1 00:00:00,060 --> 00:00:03,760 Hi everyone, and thanks for tuning into the Becker's Healthcare podcast series. 2 00:00:04,380 --> 00:00:08,920 I'm Erica Spicer Mason, a writer and editor for Becker's Healthcare. Today, 3 00:00:09,020 --> 00:00:11,520 I'm pleased to be joined by Florian Hillen, 4 00:00:11,900 --> 00:00:15,480 who will talk to us about the role of artificial intelligence in the dental 5 00:00:15,800 --> 00:00:18,640 industry. So a little bit about Florian. 6 00:00:19,230 --> 00:00:22,000 He's the founder and c e o of Vidia Health, 7 00:00:22,220 --> 00:00:24,720 an m i t spinout and dental AI company, 8 00:00:24,790 --> 00:00:28,680 working with leading dental service organizations, insurers, 9 00:00:28,740 --> 00:00:31,710 and other companies in the industry. Previously, 10 00:00:31,740 --> 00:00:35,590 Florian conducted research at the intersection of engineering and social science 11 00:00:35,770 --> 00:00:39,190 at MIT's Institute for Data Systems and Society. 12 00:00:39,850 --> 00:00:41,190 And at Harvard Business School, 13 00:00:41,850 --> 00:00:45,630 he also worked for McKinsey and Company and founded nnu, 14 00:00:45,830 --> 00:00:49,160 a digital health tech startup. So with that, 15 00:00:49,390 --> 00:00:52,440 Florian welcome and thank you so much for being here today. 16 00:00:53,470 --> 00:00:55,420 Thank you for having me, Erica. Hello everyone. 17 00:00:56,800 --> 00:00:57,460 Great. Well, 18 00:00:57,460 --> 00:01:02,310 just that short bio really captures how much experience you have in 19 00:01:02,310 --> 00:01:04,990 tech and healthcare. And so just to get us started, 20 00:01:05,130 --> 00:01:08,950 I'm wondering if you can share a little bit more about yourself and what led you 21 00:01:09,090 --> 00:01:10,950 to establishing video health. 22 00:01:12,230 --> 00:01:16,880 Yeah, absolutely. Um, I mean, so I, I spent all my life actually in healthcare, 23 00:01:17,120 --> 00:01:21,800 first on the clinical side, studying medicine for, for over six years and, and, 24 00:01:21,860 --> 00:01:25,760 and wanting to become a, a medical doctor. Um, and then into, 25 00:01:25,980 --> 00:01:27,720 in the entrepreneurship world, uh, 26 00:01:27,720 --> 00:01:30,480 at Nino as well as then at EcoHealth in California, 27 00:01:30,480 --> 00:01:34,360 which was a status quo to analyze heart science. Um, 28 00:01:34,420 --> 00:01:39,160 and throughout this time I really fell love with using technology in 29 00:01:39,160 --> 00:01:42,200 particular, uh, data science, um, 30 00:01:42,230 --> 00:01:45,920 machine learning and as we call it nowadays, ai, um, 31 00:01:46,100 --> 00:01:47,480 to advance patient care. 32 00:01:48,320 --> 00:01:51,220 And so I didn't understand the technology though, 33 00:01:51,800 --> 00:01:56,620 so I went to MIT to study computer science in graduate school. And, uh, 34 00:01:56,620 --> 00:02:01,220 during that time I did a lot of research in test X-rays, uh, breast cancer, 35 00:02:01,290 --> 00:02:04,420 mammography, uh, dermatology across, 36 00:02:05,120 --> 00:02:09,110 across the different verticals of healthcare. And I really realized, uh, 37 00:02:09,110 --> 00:02:14,070 that in dentistry we can have one of the biggest impacts as we can support 38 00:02:14,070 --> 00:02:19,070 dentists in a meaningful way as well as a huge impact because you have hundreds 39 00:02:19,070 --> 00:02:22,230 of millions of patient visits, uh, per year in US alone, 40 00:02:22,440 --> 00:02:25,750 which each one of them we can, um, help quite a lot. 41 00:02:26,130 --> 00:02:30,470 And so that's really what made me fall in love with, with dentistry, um, 42 00:02:30,490 --> 00:02:34,030 the impact we can have in terms of qualitative per patient, 43 00:02:34,090 --> 00:02:38,350 but also quantitative. And so I was very excited to contact video health, um, 44 00:02:38,410 --> 00:02:39,510 to support dentists. 45 00:02:41,420 --> 00:02:45,600 So Florian, I'm really excited to dig into this conversation today. 46 00:02:45,860 --> 00:02:48,240 And just based on your short bio, 47 00:02:48,420 --> 00:02:52,000 it sounds like you have so much experience in tech and healthcare, 48 00:02:52,580 --> 00:02:54,480 but just to give our listeners some context, 49 00:02:54,740 --> 00:02:58,560 I'm wondering if you can just share a little bit more about yourself and also 50 00:02:58,750 --> 00:03:02,080 what led you to establishing video health and what it does. 51 00:03:03,180 --> 00:03:07,190 Yeah, absolutely, Erica. So, um, as you just read, um, 52 00:03:07,310 --> 00:03:10,510 I spent all my life so far actually in healthcare. Um, 53 00:03:11,110 --> 00:03:13,350 I used to be actually a medical student for six years, 54 00:03:13,350 --> 00:03:15,670 trained to become a medical doctor. Um, 55 00:03:15,790 --> 00:03:18,430 I then founded a tech company as well as worked in a, 56 00:03:18,430 --> 00:03:22,430 in a company in Silicon Valley to, uh, do an AI powered, 57 00:03:23,290 --> 00:03:26,070 um, status quo to automatically analyze hard sounds. 