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 00:00:09,679 --> 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 00:00:30,080 --> 00:00:32,240 This is Gracelyn Keller with the Becker's Health 11 00:00:32,240 --> 00:00:34,240 Care Podcast, and we are live at the 12 00:00:34,240 --> 00:00:37,620 9th Annual Health IT Digital Health and RCM 13 00:00:37,920 --> 00:00:38,420 Conference. 14 00:00:38,960 --> 00:00:41,600 I am joined right now by Rich Zane, 15 00:00:41,600 --> 00:00:44,145 who is the chief innovation officer at UCHealth. 16 00:00:44,284 --> 00:00:46,125 So, Rich, thanks so much for joining me. 17 00:00:46,125 --> 00:00:47,645 And to get us started, could you please 18 00:00:47,645 --> 00:00:49,804 share a little bit more about yourself, your 19 00:00:49,804 --> 00:00:51,104 background, and your role? 20 00:00:51,484 --> 00:00:53,325 Yeah. Thanks for having me. Really thrilled to 21 00:00:53,325 --> 00:00:55,245 be here. I'm Rich Zane. I'm the chief 22 00:00:55,245 --> 00:00:57,820 innovation officer for UCHealth, which is the University 23 00:00:57,820 --> 00:00:59,199 of Colorado Health System, 24 00:00:59,659 --> 00:01:03,039 14 hospital system based in Colorado, almost $9,000,000,000 25 00:01:03,500 --> 00:01:04,159 in revenue. 26 00:01:04,780 --> 00:01:07,099 My role as chief innovation officer is really 27 00:01:07,099 --> 00:01:07,920 to interface 28 00:01:08,459 --> 00:01:12,219 with technology companies solving pragmatic problems and building 29 00:01:12,219 --> 00:01:15,625 solutions and then participating in value creation. I 30 00:01:15,625 --> 00:01:17,224 also have another role as chair of the 31 00:01:17,224 --> 00:01:19,784 department of emergency medicine. So the lens by 32 00:01:19,784 --> 00:01:22,104 which I interact with these companies is really 33 00:01:22,104 --> 00:01:23,644 from the lens of a physician 34 00:01:23,944 --> 00:01:25,864 and what's best for our patients. So we're 35 00:01:25,864 --> 00:01:27,784 very patient centered in the way we adopt 36 00:01:27,784 --> 00:01:29,700 and utilize and deploy technology. 37 00:01:30,480 --> 00:01:32,400 Wonderful. Well, thanks for taking the time to 38 00:01:32,400 --> 00:01:34,100 be here. And first question, 39 00:01:34,480 --> 00:01:37,120 AI adoption is exploding in health care right 40 00:01:37,120 --> 00:01:38,640 now. So in your view, what is the 41 00:01:38,640 --> 00:01:41,540 most significant or promising application of this technology? 42 00:01:41,974 --> 00:01:44,534 And how is this informing your organization's innovation 43 00:01:44,534 --> 00:01:45,034 strategy? 44 00:01:45,734 --> 00:01:47,494 I think it's important that when you speak 45 00:01:47,494 --> 00:01:48,314 about AI, 46 00:01:48,935 --> 00:01:50,875 we understand what definitionally 47 00:01:51,254 --> 00:01:53,894 we're referring to. And I bet that almost 48 00:01:53,894 --> 00:01:55,814 everybody listening to this or here at this 49 00:01:55,814 --> 00:01:58,350 conference will have a different definition of what 50 00:01:58,350 --> 00:02:00,829 AI is. And the reality is that in 51 00:02:00,829 --> 00:02:03,650 health care, like most industries, we've been using 52 00:02:03,709 --> 00:02:06,049 AI for at least a decade. 53 00:02:06,590 --> 00:02:08,210 The hype curve has certainly 54 00:02:09,310 --> 00:02:12,534 increased and the curve is steeper than it's 55 00:02:12,534 --> 00:02:15,094 ever been. But I think what's really important 56 00:02:15,094 --> 00:02:16,775 when we think about AI is that we 57 00:02:16,775 --> 00:02:18,074 really think about intelligence. 