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 00:00:29,170 --> 00:00:31,410 This is Gracelyn Keller with the Becker's Healthcare 11 00:00:31,410 --> 00:00:33,250 Podcast, and we are live at the 9th 12 00:00:33,250 --> 00:00:36,869 Annual Health IT Digital Health and RCM Conference. 13 00:00:37,409 --> 00:00:39,969 I'm currently joined by Kung Win, who is 14 00:00:39,969 --> 00:00:43,125 the assistant executive medical director and care transformation 15 00:00:43,265 --> 00:00:46,065 at Kaiser Permanente. So thanks so much for 16 00:00:46,065 --> 00:00:48,065 being here today, and would love to get 17 00:00:48,065 --> 00:00:50,304 us started by having you introduce yourself and 18 00:00:50,304 --> 00:00:51,905 telling us a little bit more about your 19 00:00:51,905 --> 00:00:52,725 role and background. 20 00:00:53,185 --> 00:00:54,784 Great. Thank you very much, and happy to 21 00:00:54,784 --> 00:00:56,385 be here. It sounds like a very, it 22 00:00:56,385 --> 00:00:58,649 is has been a very exciting event. So 23 00:00:58,649 --> 00:01:00,649 my name is, doctor Kang Nguyen. First and 24 00:01:00,649 --> 00:01:02,750 foremost, a very proud family physician. 25 00:01:03,210 --> 00:01:04,829 I'm a part of the Kaiser Permanente, 26 00:01:05,369 --> 00:01:05,869 group. 27 00:01:06,329 --> 00:01:08,750 Kaiser Permanente is actually made up of multiple 28 00:01:08,810 --> 00:01:09,310 entities. 29 00:01:10,084 --> 00:01:12,325 First and foremost, it is an insurance plan. 30 00:01:12,325 --> 00:01:14,885 So that's the Kaiser Foundation health plan, and 31 00:01:14,885 --> 00:01:15,784 that is national. 32 00:01:16,165 --> 00:01:19,045 There's also Kaiser Foundation Hospitals that manages our 33 00:01:19,045 --> 00:01:21,144 multitude of hospitals throughout the country. 34 00:01:21,444 --> 00:01:23,444 And then the third entity is really the 35 00:01:23,444 --> 00:01:26,219 Permanente medical groups. So that's the group of 36 00:01:26,219 --> 00:01:27,759 doctors that that are independent. 37 00:01:28,299 --> 00:01:30,719 And my group is the Southern California Permanente 38 00:01:30,939 --> 00:01:32,479 Medical Group in Southern California. 39 00:01:32,859 --> 00:01:34,780 They're actually in that, area. I have the 40 00:01:34,780 --> 00:01:37,039 role and responsibility of being the care transformation 41 00:01:37,179 --> 00:01:37,679 leader 42 00:01:38,025 --> 00:01:40,525 over operations and technology in Southern California. 43 00:01:40,905 --> 00:01:43,145 I'm also the founder and the current medical 44 00:01:43,145 --> 00:01:46,585 director for Southern California's Virtual Medical Center that 45 00:01:46,585 --> 00:01:49,165 helps assist in synchronous and asynchronous care. 46 00:01:49,465 --> 00:01:52,105 And more recently, I'm, been appointed to be 47 00:01:52,105 --> 00:01:55,109 the chief chief medical officer for care navigation 48 00:01:55,109 --> 00:01:58,229 for the Permanente Foundation oversee, helping all of 49 00:01:58,229 --> 00:02:00,469 our medical groups work with the Kaiser health 50 00:02:00,469 --> 00:02:00,969 plan. 51 00:02:01,430 --> 00:02:03,349 Wonderful. Well, thank you for taking the time 52 00:02:03,349 --> 00:02:05,849 to be here. And let's begin our conversation 53 00:02:05,989 --> 00:02:08,233 with AI adoption. As you know, this is 54 00:02:08,233 --> 00:02:09,422 exploding in health care. So in your view, 55 00:02:09,422 --> 00:02:10,741 what is the most significant or promising application 56 00:02:10,741 --> 00:02:12,276 of AI right now, and how is this 57 00:02:12,276 --> 00:02:13,465 informing your organization's innovation strategy? 