58 00:03:26,890 --> 00:03:28,550 And throughout these experiences, 59 00:03:28,750 --> 00:03:32,790 I absolutely fell in love with using data science, 60 00:03:33,180 --> 00:03:35,550 machine learning, or you can, you know, 61 00:03:35,950 --> 00:03:40,670 summarize it as artificial intelligence in order to advance patient 62 00:03:40,740 --> 00:03:43,200 care. Um, at that point though, 63 00:03:43,240 --> 00:03:46,680 I didn't really understand the technology well enough and understood healthcare 64 00:03:46,680 --> 00:03:48,120 and business. Um, 65 00:03:48,120 --> 00:03:51,880 and so I went to m i t to study computer science in graduate studies, 66 00:03:51,980 --> 00:03:55,880 and I was doing a lot of research in chest x-rays, 67 00:03:55,900 --> 00:03:59,520 breast cancer and mammography, um, as well as in dentistry. 68 00:04:00,300 --> 00:04:04,480 And during that time, I absolutely fell in love with dentistry. Um, 69 00:04:04,500 --> 00:04:05,200 and there are many, 70 00:04:05,200 --> 00:04:08,640 many reasons which we could talk about the entire time of this podcast, 71 00:04:09,420 --> 00:04:14,300 but one of the reasons really is that AI and what we are doing 72 00:04:15,080 --> 00:04:18,020 can significantly actually help our customers, 73 00:04:18,040 --> 00:04:22,860 the dental clinicians on the ground in terms of providing better patient 74 00:04:22,890 --> 00:04:23,480 care, 75 00:04:23,480 --> 00:04:28,430 as well as saving them time so we can have a significant impact to our customers 76 00:04:28,430 --> 00:04:29,550 and our patients' lives, 77 00:04:30,310 --> 00:04:35,100 while also having a huge impact as every one of us right goes to the dentist 78 00:04:35,210 --> 00:04:40,060 regularly, and we have several hundreds of millions of patient visits per year, 79 00:04:40,520 --> 00:04:42,020 we can positively impact. 80 00:04:42,760 --> 00:04:47,060 And so that's what led me really to founding video health, which by the way, 81 00:04:47,080 --> 00:04:50,620 the data means from Latin to improve, um, and to see, 82 00:04:50,840 --> 00:04:55,080 so to improve healthcare, our first product, so to say, 83 00:04:55,080 --> 00:04:57,960 is video ai. And, and what really does Erica, 84 00:04:58,100 --> 00:05:01,720 is that every time you go to your dentist and they do a, 85 00:05:01,760 --> 00:05:06,480 a general checkup and they take x-rays to check your oral health status, 86 00:05:06,820 --> 00:05:08,120 um, in these radiographs, 87 00:05:08,870 --> 00:05:13,050 our FDA approved algorithms automatically diagnose, um, 88 00:05:13,050 --> 00:05:17,930 the radiographs and identify to a high accuracy decay, 89 00:05:18,240 --> 00:05:22,210 periodontal disease, endodontic disease, and, and other symptoms, 90 00:05:22,820 --> 00:05:27,690 which really helps on the one side to improve the patient care as 91 00:05:27,710 --> 00:05:32,210 it supports the dentist to not miss anything. But on the other side also, 92 00:05:32,210 --> 00:05:36,850 it really improves the patient experience as it provides a second opinion 93 00:05:37,740 --> 00:05:40,330 right there, right then for the patient, um, 94 00:05:40,390 --> 00:05:44,490 if this treatment is really necessary or not. And so, 95 00:05:45,190 --> 00:05:45,930 um, that's, 96 00:05:45,930 --> 00:05:50,770 that's how we really use this technology to have an impact for our customer in 97 00:05:50,770 --> 00:05:52,970 terms of saving time and a better patient experience, 98 00:05:53,470 --> 00:05:56,290 but also have a positive impact on patient care in general. 99 00:05:58,370 --> 00:05:59,203 Absolutely. 100 00:05:59,380 --> 00:06:03,880 And it's really fascinating to me to hear how artificial 101 00:06:03,880 --> 00:06:08,400 intelligence or AI is being applied in various ways in 102 00:06:08,400 --> 00:06:11,920 healthcare. And in doing so, you know, 103 00:06:11,920 --> 00:06:16,400 we know that a lot of folks are excited about this technology and some 104 00:06:16,890 --> 00:06:20,200 might be more hesitant. So I'm just curious to know, 105 00:06:20,260 --> 00:06:22,720 in your experience and your work with clinicians, 106 00:06:23,190 --> 00:06:28,000 what level of enthusiasm or adoption are you seeing toward AI and 107 00:06:28,100 --> 00:06:30,600 are there any specific challenges, concerns, 108 00:06:30,600 --> 00:06:31,960 or opportunities that you're hearing? 109 00:06:33,180 --> 00:06:34,470 Yeah, that is a great question. 110 00:06:34,810 --> 00:06:38,950 And as I've been working in healthcare for the past decade, 111 00:06:40,010 --> 00:06:43,190 um, you know, previously working and selling to, for instance, 112 00:06:43,470 --> 00:06:47,510 gynecologists and, um, cardiologists and in general doctors, 113 00:06:48,290 --> 00:06:48,750 um, 114 00:06:48,750 --> 00:06:53,630 I think in general the enthusiasm in dentistry around AI and the adoption and 115 00:06:53,630 --> 00:06:58,390 the willingness to try it is significantly greater than in any other 116 00:06:58,390 --> 00:07:03,030 healthcare vertical industry I've ever been to. And that's extremely exciting. 