58 00:02:18,694 --> 00:02:21,574 And just like AI, intelligence can mean everything 59 00:02:21,574 --> 00:02:23,735 and nothing. And to us, it means making 60 00:02:23,735 --> 00:02:26,909 better decisions in health care. So what AI 61 00:02:26,909 --> 00:02:29,469 will do is allow us to adjudicate almost 62 00:02:29,469 --> 00:02:30,530 infinity variables, 63 00:02:30,909 --> 00:02:31,730 make better 64 00:02:32,270 --> 00:02:34,770 decisions in health care, whether that's choosing pharmacotherapy 65 00:02:35,069 --> 00:02:35,730 at the bedside, 66 00:02:36,189 --> 00:02:39,810 deploying capital, organizing operating rooms, infusion centers, 67 00:02:40,425 --> 00:02:43,465 more accurately doing revenue cycle. That's what AI 68 00:02:43,465 --> 00:02:45,085 is to us. How it's deployed 69 00:02:45,625 --> 00:02:47,724 is just simply math, not magic. 70 00:02:48,905 --> 00:02:50,765 And on a daily basis, health care leaders 71 00:02:50,765 --> 00:02:50,925 are managing greater volumes of data and more 72 00:02:50,925 --> 00:02:51,085 devices across a growing number of care settings. 73 00:02:51,085 --> 00:02:51,645 So in this complex 74 00:02:52,185 --> 00:02:52,685 environment, 75 00:02:53,580 --> 00:02:55,280 growing number of care settings. 76 00:02:55,580 --> 00:02:55,659 So in this complex environment, what clinical data 77 00:02:55,659 --> 00:02:56,726 integration tools or practices are you seeing drive 78 00:02:56,726 --> 00:02:58,699 improvements in patient outcomes? And can you share 79 00:02:58,699 --> 00:02:59,759 a specific example of 80 00:03:00,060 --> 00:03:01,520 that? I would 81 00:03:01,819 --> 00:03:02,560 love to. 82 00:03:06,724 --> 00:03:09,044 So when we think about integration, we think 83 00:03:09,044 --> 00:03:09,865 about workflows. 84 00:03:10,245 --> 00:03:11,305 And when providers 85 00:03:11,844 --> 00:03:14,645 deliver care, we have some guiding principles about 86 00:03:14,645 --> 00:03:16,645 how we do that. One is we will 87 00:03:16,645 --> 00:03:18,885 never make a provider leave their workflow. And 88 00:03:18,885 --> 00:03:21,205 for us, our workflow is our electronic health 89 00:03:21,205 --> 00:03:24,219 record. The other is the adoption of tools 90 00:03:24,280 --> 00:03:26,200 cannot make it harder, has to make it 91 00:03:26,200 --> 00:03:28,200 easier, has to be the path of least 92 00:03:28,200 --> 00:03:30,360 resistance, it has to be bulletproof right. And 93 00:03:30,360 --> 00:03:32,120 if we're gonna give a doctor one more 94 00:03:32,120 --> 00:03:34,280 thing to do, we're gonna take 2 things 95 00:03:34,280 --> 00:03:34,780 away. 96 00:03:35,134 --> 00:03:35,875 So for 97 00:03:36,254 --> 00:03:37,474 us, we use 98 00:03:38,094 --> 00:03:40,655 AI in clinical workflows around intelligence. And a 99 00:03:40,655 --> 00:03:43,055 great example for us is how we think 100 00:03:43,055 --> 00:03:44,514 about incidental findings. 101 00:03:44,974 --> 00:03:47,215 So if you have a chest x-ray because 102 00:03:47,215 --> 00:03:48,594 someone's worried about pneumonia 103 00:03:48,949 --> 00:03:50,969 or because you have been a smoker 104 00:03:51,349 --> 00:03:54,389 and we find an incidental finding, very frequently, 105 00:03:54,389 --> 00:03:57,430 those incidental findings are difficult to follow. So 106 00:03:57,430 --> 00:04:00,009 we partner with a company that uses computational 107 00:04:00,150 --> 00:04:00,650 linguistics 108 00:04:01,189 --> 00:04:03,955 to follow these incidental findings, and we get 109 00:04:03,955 --> 00:04:05,875 the patient connected with the right care and 110 00:04:05,875 --> 00:04:08,034 the right time at the right place a 111 00:04:08,034 --> 00:04:10,354 100% of the time. We've done that now 112 00:04:10,354 --> 00:04:12,675 for lung nodules. We're doing it for thyroid 113 00:04:12,675 --> 00:04:14,375 nodules. We're doing it for pancreatic 114 00:04:14,835 --> 00:04:15,814 cysts and nodules, 115 00:04:16,194 --> 00:04:19,430 for pap smears, really any screening test that 116 00:04:19,430 --> 00:04:21,509 can have an incidental finding that requires a 117 00:04:21,509 --> 00:04:24,649 follow-up, which