1 00:00:02,240 --> 00:00:02,899 At athenahealth, 2 00:00:03,279 --> 00:00:06,480 we know your ambulatory practice wants healthier, a 3 00:00:06,480 --> 00:00:09,779 healthier business, healthier care teams, and healthier patients. 4 00:00:10,160 --> 00:00:12,480 But the complexities of modern health care tech 5 00:00:12,480 --> 00:00:14,240 make it hard for you and your care 6 00:00:14,240 --> 00:00:15,855 teams to focus on what matters 7 00:00:16,414 --> 00:00:19,295 most? That's where athenahealth can help. Our AI 8 00:00:19,295 --> 00:00:22,594 native all in one solutions reduce administrative burdens, 9 00:00:22,974 --> 00:00:25,875 streamline billing and payments, and deliver critical insights 10 00:00:25,934 --> 00:00:28,734 when clinicians need it most. That means fewer 11 00:00:28,734 --> 00:00:31,614 clicks, more time for patients, and stronger bottom 12 00:00:31,614 --> 00:00:31,829 lines. 13 00:00:32,710 --> 00:00:35,989 Practicing medicine is complex, but running a practice 14 00:00:35,989 --> 00:00:37,850 can be that much simpler with athenahealth. 15 00:00:38,549 --> 00:00:42,250 See how simpler is healthier@athenahealth.com. 16 00:00:44,034 --> 00:00:45,554 Hi, everyone. This is Scott King with the 17 00:00:45,554 --> 00:00:46,935 Becker's Healthcare podcast. 18 00:00:47,554 --> 00:00:49,655 Brilled today to be joined by Donald Casey, 19 00:00:49,715 --> 00:00:51,655 associate professor of internal medicine 20 00:00:52,114 --> 00:00:54,114 at Rush Medical College. Donald, how are you 21 00:00:54,114 --> 00:00:55,975 doing today? Thanks so much for joining us. 22 00:00:56,034 --> 00:00:57,975 I'm good, Scott. Please call me Don. 23 00:00:58,280 --> 00:00:59,740 You got it, Don. Will do. 24 00:01:00,119 --> 00:01:01,880 Yeah. Appreciate you joining us. We're gonna have 25 00:01:01,880 --> 00:01:03,320 a a great conversation today. A lot of 26 00:01:03,320 --> 00:01:05,420 kind of big topics and trends, 27 00:01:05,959 --> 00:01:08,359 in health care to discuss. But before we 28 00:01:08,359 --> 00:01:09,239 get there, I was wondering if you could 29 00:01:09,239 --> 00:01:10,520 just please tell us a little bit about 30 00:01:10,520 --> 00:01:11,180 your background. 31 00:01:12,305 --> 00:01:14,704 Sure thing, Scott. First of all, thanks for 32 00:01:14,704 --> 00:01:16,784 the invitation. It's been a pleasure to be 33 00:01:16,784 --> 00:01:18,725 working with Scott Becker's team, 34 00:01:19,424 --> 00:01:21,265 over the years on on a lot of 35 00:01:21,265 --> 00:01:22,784 great events and and a lot of great 36 00:01:22,784 --> 00:01:25,105 insights, so I appreciate the opportunity to connect 37 00:01:25,105 --> 00:01:25,620 with you. 38 00:01:26,579 --> 00:01:28,900 I am by by training a general internist. 39 00:01:28,900 --> 00:01:29,959 I trained at Rush, 40 00:01:30,420 --> 00:01:31,640 in Chicago here 41 00:01:32,100 --> 00:01:34,260 for first half of my career and then 42 00:01:34,260 --> 00:01:36,760 later went into management, and then ultimately, 43 00:01:37,540 --> 00:01:39,219 where I am now. I'm sort of a 44 00:01:39,219 --> 00:01:41,319 hybrid of everything I've done in my career. 45 00:01:41,984 --> 00:01:44,784 I am no longer practice internal medicine nor 46 00:01:44,784 --> 00:01:47,504 am I in a health care delivery setting. 47 00:01:47,504 --> 00:01:49,364 I'm really focused mainly 48 00:01:50,144 --> 00:01:53,524 on the on the medical side as faculty 49 00:01:53,584 --> 00:01:55,650 at Rush where I'm an associate professor of 50 00:01:55,650 --> 00:01:56,549 internal medicine, 51 00:01:57,010 --> 00:01:59,409 but also at the Thomas Jefferson College of 52 00:01:59,409 --> 00:02:01,349 Population Health where I'm an adjunct 53 00:02:01,810 --> 00:02:03,030 professor of 54 00:02:03,329 --> 00:02:03,829 quality 55 00:02:04,450 --> 00:02:05,349 patient safety 56 00:02:05,969 --> 00:02:08,050 and also population health. And then, 57 00:02:09,014 --> 00:02:11,354 I've also, for the past eleven years, been 58 00:02:11,574 --> 00:02:13,754 on the faculty of the University of Minnesota 59 00:02:13,814 --> 00:02:15,514 Institute for Healthcare Informatics 60 00:02:16,615 --> 00:02:17,435 up in Minneapolis. 61 00:02:18,055 --> 00:02:19,254 And that's been quite, 62 00:02:19,814 --> 00:02:20,314 interesting, 63 00:02:20,775 --> 00:02:22,375 in my career to be hanging out with 64 00:02:22,375 --> 00:02:24,870 all these health care data scientists. So, 65 00:02:25,430 --> 00:02:27,269 and then I'm a subject matter expert in 66 00:02:27,269 --> 00:02:28,789 a number of a number of areas. I 67 00:02:28,789 --> 00:02:30,169 was just in 68 00:02:30,789 --> 00:02:31,289 Boston 69 00:02:32,069 --> 00:02:35,430 this past, Friday with a group called ISER. 70 00:02:35,430 --> 00:02:36,650 You may know about them. 71 00:02:37,155 --> 00:02:39,474 Institute for Clinical and Economic Review. We're really 72 00:02:39,474 --> 00:02:40,534 focused on, 73 00:02:40,914 --> 00:02:43,634 as one example of, where I work, on 74 00:02:43,634 --> 00:02:45,334 rational pricing for new, 75 00:02:46,034 --> 00:02:46,534 drugs, 76 00:02:46,914 --> 00:02:48,194 that are coming on the market, 77 00:02:48,674 --> 00:02:51,610 especially those that are very expensive. So it's 78 00:02:51,610 --> 00:02:53,210 it's a hybrid of a lot of things 79 00:02:53,210 --> 00:02:55,610 at once, and, it's doing me well at 80 00:02:55,610 --> 00:02:56,830 my point in time. 81 00:02:57,290 --> 00:02:58,730 No. You you certainly are doing a lot 82 00:02:58,730 --> 00:03:00,730 of things. I appreciate the the background info 83 00:03:00,730 --> 00:03:02,349 and the specifics there, Don. 84 00:03:02,889 --> 00:03:04,969 First topic I kinda wanted to get to 85 00:03:04,969 --> 00:03:06,349 is, you know, nearly half 86 00:03:06,665 --> 00:03:09,305 of medical practices reported using AI in some 87 00:03:09,305 --> 00:03:12,105 capacity last year and remains a key topic 88 00:03:12,105 --> 00:03:13,405 for health IT leaders. 