117 00:07:03,870 --> 00:07:06,310 I think one of the major reasons for that, there are several, 118 00:07:06,490 --> 00:07:11,400 but one of them is that dentists have 119 00:07:11,400 --> 00:07:15,000 such a broad set of responsibilities. There are, 120 00:07:15,860 --> 00:07:19,790 they are to some extent a diagnostician and a radiologist, right? 121 00:07:20,460 --> 00:07:22,070 Then they're also a surgeon. 122 00:07:22,980 --> 00:07:27,510 They are also a primary care physician as well as a business person, right? So, 123 00:07:27,730 --> 00:07:30,590 uh, a a normal clinician is kind of four job than one. 124 00:07:31,170 --> 00:07:35,790 And so us coming in and saying, Hey, we support you in this, 125 00:07:36,650 --> 00:07:39,830 in one of these tasks and, and save you time. Um, 126 00:07:39,930 --> 00:07:43,830 and that is being a diagnostician slash radiologist. Um, 127 00:07:43,890 --> 00:07:48,390 and this is in a non-competitive way. We are really there just to support at an, 128 00:07:48,390 --> 00:07:49,870 at the end of the day, 129 00:07:50,330 --> 00:07:55,110 the dentist will always have full discretion on their treatment planning 130 00:07:55,210 --> 00:07:58,270 and so on, absolutely independent of the ai. Um, 131 00:07:58,410 --> 00:08:02,830 but it's truly a win-win situation for dentists. And so we see, um, 132 00:08:03,090 --> 00:08:06,830 not a lack of conflict of interest as well as a huge interest in terms of 133 00:08:07,110 --> 00:08:07,943 adoption. 134 00:08:07,950 --> 00:08:12,350 I think the second aspect why we do see a huge enthusiasm about it 135 00:08:12,970 --> 00:08:16,630 is that dentists and also, uh, 136 00:08:16,630 --> 00:08:20,510 dental chains called DSOs, who are, um, 137 00:08:20,580 --> 00:08:25,530 some of our primary customers, uh, they're entrepreneurs themselves, 138 00:08:26,070 --> 00:08:30,770 uh, they have a business and they understand that technology enables them 139 00:08:31,430 --> 00:08:35,170 to, um, run their business more efficiently and effectively. 140 00:08:35,750 --> 00:08:40,170 And so we actually see a lot of different technology adoptions in dentistry 141 00:08:40,170 --> 00:08:41,410 right now, um, 142 00:08:41,410 --> 00:08:44,610 because dentists really do understand that this actually supports their business 143 00:08:44,920 --> 00:08:47,730 more than anything else. And so it's, it's very exciting, 144 00:08:47,730 --> 00:08:48,930 especially having come from, 145 00:08:49,040 --> 00:08:53,370 from healthcare in general to dive into dentistry and see how dentists, 146 00:08:53,510 --> 00:08:58,120 but also, um, everyone, uh, in the dental office, including, for instance, 147 00:08:58,180 --> 00:09:03,040 the hygienists and the rest of the staff are embracing AI and using 148 00:09:03,060 --> 00:09:06,520 it for in particular, better patient communication and saving time. 149 00:09:07,180 --> 00:09:12,080 So it's overall very exciting. Um, especially dental chains, uh, 150 00:09:12,110 --> 00:09:17,080 have already adopted AI and now also senior practitioners, right, 151 00:09:17,220 --> 00:09:21,360 mom and pop shop dental offices, um, of which we have around, yeah, 152 00:09:21,360 --> 00:09:25,440 90 200,000 in the United States, um, are starting to adopt it rapidly. 153 00:09:28,000 --> 00:09:28,890 It's really exciting. 154 00:09:29,270 --> 00:09:33,130 And what you described makes complete sense thinking about 155 00:09:34,110 --> 00:09:35,410 how dental practices, 156 00:09:35,440 --> 00:09:38,370 just like a lot of other healthcare organizations right now, 157 00:09:38,400 --> 00:09:42,850 they're tight on time and resources as you mentioned. So, um, 158 00:09:43,070 --> 00:09:46,930 AI really does seem like something that will, you know, 159 00:09:46,930 --> 00:09:51,520 they can happily adopt to to save them so much needed, much needed time. 160 00:09:51,900 --> 00:09:55,360 Um, so I'm just kind of leaning into that a little bit more. 161 00:09:55,620 --> 00:10:00,240 I'm wondering if you can share a few examples of specific dental 162 00:10:00,580 --> 00:10:05,120 AI features and how those are a addressing some of these common challenges like 163 00:10:05,150 --> 00:10:07,600 time and resource constraints. Um, 164 00:10:07,600 --> 00:10:09,560 so if you could say a little bit more about that, that would be great. 165 00:10:10,310 --> 00:10:14,010 Yeah, absolutely. Um, uh, so I stick to my, uh, 166 00:10:14,010 --> 00:10:15,530 to our technology first, 167 00:10:15,550 --> 00:10:18,930 and then I can also elaborate on a couple of other AI examples we are seeing in 168 00:10:18,930 --> 00:10:22,410 dentistry. So what we are really providing to the dentist, 169 00:10:22,590 --> 00:10:24,330 our video AI is, 170 00:10:25,550 --> 00:10:28,290 you can imagine it as an AI powered X reviewer. 