58 00:02:14,164 --> 00:02:16,245 Yeah. That seems to be the question of 59 00:02:16,245 --> 00:02:19,365 the day, if not the year, is where 60 00:02:19,365 --> 00:02:20,104 is AI kinda 61 00:02:22,740 --> 00:02:25,060 going? You know, I think there's, 2 ways 62 00:02:25,060 --> 00:02:26,819 to look at it. There's the short term 63 00:02:26,819 --> 00:02:28,980 view and there's a long term view. As 64 00:02:28,980 --> 00:02:30,659 part of the health care being in health 65 00:02:30,659 --> 00:02:31,800 care, obviously, 66 00:02:32,260 --> 00:02:34,680 what we wanna do is have artificial intelligence 67 00:02:34,740 --> 00:02:36,040 really help us out with 68 00:02:36,580 --> 00:02:38,040 prevention of illness 69 00:02:38,355 --> 00:02:40,115 and also help us out with prediction. So 70 00:02:40,115 --> 00:02:42,435 prevention and prediction. And then we also want, 71 00:02:42,675 --> 00:02:45,075 artificial intelligence to help assist our doctors and 72 00:02:45,075 --> 00:02:45,814 our clinicians 73 00:02:46,115 --> 00:02:47,495 with immediate care delivery. 74 00:02:47,955 --> 00:02:49,175 These things are actually, 75 00:02:49,794 --> 00:02:52,135 really, in my mind, more futuristic looking 76 00:02:52,449 --> 00:02:54,289 because we we what we have to do 77 00:02:54,289 --> 00:02:57,090 is really prepare our current datasets to be 78 00:02:57,090 --> 00:02:59,030 able to have some of the algorithms 79 00:02:59,569 --> 00:03:00,469 consume that. 80 00:03:00,849 --> 00:03:03,169 So, you know, we Kaiser has been kind 81 00:03:03,169 --> 00:03:05,250 of the early adopter for the electronic medical 82 00:03:05,250 --> 00:03:05,750 record, 83 00:03:06,105 --> 00:03:07,865 for more than 20 years now. And as 84 00:03:07,865 --> 00:03:09,305 a result, we have a lot of data 85 00:03:09,305 --> 00:03:10,985 that will help us out with that. But 86 00:03:10,985 --> 00:03:12,844 that data has been largely unstructured. 87 00:03:14,105 --> 00:03:16,844 Artificial intelligence is a is a fancy software 88 00:03:16,905 --> 00:03:18,525 that needs to ingest that data. 89 00:03:18,825 --> 00:03:20,979 So for the future for this, we have 90 00:03:20,979 --> 00:03:23,860 to basically, effectively organize our data and then 91 00:03:23,860 --> 00:03:26,500 build new datasets that are more curated so 92 00:03:26,500 --> 00:03:28,599 that we can actually take advantage of AI. 93 00:03:29,379 --> 00:03:31,560 So that's more for the future. The immediate 94 00:03:31,620 --> 00:03:33,780 role of artificial intelligence, I believe, is really 95 00:03:33,780 --> 00:03:34,439 in augmenting, 96 00:03:35,455 --> 00:03:38,354 clinicians. So things that will, release the, 97 00:03:38,814 --> 00:03:40,814 burden of care delivery. So one of the 98 00:03:40,814 --> 00:03:42,415 biggest things we've done is to roll out, 99 00:03:42,655 --> 00:03:43,635 ambient listening, 100 00:03:44,335 --> 00:03:46,175 for the doctors. And what that is is 101 00:03:46,175 --> 00:03:48,495 it's a scribe technology that will literally take 102 00:03:48,495 --> 00:03:48,900 notes, 103 00:03:49,299 --> 00:03:50,759 summarize it for the clinicians. 104 00:03:51,299 --> 00:03:54,180 And in Kaiser Permanente, we've actually deployed it 105 00:03:54,180 --> 00:03:55,479 now to over 14,000 106 00:03:56,099 --> 00:03:58,039 doctors. So the largest deployment. 