1 00:00:00,395 --> 00:00:03,805 - This is Scott Becker with the Becker's Healthcare Podcast. 2 00:00:04,815 --> 00:00:07,525 We're thrilled today to visit with Dr. Brian Miller. 3 00:00:08,085 --> 00:00:09,365 Doctor's a a PhD. 4 00:00:10,075 --> 00:00:11,485 He's Executive Vice President 5 00:00:11,485 --> 00:00:13,285 and Chief Digital Officer of Intuitive. 6 00:00:13,955 --> 00:00:17,325 Intuitive is the world's leader in robotic surgery. 7 00:00:18,115 --> 00:00:22,725 It's got this incredible both footprint, foresight, and, 8 00:00:22,745 --> 00:00:25,485 and, and way of working with surgeons 9 00:00:25,505 --> 00:00:28,165 and systems to really provide 10 00:00:28,725 --> 00:00:30,725 advanced minimally invasive surgery. 11 00:00:31,345 --> 00:00:34,285 Uh, Dr. Miller, Brian's gonna talk to us today about sort 12 00:00:34,285 --> 00:00:37,285 of the role of Chief Digital Officer, the things 13 00:00:37,285 --> 00:00:38,325 that he's watching, 14 00:00:38,395 --> 00:00:40,405 what he's most excited about, and a lot more. 15 00:00:41,415 --> 00:00:43,605 Brian, could you take a moment and and, 16 00:00:43,625 --> 00:00:44,685 and introduce yourself 17 00:00:45,025 --> 00:00:47,805 and tell us a little bit about your background and, and, 18 00:00:47,805 --> 00:00:49,925 and sort of what, what are you most focused on? 19 00:00:51,335 --> 00:00:52,985 - Yeah. And, and Scott, thank you for having me. 20 00:00:52,985 --> 00:00:55,145 And it's, uh, it's great to, great to be here today. 21 00:00:55,525 --> 00:00:58,345 And so, uh, yeah, so just a little bit about my background. 22 00:00:58,585 --> 00:01:01,985 I was, uh, trained as an engineer, so a electrical 23 00:01:02,165 --> 00:01:03,465 and computer engineer. 24 00:01:03,925 --> 00:01:06,585 Uh, but early on in school, uh, was introduced 25 00:01:06,645 --> 00:01:09,705 to this concept of human machine interface or human 26 00:01:09,705 --> 00:01:11,745 and robot interface, which, um, at 27 00:01:11,745 --> 00:01:13,305 that time had nothing to do with surgery. 28 00:01:13,405 --> 00:01:14,665 It had nothing to do with healthcare. 29 00:01:15,085 --> 00:01:17,745 Uh, but it was fascinating to understand, 30 00:01:17,965 --> 00:01:21,465 and I was a controls engineer, understand how do you program 31 00:01:22,005 --> 00:01:24,825 and develop robots so that they could interact with, uh, 32 00:01:24,825 --> 00:01:27,105 with people, uh, to do things that were, 33 00:01:27,125 --> 00:01:28,145 uh, that were interesting. 34 00:01:28,145 --> 00:01:31,865 And so, um, so went, went through school and, and, uh, and, 35 00:01:31,865 --> 00:01:33,625 and that was the focus of, of my PhD, 36 00:01:34,155 --> 00:01:36,585 which was actually humans interacting 37 00:01:36,585 --> 00:01:38,705 with virtual environments across networks. 38 00:01:38,925 --> 00:01:41,545 So you had to deal with delay, you had to deal with a, 39 00:01:41,705 --> 00:01:43,025 a range of, of challenges. 40 00:01:43,565 --> 00:01:45,945 Um, and then I was really fortunate, got lucky, 41 00:01:45,955 --> 00:01:48,345 right when I was finishing my degree, uh, 42 00:01:48,405 --> 00:01:50,145 to meet an individual, uh, Dr. 43 00:01:50,255 --> 00:01:53,745 Yuan Wong, who had started Computer motion, um, uh, 44 00:01:53,955 --> 00:01:56,025 which was a company doing similar things 45 00:01:56,025 --> 00:01:57,105 to Intuitive at the time 46 00:01:57,725 --> 00:01:59,785 and developing, you know, surgical robots. 47 00:01:59,785 --> 00:02:02,345 And first time I heard about it, but, uh, but I jumped in 48 00:02:02,405 --> 00:02:06,385 and, and my first task was to, uh, program the robot and, 49 00:02:06,385 --> 00:02:08,025 and help us get FDA clearance so 50 00:02:08,025 --> 00:02:09,945 that it could be used on, on patients. 51 00:02:10,045 --> 00:02:13,065 And so, um, and so that was, that was the beginning. 52 00:02:13,205 --> 00:02:16,145 And, and for me, uh, what's so fascinating, uh, 53 00:02:16,145 --> 00:02:17,985 I've been now at Intuitive for 24 years. 54 00:02:18,365 --> 00:02:20,305 And, uh, and when people ask me, 55 00:02:20,455 --> 00:02:21,625 well, why do you keep doing it? 56 00:02:21,695 --> 00:02:24,985 It's, it's because of this intersection between technology, 57 00:02:25,405 --> 00:02:27,625 uh, and helping patients, and it's just fascinating. 