171 00:10:28,870 --> 00:10:31,650 So every time the dentist, uh, 172 00:10:31,790 --> 00:10:36,130 as well as the hygienist or the rest of the clinical team is using dental 173 00:10:36,430 --> 00:10:38,090 x-rays to provide a diagnosis, 174 00:10:38,310 --> 00:10:43,210 our AI overlays the findings and provides additional information to 175 00:10:43,210 --> 00:10:44,043 the clinician. 176 00:10:44,310 --> 00:10:49,050 And I think with that come three benefits and those benefits, 177 00:10:49,100 --> 00:10:53,090 we've been seeing them and observed them now over years at this point, 178 00:10:53,190 --> 00:10:54,810 as well as over hundreds of customers. 179 00:10:55,870 --> 00:11:00,860 The first one is that the, uh, 180 00:11:00,860 --> 00:11:04,060 dentist or the, the hygienist, the dental clinician, um, 181 00:11:04,220 --> 00:11:08,820 together with the AI spots, lesions, um, or spots diseases much, much earlier, 182 00:11:09,560 --> 00:11:13,740 um, than without the ai. So they don't miss anything important, 183 00:11:14,560 --> 00:11:17,700 um, as well as they have a second opinion even for themselves, 184 00:11:18,070 --> 00:11:22,220 which gives them greater confidence, um, into their diagnosis. So with that, 185 00:11:22,220 --> 00:11:25,540 we truly believe that we can identify identity disease much earlier on average 186 00:11:26,210 --> 00:11:27,380 than without the ai. 187 00:11:28,220 --> 00:11:31,920 The second aspect is that they can use it, um, 188 00:11:31,940 --> 00:11:36,720 to communicate to the patient. So as you might know, dentistry is, is a, 189 00:11:37,140 --> 00:11:41,880 is an amazing industry, but it also sometimes lacks, um, uh, 190 00:11:42,040 --> 00:11:46,950 a great trust between the patient and the clinician. Often in dentistry, 191 00:11:47,710 --> 00:11:52,510 patients try to get a second opinion because they are not fully on board and 192 00:11:52,510 --> 00:11:55,800 fully trusted dental clinician that they really need, um, 193 00:11:55,800 --> 00:11:59,520 this procedure because there's a little bit of conflict of interest, um, 194 00:11:59,520 --> 00:12:03,500 to some extent. And we don't believe that that's often the case, 195 00:12:03,680 --> 00:12:07,940 but certainly it is really hard for a patient to evaluate, um, 196 00:12:07,940 --> 00:12:09,180 that because they're not an expert. 197 00:12:09,520 --> 00:12:13,820 And so the second aspect is that they can use the ai and our customers are using 198 00:12:13,820 --> 00:12:18,340 the AI to provide the second opinion directly to the patient while they're in 199 00:12:18,340 --> 00:12:22,060 the chair. So Erica, imagine you're going to a dentist, um, 200 00:12:22,080 --> 00:12:26,540 and they take what we call for biting x-rays. Um, it's diagnosed with our ai, 201 00:12:26,600 --> 00:12:30,820 and then the patient at the dentist shows you your x-rays and shows. 202 00:12:30,850 --> 00:12:33,900 Look here, these spots are picked up by the ai, 203 00:12:34,410 --> 00:12:39,300 it's an FDA-approved ai, which has been trained on millions of patients and, 204 00:12:39,400 --> 00:12:42,540 and, and over a hundred dentists trained this ai. 205 00:12:43,120 --> 00:12:46,700 And it's not just me who says that we need to, um, you know, 206 00:12:46,710 --> 00:12:50,620 treat this and you need a crown, but the eye confirmed that as well. 207 00:12:51,000 --> 00:12:55,700 So it provides you a greater confidence, um, you know, in, into the, uh, 208 00:12:55,700 --> 00:12:56,940 into your treatment plan of the dentist. 209 00:12:57,780 --> 00:13:02,600 And the third aspect is that it also saves the clinician time. 210 00:13:03,650 --> 00:13:07,190 So sometimes if you do a, what is called a full mouth X series, 211 00:13:07,210 --> 00:13:09,550 so if you recover, for instance, go into a, 212 00:13:10,190 --> 00:13:14,550 a new dental office the first time they're taking 18 different single x-ray 213 00:13:14,570 --> 00:13:19,150 images of your mouth to assess holistically, uh, your, um, 214 00:13:19,260 --> 00:13:22,170 oral health, the issue is, as you can imagine, 215 00:13:22,170 --> 00:13:23,770 that the dental has very limited time. 216 00:13:24,190 --> 00:13:28,970 And so what we can do is we can prioritize the x-rays for them to make sure 217 00:13:28,970 --> 00:13:31,570 that he picks up on the right spots, um, 218 00:13:31,570 --> 00:13:34,930 without spending too much time on the areas which are, 219 00:13:34,940 --> 00:13:37,090 which are looking very healthy, um, 220 00:13:37,150 --> 00:13:40,250 as well as there are other features where we can write back into the practice 221 00:13:40,250 --> 00:13:42,290 management system, which is, um, 222 00:13:42,290 --> 00:13:45,770 synonymous to the electronic health record and healthcare, um, 223 00:13:45,780 --> 00:13:49,210 where we can save a lot of time when it comes to around treatment planning and 224 00:13:49,210 --> 00:13:52,770 charting procedures, et cetera, et cetera. So this is how we, 225 00:13:53,070 --> 00:13:57,770 how we currently help. Now, the results of this are, 226 00:13:57,790 --> 00:14:01,130 are pretty phenomenal. So we, the great thing in dentistry, 227 00:14:01,150 --> 00:14:02,810 you can measure all of that. 228 00:14:02,870 --> 00:14:07,130 And so the first aspect I mentioned that they identify disease earlier 229 00:14:07,750 --> 00:14:10,850 and, and, and, you know, more treatable disease. Um, 230 00:14:10,950 --> 00:14:15,450 we are seeing across the board that the treatment plan value of customers who 231 00:14:15,450 --> 00:14:18,370 are using our AI increases by 26%. 