89 00:03:13,865 --> 00:03:14,764 From your perspective, 90 00:03:15,625 --> 00:03:17,705 what are the use cases that are making 91 00:03:17,705 --> 00:03:19,165 a difference right now 92 00:03:19,569 --> 00:03:21,730 and how are you leveraging them in in 93 00:03:21,730 --> 00:03:22,469 your organization? 94 00:03:23,650 --> 00:03:25,969 Yeah. I I appreciate that question. It's it's 95 00:03:25,969 --> 00:03:28,389 one that, I see often. And, 96 00:03:28,930 --> 00:03:31,010 again, I with the disclaimer, I'm no longer 97 00:03:31,010 --> 00:03:33,625 in medical practice, but I am a patient, 98 00:03:34,085 --> 00:03:36,504 and I'm involved with number of health systems. 99 00:03:38,085 --> 00:03:39,444 It's interesting that, 100 00:03:40,405 --> 00:03:43,305 we talk about nearly half are, quote, unquote, 101 00:03:43,365 --> 00:03:44,264 using AI. 102 00:03:45,040 --> 00:03:47,120 And I would I would venture to say, 103 00:03:47,120 --> 00:03:49,599 since AI is not a new topic, we've 104 00:03:49,599 --> 00:03:51,540 been using AI, so to speak, 105 00:03:51,919 --> 00:03:52,659 for years 106 00:03:53,200 --> 00:03:56,000 in many, many capacities. Now in particular, I 107 00:03:56,000 --> 00:03:56,500 think, 108 00:03:57,280 --> 00:03:59,360 as borne out by the recent event that 109 00:03:59,360 --> 00:04:01,525 I attended at, at Becker's. 110 00:04:02,544 --> 00:04:03,044 Certainly, 111 00:04:03,504 --> 00:04:05,844 medical practices from a business standpoint 112 00:04:06,224 --> 00:04:08,165 are beginning to use a lot more 113 00:04:08,784 --> 00:04:09,284 strategies 114 00:04:09,665 --> 00:04:09,985 and, 115 00:04:10,784 --> 00:04:13,925 and in information systems, for example, that deploy 116 00:04:14,489 --> 00:04:16,569 AI techniques. And and those are, you know, 117 00:04:16,569 --> 00:04:18,189 very vast in terms of, 118 00:04:18,889 --> 00:04:20,810 the issues. I've said, for example, the big 119 00:04:20,810 --> 00:04:23,850 one's reducing workflow burden. That's big one, you 120 00:04:23,850 --> 00:04:25,790 know, using natural language processing 121 00:04:26,524 --> 00:04:29,324 so that, physicians and other clinicians don't have 122 00:04:29,324 --> 00:04:30,224 to spend time 123 00:04:30,764 --> 00:04:32,144 standing in front of the, 124 00:04:32,604 --> 00:04:35,024 electronic health record as much we hope. 125 00:04:35,485 --> 00:04:38,464 So that that reducing that burden is certainly 126 00:04:38,604 --> 00:04:40,544 front and center in terms of the applications 127 00:04:40,685 --> 00:04:42,689 that are coming up, not just with the 128 00:04:42,689 --> 00:04:44,230 large electronic health 129 00:04:44,770 --> 00:04:47,730 care records, vendors, but also with, you know, 130 00:04:47,730 --> 00:04:49,410 other groups that are trying to solve for 131 00:04:49,410 --> 00:04:51,110 specific problems and specific, 132 00:04:51,810 --> 00:04:52,310 specialties. 133 00:04:53,410 --> 00:04:55,270 Obviously, revenue cycle is 134 00:04:55,625 --> 00:04:57,145 a big deal too. You know, you gotta 135 00:04:57,145 --> 00:04:59,165 keep the lights on, and revenue cycle 136 00:04:59,865 --> 00:05:01,064 is a is a, 137 00:05:01,545 --> 00:05:02,444 it's it's 138 00:05:02,985 --> 00:05:05,064 it's a big game in terms of and 139 00:05:05,064 --> 00:05:07,725 I'll use my that's my term. But, obviously, 140 00:05:07,785 --> 00:05:09,785 with keeping up with all the rules, regulations, 141 00:05:09,785 --> 00:05:11,220 and requirements of 142 00:05:11,779 --> 00:05:12,279 submitting, 143 00:05:12,660 --> 00:05:14,660 claims and then getting paid for them is 144 00:05:14,660 --> 00:05:15,160 becoming, 145 00:05:15,779 --> 00:05:18,100 I think, a big deal in terms of 146 00:05:18,100 --> 00:05:18,920 just making 147 00:05:19,699 --> 00:05:22,579 it easier, more accurate, better, obviously avoiding any 148 00:05:22,579 --> 00:05:23,399 sort of 149 00:05:23,699 --> 00:05:25,240 problems with fraud and abuse 150 00:05:25,824 --> 00:05:26,645 and cybersecurity. 