58 00:02:27,625 --> 00:02:29,985 And I continue to learn things, um, every day. 59 00:02:31,375 --> 00:02:32,515 - So that, that's fascinating. 60 00:02:32,515 --> 00:02:34,955 So 24 years in Intuitive, that's amazing. 61 00:02:35,015 --> 00:02:36,955 And the, and the amount of growth that's been seen in 62 00:02:36,955 --> 00:02:38,675 that period of time is remarkable. 63 00:02:39,505 --> 00:02:41,875 Talk a little bit about, as you look at the sort of 64 00:02:42,625 --> 00:02:46,315 this intersection of digital technology, robotics, 65 00:02:47,245 --> 00:02:50,675 other issues, what are the big issues that, 66 00:02:50,675 --> 00:02:51,835 that you think about at night 67 00:02:51,835 --> 00:02:53,995 that might keep you up at night if you were worried about 68 00:02:53,995 --> 00:02:55,355 things or just excited about things? 69 00:02:55,355 --> 00:02:57,235 What keeps you up at night when you think about Yeah. 70 00:02:57,305 --> 00:02:59,485 Sort of robotics and digital and so forth. 71 00:03:00,385 --> 00:03:03,075 - Yeah, so what, what, what keeps me up at night, uh, uh, 72 00:03:03,075 --> 00:03:04,595 both, uh, as an excitement, 73 00:03:04,595 --> 00:03:08,075 but also as, uh, uh, you know, is, is is really trying 74 00:03:08,075 --> 00:03:11,275 to get things moving, is that it, it is clear, um, 75 00:03:11,545 --> 00:03:14,675 that the power of, of analytics and, uh, 76 00:03:14,695 --> 00:03:16,835 and the data that drives it, um, 77 00:03:16,935 --> 00:03:20,675 to really deeply understand, um, not only what's going on, 78 00:03:21,095 --> 00:03:22,875 um, but guide you to, uh, 79 00:03:22,875 --> 00:03:24,595 what you can do about it, uh, to improve. 80 00:03:24,655 --> 00:03:27,155 And so, uh, so what keeps me up at night is, 81 00:03:27,215 --> 00:03:28,475 is it's staring us in the face. 82 00:03:28,585 --> 00:03:29,915 It's, it's right in front of us 83 00:03:29,945 --> 00:03:31,755 that we can have a, a big impact. 84 00:03:32,135 --> 00:03:35,675 Um, but there are challenges in quality of data, uh, 85 00:03:36,035 --> 00:03:38,595 standards around being able to connect various data sets. 86 00:03:38,815 --> 00:03:42,235 Um, and once you have unique data like, uh, uh, 87 00:03:42,235 --> 00:03:44,675 things coming from the robotic platform, um, 88 00:03:44,675 --> 00:03:46,395 and these are signals that, uh, that, 89 00:03:46,395 --> 00:03:49,235 that don't exist anywhere else, we can measure, uh, 90 00:03:49,235 --> 00:03:51,995 how a surgeon is interacting, uh, with the instruments. 91 00:03:52,015 --> 00:03:54,315 And, and once you use those unique data sets 92 00:03:54,895 --> 00:03:57,715 and you start connecting those to, uh, clinical 93 00:03:57,715 --> 00:04:00,235 or operational outcomes, that can be really powerful. 94 00:04:00,495 --> 00:04:02,435 And, uh, and, and I just wanna go faster 95 00:04:02,435 --> 00:04:04,515 because of, of, of the value it can bring. 96 00:04:05,835 --> 00:04:07,545 - Thank you. And, and in the digital world, 97 00:04:07,815 --> 00:04:10,065 when you define digital health, it's one of these kinds 98 00:04:10,065 --> 00:04:12,625 of things today where there's, there's thousands 99 00:04:12,685 --> 00:04:15,585 of different definitions or different unique definitions. 100 00:04:16,135 --> 00:04:19,545 Talk a little bit about in, in the digital space, uh, about 101 00:04:19,685 --> 00:04:22,145 how you're sort of working with digital health 102 00:04:22,925 --> 00:04:25,905 to use data responsibly and, and try 103 00:04:25,905 --> 00:04:27,105 and improve patient outcomes. 104 00:04:27,165 --> 00:04:28,825 How do these things tie together with digital health? 105 00:04:30,055 --> 00:04:31,625 - Yeah, yeah. And so our, our, 106 00:04:31,625 --> 00:04:34,345 the way we view it in our approach is like everything 107 00:04:34,345 --> 00:04:37,225 that we do at Intuitive, you know, we start off by really, 108 00:04:37,485 --> 00:04:40,745 um, being clear about articulating what is the opportunity 109 00:04:41,165 --> 00:04:42,585 or the question you're trying to answer, 110 00:04:42,685 --> 00:04:44,065 or the problem that you're trying to solve. 