232 00:14:18,950 --> 00:14:22,730 So that means that they identify, for instance, in restorative procedures, 233 00:14:22,730 --> 00:14:27,690 which is fillings and crowns, 26% more, um, you know, 234 00:14:27,690 --> 00:14:31,610 in procedures. And these are true procedures which need to happen, right? 235 00:14:32,470 --> 00:14:35,730 And the second thing is also we are seeing a significant lift, 236 00:14:36,100 --> 00:14:40,770 everything around five plus percent in what we call case acceptance rate. 237 00:14:41,030 --> 00:14:45,570 So that means, uh, case acceptance rate and dentistry means that if the dentist, 238 00:14:46,030 --> 00:14:48,010 you know, suggests the following procedures, 239 00:14:48,400 --> 00:14:51,920 what share of these suggested procedures actually end up, um, 240 00:14:51,920 --> 00:14:54,080 being confirmed by the patient and being done. 241 00:14:54,340 --> 00:14:59,230 And this is really where the second opinion directly at the chair helps 242 00:14:59,260 --> 00:15:01,950 significantly. So those are, you know, 243 00:15:02,040 --> 00:15:06,350 those are all the different aspects how our AI helps. Um, and, 244 00:15:06,370 --> 00:15:10,710 and it's pretty phenomenal that we have such a direct clinical as well as 245 00:15:10,710 --> 00:15:14,830 measurable impact, um, to our customers, but then also to the patient's lives, 246 00:15:14,930 --> 00:15:17,630 if that makes sense. Right? Yeah. Yeah. 247 00:15:17,790 --> 00:15:20,070 I I just want to mention one thing you mentioned earlier, 248 00:15:20,070 --> 00:15:23,750 and I think this is a very interesting aspect of it since, um, 249 00:15:23,950 --> 00:15:26,830 I worked a little bit in radiology before, right? And, 250 00:15:26,830 --> 00:15:30,350 and you asked about what are the challenges maybe, and I think one of the, 251 00:15:30,450 --> 00:15:34,390 the challenges less so than in radiology, but nonetheless they still exist, 252 00:15:35,130 --> 00:15:38,270 is that, um, sometimes, um, 253 00:15:38,290 --> 00:15:43,190 the clinicians think that the AI tells them what to do and they see it as 254 00:15:43,230 --> 00:15:46,550 a competitive, um, or challenging their expertise. 255 00:15:47,490 --> 00:15:52,150 And that is certainly not how we think about it, as well as how we build the ai. 256 00:15:52,730 --> 00:15:53,630 Um, it is really, 257 00:15:53,630 --> 00:15:57,950 really interesting that dentists are actually overall pretty good in diagnosing 258 00:15:57,950 --> 00:16:01,430 disease and the AI is, is really good in diagnosing disease. 259 00:16:01,890 --> 00:16:04,230 But the main point is if you bring them together, Erica, 260 00:16:04,410 --> 00:16:08,190 so the AI plus the dentists, then together, 261 00:16:08,190 --> 00:16:11,430 they're significantly better than either of them alone. 262 00:16:11,930 --> 00:16:16,350 And so we really always try to educate the market and try to educate our 263 00:16:16,590 --> 00:16:20,870 customers that, uh, this is not about competitive. We are an assisting tool. 264 00:16:21,490 --> 00:16:22,323 Um, you know, 265 00:16:22,370 --> 00:16:26,190 the jurisdiction of what the treatment plan should be and what needs to be done, 266 00:16:26,250 --> 00:16:28,390 not always lies with a clinician at the end, 267 00:16:28,890 --> 00:16:32,110 but together they can be better and faster than alone. 268 00:16:33,790 --> 00:16:38,660 Right. Absolutely. And I really appreciate how you outlined, 269 00:16:39,120 --> 00:16:39,420 you know, 270 00:16:39,420 --> 00:16:43,380 how the way that the AI features are addressing some of those issues like time 271 00:16:43,380 --> 00:16:47,420 constraints or case acceptance rate and tying that to some of the, 272 00:16:47,680 --> 00:16:50,580 the real outcomes that you're seeing. Uh, 273 00:16:50,700 --> 00:16:54,980 I know that case acceptance is a huge issue, um, at dental practices. 274 00:16:55,200 --> 00:16:59,140 And then I was really struck too by the patient engagement piece, you know, 275 00:16:59,230 --> 00:17:04,100 being able to have that conversation with the patient about what the AI 276 00:17:04,120 --> 00:17:07,380 is doing to assist with a diagnosis. And, you know, 277 00:17:07,380 --> 00:17:11,940 anytime you get a patient more involved in their care and more educated on their 278 00:17:11,940 --> 00:17:13,140 situation, it can only, 279 00:17:13,880 --> 00:17:16,660 I'm sure that can also only lead to good things as well. 280 00:17:17,780 --> 00:17:22,260 I mean, it goes absolutely Erica, and it, and it goes so far that, 281 00:17:22,510 --> 00:17:26,820 funny enough, everyone in my company, um, you know, obviously we have, 282 00:17:26,920 --> 00:17:28,700 we have dental insurance and, and, 283 00:17:28,760 --> 00:17:32,620 and tons of dentists around our headquarter in Boston are using our ai. 284 00:17:33,400 --> 00:17:35,780 And it actually goes so far that everyone in our, 285 00:17:36,160 --> 00:17:41,100 in our company is now only going to dentists who are using AI because 286 00:17:41,100 --> 00:17:44,380 they also appreciate this level of transparency, right? 