151 00:05:27,824 --> 00:05:30,225 And then I think the the biggest part 152 00:05:30,225 --> 00:05:32,545 that's exciting for me from patient care is 153 00:05:32,545 --> 00:05:33,764 the access to 154 00:05:34,145 --> 00:05:35,125 clinical information 155 00:05:35,824 --> 00:05:37,585 in many fronts. Some of it is good 156 00:05:37,585 --> 00:05:39,105 and some of it isn't so good. For 157 00:05:39,105 --> 00:05:41,060 example, the alerts that come up in the 158 00:05:41,060 --> 00:05:42,279 electronic health record, 159 00:05:42,660 --> 00:05:43,879 we're trying to minimize 160 00:05:44,420 --> 00:05:46,580 those that matter so that they don't burden 161 00:05:46,580 --> 00:05:48,500 people. And yet on the other hand, the 162 00:05:48,500 --> 00:05:51,160 amount of information that's much more readily available 163 00:05:52,020 --> 00:05:52,485 through, 164 00:05:52,884 --> 00:05:54,884 the use of, let's say, Copilot, which is 165 00:05:54,884 --> 00:05:56,584 what I use. But there are others 166 00:05:57,044 --> 00:05:59,444 compared to just using search strategies. I I 167 00:05:59,444 --> 00:06:01,125 sort of think search is, for the most 168 00:06:01,125 --> 00:06:02,904 part, unless you're trying to find a restaurant, 169 00:06:03,444 --> 00:06:06,004 pretty much, out of out of favor and 170 00:06:06,004 --> 00:06:09,500 that the ability to put more rational and 171 00:06:09,500 --> 00:06:11,120 useful information together 172 00:06:11,819 --> 00:06:13,759 on the informatics side is becoming, 173 00:06:14,300 --> 00:06:17,199 very exciting for me. This obviously translates into 174 00:06:17,740 --> 00:06:20,699 other issues such as clinical decision support. But 175 00:06:20,699 --> 00:06:22,605 also, and and we're gonna get into this 176 00:06:22,605 --> 00:06:23,345 a bit more, 177 00:06:24,045 --> 00:06:26,384 Scott, is patients are using it 178 00:06:27,644 --> 00:06:30,125 immensely and showing up in the in the 179 00:06:30,125 --> 00:06:33,245 health care environments with lots of interesting and 180 00:06:33,245 --> 00:06:34,225 useful information. 181 00:06:35,084 --> 00:06:38,279 And, that's requiring the the clinicians at the 182 00:06:38,580 --> 00:06:39,639 front end to 183 00:06:40,180 --> 00:06:42,360 handle that with respect, but also, 184 00:06:42,899 --> 00:06:44,980 to be sure that we're not getting us 185 00:06:44,980 --> 00:06:47,139 going down the wrong pathway with with, let's 186 00:06:47,139 --> 00:06:50,819 say, a hallucination about some strange drug that, 187 00:06:51,139 --> 00:06:51,779 is used, 188 00:06:52,555 --> 00:06:54,474 you know, in the woods, so to speak. 189 00:06:54,474 --> 00:06:54,794 So, 190 00:06:55,595 --> 00:06:57,115 we'll we'll leave it at that. I I 191 00:06:57,115 --> 00:06:59,194 think the, the bottom line is it's it's 192 00:06:59,194 --> 00:07:00,814 an exciting and particularly 193 00:07:01,995 --> 00:07:02,495 growing, 194 00:07:03,034 --> 00:07:04,414 challenge and opportunity. 195 00:07:05,439 --> 00:07:07,779 Yeah. Don, that's really interesting because we we 196 00:07:08,240 --> 00:07:10,180 talk obviously with a lot of systems 197 00:07:11,360 --> 00:07:14,079 about using AI. But you mentioned patients coming 198 00:07:14,079 --> 00:07:16,100 in and and, you know, kinda making, 199 00:07:16,879 --> 00:07:18,879 the appointment or whatever, therefore, easier and more 200 00:07:18,879 --> 00:07:20,835 efficient because they they have used AI and 201 00:07:20,835 --> 00:07:23,475 are prepared for that meeting. What what uses 202 00:07:23,475 --> 00:07:25,714 are you seeing from patients specifically? What are 203 00:07:25,714 --> 00:07:26,615 what are they doing? 204 00:07:26,995 --> 00:07:28,615 Well, I I I would say, 205 00:07:29,395 --> 00:07:31,235 let's put it together. I mean, we have 206 00:07:31,235 --> 00:07:32,214 the the doctor 207 00:07:32,870 --> 00:07:35,129 slash clinician relationship that includes, 208 00:07:35,990 --> 00:07:36,889 other other, 209 00:07:37,430 --> 00:07:37,930 practitioners, 210 00:07:38,550 --> 00:07:40,149 who may or may not have doctor in 211 00:07:40,149 --> 00:07:42,149 their name. Yeah. But, you know, you can 212 00:07:42,149 --> 00:07:42,889 look around, 213 00:07:43,269 --> 00:07:45,795 Scott, and let's just say this has been 214 00:07:45,795 --> 00:07:47,714 going on for a while. I can name 215 00:07:47,875 --> 00:07:50,214 I wrote down a few specialties for which 216 00:07:50,834 --> 00:07:52,615 the amount of information 217 00:07:52,915 --> 00:07:53,415 requires 218 00:07:54,514 --> 00:07:57,175 sort of these data science machine learning applications. 219 00:07:57,314 --> 00:07:58,834 I I don't like to use the term 220 00:07:58,834 --> 00:08:01,370 AI because it gets too hyped up, and 221 00:08:01,370 --> 00:08:02,430 I think it sounds 222 00:08:02,889 --> 00:08:04,189 to a lot of people 223 00:08:04,730 --> 00:08:06,649 who aren't familiar with this like it's something 224 00:08:06,649 --> 00:08:07,870 new. I mean, it actually 225 00:08:08,569 --> 00:08:10,649 first was coined almost about, 226 00:08:11,050 --> 00:08:13,355 seventy years ago at my alma mater at 227 00:08:13,355 --> 00:08:15,275 Dartmouth, had a had a meeting. The first 228 00:08:15,355 --> 00:08:16,975 that was the when the first term 229 00:08:17,355 --> 00:08:20,314 artificial intelligence appeared. But if you look at 230 00:08:20,475 --> 00:08:22,875 let's let's just tick off some specialties. Is 231 00:08:22,875 --> 00:08:24,415 that right? Radiology. 232 00:08:25,529 --> 00:08:27,790 Huge opportunities here to 233 00:08:28,330 --> 00:08:29,710 look at, for example, 234 00:08:30,089 --> 00:08:31,050 reading by, 235 00:08:32,490 --> 00:08:33,149 a nonhuman 236 00:08:33,850 --> 00:08:34,750 on top of 237 00:08:35,129 --> 00:08:38,490 what radiology experts are using to enhance, not 238 00:08:38,490 --> 00:08:38,990 to 239 00:08:39,695 --> 00:08:41,075 not to substitute, 240 00:08:42,254 --> 00:08:43,075 better insights. 