111 00:04:44,205 --> 00:04:47,225 And, and, and the reason that that is so important, um, is 112 00:04:47,225 --> 00:04:50,945 because that will then lead, uh, to identifying 113 00:04:51,095 --> 00:04:53,465 what data is necessary, um, and, 114 00:04:53,465 --> 00:04:56,065 and drive the responsible use, uh, of that, 115 00:04:56,165 --> 00:04:57,305 uh, of that information. 116 00:04:57,405 --> 00:04:59,705 And so, um, when you go through and, 117 00:04:59,705 --> 00:05:03,025 and our approach is to really engage with customers, um, so 118 00:05:03,025 --> 00:05:06,305 that collaboratively we can identify, uh, what is the value 119 00:05:06,565 --> 00:05:08,585 of, uh, of, of using data 120 00:05:08,805 --> 00:05:10,825 and analyzing it and, and improving. 121 00:05:11,445 --> 00:05:13,265 Um, and so when you get there, 122 00:05:13,285 --> 00:05:15,745 and then when you start having to tackle the things 123 00:05:15,745 --> 00:05:18,785 that are really important around privacy and security, uh, 124 00:05:18,805 --> 00:05:21,025 and the measures that, that we take as a company 125 00:05:21,165 --> 00:05:23,105 and in collaboration with our customers, 126 00:05:23,165 --> 00:05:24,545 so we can address those concerns. 127 00:05:24,845 --> 00:05:27,305 If we've got the why we're doing it and, 128 00:05:27,305 --> 00:05:28,825 and the value that it will bring, 129 00:05:29,295 --> 00:05:31,825 then people get into problem solving modes and, 130 00:05:31,825 --> 00:05:34,185 and you can work through, uh, some of those challenges. 131 00:05:34,525 --> 00:05:35,905 And that's the approach that we've taken. 132 00:05:36,045 --> 00:05:37,945 And, and while you have to be really thoughtful 133 00:05:37,945 --> 00:05:40,145 and really careful about those types of things, 134 00:05:40,445 --> 00:05:42,945 if you get the why and you get the value, then we found 135 00:05:42,945 --> 00:05:44,065 that we, uh, we can move 136 00:05:44,065 --> 00:05:45,345 forward together with our customers. 137 00:05:46,945 --> 00:05:48,995 - Tell us a little bit about, you serve 138 00:05:48,995 --> 00:05:51,795 as Chief Digital Officer at the most advanced robotic 139 00:05:51,795 --> 00:05:52,875 company in the world. 140 00:05:53,865 --> 00:05:55,515 Talk a little bit about, at least the advanced, 141 00:05:55,515 --> 00:05:57,035 most advanced robotic surgery company, 142 00:05:57,170 --> 00:05:58,910 the World Digital Health Robotic Surgery. 143 00:06:00,065 --> 00:06:03,085 How do you work on supporting hospitals and health systems? 144 00:06:03,315 --> 00:06:06,005 What approaches, particularly at a time where hospitals, 145 00:06:06,005 --> 00:06:08,365 health systems are facing so many financial 146 00:06:08,365 --> 00:06:11,325 and staffing headwinds, uh, how do you go about trying 147 00:06:11,325 --> 00:06:12,285 to make sure you're supporting your 148 00:06:12,445 --> 00:06:13,045 hospitals and health systems? 149 00:06:13,965 --> 00:06:17,415 - Yeah, so our, our view, so we view the efforts that, 150 00:06:17,415 --> 00:06:20,855 that we decide to invest in, um, in, in the same way 151 00:06:20,855 --> 00:06:23,455 that customers look at their hospital, which is, uh, 152 00:06:23,815 --> 00:06:26,335 captured in, in what's called a quadruple aim, uh, 153 00:06:26,385 --> 00:06:28,895 which involves, uh, improving patient outcomes. 154 00:06:28,915 --> 00:06:30,455 That's, that's why we are all in this. 155 00:06:30,835 --> 00:06:35,335 Um, but also patient experience care, team experience, uh, 156 00:06:35,335 --> 00:06:37,895 and then ultimately, uh, you know, bringing that together 157 00:06:37,995 --> 00:06:40,415 to, uh, to reduce the, uh, the total cost to treat. 158 00:06:40,435 --> 00:06:44,375 And so, um, and so our approach in, in viewing, uh, 159 00:06:44,375 --> 00:06:46,855 the types of things that we do through that lens, you know, 160 00:06:46,855 --> 00:06:48,175 allows us to connect, uh, 161 00:06:48,175 --> 00:06:50,135 with our customers in areas that matter to them. 162 00:06:50,755 --> 00:06:52,695 Um, and, uh, and, 163 00:06:52,735 --> 00:06:54,295 and we're able to, uh, uh, 164 00:06:54,295 --> 00:06:56,335 to start putting an action plan together and, 165 00:06:56,335 --> 00:06:57,375 and moving down the path. 166 00:06:57,835 --> 00:06:59,855 Um, we have this concept that, uh, 167 00:06:59,855 --> 00:07:01,055 that we call the virtuous loop. 168 00:07:01,595 --> 00:07:03,855 And, uh, and, and it's, and it's powerful 169 00:07:03,855 --> 00:07:07,535 because what it allows you to do is once you have, uh, data 170 00:07:07,565 --> 00:07:10,855 that is, is high quality and it's the right data, um, 171 00:07:11,035 --> 00:07:12,815 and you go in and you start to extract 172 00:07:12,815 --> 00:07:14,215 what are those important insights 173 00:07:14,525 --> 00:07:16,015 that you can get from that data? 174 00:07:16,515 --> 00:07:18,095 Um, um, and, 175 00:07:18,095 --> 00:07:20,015 and then the next step that you take is you go, okay, 176 00:07:20,015 --> 00:07:21,055 well, what can we do about it? 177 00:07:21,275 --> 00:07:25,375 And so, um, so by providing an ability to go from data 178 00:07:25,635 --> 00:07:28,295 to insights and then ultimately action, um, 179 00:07:28,395 --> 00:07:32,615 but being able to see where, uh, uh, hospitals currently at 180 00:07:32,795 --> 00:07:34,375 so that they can measure and say, okay, 181 00:07:34,375 --> 00:07:35,615 how are we doing in this space? 182 00:07:35,955 --> 00:07:38,855 But then as they apply those actions, being able to track 183 00:07:38,855 --> 00:07:41,495 and monitor to make sure that they're improving, um, 184 00:07:41,685 --> 00:07:44,375 that has been an approach that has been, uh, uh, you know, 185 00:07:44,375 --> 00:07:45,695 very, uh, very important 186 00:07:45,695 --> 00:07:48,615 and very powerful, uh, as we engage with our customers, 187 00:07:48,615 --> 00:07:52,495 because then they can see how the various digital solutions 188 00:07:52,495 --> 00:07:55,735 that we offer are actually impacting, uh, their business, 189 00:07:55,735 --> 00:07:58,055 whether it's better clinical outcomes, um, 190 00:07:58,075 --> 00:07:59,815 or improving their operational efficiencies. 191 00:08:01,225 --> 00:08:02,655 - Thank you very much. And, and, 192 00:08:02,655 --> 00:08:06,895 and right now it's tremendous discussions around ai, 193 00:08:07,545 --> 00:08:11,135 generative ai, machine learning in so many terms 194 00:08:11,135 --> 00:08:14,015 that are newer to a lot of us, probably not newer to you, 195 00:08:14,035 --> 00:08:15,375 but newer to the rest of us. 196 00:08:17,155 --> 00:08:19,615 Why should people invest now in these concepts 197 00:08:19,715 --> 00:08:21,935 and these tools to help surgeries? 198 00:08:22,315 --> 00:08:23,495 Why is now the time? 199 00:08:24,085 --> 00:08:28,135 What are some of your thoughts around that, Brian? Yeah, 200 00:08:28,135 --> 00:08:29,775 - It's, it's a, it is a great question. 201 00:08:29,875 --> 00:08:32,215 Now, I'll, I'll start off, I'll go back to the, uh, 202 00:08:32,215 --> 00:08:33,415 the virtuous loop for a moment. 203 00:08:33,655 --> 00:08:35,495 'cause it will help, uh, it will help highlight that. 204 00:08:35,555 --> 00:08:38,015 And so that concept of, of the virtuous loop, 205 00:08:38,015 --> 00:08:40,535 we actually see three areas, um, that, 206 00:08:40,595 --> 00:08:41,735 uh, that we're focusing on. 207 00:08:41,875 --> 00:08:44,695 And, and we have heard from our customers that matter 208 00:08:44,715 --> 00:08:47,055 to them, and that's around improving outcomes. 209 00:08:47,515 --> 00:08:50,535 Um, and so using that data, finding insights and, 210 00:08:50,555 --> 00:08:51,615 and then those actions 211 00:08:51,635 --> 00:08:53,415 and closing that loop around, uh, 212 00:08:53,415 --> 00:08:54,415 improving patient outcomes. 213 00:08:55,205 --> 00:08:58,805 The second is, uh, um, uh, enabling personalized learning. 214 00:08:59,385 --> 00:09:01,645 And so this is, uh, leveraging those data 215 00:09:01,665 --> 00:09:04,525 and insights to be able to say, Hey, uh, if we want 216 00:09:04,525 --> 00:09:07,165 to engage in a continuous improvement program, um, 217 00:09:07,375 --> 00:09:09,245 where do we need to spend our time and energy? 218 00:09:09,465 --> 00:09:12,565 You know, surgeons and care teams, they are busy, uh, 219 00:09:12,585 --> 00:09:15,845 as you said, there is, uh, challenges in, in, uh, shortage 220 00:09:15,865 --> 00:09:17,205 of healthcare, uh, workers. 221 00:09:17,705 --> 00:09:20,205 Um, and so having very purposeful ways 222 00:09:20,355 --> 00:09:21,365 that they spend their time 223 00:09:21,385 --> 00:09:23,045 to improve is really, really important. 