287 00:17:45,040 --> 00:17:47,660 So I I do believe that there will be, uh, 288 00:17:47,780 --> 00:17:52,000 a world in the next two to three years where patients will actually request, 289 00:17:52,740 --> 00:17:56,640 um, you know, to have their dentist using AI just as a, as a second opinion, 290 00:17:56,780 --> 00:17:57,880 as a layer of transparency. 291 00:17:59,380 --> 00:18:01,870 Yeah, I I can see that too. Absolutely. 292 00:18:03,090 --> 00:18:06,510 So there are definitely clear benefits here that you've outlined. 293 00:18:06,650 --> 00:18:11,550 And so I'm wondering if you can just give some advice to that dental 294 00:18:11,630 --> 00:18:15,670 organization that hasn't yet adopted ai. Maybe they're on the fence, 295 00:18:15,670 --> 00:18:19,910 maybe they're thinking about it. What would you say to them to get started? 296 00:18:19,940 --> 00:18:21,230 What would you recommend first? 297 00:18:23,130 --> 00:18:25,180 Yeah, , I think to get started, uh, 298 00:18:25,320 --> 00:18:29,500 the best thing is what you reach out to me or our company at video health ai, 299 00:18:30,120 --> 00:18:31,500 um, just simply to, 300 00:18:31,880 --> 00:18:35,460 to get a little bit more in touch to understand how does this technology work? 301 00:18:35,920 --> 00:18:37,140 How is it implemented? 302 00:18:37,730 --> 00:18:42,100 What is the change management and processes for their clinicians to use it, 303 00:18:42,430 --> 00:18:47,300 right? So just just to get educated or to get consulted, um, you know, by, 304 00:18:47,480 --> 00:18:52,140 by my consulting team about what are best practices to implement a technology 305 00:18:52,170 --> 00:18:56,220 such as this, right? I think the technology, honestly is, 306 00:18:56,280 --> 00:19:01,060 is is really great for any dental clinician and in particular dental 307 00:19:01,280 --> 00:19:05,610 chains. So we call them DSOs, right? Dental service organizations, um, 308 00:19:06,370 --> 00:19:10,380 because besides the benefits we've just discussed right around, you know, 309 00:19:10,380 --> 00:19:14,180 increasing treatment plan, increasing, uh, case acceptance and saving time, 310 00:19:15,270 --> 00:19:19,530 um, if you have a small dental chain, uh, there's a fourth value add, 311 00:19:19,700 --> 00:19:24,610 which means that you can standardize your clinical care. 312 00:19:25,190 --> 00:19:28,090 So what I mean by that is if you're a dentist and you have five dental offices, 313 00:19:28,990 --> 00:19:30,250 um, you know, as a, as a, 314 00:19:30,330 --> 00:19:33,810 a self-made entrepreneur to say you can visit each day of the week, 315 00:19:33,810 --> 00:19:36,090 you can visit one of these offices and you get to know them. 316 00:19:36,550 --> 00:19:41,410 But if you become a dental chain over 10 locations and you have in each 317 00:19:41,610 --> 00:19:44,690 location, you know, to dentists and for hygienists, 318 00:19:45,000 --> 00:19:48,650 then all of a sudden you have over 50 clinicians and all of them have a 319 00:19:48,650 --> 00:19:53,050 different, you know, clinical rigor or a different, um, sensitivity. 320 00:19:53,590 --> 00:19:58,250 And so what we really have been seeing is that our video AI really 321 00:19:58,340 --> 00:20:02,850 helps to introduce a standard of care in calibrating all these clinicians 322 00:20:03,130 --> 00:20:06,930 together, which significantly helps the chief dental office that, and honestly, 323 00:20:06,950 --> 00:20:09,850 to manage clinical care and quality programs. 324 00:20:10,390 --> 00:20:14,290 And so I think it's really relevant for every dental clinician and in particular 325 00:20:14,290 --> 00:20:18,570 for dental chains, uh, which have more than 10 locations now, 326 00:20:19,770 --> 00:20:22,460 what, what should they think about, right? And, and maybe that's, 327 00:20:22,460 --> 00:20:24,100 that's a good thing to think about it, 328 00:20:24,100 --> 00:20:26,580 besides getting educated and reaching out and all that. 329 00:20:27,100 --> 00:20:30,340 I think what's very important is number one, the implementation, 330 00:20:30,800 --> 00:20:35,420 and then number two, the change management process. And so implementation, 331 00:20:35,840 --> 00:20:39,380 um, is something which is really important. We, we spent significant, 332 00:20:40,720 --> 00:20:44,820 um, years honestly, on implementing it as smooth into the workflow. 