1 00:00:02,759 --> 00:00:09,040 Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News. I'm here with the 2 00:00:09,080 --> 00:00:12,880 Speaker 1: CEO of GE Healthcare, Peter Rdueni. Peter, great to see 3 00:00:12,880 --> 00:00:13,800 Speaker 1: you in person. 4 00:00:13,600 --> 00:00:15,000 Speaker 2: Katie, thank you for having me on. 5 00:00:15,440 --> 00:00:17,200 Speaker 1: Let's start with the news of this morning, and that 6 00:00:17,320 --> 00:00:20,480 Speaker 1: is that GE Healthcare has signed a seven year partnership 7 00:00:20,680 --> 00:00:24,239 Speaker 1: with Sutter Health to provide aipowered medical technology and software 8 00:00:24,320 --> 00:00:28,600 Speaker 1: upgrades to the California nonprofit health system, expected to generate 9 00:00:28,680 --> 00:00:32,080 Speaker 1: a billion dollars in revenue over the life of this partnership. 10 00:00:32,360 --> 00:00:35,280 Speaker 1: Talk to us a little bit more about this particular 11 00:00:35,400 --> 00:00:37,559 Speaker 1: tie up and whether we should expect to see more 12 00:00:37,600 --> 00:00:38,240 Speaker 1: from you guys. 13 00:00:38,680 --> 00:00:40,800 Speaker 2: Yeah, no, well, thank you very much. You know, we're 14 00:00:40,880 --> 00:00:44,519 Speaker 2: super excited to work with many of our customers and partners, 15 00:00:44,520 --> 00:00:47,760 Speaker 2: but in this case with Sutter Health, as you may know, 16 00:00:48,000 --> 00:00:51,080 Speaker 2: one of the largest, really largest systems in Northern California, 17 00:00:51,120 --> 00:00:53,600 Speaker 2: but one of the top ten in this country, and 18 00:00:53,680 --> 00:00:56,200 Speaker 2: it's been a big focus of ours where we make 19 00:00:56,480 --> 00:01:01,080 Speaker 2: lots of critical equipment that's used for diagnosis, services, training, 20 00:01:01,240 --> 00:01:03,160 Speaker 2: and what we've been pivoting on is how do you 21 00:01:03,200 --> 00:01:05,959 Speaker 2: integrate all of those to do what we call deliver 22 00:01:06,080 --> 00:01:09,280 Speaker 2: precision care. And so just at this conference, you hear 23 00:01:09,280 --> 00:01:12,240 Speaker 2: about all these new devices and drugs, many of the 24 00:01:12,240 --> 00:01:15,399 Speaker 2: things that enable those we make, and so this relationship 25 00:01:15,760 --> 00:01:18,440 Speaker 2: will really refresh all of their system I think over 26 00:01:18,560 --> 00:01:22,560 Speaker 2: three hundred locales that are opening outpatient centers all over 27 00:01:22,640 --> 00:01:24,680 Speaker 2: and the exciting part is for the three and a 28 00:01:24,760 --> 00:01:27,600 Speaker 2: half four million patients that they take care of, they're 29 00:01:27,600 --> 00:01:28,920 Speaker 2: going to have state of the art equipment. 30 00:01:29,200 --> 00:01:31,880 Speaker 1: Let's talk a little bit more about the AI powered piece, 31 00:01:31,959 --> 00:01:34,480 Speaker 1: because we talk about AI from all angles, and the 32 00:01:34,560 --> 00:01:37,560 Speaker 1: question we always ask is what is the application? But 33 00:01:37,680 --> 00:01:40,600 Speaker 1: you think about medical technology, it seems like that would 34 00:01:40,640 --> 00:01:42,640 Speaker 1: be a bit of a natural fit. YEA. 35 00:01:42,959 --> 00:01:45,880 Speaker 2: Our industry is one of the industries I think that's 36 00:01:45,920 --> 00:01:48,520 Speaker 2: really grasping it in all aspects of it. But from 37 00:01:48,560 --> 00:01:51,320 Speaker 2: a ge healthcare standpoint, we kind of think about it 38 00:01:51,320 --> 00:01:53,800 Speaker 2: in three areas. The first part is kind of AI insides. 39 00:01:53,880 --> 00:01:56,400 Speaker 2: If you look at all of our products at this 40 00:01:56,520 --> 00:01:59,520 Speaker 2: point coming out, there's some embedded AI and that either 41 00:01:59,560 --> 00:02:03,400 Speaker 2: means better productivity, you can get more scans or studies done, 42 00:02:03,680 --> 00:02:06,800 Speaker 2: or it actually helps pinpoint or actually help a physician 43 00:02:06,960 --> 00:02:10,120 Speaker 2: with a diagnosis. Those are the first two second areas. 