107 00:03:58,739 --> 00:04:01,060 That's one example. Another example in terms of 108 00:04:01,060 --> 00:04:03,799 augmenting is using natural language processing 109 00:04:04,205 --> 00:04:06,224 to help classify patient emails. 110 00:04:06,604 --> 00:04:08,465 And when we classify the patient emails 111 00:04:09,085 --> 00:04:11,164 according to what they typed, we can better 112 00:04:11,164 --> 00:04:12,944 direct that, for better care. 113 00:04:13,485 --> 00:04:15,884 We're also using some early predictive models for 114 00:04:15,884 --> 00:04:18,944 things like mammography screening, for high risk patients 115 00:04:19,220 --> 00:04:21,080 as well as looking into imaging, 116 00:04:21,540 --> 00:04:24,020 to look for cardiovascular disease, for example, imaging 117 00:04:24,020 --> 00:04:25,000 in the back of the eye. 118 00:04:26,100 --> 00:04:28,920 And chips and gears just slightly to data. 119 00:04:29,460 --> 00:04:31,939 Currently, health care leaders are managing greater volumes 120 00:04:31,939 --> 00:04:33,875 of data and more devices on a growing 121 00:04:33,875 --> 00:04:35,735 number of care settings and populations. 122 00:04:36,354 --> 00:04:38,274 And this is a very complex environment that 123 00:04:38,274 --> 00:04:40,754 we find ourselves in. So what clinical data 124 00:04:40,754 --> 00:04:43,314 integration tools or practices are you seeing drive 125 00:04:43,314 --> 00:04:44,935 improvements in patient outcomes? 126 00:04:45,810 --> 00:04:47,970 Yeah. You know, that's, it's funny because that 127 00:04:47,970 --> 00:04:50,370 topic is coming up right now. But the 128 00:04:50,370 --> 00:04:52,290 truth in reality is we actually have been 129 00:04:52,290 --> 00:04:54,290 collecting data for a very long time in 130 00:04:54,290 --> 00:04:57,270 health care. If you think about home cardiac 131 00:04:57,330 --> 00:05:00,525 devices and cardiac monitors, they've been collecting 132 00:05:00,904 --> 00:05:02,125 information forever, 133 00:05:02,824 --> 00:05:05,245 and alerting, clinicians and doctors to, 134 00:05:05,625 --> 00:05:08,904 things like, dangerous, arrhythmias and so forth. So 135 00:05:08,904 --> 00:05:10,665 that's been going on for a while. I 136 00:05:10,665 --> 00:05:12,585 think that the number of things that we 137 00:05:12,585 --> 00:05:14,605 can do now is is gonna increase. 138 00:05:14,970 --> 00:05:16,810 So what's really gonna have to happen is 139 00:05:16,810 --> 00:05:19,129 our ability to synthesize the data and to 140 00:05:19,129 --> 00:05:21,770 summarize it. So at Kaiser Permanente, we are 141 00:05:21,770 --> 00:05:24,889 looking at things like, continuous glucose monitoring for 142 00:05:24,889 --> 00:05:25,389 diabetics 143 00:05:26,009 --> 00:05:28,110 and really being able to, put that into, 144 00:05:28,970 --> 00:05:29,949 graphs and algorithms 145 00:05:30,394 --> 00:05:32,235 that are able to alert us to changes 146 00:05:32,235 --> 00:05:33,995 in therapy in the in the therapy of 147 00:05:33,995 --> 00:05:34,654 the patient. 