241 00:08:44,575 --> 00:08:47,134 Pathology, you know, that's a huge area where 242 00:08:47,134 --> 00:08:49,455 the the for example, the tissues that are 243 00:08:49,455 --> 00:08:49,955 being 244 00:08:50,335 --> 00:08:53,840 analyzed are subject to tremendous amounts of computing 245 00:08:53,840 --> 00:08:54,340 power 246 00:08:54,799 --> 00:08:56,559 in terms of learning. You know, just pick 247 00:08:56,559 --> 00:08:58,179 the cancer cells, for example. 248 00:08:58,559 --> 00:08:59,059 Dermatology. 249 00:08:59,600 --> 00:09:01,379 Right? That's another area that 250 00:09:01,759 --> 00:09:03,840 is is really being used on a daily 251 00:09:03,840 --> 00:09:06,019 basis. So patients can walk into their dermatologist 252 00:09:06,399 --> 00:09:07,860 and have, let's say, 253 00:09:08,235 --> 00:09:10,554 a problem with risk of melanoma and be 254 00:09:10,554 --> 00:09:12,414 subject to cameras that will 255 00:09:12,875 --> 00:09:16,174 be used using artificial intelligence to help guide, 256 00:09:16,875 --> 00:09:19,355 not only the presence of melanoma, but perhaps 257 00:09:19,355 --> 00:09:21,929 the risk of it. Oncology is a huge 258 00:09:21,929 --> 00:09:22,429 issue, 259 00:09:23,129 --> 00:09:25,149 something that I've been focused on a lot. 260 00:09:25,850 --> 00:09:26,909 Cardiac electrophysiology. 261 00:09:27,529 --> 00:09:29,289 I mean, you if someone goes in for 262 00:09:29,289 --> 00:09:31,070 atrial fibrillation, for example, 263 00:09:31,850 --> 00:09:34,190 the amount of data in these electrophysiologic, 264 00:09:35,210 --> 00:09:37,664 mappings when ablation is done is huge. You 265 00:09:37,664 --> 00:09:38,725 know, there's biosensing 266 00:09:39,745 --> 00:09:43,264 in in the world of, cardiac cardiovascular medicine 267 00:09:43,264 --> 00:09:44,644 all over the place. Ophthalmology, 268 00:09:45,424 --> 00:09:46,884 you know, getting your eyes checked 269 00:09:47,264 --> 00:09:50,180 with a camera that then can automatically, without 270 00:09:50,180 --> 00:09:52,660 even seeing a doctor, be, subject to an 271 00:09:52,660 --> 00:09:54,740 analysis that tells you if you're at risk 272 00:09:54,740 --> 00:09:55,879 for, let's say, early 273 00:09:56,500 --> 00:09:59,059 macular degeneration or diabetic eye disease. I mean, 274 00:09:59,059 --> 00:10:01,559 these things are in practice now, Scott. So 275 00:10:01,940 --> 00:10:03,700 what I'm what I'm trying to say is 276 00:10:03,700 --> 00:10:04,019 that, 277 00:10:05,004 --> 00:10:05,824 there are, 278 00:10:06,204 --> 00:10:09,564 you know, a growing growing large number of 279 00:10:09,564 --> 00:10:11,564 use cases, so to speak, from the standpoint 280 00:10:11,564 --> 00:10:14,544 of patient care. Certainly on the business side, 281 00:10:14,605 --> 00:10:16,125 we we talk about it a lot. But 282 00:10:16,125 --> 00:10:17,964 from the standpoint of what matters in health 283 00:10:17,964 --> 00:10:19,264 care, that to me is where 284 00:10:20,299 --> 00:10:22,860 the new evolution and discovery are very, very 285 00:10:22,860 --> 00:10:23,360 exciting. 286 00:10:25,100 --> 00:10:28,320 Absolutely. And, Don, as virtual care expands from 287 00:10:29,019 --> 00:10:30,080 AI enabled tools 288 00:10:30,700 --> 00:10:33,519 and remote monitoring to broader digital health platforms, 289 00:10:33,659 --> 00:10:34,959 introducing new technology 290 00:10:35,774 --> 00:10:38,334 brings new challenges. So what advice do you 291 00:10:38,334 --> 00:10:42,495 have for leaders navigating everything from governance to 292 00:10:42,495 --> 00:10:43,475 patient engagement? 293 00:10:44,254 --> 00:10:44,754 And 294 00:10:45,054 --> 00:10:46,274 can you share an example 295 00:10:46,735 --> 00:10:49,235 from your experience that's kind of balanced innovation 296 00:10:49,375 --> 00:10:51,320 with operational constraints? 297 00:10:52,740 --> 00:10:54,039 Well, obviously, 298 00:10:54,500 --> 00:10:56,740 there's the monetary aspect of this. I mean, 299 00:10:56,740 --> 00:10:59,079 you can't you don't you don't have limited 300 00:10:59,139 --> 00:11:01,875 unlimited budgets like some large health systems 301 00:11:02,674 --> 00:11:04,195 do. I mean, Mayo Clinic's got a whole 302 00:11:04,195 --> 00:11:07,235 office building with IBM across across the way 303 00:11:07,235 --> 00:11:08,054 from it. 304 00:11:08,434 --> 00:11:09,414 But that's obviously, 305 00:11:10,034 --> 00:11:12,774 a business strategy that is also enhancing Mayo's, 306 00:11:13,235 --> 00:11:14,294 you know, supportive 307 00:11:14,949 --> 00:11:15,449 care. 308 00:11:16,070 --> 00:11:17,909 That's an extreme example. But from day to 309 00:11:17,909 --> 00:11:20,230 day, the average health system doesn't have that 310 00:11:20,230 --> 00:11:21,110 type of act, 311 00:11:21,669 --> 00:11:22,970 access, so to speak. 312 00:11:23,429 --> 00:11:25,829 I'd say, let's back out of that question 313 00:11:25,829 --> 00:11:27,690 for a minute if I might. I mentioned 314 00:11:27,990 --> 00:11:28,490 sensing. 