44 00:02:10,120 --> 00:02:13,000 Speaker 2: In like a departmental do you think about labor and 45 00:02:13,040 --> 00:02:16,200 Speaker 2: delivery department or radiology, how do you run it more effectively? 46 00:02:16,240 --> 00:02:19,280 Speaker 2: In that case, it's about moving data for the right decisions. 47 00:02:19,520 --> 00:02:22,080 Speaker 2: And then Enterprise, we actually have a product called Command 48 00:02:22,120 --> 00:02:25,840 Speaker 2: Center which actually helps an institution manage the flow of patients. 49 00:02:25,880 --> 00:02:28,000 Speaker 2: And I think this is again just the beginning of 50 00:02:28,040 --> 00:02:30,160 Speaker 2: where this is happening, and this will be part of 51 00:02:30,200 --> 00:02:32,239 Speaker 2: our relationship with Sutter as well. 52 00:02:32,560 --> 00:02:35,799 Speaker 1: I'm curious about the impact you see on the workforce. 53 00:02:35,960 --> 00:02:38,680 Speaker 1: You know, as you know very well, there's a clinician 54 00:02:39,280 --> 00:02:42,560 Speaker 1: shortage of sorts. How do you see these AI tools 55 00:02:42,600 --> 00:02:46,000 Speaker 1: possibly changing the workforce when it comes to the health system. 56 00:02:46,280 --> 00:02:48,480 Speaker 2: Yeah, I think it's a couple. It's a great question. 57 00:02:48,639 --> 00:02:50,760 Speaker 2: I think the first part is the more you can 58 00:02:50,840 --> 00:02:54,320 Speaker 2: make these products automate many tasks that really are not 59 00:02:54,520 --> 00:02:57,120 Speaker 2: value added. That's a first step, and you know we're 60 00:02:57,120 --> 00:02:59,480 Speaker 2: doing that, other companies are doing that. That says the 61 00:02:59,520 --> 00:03:02,640 Speaker 2: precious time of the technologists or the nurse or the 62 00:03:02,680 --> 00:03:06,079 Speaker 2: caregiver can be on those critical things that only a 63 00:03:06,160 --> 00:03:08,200 Speaker 2: human really can make the difference on. I think those 64 00:03:08,200 --> 00:03:11,680 Speaker 2: are the first steps. Broadly, though, these technologies are going 65 00:03:11,760 --> 00:03:15,280 Speaker 2: to open up to other users that typically haven't used 66 00:03:15,280 --> 00:03:18,560 Speaker 2: the device because there's been too much expertise to enable 67 00:03:18,600 --> 00:03:20,840 Speaker 2: them to actually use it. And so I think this 68 00:03:21,000 --> 00:03:24,000 Speaker 2: labor shortage that we're feeling, and we play a part 69 00:03:24,000 --> 00:03:27,280 Speaker 2: of helping training and development, but the tools themselves are 70 00:03:27,280 --> 00:03:31,000 Speaker 2: going to actually make things more accessible to more users. 71 00:03:31,560 --> 00:03:34,200 Speaker 1: And I'm curious, I mean, do you think that you 72 00:03:34,200 --> 00:03:36,440 Speaker 1: think about all the different areas that you touch, of 73 00:03:36,440 --> 00:03:41,280 Speaker 1: course at GE Healthcare, from ultrasounds to imaging, ventilators, diagnostics. 74 00:03:41,360 --> 00:03:44,120 Speaker 1: Do you think that AI will ultimately touch all of 75 00:03:44,160 --> 00:03:46,920 Speaker 1: those areas, infiltrate all of those areas or are there 76 00:03:46,920 --> 00:03:50,080 Speaker 1: any certain sectors or parts of your business that you 77 00:03:50,120 --> 00:03:51,920 Speaker 1: think will always be. 78 00:03:51,760 --> 00:03:56,760 Speaker 2: Human Well, I think I think the beautiful thing about 79 00:03:56,800 --> 00:03:59,640 Speaker 2: AI relative to this combo, I think is this combination 80 00:03:59,760 --> 00:04:02,640 Speaker 2: of the human touch factor of care right it is 81 00:04:02,760 --> 00:04:06,840 Speaker 2: one to one patient clinician relationship. I think AI is 82 00:04:06,840 --> 00:04:08,560 Speaker 2: going to ultimately help free up more time. 83 00:04:08,440 --> 00:04:08,920 Speaker 1: To do that. 84 00:04:09,440 --> 00:04:11,440 Speaker 2: And so when we think about there's clearly in our 85 00:04:11,480 --> 00:04:15,160 Speaker 2: portfolio modalities as we call them, that will first be 86 00:04:15,200 --> 00:04:18,080 Speaker 2: more affected because of the nature of it, but it'll evolve. 