prior to this deployment of technology 118 00:04:25,110 --> 00:04:27,509 was really impossible for any single human or 119 00:04:27,509 --> 00:04:29,289 group of humans to keep track of. 120 00:04:29,909 --> 00:04:32,064 And when we adopt AI 121 00:04:32,365 --> 00:04:35,805 and are managing greater volumes of data, IT 122 00:04:35,805 --> 00:04:38,604 teams become critical. So how can health care 123 00:04:38,604 --> 00:04:39,104 organizations 124 00:04:39,404 --> 00:04:42,204 better support IT and clinical teams as they 125 00:04:42,204 --> 00:04:44,204 carry out innovation efforts, and what are some 126 00:04:44,204 --> 00:04:45,904 of the common pitfalls you see? 127 00:04:47,829 --> 00:04:50,389 So from a perspective of how we integrate 128 00:04:50,389 --> 00:04:52,629 and use our IT teams, we're very fond 129 00:04:52,629 --> 00:04:54,949 of saying that our innovation strategy is our 130 00:04:54,949 --> 00:04:57,209 IT strategy, is our quality strategy, 131 00:04:57,589 --> 00:04:59,050 is our virtual health strategy, 132 00:04:59,430 --> 00:04:59,930 etcetera. 133 00:05:00,334 --> 00:05:01,935 So they are part and parcel of the 134 00:05:01,935 --> 00:05:03,855 team. Just like a doctor, a nurse, an 135 00:05:03,855 --> 00:05:06,435 executive, IT is really crucial 136 00:05:06,735 --> 00:05:08,834 to how we deliver health care. 137 00:05:09,214 --> 00:05:10,435 Some of the common pitfalls 138 00:05:10,975 --> 00:05:12,895 are that if you ask someone what their 139 00:05:12,895 --> 00:05:14,250 ideal state would be, 140 00:05:14,649 --> 00:05:16,250 and they don't have to be a novice 141 00:05:16,250 --> 00:05:18,490 in IT, but they simply want to develop 142 00:05:18,490 --> 00:05:20,329 a tool or use a tool, there's a 143 00:05:20,329 --> 00:05:21,850 1 in 3 chance that that tool already 144 00:05:21,850 --> 00:05:23,689 exists and they don't know about it. There's 145 00:05:23,689 --> 00:05:25,290 a 1 in 3 chance that they have 146 00:05:25,290 --> 00:05:27,525 a great idea. We have something that can 147 00:05:27,525 --> 00:05:29,605 be optimized to meet their needs, and there's 148 00:05:29,605 --> 00:05:31,545 a 1 in 3 chance that's just impossible 149 00:05:31,685 --> 00:05:33,305 technologically. So it's understanding 150 00:05:34,004 --> 00:05:36,645 what the guardrails are around technology, being able 151 00:05:36,645 --> 00:05:39,764 to execute, bring into workflows, change management, and 152 00:05:39,764 --> 00:05:41,705 make sure that the tool is actually useful. 153 00:05:42,720 --> 00:05:45,120 And finally, as we wrap our conversation, what 154 00:05:45,120 --> 00:05:46,959 is your top piece of advice for health 155 00:05:46,959 --> 00:05:49,620 care leaders as they prepare for further advancements 156 00:05:49,680 --> 00:05:52,399 in technology and greater demands for care? To 157 00:05:52,399 --> 00:05:53,620 really take a deep breath, 158 00:05:54,160 --> 00:05:56,079 technology is a tool that will help us 159 00:05:56,079 --> 00:05:59,584 deliver better care, faster, cheaper, but it's never 160 00:05:59,584 --> 00:06:00,324 gonna replace 161 00:06:00,704 --> 00:06:02,725 human interaction and human adjudication. 162 00:06:03,264 --> 00:06:05,665 So it's really just a tool like anything 163 00:06:05,665 --> 00:06:06,165 else, 164 00:06:06,545 --> 00:06:08,324 and it's really the tool 165 00:06:08,939 --> 00:06:11,040 that is being deployed, not 166 00:06:11,660 --> 00:06:13,920 replacing humans or replacing interaction. 167 00:06:14,779 --> 00:06:16,699 Well, Rich, thanks so much for joining me 168 00:06:16,699 --> 00:06:19,100 today on the Becker's healthcare podcast. Again, we're 169 00:06:19,100 --> 00:06:21,340 live at the 9th annual health IT digital 170 00:06:21,340 --> 00:06:23,980 health and RCM conference. Thank you. Thank you 171 00:06:23,980 --> 00:06:24,674 for having me.