1 00:00:00,155 --> 00:00:03,045 - This is Scott Becker with the Becker's Healthcare Podcast. 2 00:00:03,865 --> 00:00:05,245 I'm thrilled today to be joined 3 00:00:05,245 --> 00:00:08,045 by your brilliant chief executive officer and leader. 4 00:00:08,575 --> 00:00:11,365 We're joined today by Jim Jacobs, the president 5 00:00:11,365 --> 00:00:12,725 and the CEO of Quant. 6 00:00:12,905 --> 00:00:15,485 Uh, he's gonna talk today about data management, 7 00:00:15,485 --> 00:00:17,125 about artificial intelligence 8 00:00:17,185 --> 00:00:21,045 and more Jim's the kind of leader who's been in the space 9 00:00:21,145 --> 00:00:23,645 of sort of decision making, clinical decision making 10 00:00:23,665 --> 00:00:24,965 and support, uh, 11 00:00:25,105 --> 00:00:26,325 before it was something 12 00:00:26,325 --> 00:00:28,165 that was talked about every single day. 13 00:00:28,555 --> 00:00:31,005 He's got himself a master's in decision support. 14 00:00:31,465 --> 00:00:33,445 Uh, he's been the leader of a few companies. 15 00:00:33,475 --> 00:00:35,525 He's been now with qu leading quant for, 16 00:00:35,525 --> 00:00:37,085 I think six, seven years now. 17 00:00:37,225 --> 00:00:39,325 And just a terrific person to visit with. 18 00:00:40,105 --> 00:00:41,445 Jim, thank you for being here. 19 00:00:41,625 --> 00:00:43,565 Can you take a moment to tell us a little bit 20 00:00:43,565 --> 00:00:45,005 about yourself and about Met? 21 00:00:46,755 --> 00:00:48,445 - Sure, I'd be happy to, and thank you so much 22 00:00:48,505 --> 00:00:50,125 for the opportunity to speak with you 23 00:00:50,145 --> 00:00:51,685 and, uh, your audience. 24 00:00:51,985 --> 00:00:55,925 Um, yeah, I've been in healthcare for a long time, uh, 25 00:00:55,925 --> 00:00:58,445 currently president, CEO at quant. 26 00:00:58,825 --> 00:01:01,005 I'm very fortunate to be a part of an amazing team 27 00:01:01,005 --> 00:01:04,205 that's been pioneering active data archiving 28 00:01:04,205 --> 00:01:06,285 and data management since 1999. 29 00:01:06,955 --> 00:01:08,685 Very much look forward to the discussion, 30 00:01:08,705 --> 00:01:11,245 and we are absolutely in an interesting time right now. 31 00:01:11,945 --> 00:01:14,485 Uh, things are actually getting more interesting, uh, 32 00:01:14,485 --> 00:01:15,845 the further we go, so I look 33 00:01:15,845 --> 00:01:16,965 forward to having this discussion. 34 00:01:17,865 --> 00:01:19,005 - Jim, thank you so much. 35 00:01:19,265 --> 00:01:21,525 Uh, you know, we, we all know 36 00:01:21,555 --> 00:01:24,565 that healthcare leaders are facing an overwhelming spike in 37 00:01:24,565 --> 00:01:25,925 technology offerings. 38 00:01:26,625 --> 00:01:29,405 So many d different offerings out there, sort 39 00:01:29,405 --> 00:01:32,165 of amid this rapid innovation amidst so many offerings, 40 00:01:32,165 --> 00:01:36,445 being, being sort of forward it or put in front of leaders. 41 00:01:37,385 --> 00:01:38,805 What's important for leaders 42 00:01:38,905 --> 00:01:40,965 to keep in mind and, and, and why? 43 00:01:41,425 --> 00:01:42,425 Why is it important? 44 00:01:44,085 --> 00:01:45,775 - Yeah. There's a couple of real important things 45 00:01:45,775 --> 00:01:48,055 to keep in mind, which is, uh, are the new systems 46 00:01:48,685 --> 00:01:51,055 that you're looking at replacing, uh, old systems? 47 00:01:51,195 --> 00:01:52,255 Are there overlaps? 48 00:01:53,285 --> 00:01:55,545 Do other systems need to be rationalized? 49 00:01:56,485 --> 00:01:59,185 And are there systems that can actually be archived 50 00:01:59,925 --> 00:02:02,945 to help free up dollars with the margin pressures that are 51 00:02:02,945 --> 00:02:04,985 so extreme, it's often the case 52 00:02:04,985 --> 00:02:07,305 that we can actually help free up the dollars. 53 00:02:07,485 --> 00:02:10,345 And so really those two aspects. 54 00:02:10,345 --> 00:02:13,225 Plus looking at security, are there systems that you have 55 00:02:13,225 --> 00:02:15,145 that are older, that don't have good security? 