315 00:11:29,325 --> 00:11:32,225 I mean, sensing devices that patients are wearing, 316 00:11:32,365 --> 00:11:34,125 and I don't like the term wearables because 317 00:11:34,125 --> 00:11:36,465 not all sensing devices are wearable. But, 318 00:11:37,004 --> 00:11:38,785 I'm working, for example, on 319 00:11:39,165 --> 00:11:41,725 a device that can measure your blood pressure 320 00:11:41,725 --> 00:11:42,625 every beat. 321 00:11:43,299 --> 00:11:46,519 And, if your heart rate is is 60 322 00:11:46,579 --> 00:11:48,279 per minute, that's 3,600 323 00:11:48,819 --> 00:11:50,679 blood pressures taken in an hour. 324 00:11:51,220 --> 00:11:53,779 So whether we like it or not and 325 00:11:53,779 --> 00:11:55,399 these are this is one of 326 00:11:56,394 --> 00:11:58,634 many dozens of different types of devices around 327 00:11:58,634 --> 00:11:59,294 the world. 328 00:11:59,835 --> 00:12:01,595 And part of it is we don't know, 329 00:12:01,595 --> 00:12:03,514 you know, what's real and what isn't. The 330 00:12:03,514 --> 00:12:05,615 the ability to validate these devices 331 00:12:06,235 --> 00:12:08,154 you know, we're just getting started on it. 332 00:12:08,154 --> 00:12:10,919 But, certainly, you're gonna need, let's say, that 333 00:12:10,919 --> 00:12:13,320 we use the term artificial intelligence to sort 334 00:12:13,320 --> 00:12:13,820 out 335 00:12:14,440 --> 00:12:17,320 what these new devices are actually telling us. 336 00:12:17,320 --> 00:12:19,320 It isn't just, you know, my blood pressure 337 00:12:19,320 --> 00:12:20,539 was one forty anymore. 338 00:12:21,320 --> 00:12:22,860 So I think that patients 339 00:12:23,399 --> 00:12:24,220 are are 340 00:12:24,735 --> 00:12:26,975 already using more and more AI in their 341 00:12:26,975 --> 00:12:27,875 daily lives. 342 00:12:28,654 --> 00:12:29,054 And, 343 00:12:29,534 --> 00:12:31,934 you know, how how do we decide what's 344 00:12:31,934 --> 00:12:33,934 what's good and what's bad? And that's that's 345 00:12:33,934 --> 00:12:37,315 a an interface that, health systems have to 346 00:12:38,370 --> 00:12:40,850 really start working much more hard on. This 347 00:12:40,850 --> 00:12:42,529 is this is a new game. Certainly, in 348 00:12:42,529 --> 00:12:43,990 in the inpatient side, 349 00:12:45,009 --> 00:12:46,230 hospitals are using, 350 00:12:46,769 --> 00:12:48,309 you know, machine learning 351 00:12:48,690 --> 00:12:51,345 and predictive modeling and all these other 352 00:12:51,824 --> 00:12:54,004 things for people with really sick, 353 00:12:55,105 --> 00:12:57,105 who are really sick in, let's say, intensive 354 00:12:57,105 --> 00:12:59,424 care units trying to find out who's at 355 00:12:59,424 --> 00:13:01,504 risk for sepsis, etcetera. I mean, there's a 356 00:13:01,504 --> 00:13:03,985 lots lots going on in that regard that 357 00:13:03,985 --> 00:13:05,764 apply to the daily practice. 358 00:13:06,870 --> 00:13:09,589 And with that comes responsibility again to be 359 00:13:09,589 --> 00:13:11,529 sure that we're not causing harm. 360 00:13:12,069 --> 00:13:14,949 And my colleague, Constantina Alferas, who's the head 361 00:13:14,949 --> 00:13:17,129 of IHI, the Institute for Healthcare Informatics 362 00:13:18,245 --> 00:13:20,245 at University of Minnesota, has a book out 363 00:13:20,245 --> 00:13:22,664 about 450 pages saying the, 364 00:13:23,284 --> 00:13:24,565 it's it's called the, 365 00:13:25,445 --> 00:13:27,945 the strengths, so to speak, and the perils 366 00:13:28,004 --> 00:13:30,644 of artificial intelligence. And it's it's a book 367 00:13:30,644 --> 00:13:32,584 I recommend to everyone. It it's 368 00:13:33,190 --> 00:13:35,029 available. I'm not pitching the book. I'm just 369 00:13:35,029 --> 00:13:36,629 telling you that's 450 370 00:13:36,629 --> 00:13:37,129 pages. 371 00:13:37,590 --> 00:13:39,670 So we have a lot a lot a 372 00:13:39,670 --> 00:13:42,170 lot of, thinking to do about 373 00:13:42,629 --> 00:13:44,889 how we, go down this road. 374 00:13:45,910 --> 00:13:48,649 I also think that in the health system, 375 00:13:49,404 --> 00:13:50,225 to your point, 376 00:13:50,764 --> 00:13:51,804 I I think that, 377 00:13:52,605 --> 00:13:54,684 leaders can't just shoot from the hip and 378 00:13:54,684 --> 00:13:56,684 delegate and say, wow. Here's an it's something 379 00:13:56,684 --> 00:13:57,985 with AI that we're doing. 380 00:13:58,445 --> 00:13:59,884 I think they have to get down in 381 00:13:59,884 --> 00:14:01,105 the weeds every day 382 00:14:01,539 --> 00:14:02,360 and continuously 383 00:14:03,620 --> 00:14:06,519 get hands on with what's happening. Alright? Because 384 00:14:06,899 --> 00:14:09,460 clinicians, as even some of the specialties I 385 00:14:09,460 --> 00:14:11,399 mentioned that are relevant to health systems, 386 00:14:12,419 --> 00:14:14,894 are already doing this. And so the other 387 00:14:14,894 --> 00:14:17,054 the other lens is governance can no longer 388 00:14:17,054 --> 00:14:17,634 be passive. 389 00:14:18,414 --> 00:14:20,735 They have to show up and be, ready 390 00:14:20,735 --> 00:14:21,394 to support 391 00:14:21,695 --> 00:14:23,534 the health system as well. So it's a 392 00:14:23,534 --> 00:14:27,214 it's a it's a hybrid of looking at 393 00:14:27,214 --> 00:14:28,274 the organizational 394 00:14:28,735 --> 00:14:29,235 structure 395 00:14:29,740 --> 00:14:32,799 from the standpoint of who exactly is accountable. 396 00:14:33,420 --> 00:14:35,100 And I think the leaders have to hold 397 00:14:35,100 --> 00:14:37,580 themselves accountable as well. I mean, hospitals, as 398 00:14:37,580 --> 00:14:38,480 we know, will 399 00:14:38,860 --> 00:14:41,899 more and more become what I call, centers 400 00:14:41,899 --> 00:14:43,600 for advanced sick care. 401 00:14:44,205 --> 00:14:46,865 That's without question, not gonna change. 