87 00:04:18,200 --> 00:04:21,600 Speaker 2: So I mean a specific example, like I mentioned is 88 00:04:21,640 --> 00:04:24,720 Speaker 2: an MRI, the ability to actually change actually how the 89 00:04:25,080 --> 00:04:28,520 Speaker 2: product makes an image first time in so thirty forty years, 90 00:04:28,560 --> 00:04:32,159 Speaker 2: which actually makes it go significantly faster. On the other side, 91 00:04:32,240 --> 00:04:35,200 Speaker 2: all the patient monitoring in a hospital, all of that 92 00:04:35,320 --> 00:04:38,600 Speaker 2: data today really isn't used. If you can actually predict 93 00:04:38,680 --> 00:04:41,160 Speaker 2: if you're actually in a hospital ward you may need 94 00:04:41,200 --> 00:04:44,039 Speaker 2: a nurse and actually call them before you actually have 95 00:04:44,080 --> 00:04:47,839 Speaker 2: an issue, that's a significant improvement for that clinician taking 96 00:04:47,839 --> 00:04:50,200 Speaker 2: care of you, and it frees up capacity. All those 97 00:04:50,240 --> 00:04:52,960 Speaker 2: are different variations of how we think AI is going 98 00:04:53,040 --> 00:04:54,960 Speaker 2: to help change care delivery for the better. 99 00:04:55,360 --> 00:04:58,159 Speaker 1: So this is a partnership that you signed with Sutter Health. 100 00:04:58,440 --> 00:05:01,840 Speaker 1: How are you balancing partner ships versus potential M and 101 00:05:01,880 --> 00:05:03,880 Speaker 1: A because there is a lot of optimism when it 102 00:05:03,920 --> 00:05:05,400 Speaker 1: comes to merger activity. Yeah. 103 00:05:05,680 --> 00:05:07,760 Speaker 2: Look, and we just had our investor day, you know, 104 00:05:07,839 --> 00:05:09,880 Speaker 2: Katie a few months back, and we talked about M 105 00:05:09,920 --> 00:05:11,520 Speaker 2: and A is going to be a very important part. 106 00:05:12,360 --> 00:05:14,880 Speaker 2: We're excited about twenty twenty five and beyond in the 107 00:05:14,960 --> 00:05:18,040 Speaker 2: environment that we're seeing around the world. So tuck in 108 00:05:18,320 --> 00:05:20,200 Speaker 2: M and A for us makes a lot of sense. 109 00:05:20,279 --> 00:05:22,279 Speaker 2: The breath of the company we have, we have lots 110 00:05:22,279 --> 00:05:25,440 Speaker 2: of opportunities to i'd say, fill out the solution for 111 00:05:25,600 --> 00:05:28,320 Speaker 2: customers so that there's a better end to end capability. 112 00:05:28,560 --> 00:05:31,480 Speaker 2: And then on the customer side, these type of relationships, 113 00:05:31,720 --> 00:05:35,039 Speaker 2: we see more and more customers wanting to have not 114 00:05:35,080 --> 00:05:38,640 Speaker 2: a relationship of a transactive one, but a real partnership 115 00:05:38,680 --> 00:05:41,559 Speaker 2: where we're actually getting our hands dirty to help solve 116 00:05:41,640 --> 00:05:45,040 Speaker 2: some of their challenges. And you know, we've done over 117 00:05:45,040 --> 00:05:47,000 Speaker 2: one hundred and twenty of these. It's been about five 118 00:05:47,040 --> 00:05:49,840 Speaker 2: billion since we've spun out, but obviously this has a 119 00:05:49,920 --> 00:05:52,680 Speaker 2: billion dollars by itself represents you know, one of the 120 00:05:52,760 --> 00:05:54,080 Speaker 2: largest that we've ever done. 121 00:05:54,400 --> 00:05:59,080 Speaker 1: Yeah. Absolutely, since spent off, this partnership quite large. Let's 122 00:05:59,120 --> 00:06:01,039 Speaker 1: talk a little bit more about your investor day. It 123 00:06:01,080 --> 00:06:03,080 Speaker 1: was interesting you take a look at the details. It 124 00:06:03,120 --> 00:06:04,719 Speaker 1: seems like there was a lot of focus, of course, 125 00:06:04,720 --> 00:06:08,599 Speaker 1: on the pharmaceutical diagnostic segment. I know that's your fastest 126 00:06:08,640 --> 00:06:12,680 Speaker 1: growing segment segment, and a lot of focus on imaging 127 00:06:12,800 --> 00:06:16,520 Speaker 1: agents for example. How do you expect that that market 128 00:06:16,600 --> 00:06:19,000 Speaker 1: will change over the next five years or so. 129 00:06:19,360 --> 00:06:21,680 Speaker 2: Yeah, So one of the exciting things, and that's being 130 00:06:21,720 --> 00:06:24,760 Speaker 2: discussed by a lot of pharmaceutical companies here at the 131 00:06:24,800 --> 00:06:29,640 Speaker 2: conference is this evolution of radio pharmaceuticals used in therapy. 