148 00:05:34,955 --> 00:05:37,055 And we're also looking at home based monitoring 149 00:05:37,194 --> 00:05:38,814 for things like o two sats 150 00:05:39,274 --> 00:05:41,834 and weight based care. So that's that's all 151 00:05:41,834 --> 00:05:44,199 the things we have, that are coming. The 152 00:05:44,199 --> 00:05:45,959 real crux of data is basically what to 153 00:05:45,959 --> 00:05:48,919 do with it. And so behind that really 154 00:05:48,919 --> 00:05:51,659 is the, is a need to really, really 155 00:05:51,720 --> 00:05:53,720 really to organize operations to be able to 156 00:05:53,720 --> 00:05:55,019 consume all this data. 157 00:05:55,894 --> 00:05:58,375 And as we talk about this great volume 158 00:05:58,375 --> 00:06:01,194 of data, AI adoption, all of these technological 159 00:06:01,495 --> 00:06:01,995 innovations, 160 00:06:02,295 --> 00:06:05,254 our burdens on our a IT staffs are 161 00:06:05,254 --> 00:06:06,394 becoming increasingly 162 00:06:06,935 --> 00:06:07,435 great. 163 00:06:08,389 --> 00:06:10,470 So I'd love to hear how you think 164 00:06:10,470 --> 00:06:12,949 health care organizations can better support both our 165 00:06:12,949 --> 00:06:15,189 IT and our clinical teams as we're carrying 166 00:06:15,189 --> 00:06:17,909 out innovation efforts, and if you've seen any 167 00:06:17,909 --> 00:06:19,610 common pitfalls in this area. 168 00:06:19,985 --> 00:06:23,024 Yeah. It's a it's, it's, it's becoming a 169 00:06:23,024 --> 00:06:24,464 a big question. You know, there are a 170 00:06:24,464 --> 00:06:26,064 lot of things that are coming out. We 171 00:06:26,064 --> 00:06:27,444 call them bright shiny objects, 172 00:06:28,225 --> 00:06:30,865 from IT and, from devices and products that 173 00:06:30,865 --> 00:06:33,040 people are seeing. And the real question we 174 00:06:33,040 --> 00:06:35,040 have to ask ourselves is is really, 175 00:06:35,680 --> 00:06:37,460 what problem are we trying to solve? 176 00:06:37,920 --> 00:06:39,680 And I think that in health care, that 177 00:06:39,680 --> 00:06:42,080 is a really, big challenge to really to 178 00:06:42,080 --> 00:06:43,680 start off with that. Like, you know, what 179 00:06:43,680 --> 00:06:45,600 are we actually trying to solve with these 180 00:06:45,600 --> 00:06:47,615 tools? I think that actually will help out 181 00:06:47,615 --> 00:06:49,375 our IT colleagues a lot because then they 182 00:06:49,375 --> 00:06:50,814 will begin to know what to focus in 183 00:06:50,814 --> 00:06:54,115 on. There's another, kind of phenomenon that's emerging, 184 00:06:54,334 --> 00:06:56,595 and that is the the phenomenon of technology, 185 00:06:57,535 --> 00:06:58,035 becoming, 186 00:06:58,735 --> 00:06:59,555 more capable 187 00:06:59,860 --> 00:07:02,199 and available than what we can possibly consume. 188 00:07:02,819 --> 00:07:04,980 So there are 2 concepts that we're looking 189 00:07:04,980 --> 00:07:06,360 into, and that is basically, 190 00:07:06,900 --> 00:07:10,580 technology being a push and, operations and business 191 00:07:10,580 --> 00:07:11,560 being a pull. 192 00:07:12,074 --> 00:07:14,014 So those have to start to harmonize. 193 00:07:14,555 --> 00:07:16,555 A lot of times, in when we start 194 00:07:16,555 --> 00:07:18,555 to think about delivery of care, there are 195 00:07:18,555 --> 00:07:19,995 things that we've done for a very long 196 00:07:19,995 --> 00:07:20,495 time. 197 00:07:20,875 --> 00:07:23,134 And we don't really go back to see 198 00:07:23,354 --> 00:07:24,875 if we can do them better. It's just 199 00:07:24,875 --> 00:07:26,414 the way we've always done it. 200 00:07:26,769 --> 00:07:28,069 So having technologies 201 00:07:28,529 --> 00:07:30,610 that have capabilities that are new, the bright 202 00:07:30,610 --> 00:07:33,409 shining object, is good if we introduce them 203 00:07:33,409 --> 00:07:34,889 in a way to to say, is there 204 00:07:34,889 --> 00:07:36,930 a way to make your operations more efficient 205 00:07:36,930 --> 00:07:38,310 than you would have ever thought? 