56 00:02:15,885 --> 00:02:17,265 As you're facing new choices, 57 00:02:17,405 --> 00:02:19,065 making sure you're filling in the gaps 58 00:02:19,125 --> 00:02:22,105 and creating a complete plan is one 59 00:02:22,105 --> 00:02:23,225 of the recommendations we make. 60 00:02:24,905 --> 00:02:26,495 - Thank you. And when you look at sort 61 00:02:26,495 --> 00:02:29,695 of digital transformation to population health initiatives, 62 00:02:30,115 --> 00:02:32,335 health organizations are relying on data 63 00:02:32,395 --> 00:02:35,255 to make sustainable improvements as it comes 64 00:02:35,255 --> 00:02:37,095 to data management and legacy data. 65 00:02:37,095 --> 00:02:39,015 Everybody's dealing with so much legacy data. 66 00:02:39,755 --> 00:02:42,815 Wh what key challenges are organizations facing 67 00:02:43,475 --> 00:02:45,935 and what steps can they take to navigate those challenges of 68 00:02:45,935 --> 00:02:46,935 how to deal with legacy data? 69 00:02:46,935 --> 00:02:48,415 This comes up seemingly every day. 70 00:02:49,075 --> 00:02:50,575 How, how can organizations deal with 71 00:02:50,575 --> 00:02:51,975 and what steps they take to navigate that? 72 00:02:53,205 --> 00:02:54,375 - Yeah, that's a great question 73 00:02:54,675 --> 00:02:57,975 and it's an involved, uh, set of discussions, 74 00:02:57,995 --> 00:03:00,845 but it, at the, at its most basic level, it's, 75 00:03:00,995 --> 00:03:04,245 it's assessing the data you have, making sure 76 00:03:04,275 --> 00:03:06,925 that you've got a good data governance program in place, 77 00:03:07,595 --> 00:03:09,605 that the right stakeholders are at the table, 78 00:03:09,605 --> 00:03:11,885 having discussions about the usefulness of data. 79 00:03:12,455 --> 00:03:15,285 We're a big believer in leaving data in discreet form, 80 00:03:15,465 --> 00:03:17,405 get it out of the systems, the older systems, 81 00:03:17,705 --> 00:03:21,485 and put it all together so that it can be accessible from, 82 00:03:21,595 --> 00:03:23,805 from new capabilities and new technologies. 83 00:03:24,665 --> 00:03:26,485 And we'd also recommend people take a step 84 00:03:26,485 --> 00:03:27,605 back and take a broader view. 85 00:03:28,055 --> 00:03:31,565 There are, there are immediate short term cost discussions 86 00:03:31,565 --> 00:03:34,485 that people have, but, uh, we found 87 00:03:34,485 --> 00:03:35,925 that if you really take a step back 88 00:03:35,925 --> 00:03:39,085 and look at total cost, uh, of what the data means, 89 00:03:39,085 --> 00:03:42,445 what the value of the data is, what are, what are the risks 90 00:03:42,515 --> 00:03:45,725 that you're really facing, it's a much better discussion 91 00:03:45,725 --> 00:03:49,165 to think about, uh, overall cost of the organization instead 92 00:03:49,165 --> 00:03:52,445 of just point expenses that you have, uh, 93 00:03:53,105 --> 00:03:54,125 on any given day today. 94 00:03:55,845 --> 00:03:57,485 - A hundred percent. And we hear that so often 95 00:03:58,225 --> 00:03:59,445 as systems try 96 00:03:59,445 --> 00:04:01,925 and hit this right balance between point solutions and, 97 00:04:01,925 --> 00:04:03,525 and larger, broader solutions. 98 00:04:04,555 --> 00:04:06,845 Talk about a data from perspective of 99 00:04:07,605 --> 00:04:08,765 artificial intelligence. 100 00:04:09,675 --> 00:04:11,725 Everybody sees artificial intelligence 101 00:04:12,325 --> 00:04:14,285 becoming increasingly integrated into healthcare 102 00:04:14,385 --> 00:04:15,445 in a lot of different ways. 103 00:04:16,625 --> 00:04:18,565 How do you make sure that your data infrastructure 104 00:04:19,165 --> 00:04:22,205 ultimately works in tandem with AI tools 105 00:04:22,265 --> 00:04:23,885 and continuous advancements here? 106 00:04:24,745 --> 00:04:25,765 How do you make that work 107 00:04:26,345 --> 00:04:27,605 and maybe what do you see the next five, 108 00:04:27,625 --> 00:04:29,685 10 years in data management, you know, 109 00:04:29,685 --> 00:04:30,965 that you do this consistent 110 00:04:30,965 --> 00:04:33,325 with the way that'll allow AI to work with you? 111 00:04:33,325 --> 00:04:35,445 Well, any thoughts there for systems? 