132 00:06:29,720 --> 00:06:32,880 Speaker 2: So we are a diagnostic company, not a therapy company. 133 00:06:32,880 --> 00:06:35,960 Speaker 2: But these drugs that are arising, and they basically are 134 00:06:36,000 --> 00:06:39,520 Speaker 2: a radioactive tracer that goes to a cancer cell actually 135 00:06:39,520 --> 00:06:43,159 Speaker 2: helps eliminate the cancer and doesn't hurt the good sales 136 00:06:43,200 --> 00:06:46,120 Speaker 2: around it. We have the equipment that actually helps what 137 00:06:46,200 --> 00:06:49,080 Speaker 2: clinicians would say, see what you treat, and treat what 138 00:06:49,120 --> 00:06:52,600 Speaker 2: you see. And also a host of the diagnostic agents. 139 00:06:52,680 --> 00:06:54,960 Speaker 2: One that we spoke at Investor Days actually on the 140 00:06:55,000 --> 00:06:59,200 Speaker 2: cardiology side called Ficcado, and what it's used for is 141 00:06:59,240 --> 00:07:02,760 Speaker 2: in a PET scan to do cardiac profusion and it 142 00:07:02,800 --> 00:07:06,800 Speaker 2: will replace products that have been used in older systems 143 00:07:06,880 --> 00:07:11,480 Speaker 2: with higher specificity and sensitivity, which ultimately means a better diagnosis. 144 00:07:11,480 --> 00:07:14,960 Speaker 2: And that's actually launching this March March April. So we're 145 00:07:15,000 --> 00:07:19,440 Speaker 2: super excited about Fricado and this pet cardiology market area. 146 00:07:19,800 --> 00:07:21,679 Speaker 1: And Peter, I only have time for one more question, 147 00:07:21,800 --> 00:07:23,400 Speaker 1: and I want to go to China. Of course, you 148 00:07:23,440 --> 00:07:27,280 Speaker 1: acknowledge that there's been weakness in China on your third 149 00:07:27,360 --> 00:07:30,160 Speaker 1: quarter earnings call, and that's one of the lingering questions. 150 00:07:30,200 --> 00:07:33,760 Speaker 1: I would say, over your stock that China recovery. What 151 00:07:33,960 --> 00:07:35,480 Speaker 1: is your viewpoint right now? 152 00:07:36,200 --> 00:07:39,720 Speaker 2: Yeah, Well, first of all, i'd say overall, we're optimistic 153 00:07:39,760 --> 00:07:42,760 Speaker 2: about twenty five for the whole globe. I think US 154 00:07:43,200 --> 00:07:46,080 Speaker 2: EU a lot of things China. I think my views 155 00:07:46,080 --> 00:07:48,400 Speaker 2: haven't changed from what I've said to Investor Day, which 156 00:07:48,440 --> 00:07:51,360 Speaker 2: is we're bullish on the future of China. It will 157 00:07:51,400 --> 00:07:54,640 Speaker 2: be one of the largest, if not the largest healthcare 158 00:07:54,680 --> 00:07:56,800 Speaker 2: market in the world at some point down the road. 159 00:07:57,200 --> 00:07:58,960 Speaker 2: We believe the first half is going to be a 160 00:07:59,000 --> 00:08:02,040 Speaker 2: little bit more subdued dude as stimulus and some of 161 00:08:02,080 --> 00:08:04,480 Speaker 2: the other programs they have get work through. But we're 162 00:08:04,520 --> 00:08:07,720 Speaker 2: optimistic that the second half of twenty twenty five we 163 00:08:07,840 --> 00:08:10,560 Speaker 2: start to see the recovery, and then twenty six twenty 164 00:08:10,600 --> 00:08:13,400 Speaker 2: seven beyond that it gets back to a more normative 165 00:08:13,480 --> 00:08:14,679 Speaker 2: rate of growth. 166 00:08:14,800 --> 00:08:16,440 Speaker 1: All right, Peter, that's a good place to leave it. 167 00:08:16,520 --> 00:08:17,920 Speaker 1: Really appreciate you taking the time. 168 00:08:18,120 --> 00:08:18,480 Speaker 2: Thank you. 169 00:08:18,920 --> 00:08:22,119 Speaker 1: That is Peter Arduini. He is the CEO of ge 170 00:08:22,200 --> 00:08:22,680 Speaker 1: Healthcare