224 00:09:23,145 --> 00:09:25,925 And so that's the second. And the third one is, 225 00:09:26,345 --> 00:09:29,005 as you back up and look at just the overall, what it takes 226 00:09:29,025 --> 00:09:32,445 to deliver care, uh, is a range of, of things. 227 00:09:32,555 --> 00:09:34,285 It's not just what happens in the operating room, 228 00:09:34,545 --> 00:09:36,205 but it's what happens before and after. 229 00:09:36,265 --> 00:09:39,205 And so closing that loop around optimizing efficiency 230 00:09:39,385 --> 00:09:40,485 and the insights 231 00:09:40,485 --> 00:09:41,685 and the information that we can 232 00:09:41,685 --> 00:09:42,885 provide to help them do that. 233 00:09:42,985 --> 00:09:45,125 And so, so that's kind of the framing 234 00:09:45,305 --> 00:09:47,405 and the framework with which we think now, 235 00:09:47,405 --> 00:09:50,285 when you get into things like artificial intelligence 236 00:09:50,285 --> 00:09:53,885 and machine learning, I think for me, I view it as overall, 237 00:09:53,965 --> 00:09:56,525 I think it's really important for inve executives 238 00:09:56,525 --> 00:09:58,965 to invest in, in data-driven, uh, 239 00:09:59,345 --> 00:10:00,525 uh, continuous improvement. 240 00:10:00,785 --> 00:10:03,845 And, uh, and, and we've been able to see, uh, 241 00:10:03,845 --> 00:10:05,405 that when you look at it in that construct, 242 00:10:05,405 --> 00:10:06,405 you got high quality data, 243 00:10:06,505 --> 00:10:10,205 and it's the right data combined together that the insights 244 00:10:10,205 --> 00:10:12,285 that it can generate are truly meaningful, 245 00:10:12,385 --> 00:10:15,565 and they can start to see those improvements, uh, which help 246 00:10:15,595 --> 00:10:16,805 with some of the headwinds 247 00:10:16,805 --> 00:10:19,205 and some of the stresses that, uh, uh, that they have. 248 00:10:19,745 --> 00:10:22,925 Um, and ai and ml, uh, it's a tool, but, 249 00:10:22,925 --> 00:10:25,125 but it, it has helped us advance and, 250 00:10:25,465 --> 00:10:29,005 and, uh, tackle some of the more complex problems 251 00:10:29,155 --> 00:10:30,565 that have large data sets. 252 00:10:30,585 --> 00:10:32,565 And, and it's hard for humans or, 253 00:10:32,565 --> 00:10:34,645 and sometimes impossible for humans to be able 254 00:10:34,645 --> 00:10:37,645 to see the patterns or, or understand the, uh, the trends. 255 00:10:37,705 --> 00:10:40,485 And so, so that's why, in my opinion, they ought to invest, 256 00:10:40,505 --> 00:10:42,685 not because of AI and ml, uh, but it's 257 00:10:42,685 --> 00:10:45,405 because of this data driven continuous improvement 258 00:10:45,405 --> 00:10:46,885 that can, uh, that can be had. 259 00:10:46,905 --> 00:10:50,365 And so, just a quick example of, uh, of, of what we've seen. 260 00:10:50,465 --> 00:10:53,045 So, uh, we worked with Adventist Health, uh, in, 261 00:10:53,045 --> 00:10:55,445 in Simi Valley, uh, in, in Ventura, 262 00:10:55,445 --> 00:10:56,925 California, so Southern California. 263 00:10:57,225 --> 00:11:00,005 And, uh, what they were looking at is they were new 264 00:11:00,005 --> 00:11:02,565 to their program, it was, uh, about three years ago. 265 00:11:02,785 --> 00:11:05,845 And so, um, uh, they had three DA Vincis and, 266 00:11:05,905 --> 00:11:08,445 and 20 surgeons that were, uh, uh, becoming, 267 00:11:08,625 --> 00:11:09,845 uh, da Vinci surgeons. 268 00:11:10,265 --> 00:11:13,205 And, and they were noticing that they were, you know, 269 00:11:13,205 --> 00:11:15,765 losing patients to, uh, to other hospitals in the area. 270 00:11:15,865 --> 00:11:18,565 And so, uh, they wanted to understand 271 00:11:18,705 --> 00:11:19,925 how can they build their program 272 00:11:20,305 --> 00:11:22,125 and really start to show, uh, 273 00:11:22,125 --> 00:11:23,965 that they were doing it responsibly and, 274 00:11:23,965 --> 00:11:25,925 and that there was an IROI for, 275 00:11:25,945 --> 00:11:27,045 uh, for their healthcare system. 276 00:11:27,105 --> 00:11:30,965 And so, um, uh, in working with them, we started to apply, 277 00:11:31,465 --> 00:11:33,285 uh, some of our digital solutions from, 278 00:11:33,285 --> 00:11:36,765 from our digital portfolio to different areas, uh, 279 00:11:37,115 --> 00:11:40,005 that are required to build a healthy robotics program. 