333 00:20:45,400 --> 00:20:50,320 So we are now directly integrated or even embedded into the most of 334 00:20:50,320 --> 00:20:54,360 the major practice management systems, which means that, you know, 335 00:20:54,410 --> 00:20:57,480 insulation is less than 30 minutes, um, 336 00:20:57,580 --> 00:21:01,920 for any office to onboard N O I. The second aspect of it is, 337 00:21:02,380 --> 00:21:06,460 um, change management and onboarding. And there good and bad news, 338 00:21:06,460 --> 00:21:08,220 they're good news, um, 339 00:21:08,240 --> 00:21:12,880 in the sense that it's not that much of change management because 340 00:21:12,880 --> 00:21:14,400 essentially, um, 341 00:21:14,400 --> 00:21:19,240 how they would use the AI is they use it similar to every X reviewer 342 00:21:19,240 --> 00:21:22,440 they're using right now, like a Dexus or a care stream, right? 343 00:21:22,440 --> 00:21:25,320 That is an existing workflow. They are, um, 344 00:21:25,430 --> 00:21:28,680 they are doing with every single patient who gets an x-ray today, 345 00:21:28,820 --> 00:21:32,240 and we are just asking them to do the same thing, but now with video ai, 346 00:21:32,540 --> 00:21:34,840 so they have the same x-rays, the same functionalities, 347 00:21:34,860 --> 00:21:39,390 but now they have AI on it. At the same time though, we've seen that, um, 348 00:21:39,800 --> 00:21:44,150 explaining to the clinicians how to use the AI and how to communicate with the 349 00:21:44,170 --> 00:21:48,430 AI to the patient and so on is extremely valuable. And so that's why, 350 00:21:48,430 --> 00:21:51,790 for instance, what we are doing is after we implemented it, which you know, 351 00:21:51,840 --> 00:21:54,470 takes less than 30 minutes, but then we, 352 00:21:54,570 --> 00:21:58,950 we only do in-person onboardings to train the entire stuff of the dental 353 00:21:59,310 --> 00:22:03,190 practice of how to leverage the AI to the best of the possibilities. 354 00:22:04,010 --> 00:22:07,510 And then the third aspect of it is that after one week, two weeks, 355 00:22:07,630 --> 00:22:10,950 a month of them using the software, um, 356 00:22:11,250 --> 00:22:12,750 we will provide results. 357 00:22:13,820 --> 00:22:18,120 We will share with the clinical team on the ground how many findings have been 358 00:22:18,120 --> 00:22:20,840 found by the AI and how many have been accepted, et cetera. 359 00:22:21,460 --> 00:22:26,080 And that is a very interesting and very important point to close the change 360 00:22:26,080 --> 00:22:28,640 management loop. So you explain why it's relevant, 361 00:22:28,860 --> 00:22:32,920 but then also after a certain amount of time you share with everyone who fus 362 00:22:32,920 --> 00:22:35,680 this new technology, what the impact of this new technology is. 363 00:22:36,180 --> 00:22:40,920 And if you execute this really, really well, and I have an entire team, um, 364 00:22:41,060 --> 00:22:45,360 you know, our customer success team, which is majorly uh, ex hygienists who, 365 00:22:45,380 --> 00:22:49,200 who started joining us, um, if you do this really well, um, 366 00:22:49,350 --> 00:22:53,440 then you successfully implemented AI and then you see all the benefits. Um, 367 00:22:53,440 --> 00:22:56,320 but that is a very important part of it. And I think often, 368 00:22:56,340 --> 00:23:00,440 to be honest with you, Erica, it's often, it's often overlooked a little bit. 369 00:23:00,940 --> 00:23:04,360 Um, if you implement new technologies, um, you know, 370 00:23:04,590 --> 00:23:06,600 they get sold and then no one uses them. 371 00:23:06,600 --> 00:23:11,120 And so we try to really keep ourselves accountable to have our customers using 372 00:23:11,120 --> 00:23:12,960 the technology every day, every time. 373 00:23:14,560 --> 00:23:15,650 Yeah, absolutely. I, 374 00:23:15,850 --> 00:23:19,930 I appreciate you touching on the change management piece because you know, 375 00:23:19,930 --> 00:23:21,810 especially with staffing shortages, 376 00:23:21,810 --> 00:23:25,170 we know it's important for the employees to feel supported as well, 377 00:23:25,310 --> 00:23:28,410 and you know, and as if they're, 378 00:23:28,410 --> 00:23:32,670 they have the buy-in as there, you know, um, so yeah, I, 379 00:23:32,750 --> 00:23:35,630 I appreciate you touching on that. Absolutely. Um, 380 00:23:35,630 --> 00:23:39,590 so I know you had already kind of alluded to where you see 381 00:23:40,450 --> 00:23:42,390 AI and dental care going in the future. 382 00:23:42,650 --> 00:23:46,540 You had mentioned that you're kind of anticipating patients might start to 383 00:23:46,680 --> 00:23:50,000 actually request AI services during their dental visit. 