112 00:04:37,005 --> 00:04:39,295 - Yeah, we think the data's foundational, uh, 113 00:04:39,295 --> 00:04:43,515 getting the data organized, having it, uh, uh, in a way 114 00:04:43,515 --> 00:04:44,715 that it's easily accessed 115 00:04:44,715 --> 00:04:46,795 because it needs to be in discreet format 116 00:04:47,015 --> 00:04:50,075 and organized around patients 117 00:04:50,135 --> 00:04:52,635 or around whatever the entities are that you're going 118 00:04:52,635 --> 00:04:54,035 to maybe use the data. 119 00:04:54,775 --> 00:04:57,995 Uh, we've even recently seen people using long-term patient 120 00:04:57,995 --> 00:05:01,075 accounting data for payer scorecards and denial management. 121 00:05:01,775 --> 00:05:05,355 So making sure there's good hygiene around the data, uh, 122 00:05:05,455 --> 00:05:09,545 is such a key, uh, that we see that, that, um, uh, 123 00:05:09,765 --> 00:05:11,825 drives good AI projects. 124 00:05:12,445 --> 00:05:15,745 Uh, we also recommend people stay away from sort of 125 00:05:15,745 --> 00:05:17,305 what we call the easy button of just dumping 126 00:05:17,305 --> 00:05:18,505 data into a PDF. 127 00:05:19,165 --> 00:05:21,145 Uh, it makes it much more difficult to do things 128 00:05:21,145 --> 00:05:22,785 with the data, uh, 129 00:05:22,925 --> 00:05:27,425 and keeping it in a, in available form is critical as far as 130 00:05:27,425 --> 00:05:29,345 what the next to five to 10 years. 131 00:05:29,805 --> 00:05:33,265 Um, that just makes me smile broadly. I don't actually know. 132 00:05:33,545 --> 00:05:36,065 I think that some of the biggest opportunities 133 00:05:36,205 --> 00:05:40,445 around disease management answering questions like, 134 00:05:40,915 --> 00:05:43,165 what are the early indicators of Alzheimer's? 135 00:05:43,665 --> 00:05:46,005 Uh, when do we understand, uh, when, 136 00:05:46,005 --> 00:05:49,285 when patients are actually starting to have issues years 137 00:05:49,425 --> 00:05:53,085 before, uh, the significant events start to onset. 138 00:05:53,705 --> 00:05:55,845 So we believe that the technologies 139 00:05:55,915 --> 00:05:58,325 that are coming about are phenomenal. 140 00:05:58,325 --> 00:06:00,925 They're amazing. The sky's the limit in terms 141 00:06:00,925 --> 00:06:02,325 of the problems they can help solve. 142 00:06:03,065 --> 00:06:04,285 And from a data management, 143 00:06:04,385 --> 00:06:06,005 the hospitals just need to get ready. 144 00:06:06,005 --> 00:06:07,525 They need to get prepared, they need 145 00:06:07,525 --> 00:06:10,965 to make sure they have a good program for valuing the data, 146 00:06:11,225 --> 00:06:12,805 making sure that data's gonna be available 147 00:06:13,665 --> 00:06:14,965 and spend the money now 148 00:06:15,705 --> 00:06:17,365 to make sure you're prepared for the future. 149 00:06:18,915 --> 00:06:20,775 - And lemme ask you a another question. 150 00:06:20,875 --> 00:06:22,495 I'm gonna drive into two different questions. 151 00:06:22,695 --> 00:06:24,415 I I I'll ask you to wrap up. 152 00:06:24,565 --> 00:06:27,135 What else should the listeners be thinking about leaders be 153 00:06:27,135 --> 00:06:28,815 thinking about before we get there? 154 00:06:28,915 --> 00:06:30,055 Jim, I'd love to ask you, 155 00:06:30,805 --> 00:06:32,575 what are you most excited about this year? 156 00:06:32,685 --> 00:06:34,855 What are you most focused on and excited about this year? 157 00:06:36,435 --> 00:06:39,445 - That there are new use cases for data 158 00:06:39,795 --> 00:06:41,245 that are already coming to light, 159 00:06:41,905 --> 00:06:44,525 and they are sort of proving out the fact 160 00:06:44,525 --> 00:06:46,085 that we're at the tip of the iceberg. 161 00:06:46,575 --> 00:06:47,845 We're at the very beginning of 162 00:06:47,845 --> 00:06:50,645 what I would call an AI adoption curve, if you will. 163 00:06:51,325 --> 00:06:54,525 I missed, I mentioned the patient accounting, uh, one 164 00:06:54,605 --> 00:06:57,165 that's brand new in the past, say, 12 months. 