402 00:14:47,485 --> 00:14:49,325 But as we know, you know, there are 403 00:14:49,325 --> 00:14:51,825 new areas where, you know, 404 00:14:52,285 --> 00:14:53,425 patients are using, 405 00:14:54,684 --> 00:14:57,325 different aspects of this, including hospital at home. 406 00:14:57,325 --> 00:14:59,970 That's one paradigm. It isn't the only paradigm 407 00:15:00,509 --> 00:15:02,190 to get out of the hospital and not 408 00:15:02,190 --> 00:15:04,210 be in there. So I think that, 409 00:15:05,230 --> 00:15:06,210 from my standpoint, 410 00:15:07,149 --> 00:15:08,830 the best thing they can do also is 411 00:15:08,830 --> 00:15:10,990 e even within their health system is engage 412 00:15:10,990 --> 00:15:12,850 the clinical experts in the specialties. 413 00:15:13,544 --> 00:15:15,485 As one example that I spoke about, 414 00:15:16,664 --> 00:15:18,825 with the use cases that show, and this 415 00:15:18,825 --> 00:15:20,684 is the important word, Scott, impact 416 00:15:21,544 --> 00:15:24,504 on population health, not just, wow, it did 417 00:15:24,504 --> 00:15:27,050 x, y, and z, and someone likes us. 418 00:15:27,050 --> 00:15:29,050 I mean, that's important. But on the other 419 00:15:29,050 --> 00:15:29,550 hand, 420 00:15:30,410 --> 00:15:32,330 there's a lot of this that's embedded in 421 00:15:32,330 --> 00:15:33,950 the technology and will become, 422 00:15:34,410 --> 00:15:35,550 heavier and heavier 423 00:15:36,090 --> 00:15:37,610 as we go along. And so I I 424 00:15:37,610 --> 00:15:38,750 do think it requires, 425 00:15:39,290 --> 00:15:40,830 leaders to, in essence, 426 00:15:41,375 --> 00:15:42,815 get out of the house and learn as 427 00:15:42,815 --> 00:15:43,794 much as they can. 428 00:15:44,174 --> 00:15:46,575 And as I said, read books like, doctor 429 00:15:46,575 --> 00:15:48,654 Alifaras and find out what the what the 430 00:15:48,654 --> 00:15:51,214 risks are, not just the benefits, because there 431 00:15:51,214 --> 00:15:51,875 are risks. 432 00:15:52,975 --> 00:15:54,754 Absolutely. And it's certainly a very 433 00:15:55,110 --> 00:15:57,350 timely topic that everyone does need to kind 434 00:15:57,350 --> 00:15:59,610 of stay current on education with, 435 00:16:00,389 --> 00:16:00,970 of course. 436 00:16:01,750 --> 00:16:04,009 How are you seeing recent legislation, 437 00:16:04,629 --> 00:16:06,970 both state and federal, affect health care organizations 438 00:16:07,190 --> 00:16:08,684 and health care IT 439 00:16:09,384 --> 00:16:09,884 specifically. 440 00:16:10,345 --> 00:16:11,245 Have you adjusted 441 00:16:11,784 --> 00:16:13,084 strategies in response? 442 00:16:14,264 --> 00:16:17,164 Well, I I think that the question 443 00:16:17,865 --> 00:16:19,324 there there's a lot in there. 444 00:16:19,625 --> 00:16:21,144 I I do know because I watch c 445 00:16:21,144 --> 00:16:22,839 span a lot that certainly if you just 446 00:16:22,839 --> 00:16:25,720 look at the, commerce department, there's a whole 447 00:16:25,720 --> 00:16:28,600 lot centered in that one area of the 448 00:16:28,600 --> 00:16:29,100 government 449 00:16:29,799 --> 00:16:32,139 that's focused on this large scale 450 00:16:32,679 --> 00:16:33,179 discussion 451 00:16:33,559 --> 00:16:36,919 of not just AI, but the advancement of 452 00:16:37,365 --> 00:16:39,284 again, I don't even like the term digital 453 00:16:39,284 --> 00:16:39,784 technology 454 00:16:40,565 --> 00:16:42,004 around the world. I mean, there are all 455 00:16:42,004 --> 00:16:44,565 sorts of issues with cybersecurity that we can't 456 00:16:44,565 --> 00:16:47,304 even imagine right now, right, as one issue. 457 00:16:48,644 --> 00:16:50,600 But, you know, that's important 458 00:16:50,899 --> 00:16:54,360 to pay attention to from a legislative standpoint 459 00:16:54,500 --> 00:16:55,879 to to not just 460 00:16:56,259 --> 00:16:57,539 wait for a bill to come out, but 461 00:16:57,539 --> 00:16:59,700 to listen to these discussions that are occurring. 462 00:16:59,700 --> 00:17:01,779 I I find, quite frankly, people get upset 463 00:17:01,779 --> 00:17:02,600 about politics. 464 00:17:03,220 --> 00:17:05,674 If you listen to the commerce committee in 465 00:17:05,674 --> 00:17:06,255 the house, 466 00:17:06,714 --> 00:17:08,234 there are a lot of smart people there 467 00:17:08,234 --> 00:17:10,714 who actually have like minds about some of 468 00:17:10,714 --> 00:17:12,335 these issues such as cybersecurity. 