280 00:11:40,345 --> 00:11:43,165 And, um, and just to highlight a few, uh, 281 00:11:43,265 --> 00:11:46,645 we have Intuitive Hub, which is our edge compute device at 282 00:11:46,645 --> 00:11:49,805 the point of care inside of the operating room that allows 283 00:11:49,865 --> 00:11:52,805 for capturing of this rich data that that can be analyzed. 284 00:11:53,315 --> 00:11:56,205 It's also the conduit for bringing in, uh, information 285 00:11:56,205 --> 00:11:57,245 for clinical decisions. 286 00:11:57,245 --> 00:11:58,485 So we have telepresence 287 00:11:58,485 --> 00:12:01,125 where you can connect in an expert if you need a consult 288 00:12:01,305 --> 00:12:03,125 or you need, uh, a second opinion. 289 00:12:03,505 --> 00:12:06,405 Um, so they started to, they adopted that, uh, 290 00:12:06,405 --> 00:12:09,645 they also started using my Intuitive, which is a, uh, uh, 291 00:12:09,785 --> 00:12:12,205 an app with which surgeons can come on 292 00:12:12,225 --> 00:12:13,485 and they can understand. 293 00:12:13,585 --> 00:12:16,165 We give their data back to them, they can understand 294 00:12:16,225 --> 00:12:18,165 how they've done, where they're performing. 295 00:12:18,475 --> 00:12:21,445 They've got a timeline that shows them every step of the way 296 00:12:21,445 --> 00:12:23,925 during the procedure, when did I use this instrument? 297 00:12:23,955 --> 00:12:26,245 When did I do that? And they're able to use that 298 00:12:26,265 --> 00:12:27,565 and sit down with their care teams 299 00:12:27,585 --> 00:12:30,005 and go, okay, there's a point in time in the, 300 00:12:30,025 --> 00:12:33,165 in the procedure where we had, uh, there was no activity. 301 00:12:33,355 --> 00:12:34,565 What, what was going on? Did 302 00:12:34,565 --> 00:12:35,685 we not have the right instrument? 303 00:12:35,705 --> 00:12:36,885 Was somebody running down the hall? 304 00:12:36,945 --> 00:12:38,685 So they were able to break it down 305 00:12:39,025 --> 00:12:40,045 and start to understand 306 00:12:40,045 --> 00:12:41,925 where they had opportunities to improve. 307 00:12:42,225 --> 00:12:43,245 And then they started seeing 308 00:12:43,245 --> 00:12:45,285 that improvement in subsequent procedures. 309 00:12:45,745 --> 00:12:48,125 Um, they also started to activate, uh, learning, 310 00:12:48,465 --> 00:12:52,605 so giving the surgeons, uh, uh, access to tools 311 00:12:52,615 --> 00:12:54,885 where they could continuously do self-improvement. 312 00:12:55,105 --> 00:12:57,645 Uh, with our sim now, which is a virtual reality simulator 313 00:12:57,695 --> 00:13:00,405 where a surgeon can sit down and practice skills, drills 314 00:13:00,405 --> 00:13:02,405 and, and, uh, and techniques, um, 315 00:13:02,425 --> 00:13:04,885 and then access to remote proctoring where, uh, where 316 00:13:05,025 --> 00:13:08,805 as I mentioned before, they could bring in expertise into, 317 00:13:08,945 --> 00:13:10,205 uh, into the operating room. 318 00:13:10,585 --> 00:13:12,845 And finally they said, okay, let's look at our whole program 319 00:13:13,665 --> 00:13:14,885 and do analytics. 320 00:13:15,025 --> 00:13:16,325 We have, uh, um, uh, 321 00:13:16,325 --> 00:13:18,005 what we call our custom hospital analytics, 322 00:13:18,175 --> 00:13:20,365 where they could look across their entire surgery service 323 00:13:20,435 --> 00:13:23,845 line and understand how robotics was comparing to open 324 00:13:23,865 --> 00:13:25,885 and lap, uh, both clinically 325 00:13:25,885 --> 00:13:29,245 and operationally, uh, to see how things were improving and, 326 00:13:29,265 --> 00:13:32,125 and to see that the robotics program was, uh, uh, was, 327 00:13:32,145 --> 00:13:33,485 was improving quick, quickly. 328 00:13:34,265 --> 00:13:35,885 Um, and so when they looked at it 329 00:13:35,885 --> 00:13:37,045 and said, all right, now let's just see 330 00:13:37,045 --> 00:13:38,205 what are the, what are the outcomes? 331 00:13:38,235 --> 00:13:40,205 What, what are we seeing in our business impact? 332 00:13:40,545 --> 00:13:42,445 Um, they started to see 333 00:13:42,445 --> 00:13:43,925 that they were getting increased market share. 334 00:13:44,345 --> 00:13:46,565 Um, and so they were solving their initial problem 335 00:13:46,595 --> 00:13:48,245 that they wanted to, to, to solve. 