165 00:06:57,825 --> 00:07:01,485 So I'm excited about the fact that the marriage of ai, 166 00:07:01,895 --> 00:07:05,125 generative AI and, and data, uh, more 167 00:07:05,125 --> 00:07:07,005 and more hospitals are valuing the data. 168 00:07:07,345 --> 00:07:09,605 Um, they view the data more and more as an asset. 169 00:07:10,435 --> 00:07:11,495 And the more that happens, 170 00:07:11,675 --> 00:07:14,135 we think the richer the data sets will be, 171 00:07:15,135 --> 00:07:16,675 the richer the analysis will be, 172 00:07:16,675 --> 00:07:18,195 the richer the insights will be. 173 00:07:19,055 --> 00:07:23,355 And AI has become a catalyst to really drive that forward. 174 00:07:24,035 --> 00:07:26,715 I think Salesforce has a phenomenal commercial outright now, 175 00:07:26,715 --> 00:07:30,675 and they say, if AI is the new Wild West, doesn't 176 00:07:30,675 --> 00:07:32,235 that make data the new gold? 177 00:07:32,935 --> 00:07:34,915 Uh, we've believed that for a very long time 178 00:07:35,015 --> 00:07:36,155 and think it the, um, 179 00:07:36,655 --> 00:07:38,475 what's happening now is proving that out. 180 00:07:40,075 --> 00:07:41,255 - But, but it's interesting what you say 181 00:07:41,255 --> 00:07:44,135 because if you just dump it into a PDF, it makes it very, 182 00:07:44,135 --> 00:07:46,495 very hard for the ai, different sort of algorithms 183 00:07:46,495 --> 00:07:48,295 that are coming, the different ways of driving that 184 00:07:48,555 --> 00:07:49,775 to use that data. 185 00:07:49,915 --> 00:07:51,615 So I think that point is so well taken. 186 00:07:52,775 --> 00:07:54,735 Anything else our wizards should be thinking about? Jim? 187 00:07:56,505 --> 00:07:58,945 - I think that, um, when you think about data, one 188 00:07:58,945 --> 00:08:01,585 of the main drivers has always been around compliance. 189 00:08:02,125 --> 00:08:03,665 And that's a, that's a very good driver. 190 00:08:04,485 --> 00:08:05,585 If hospitals more 191 00:08:05,585 --> 00:08:07,945 and more adopt the point of view that data is, is an asset 192 00:08:07,945 --> 00:08:10,945 that it's valuable, then I think people are gonna want 193 00:08:10,945 --> 00:08:11,945 to keep it around longer. 194 00:08:12,535 --> 00:08:15,105 Because to your question about what's gonna happen in five 195 00:08:15,105 --> 00:08:17,185 years, no one really knows. 196 00:08:17,685 --> 00:08:19,265 So if you've gotten rid of a lot of data, 197 00:08:19,285 --> 00:08:22,185 if you've deleted a lot of data under the guise 198 00:08:22,185 --> 00:08:23,465 of a compliance regulation, 199 00:08:24,165 --> 00:08:26,675 we believe there's huge opportunities that are being missed. 200 00:08:27,615 --> 00:08:29,955 And that an eye to the future is critical 201 00:08:29,955 --> 00:08:32,195 because it's a very exciting future that's in front of us. 202 00:08:34,545 --> 00:08:36,045 - Jim, I wanna thank you for joining us. 203 00:08:36,045 --> 00:08:37,165 You're one of the most principled 204 00:08:37,165 --> 00:08:38,965 and centered leaders I get to visit with. 205 00:08:39,125 --> 00:08:41,125 I can't tell you much. I appreciate your time in the 206 00:08:41,125 --> 00:08:42,165 working with qu. 207 00:08:42,505 --> 00:08:44,965 Uh, for those that are e listening in, uh, 208 00:08:45,405 --> 00:08:47,925 quant will also be at the Becker's Healthcare annual 209 00:08:47,925 --> 00:08:51,245 meeting, which is April 8th to 11th in Chicago. 210 00:08:51,875 --> 00:08:53,565 They have a booth 4 27. 211 00:08:54,175 --> 00:08:56,725 Would love to have you come by and say hello to Quant. 212 00:08:56,745 --> 00:08:59,325 But, uh, Jim, what a pleasure to visit with you 213 00:08:59,345 --> 00:09:00,525 and what an amazing career. 214 00:09:00,895 --> 00:09:02,365 Thank you so much for joining us today 215 00:09:02,365 --> 00:09:03,485 on the Becker's Healthcare Podcast. 216 00:09:04,515 --> 00:09:05,645 - Well, thank you so much for your time. 217 00:09:05,805 --> 00:09:07,645 I appreciate and have a wonderful day.