 for what you what you need if you 206 00:07:21,835 --> 00:07:24,155 don't really have the direct input. So silos 207 00:07:24,155 --> 00:07:25,514 is a big problem, I think, in health 208 00:07:25,514 --> 00:07:27,900 care. My advice would be to include people 209 00:07:27,900 --> 00:07:30,720 early, you know, to listen to everyone's opinion. 210 00:07:31,020 --> 00:07:33,020 Obviously, you know, you can't always make decision 211 00:07:33,020 --> 00:07:35,580 by consensus, but listen to them because otherwise, 212 00:07:35,580 --> 00:07:37,100 what happens is you create these tools, and 213 00:07:37,100 --> 00:07:38,685 I've seen this happen, and then people don't 214 00:07:38,685 --> 00:07:40,125 use them. You think it's gonna be great, 215 00:07:40,125 --> 00:07:41,884 but it isn't. But, I think one way 216 00:07:41,884 --> 00:07:43,564 to avoid it is to really engage everyone 217 00:07:43,564 --> 00:07:44,384 early on. 218 00:07:45,324 --> 00:07:47,745 Absolutely. And as we wrap up our conversation, 219 00:07:48,044 --> 00:07:49,404 I'd love to know your top piece of 220 00:07:49,404 --> 00:07:51,449 advice for health care leaders as they prepare 221 00:07:51,449 --> 00:07:54,410 for further advancements in technology and greater demands 222 00:07:54,410 --> 00:07:57,050 for care. That's a big question. But, probably 223 00:07:57,050 --> 00:07:58,889 my top piece of advice is don't be 224 00:07:58,889 --> 00:08:01,129 afraid. You know, it's kind of interesting because 225 00:08:01,129 --> 00:08:03,209 I'll be out talking to doctors and everyone 226 00:08:03,209 --> 00:08:04,810 is scared. Oh, AI is taking over the 227 00:08:04,810 --> 00:08:06,169 world. AI, I'll get rid of doctors. You 228 00:08:06,169 --> 00:08:07,995 know, you can read articles online. And and 229 00:08:07,995 --> 00:08:09,535 if you start thinking about 230 00:08:09,915 --> 00:08:12,254 AI, you know, not as a scary thing, 231 00:08:12,955 --> 00:08:15,194 I mean, anyone who you've watches Netflix, right, 232 00:08:15,194 --> 00:08:16,634 AI is there. It's telling you what your 233 00:08:16,634 --> 00:08:18,254 next pick is. Or if you use Spotify, 234 00:08:18,314 --> 00:08:19,535 AI is giving you suggestions. 235 00:08:19,835 --> 00:08:21,615 So I think health care organizations 236 00:08:22,310 --> 00:08:24,149 really need to recognize that, 237 00:08:24,789 --> 00:08:26,649 the way that they approach this, 238 00:08:27,269 --> 00:08:29,509 should be very thoughtful. Don't just throw something 239 00:08:29,509 --> 00:08:30,949 out that, you know, you think is gonna 240 00:08:30,949 --> 00:08:32,389 save the world if you haven't engaged your 241 00:08:32,389 --> 00:08:34,330 end users, your doctors, your clinicians, 242 00:08:35,269 --> 00:08:37,190 and also patients. You know, patients are 243 00:08:37,884 --> 00:08:39,884 have the idea that, you know, AI may 244 00:08:39,884 --> 00:08:42,204 be replacing doctors. So, you know, be thoughtful 245 00:08:42,204 --> 00:08:42,944 in the applications 246 00:08:43,245 --> 00:08:45,644 that you create. Be thoughtful in how you 247 00:08:45,644 --> 00:08:47,164 market this and really think of it as 248 00:08:47,164 --> 00:08:47,824 a tool. 249 00:08:48,125 --> 00:08:50,125 It may be, you know, we always talk 250 00:08:50,125 --> 00:08:51,990 about how there's always, you know, a a 251 00:08:51,990 --> 00:08:54,070 peak of excitement and then a trough of 252 00:08:54,070 --> 00:08:56,070 disillusionment, you know, and that that may happen 253 00:08:56,070 --> 00:08:57,269 as well, but don't give up on it 254 00:08:57,269 --> 00:08:59,029 because I really do think the technologies that 255 00:08:59,029 --> 00:09:00,629 are out there and how they're evolving is 256 00:09:00,629 --> 00:09:02,070 really gonna change how we can take care 257 00:09:02,070 --> 00:09:04,389 of patients and improve the experience for everyone 258 00:09:04,389 --> 00:09:05,529 who works in health care. 259 00:09:06,105 --> 00:09:08,105 Absolutely. Well, Shelly, thanks so much for taking 260 00:09:08,105 --> 00:09:09,544 the time to join me today on the 261 00:09:09,544 --> 00:09:11,464 Becker's Health Care Podcast. Again, we're live at 262 00:09:11,464 --> 00:09:13,945 the 9th Annual Health IT Digital Health and 263 00:09:13,945 --> 00:09:16,924 RCM Conference. Thank you. Yep. Thanks so much.