206 00:07:39,185 --> 00:07:42,625 So viewing these, these technologies is actually very, 207 00:07:42,625 --> 00:07:44,944 very helpful. Ambi and Scribe is a good 208 00:07:44,944 --> 00:07:46,865 example of that. I can tell you countless 209 00:07:46,865 --> 00:07:47,365 doctors 210 00:07:47,665 --> 00:07:49,345 who saw this technology and said I would 211 00:07:49,345 --> 00:07:50,404 never use this. 212 00:07:51,120 --> 00:07:52,879 But the moment they started using it, the 213 00:07:52,879 --> 00:07:54,960 adoption goes through the roof. I I literally 214 00:07:54,960 --> 00:07:56,720 have not met a single person yet who 215 00:07:56,720 --> 00:07:58,879 hasn't said that they couldn't use ambient listening 216 00:07:58,879 --> 00:07:59,780 in some capacity. 217 00:08:00,800 --> 00:08:03,074 At the same time, the business pool has 218 00:08:03,074 --> 00:08:04,915 to be we have to be able to, 219 00:08:04,915 --> 00:08:06,995 on the operational side, really clearly define what 220 00:08:06,995 --> 00:08:08,514 we need so that we can go ahead 221 00:08:08,514 --> 00:08:10,754 and tell the technology. So you have to 222 00:08:10,754 --> 00:08:14,295 reconcile these two forces. 1 is a technology 223 00:08:14,435 --> 00:08:16,514 which we don't necessarily know what we're gonna 224 00:08:16,514 --> 00:08:17,335 use it for 225 00:08:17,680 --> 00:08:19,439 and finding ways that it can be used 226 00:08:19,439 --> 00:08:21,360 better. It it can help us better. And 227 00:08:21,360 --> 00:08:23,759 then really being able to define the operational 228 00:08:23,759 --> 00:08:24,979 needs so that the technologist 229 00:08:25,519 --> 00:08:26,740 can build it for us. 230 00:08:27,360 --> 00:08:29,599 And as we wrap our conversation up, what 231 00:08:29,599 --> 00:08:31,584 is your top piece of advice for health 232 00:08:31,584 --> 00:08:33,985 care leaders as they prepare for further advancements 233 00:08:33,985 --> 00:08:36,485 in technology and greater demands for care? 234 00:08:36,865 --> 00:08:39,585 You know, keeping your, your mind open to 235 00:08:39,585 --> 00:08:41,125 what technology can do, 236 00:08:41,504 --> 00:08:43,585 the biggest barrier will be around, 237 00:08:43,985 --> 00:08:45,600 adoption in my mind. 238 00:08:46,159 --> 00:08:47,759 You know, by nature, health care is a 239 00:08:47,759 --> 00:08:50,319 very conservative field. But at the same time, 240 00:08:50,319 --> 00:08:51,839 there are certain risks that I think we 241 00:08:51,839 --> 00:08:53,220 need to take with technologies 242 00:08:53,600 --> 00:08:55,600 as long as there's some backup plan. So 243 00:08:55,600 --> 00:08:57,519 that would be my biggest advice is being 244 00:08:57,519 --> 00:08:59,279 willing to take a chance, but also being 245 00:08:59,279 --> 00:09:01,514 able to develop the operations to catch the 246 00:09:01,514 --> 00:09:03,914 system if there's something that's wrong and being 247 00:09:03,914 --> 00:09:05,534 able to iterate and move faster. 248 00:09:06,315 --> 00:09:08,875 Absolutely. Well, doctor Nguyen, thanks so much for 249 00:09:08,875 --> 00:09:11,214 joining me today on the Becker's Healthcare podcast. 250 00:09:11,355 --> 00:09:13,514 Again, we are live at the 9th annual 251 00:09:13,514 --> 00:09:16,696 Health IT Digital Health and RCM conference. Thank 252 00:09:16,696 --> 00:09:17,436 you so 253 00:09:20,616 --> 00:09:20,901 much.