469 00:17:12,794 --> 00:17:13,294 So, 470 00:17:14,315 --> 00:17:15,994 I I think it's, if you're you're just 471 00:17:15,994 --> 00:17:17,674 gonna learn about it watching the news or 472 00:17:17,674 --> 00:17:19,755 reading the the New York Times, forget about 473 00:17:19,755 --> 00:17:20,009 it. 474 00:17:20,970 --> 00:17:23,130 I do do spend a lot of time, 475 00:17:23,609 --> 00:17:26,269 specifically on the regulatory side. The FDA, 476 00:17:27,130 --> 00:17:29,529 the Food and Drug Administration has something which 477 00:17:29,529 --> 00:17:30,829 we nicknamed Cheddar, 478 00:17:31,369 --> 00:17:33,450 c d r h, Center for Devices and 479 00:17:33,450 --> 00:17:34,575 Radiologic Health, 480 00:17:35,375 --> 00:17:36,034 is really 481 00:17:36,335 --> 00:17:36,835 evolving, 482 00:17:37,375 --> 00:17:40,255 its regular regulatory approach, not just to the 483 00:17:40,255 --> 00:17:42,434 devices themselves, but something called, 484 00:17:42,815 --> 00:17:44,734 and this is their term, software as a 485 00:17:44,734 --> 00:17:46,514 medical device. So you can imagine 486 00:17:46,974 --> 00:17:48,414 let's say you've got an app on your 487 00:17:48,414 --> 00:17:50,190 phone that will tell you if 488 00:17:50,669 --> 00:17:52,669 you have signs of depression and that you 489 00:17:52,669 --> 00:17:53,730 should seek help. 490 00:17:54,109 --> 00:17:56,029 Those things have to be regulated from a 491 00:17:56,190 --> 00:17:58,669 from the standpoint of being sure that these 492 00:17:58,669 --> 00:17:58,990 aren't, 493 00:17:59,950 --> 00:18:02,589 you know, hooting and hollering about nothing and 494 00:18:02,589 --> 00:18:04,990 just sort of stuff. I mean, we're talking 495 00:18:04,990 --> 00:18:07,865 about peace people's health and people's lives now. 496 00:18:08,325 --> 00:18:09,465 And they're just beginning, 497 00:18:09,924 --> 00:18:11,924 to look at, they've been they've been at 498 00:18:11,924 --> 00:18:13,845 this for several years. I I would bet 499 00:18:13,845 --> 00:18:16,244 you most, health care leaders are not even 500 00:18:16,244 --> 00:18:18,664 aware of what CDRH is or does. But 501 00:18:18,884 --> 00:18:21,019 I think they're at least looking at things 502 00:18:21,019 --> 00:18:23,359 like AI enabled device software functions, 503 00:18:24,619 --> 00:18:25,440 which includes, 504 00:18:25,899 --> 00:18:26,399 how 505 00:18:26,779 --> 00:18:27,279 manufacturers 506 00:18:27,579 --> 00:18:28,720 should handle updates, 507 00:18:29,659 --> 00:18:30,960 monitoring, and transparency. 508 00:18:32,380 --> 00:18:34,319 You know, then these things are 509 00:18:34,674 --> 00:18:35,174 always, 510 00:18:36,434 --> 00:18:39,234 subject to lots of change on a regular 511 00:18:39,234 --> 00:18:40,295 basis given 512 00:18:40,835 --> 00:18:41,335 the, 513 00:18:42,195 --> 00:18:45,315 evaluate the evolution of the software, but also 514 00:18:45,315 --> 00:18:47,555 the evolution of information that comes out of 515 00:18:47,555 --> 00:18:48,214 the work. 516 00:18:48,619 --> 00:18:50,059 So that, you know, if we're just talking 517 00:18:50,059 --> 00:18:51,279 about, let's say, algorithms, 518 00:18:51,980 --> 00:18:54,320 how are we learning and improving over time? 519 00:18:54,700 --> 00:18:56,779 And then the amount of data that we're 520 00:18:56,779 --> 00:18:57,279 generating 521 00:18:57,980 --> 00:19:00,559 is enormous. It it's beyond belief. 522 00:19:01,714 --> 00:19:03,315 And the use of real what we call 523 00:19:03,315 --> 00:19:05,255 real world evidence is also 524 00:19:05,795 --> 00:19:08,355 coming about so that these devices, for example, 525 00:19:08,355 --> 00:19:09,654 that are occurring everywhere 526 00:19:10,195 --> 00:19:13,095 contain information. We have to analyze those 527 00:19:13,795 --> 00:19:14,195 and, 528 00:19:14,674 --> 00:19:15,414 and use, 529 00:19:16,035 --> 00:19:17,255 you know, them to 530 00:19:17,849 --> 00:19:18,990 not just evaluate 531 00:19:19,769 --> 00:19:20,269 the 532 00:19:21,049 --> 00:19:24,029 device itself from a post market surveillance standpoint, 533 00:19:24,089 --> 00:19:26,890 but for effectiveness evaluation. Right? That's really what 534 00:19:26,890 --> 00:19:28,509 we're what we're looking for. 535 00:19:29,130 --> 00:19:31,210 And, you know, here in Chicago, if I 536 00:19:31,210 --> 00:19:32,750 can put a pitch in, Scott, 537 00:19:33,954 --> 00:19:35,954 we have an exciting time because 538 00:19:36,514 --> 00:19:38,434 and this is a little bit off message, 539 00:19:38,434 --> 00:19:39,794 but I do think it's going to be 540 00:19:39,794 --> 00:19:41,414 applicable to health care. 541 00:19:41,954 --> 00:19:45,254 We have a giant effort in quantum computing 542 00:19:45,619 --> 00:19:47,619 down on the lake that's begin just beginning 543 00:19:47,619 --> 00:19:49,299 to start up. I'm sure you've heard about 544 00:19:49,299 --> 00:19:49,799 this. 545 00:19:50,420 --> 00:19:52,340 And it's amazing to me to see that 546 00:19:52,340 --> 00:19:55,559 University of Illinois, University of Chicago Northwestern, Illinois 547 00:19:55,619 --> 00:19:57,460 Tech, which used to be IIT and some 548 00:19:57,460 --> 00:19:57,960 other, 549 00:19:58,740 --> 00:20:01,160 local universities here are going together 550 00:20:01,515 --> 00:20:03,434 out to Silicon Valley to raise money for 551 00:20:03,434 --> 00:20:05,375 this. There's also IBM, Google. 