336 00:13:48,675 --> 00:13:49,845 They were also lowering costs, 337 00:13:49,905 --> 00:13:52,325 so they were getting quicker in the operating room 338 00:13:52,645 --> 00:13:54,965 'cause they were taking out some of that, uh, idle time. 339 00:13:55,545 --> 00:13:57,085 And they also were looking saying, Hey, 340 00:13:57,085 --> 00:13:58,405 can I use this set of instruments? 341 00:13:58,405 --> 00:14:00,525 And they were able to control the cost of, of that. 342 00:14:00,585 --> 00:14:02,965 So they were getting that total cost to treat, 343 00:14:02,965 --> 00:14:04,085 that's part of the quad aim. 344 00:14:04,385 --> 00:14:07,525 And then finally, uh, they were a better, uh, uh, surgeon 345 00:14:07,585 --> 00:14:10,445 and, and care team experience by giving them access 346 00:14:10,445 --> 00:14:12,405 to those tools, uh, for self-improvement. 347 00:14:14,075 --> 00:14:17,305 - Thank you. Take a moment on this question. 348 00:14:17,365 --> 00:14:18,585 And, and bear with me for a second. 349 00:14:18,845 --> 00:14:23,025 So you did 25, 30 years ago, a master's in science 350 00:14:23,125 --> 00:14:25,265 and a PhD in mechanical engineering 351 00:14:25,845 --> 00:14:28,105 and robotics and haptics. 352 00:14:28,645 --> 00:14:31,465 And 25 years later, I mean, you did 353 00:14:31,465 --> 00:14:33,945 that at Northwestern brilliant academic institution. 354 00:14:34,325 --> 00:14:36,345 You've been in robotics for 25 plus years. 355 00:14:38,555 --> 00:14:39,835 I, I'll ask you two questions. 356 00:14:41,125 --> 00:14:43,675 First is, what are you most excited about 357 00:14:43,815 --> 00:14:46,755 for the future in terms of robotics and digital health? 358 00:14:47,455 --> 00:14:50,035 And the second question is, did you ever envision, 359 00:14:50,035 --> 00:14:52,445 because you got into robotics early when, 360 00:14:52,445 --> 00:14:53,965 when it was just in the evolving field, 361 00:14:54,945 --> 00:14:57,125 did you ever think the advances that have come 362 00:14:58,405 --> 00:15:00,425 to this point would come? 363 00:15:01,065 --> 00:15:02,505 I mean, how did you look at 25 years 364 00:15:02,505 --> 00:15:03,665 ago versus what you see today? 365 00:15:04,245 --> 00:15:05,625 And then what are you excited about for the future? 366 00:15:07,045 --> 00:15:10,335 - Yeah, so I'll, I'll start off yeah, with, with your, 367 00:15:10,355 --> 00:15:11,375 uh, your second question. 368 00:15:11,615 --> 00:15:13,895 I would love to be able to say 25 years ago 369 00:15:14,085 --> 00:15:16,615 that I could predict that we would be where we're at today 370 00:15:16,675 --> 00:15:18,215 and, and the future would look like this. 371 00:15:18,635 --> 00:15:21,575 Um, but, but I would say that, uh, uh, I, I, 372 00:15:21,815 --> 00:15:22,935 I did not predict it. 373 00:15:23,235 --> 00:15:26,295 And, uh, now it was, you know, a lot of people, uh, 374 00:15:26,435 --> 00:15:29,455 and a lot of hard work and, uh, and dedication 375 00:15:29,515 --> 00:15:30,815 and focus on doing it. 376 00:15:31,115 --> 00:15:33,335 Um, and so when I look back going, Hey, I, 377 00:15:33,455 --> 00:15:35,935 I can see why this much progress has been made 378 00:15:35,955 --> 00:15:38,935 and the impact on patients is, uh, has, has been seen. 379 00:15:39,395 --> 00:15:41,255 Um, but, but it is some, uh, 380 00:15:41,315 --> 00:15:43,335 un unbelievably remarkable things that, uh, 381 00:15:43,335 --> 00:15:44,695 that the teams have been doing over the years. 382 00:15:44,755 --> 00:15:48,895 And so I, I definitely did not, uh, think 25 years, uh, uh, 383 00:15:49,075 --> 00:15:51,095 ago that we would be sitting here where we're sitting now, 384 00:15:51,235 --> 00:15:54,575 um, which, which makes me, then as I look to the future, go, 385 00:15:54,635 --> 00:15:56,975 man, um, I think it's gonna be very different than 386 00:15:56,975 --> 00:15:58,215 what I can envision today. 387 00:15:58,555 --> 00:16:00,735 Um, now I've got 25 years of experience and, 388 00:16:00,735 --> 00:16:03,575 and a little bit more, uh, uh, a little bit more, uh, uh, 389 00:16:03,575 --> 00:16:04,775 knowledge about the space. 