384 00:23:50,260 --> 00:23:52,040 But just as we close out here, 385 00:23:52,220 --> 00:23:57,200 is there anything else that excites you looking to the future in this space and, 386 00:23:57,300 --> 00:23:58,920 and what you might expect on the line? 387 00:23:59,870 --> 00:24:04,740 Yeah, absolutely. Um, I mean, I think that in the next few years, and it, 388 00:24:04,740 --> 00:24:08,540 it will go much faster than, than we thought it would go. Um, 389 00:24:08,780 --> 00:24:13,670 I believe that AI supported diagnosis and treatment planning will 390 00:24:13,670 --> 00:24:14,750 become the standard of care. 391 00:24:15,250 --> 00:24:19,470 So I think in three years we will live in a world where you are going to your 392 00:24:19,470 --> 00:24:23,790 clinician and you will have video AI supporting the clinician in the diagnosis 393 00:24:23,810 --> 00:24:28,270 and treatment plan. Um, I also do believe that number two, 394 00:24:29,390 --> 00:24:34,250 and, and we are starting to work on this already, is that AI will support, 395 00:24:34,550 --> 00:24:34,770 uh, 396 00:24:34,770 --> 00:24:39,250 clinicians as well as the rest of the staff in automating a lot of processes. 397 00:24:39,350 --> 00:24:43,530 Let that be administrative tasks like writing into the practice management 398 00:24:43,530 --> 00:24:47,650 system all the way to, for instance, claims processing, right? Like, 399 00:24:47,650 --> 00:24:50,930 so for instance, if, if, uh, you know, Erica, you were there and, 400 00:24:50,950 --> 00:24:52,650 and you propose to get a crown, 401 00:24:52,960 --> 00:24:56,810 then this often needs to be sent for pre-authorization to your carrier and so 402 00:24:56,810 --> 00:24:58,290 on. And I think AI will play a big role, 403 00:24:58,630 --> 00:25:03,330 and I do believe we will live in a world in a not too distant future where 404 00:25:03,590 --> 00:25:06,170 the AI supports in a diagnostic, the treatment planning, 405 00:25:06,590 --> 00:25:10,930 but then also in these claims processing to enable this in real time. 406 00:25:11,550 --> 00:25:16,490 So you can be in a dental office and the AI supports the clinicians 407 00:25:16,490 --> 00:25:19,970 to say, okay, on tweet number nine, they need to be a crown. Um, 408 00:25:20,230 --> 00:25:22,650 and we have verified this with your insurance carrier, 409 00:25:22,830 --> 00:25:26,930 and they will approve the crown, and this is how you have to think about this. 410 00:25:26,990 --> 00:25:31,370 And I think this will significantly improve the patient experience as well as 411 00:25:31,730 --> 00:25:36,170 automate a lot of backend burden from a lot of dental chains as well as, uh, 412 00:25:36,170 --> 00:25:38,850 dental clinicians. So I'm, I'm very, very excited about it. 413 00:25:39,470 --> 00:25:42,730 And then the last piece of it is the long term, right? So short term, 414 00:25:42,730 --> 00:25:45,370 medium term, and the long term consequences. And I, 415 00:25:45,530 --> 00:25:49,690 I truly believe maybe also coming from Europe where you don't have such a big 416 00:25:49,690 --> 00:25:53,770 divide between dentistry and healthcare. I believe that in the long term, um, 417 00:25:54,030 --> 00:25:56,610 AI will enable medical, dental integration, 418 00:25:57,190 --> 00:26:02,170 and we will live in a world where many patients are going to the dentist 419 00:26:02,750 --> 00:26:06,610 for their regular checkups, cosmetic reasons and whatnot. Um, 420 00:26:06,870 --> 00:26:11,330 but there are a lot of people in the United States who have undiagnosed and 421 00:26:11,330 --> 00:26:13,890 unidentified, for instance, diabetes and hypertension. 422 00:26:14,390 --> 00:26:18,210 And I do believe that with the amounts of big data we are collecting right now 423 00:26:18,400 --> 00:26:20,810 that we will be in a, in a, in a, 424 00:26:20,810 --> 00:26:25,300 in a place to be predicting which dental patients 425 00:26:25,670 --> 00:26:28,100 might have diabetes or hypertension risks, 426 00:26:28,440 --> 00:26:31,980 and then refer them out to the right primary care physician to identify these 427 00:26:32,170 --> 00:26:36,580 significant health risks and systemic health risks much, much earlier. 428 00:26:37,160 --> 00:26:42,020 And I think we will get to a place where dentistry and healthcare will be 429 00:26:42,020 --> 00:26:42,900 much more joined together. 430 00:26:44,700 --> 00:26:49,280 Mm, fascinating. I haven't yet heard that thought of, you know, 431 00:26:49,280 --> 00:26:52,760 the integration of medical and dental care in the future with ai. And so that, 432 00:26:53,000 --> 00:26:56,360 I really appreciate you sharing that and, and your future outlook. 433 00:26:56,360 --> 00:26:59,440 It really feels like the possibilities are pretty endless, 434 00:26:59,440 --> 00:27:03,720 and they'll probably be here sooner than we expect. So thank you again, 435 00:27:03,720 --> 00:27:05,520 Florian for everything that you've shared today. 436 00:27:06,170 --> 00:27:08,480 Absolutely. Thank you. Thank you for having me. 437 00:27:09,040 --> 00:27:11,770 Wonderful. Well, thank you again to Florian, 438 00:27:12,030 --> 00:27:16,330 and also we'd like to thank Vidia Health for sponsoring this episode today. 439 00:27:16,990 --> 00:27:21,210 You can tune into more podcasts and virtual events from Becker's Healthcare by 440 00:27:21,210 --> 00:27:23,490 visiting Becker's hospital review.com.