552 00:20:06,154 --> 00:20:07,595 You know, you can you can throw all 553 00:20:07,595 --> 00:20:09,134 the big names into that. 554 00:20:09,434 --> 00:20:11,695 And quantum computing is going 555 00:20:12,315 --> 00:20:13,914 to obviously take a lot of energy, but 556 00:20:13,914 --> 00:20:15,775 it's also gonna increase the speed 557 00:20:16,250 --> 00:20:19,049 by which we, are now using the so 558 00:20:19,049 --> 00:20:21,630 called AI enabled devices here, 559 00:20:22,170 --> 00:20:23,309 which means that, 560 00:20:24,009 --> 00:20:25,289 we have a long way to go in 561 00:20:25,289 --> 00:20:25,950 terms of 562 00:20:26,809 --> 00:20:29,369 learning as much as we can about, what 563 00:20:29,369 --> 00:20:30,890 works. And so that to me is kind 564 00:20:30,890 --> 00:20:33,154 of exciting for the future and an example 565 00:20:33,154 --> 00:20:33,974 of why 566 00:20:34,275 --> 00:20:36,914 Chicago is, still a pretty exciting place to 567 00:20:36,914 --> 00:20:37,414 be. 568 00:20:38,115 --> 00:20:39,335 It certainly is. 569 00:20:39,634 --> 00:20:41,974 Don, you shared so so many great thoughts 570 00:20:42,275 --> 00:20:44,454 on where technology is at in health care 571 00:20:44,595 --> 00:20:47,349 and so many great practical use cases. I 572 00:20:47,589 --> 00:20:49,429 what I wanna ask for your last question 573 00:20:49,429 --> 00:20:51,669 is, what's your top piece of advice for 574 00:20:51,669 --> 00:20:53,750 health care leaders as they prepare for further 575 00:20:53,750 --> 00:20:54,970 advancements in technology 576 00:20:55,349 --> 00:20:57,049 and rising demands for care? 577 00:20:57,349 --> 00:20:59,109 Okay. Well, now you've now you've got me 578 00:20:59,109 --> 00:21:01,464 right in my sweet spot. My number one, 579 00:21:01,464 --> 00:21:04,525 number two, number three, number 10, big dot 580 00:21:04,664 --> 00:21:05,964 is high blood pressure. 581 00:21:06,585 --> 00:21:09,065 Yeah. It's not anything that anyone pays attention 582 00:21:09,065 --> 00:21:10,744 to in the C Suite or in the 583 00:21:10,744 --> 00:21:13,484 Governance Room. But to me, it's the largest 584 00:21:13,704 --> 00:21:14,845 problem in the world. 585 00:21:15,210 --> 00:21:16,589 And I'm wearing a device. 586 00:21:17,130 --> 00:21:18,890 I wore it last night, but I'm wearing 587 00:21:18,890 --> 00:21:21,289 a device that measures my blood pressure every 588 00:21:21,289 --> 00:21:22,829 beat. I told you about that. 589 00:21:23,529 --> 00:21:24,750 And I think that, 590 00:21:25,690 --> 00:21:26,990 I I would advise 591 00:21:27,454 --> 00:21:28,355 each of these, 592 00:21:28,894 --> 00:21:31,394 leaders to get something that's validated 593 00:21:31,934 --> 00:21:34,414 and learn more about their blood pressure, not 594 00:21:34,414 --> 00:21:36,494 I went to the doctor's office, you know, 595 00:21:36,494 --> 00:21:38,255 in April, and it was one thirty eight 596 00:21:38,255 --> 00:21:39,075 over 70. 597 00:21:39,694 --> 00:21:41,375 I mean, that's like saying the temperature in 598 00:21:41,375 --> 00:21:42,595 Chicago in April 599 00:21:42,910 --> 00:21:43,410 was 600 00:21:44,670 --> 00:21:45,650 62. 601 00:21:46,109 --> 00:21:48,670 And therefore, the temperature in Chicago the whole 602 00:21:48,670 --> 00:21:51,309 year is 62. It's just just not correct. 603 00:21:51,309 --> 00:21:53,390 Right? So I I would say, 604 00:21:53,869 --> 00:21:55,515 learn learn some of these. Get get to 605 00:21:55,515 --> 00:21:57,195 get to learn some of these things. Get 606 00:21:57,195 --> 00:21:58,795 down in the weeds. Go go into the 607 00:21:58,795 --> 00:21:59,295 radiology 608 00:21:59,914 --> 00:22:02,394 department and see how the radiologists are using 609 00:22:02,394 --> 00:22:03,615 this. Talk to the, 610 00:22:04,315 --> 00:22:05,295 cardiac electrophysiologist. 611 00:22:05,914 --> 00:22:08,174 I'm I'm dealing with specialists here, but, obviously, 612 00:22:09,119 --> 00:22:12,000 I think the frontline clinicians in general internal 613 00:22:12,000 --> 00:22:14,099 medicine and family medicine can easily 614 00:22:14,640 --> 00:22:16,480 tell you and show you how they're beginning 615 00:22:16,480 --> 00:22:18,819 to to use this type of information. Certainly, 616 00:22:19,440 --> 00:22:21,519 we wanna worry about revenue cycle too. So 617 00:22:21,519 --> 00:22:23,940 maybe they can have a conversation about documentation 618 00:22:24,454 --> 00:22:26,454 and coding as well. But I I think 619 00:22:26,454 --> 00:22:27,894 it's just get out of the house and 620 00:22:27,894 --> 00:22:28,954 get in the weeds. 621 00:22:29,734 --> 00:22:31,095 Don, thanks so much for joining us. It 622 00:22:31,095 --> 00:22:32,454 was a great conversation. I look forward to 623 00:22:32,454 --> 00:22:34,714 working with you again soon. Thank you, sir. 624 00:22:37,109 --> 00:22:37,849 At athenahealth, 625 00:22:38,150 --> 00:22:40,809 we know your ambulatory practice wants healthier, 626 00:22:41,269 --> 00:22:44,070 a healthier business, healthier care teams, and healthier 627 00:22:44,070 --> 00:22:44,570 patients. 628 00:22:45,029 --> 00:22:47,349 But the complexities of modern health care tech 629 00:22:47,349 --> 00:22:49,109 make it hard for you and your care 630 00:22:49,109 --> 00:22:50,865 teams to focus on what matters most. 631 00:22:51,505 --> 00:22:53,204 That's where athenahealth can help. 632 00:22:53,585 --> 00:22:56,384 Our AI native all in one solutions reduce 633 00:22:56,384 --> 00:22:57,444 administrative burdens, 634 00:22:57,744 --> 00:23:00,785 streamline billing and payments, and deliver critical insights 635 00:23:00,785 --> 00:23:03,585 when clinicians need it most. That means fewer 636 00:23:03,585 --> 00:23:06,464 clicks, more time for patients, and stronger bottom 637 00:23:06,464 --> 00:23:06,750 lines. 638 00:23:07,630 --> 00:23:10,829 Practicing medicine is complex, but running a practice 639 00:23:10,829 --> 00:23:12,690 can be that much simpler with athenahealth. 640 00:23:13,390 --> 00:23:17,089 See how simpler is healthier at athenahealth.com.