390 00:16:05,315 --> 00:16:06,495 Um, but, uh, 391 00:16:06,495 --> 00:16:08,375 but I, I think, you know, next 25 years 392 00:16:08,375 --> 00:16:09,415 are gonna be unbelievable. 393 00:16:09,605 --> 00:16:12,215 There's, there's two areas where I am, uh, 394 00:16:12,215 --> 00:16:15,655 really excited about and, uh, and excited to see the impact. 395 00:16:15,795 --> 00:16:17,895 Uh, 'cause teams are working on these things today. 396 00:16:17,995 --> 00:16:20,975 And, and, and the first one is what I alluded to, uh, 397 00:16:20,975 --> 00:16:23,175 with regard to that personalized learning. 398 00:16:23,515 --> 00:16:25,335 And when you think about, you know, 399 00:16:25,335 --> 00:16:28,695 we've done over 12 million million procedures, uh, uh, 400 00:16:28,875 --> 00:16:30,615 to date with, uh, with Da Vinci 401 00:16:30,795 --> 00:16:32,055 and capturing 402 00:16:32,055 --> 00:16:34,375 that rich data over those 12 million procedures. 403 00:16:34,375 --> 00:16:36,815 And that continues to grow every single day, uh, 404 00:16:36,875 --> 00:16:41,055 as we do procedures, um, uh, that knowledge of here is 405 00:16:41,055 --> 00:16:43,055 what was done, here's the technique, 406 00:16:43,205 --> 00:16:44,775 here is the outcome for the patient. 407 00:16:44,995 --> 00:16:48,175 And, and the learning over that, being able to harness that 408 00:16:48,555 --> 00:16:51,295 and then deliver that back to surgeons 409 00:16:51,295 --> 00:16:54,495 that are early in their career going, look here is, 410 00:16:54,525 --> 00:16:57,095 here are best practices, here is the way to do things, 411 00:16:57,475 --> 00:16:58,575 um, is just powerful. 412 00:16:58,635 --> 00:17:01,095 And, and in the age of compute, uh, 413 00:17:01,155 --> 00:17:04,775 and things that are always online, uh, the ability to spread 414 00:17:04,775 --> 00:17:06,455 that throughout the world very quickly 415 00:17:06,715 --> 00:17:07,935 is, is extremely exciting. 416 00:17:07,935 --> 00:17:09,215 And so that will continue to grow. 417 00:17:09,995 --> 00:17:14,575 The second, um, is, uh, uh, you know, moving into a, 418 00:17:14,735 --> 00:17:18,295 a realm of being able to give surgeons information 419 00:17:18,835 --> 00:17:21,375 in real time, why they're doing the procedure 420 00:17:21,405 --> 00:17:22,455 that they've never had before. 421 00:17:23,495 --> 00:17:26,675 So this is the ability to go in and see beneath tissue. 422 00:17:26,935 --> 00:17:29,595 So advanced imaging technologies where you can, uh, 423 00:17:29,595 --> 00:17:30,995 where you can see the beneath tissue, 424 00:17:31,095 --> 00:17:33,275 you can identify structures that you can't see. 425 00:17:33,775 --> 00:17:34,835 Um, and these are things 426 00:17:34,835 --> 00:17:37,555 that will not only reduce complications in surgery, 427 00:17:37,815 --> 00:17:39,875 but have the potential to eliminate 'em, 428 00:17:39,985 --> 00:17:41,995 because you can see 'em, you can avoid 'em. 429 00:17:42,295 --> 00:17:45,715 And so that is a, a, an area that will continue to grow. 430 00:17:46,175 --> 00:17:48,755 Um, but I, I'm really excited about what we can do 431 00:17:49,065 --> 00:17:51,925 and in, in kind of this next, uh, this next phase 432 00:17:52,265 --> 00:17:54,845 of being able to really drive better patient outcomes. 433 00:17:56,225 --> 00:17:59,575 - Brian, Dr. Miller, thank you so much. 434 00:17:59,765 --> 00:18:02,215 What a, what a fascinating field you ended up being in the 435 00:18:02,215 --> 00:18:05,295 leadership of at, at the leading robotics company, 436 00:18:05,975 --> 00:18:07,215 surgical robotics company in the world. 437 00:18:07,375 --> 00:18:10,495 Intuitive. Thank you so much for sharing some 438 00:18:10,495 --> 00:18:11,495 of your thoughts with us today. 439 00:18:11,495 --> 00:18:13,895 What a pleasure. I always learn something when I talk to 440 00:18:14,455 --> 00:18:17,335 yourself and people from intuitive fastening, 441 00:18:17,335 --> 00:18:18,935 what you're doing, 12,000, 442 00:18:18,935 --> 00:18:20,935 12 million procedures so far. Is that what I heard? 443 00:18:21,685 --> 00:18:22,895 - Yeah, 12 million and counting. 444 00:18:23,905 --> 00:18:26,605 - That's an amazing number. Who would've thunk it? 445 00:18:27,175 --> 00:18:28,765 Thank you so much for joining us today. 446 00:18:29,695 --> 00:18:30,645 - Thank you for having me.