1 00:00:00,840 --> 00:00:02,040 Science. 2 00:00:02,760 --> 00:00:06,176 The very word for many of you conjures unhappy memories of boredom 3 00:00:06,200 --> 00:00:09,096 in high school biology or physics class. 4 00:00:09,120 --> 00:00:12,216 But let me assure that what you did there 5 00:00:12,240 --> 00:00:14,416 had very little to do with science. 6 00:00:14,440 --> 00:00:16,736 That was really the "what" of science. 7 00:00:16,760 --> 00:00:19,480 It was the history of what other people had discovered. 8 00:00:20,720 --> 00:00:23,056 What I'm most interested in as a scientist 9 00:00:23,080 --> 00:00:25,216 is the "how" of science. 10 00:00:25,240 --> 00:00:29,056 Because science is knowledge in process. 11 00:00:29,080 --> 00:00:32,536 We make an observation, guess an explanation for that observation, 12 00:00:32,560 --> 00:00:34,616 and then make a prediction that we can test 13 00:00:34,640 --> 00:00:36,560 with an experiment or other observation. 14 00:00:37,080 --> 00:00:38,416 A couple of examples. 15 00:00:38,440 --> 00:00:42,016 First of all, people noticed that the Earth was below, the sky above, 16 00:00:42,040 --> 00:00:45,920 and both the Sun and the Moon seemed to go around them. 17 00:00:46,720 --> 00:00:48,256 Their guessed explanation 18 00:00:48,280 --> 00:00:51,360 was that the Earth must be the center of the universe. 19 00:00:52,240 --> 00:00:55,440 The prediction: everything should circle around the Earth. 20 00:00:56,120 --> 00:00:57,776 This was first really tested 21 00:00:57,800 --> 00:01:00,616 when Galileo got his hands on one of the first telescopes, 22 00:01:00,640 --> 00:01:03,016 and as he gazed into the night sky, 23 00:01:03,040 --> 00:01:06,736 what he found there was a planet, Jupiter, 24 00:01:06,760 --> 00:01:10,760 with four moons circling around it. 25 00:01:11,760 --> 00:01:16,136 He then used those moons to follow the path of Jupiter 26 00:01:16,160 --> 00:01:19,896 and found that Jupiter also was not going around the Earth 27 00:01:19,920 --> 00:01:21,880 but around the Sun. 28 00:01:23,160 --> 00:01:25,440 So the prediction test failed. 29 00:01:26,400 --> 00:01:28,496 And this led to the discarding of the theory 30 00:01:28,520 --> 00:01:30,696 that the Earth was the center of the universe. 31 00:01:30,720 --> 00:01:34,816 Another example: Sir Isaac Newton noticed that things fall to the Earth. 32 00:01:34,840 --> 00:01:37,760 The guessed explanation was gravity, 33 00:01:38,520 --> 00:01:41,656 the prediction that everything should fall to the Earth. 34 00:01:41,680 --> 00:01:45,240 But of course, not everything does fall to the Earth. 35 00:01:46,200 --> 00:01:47,760 So did we discard gravity? 36 00:01:48,920 --> 00:01:53,336 No. We revised the theory and said, gravity pulls things to the Earth 37 00:01:53,360 --> 00:01:57,560 unless there is an equal and opposite force in the other direction. 38 00:01:58,160 --> 00:02:00,320 This led us to learn something new. 39 00:02:00,920 --> 00:02:04,176 We began to pay more attention to the bird and the bird's wings, 40 00:02:04,200 --> 00:02:06,576 and just think of all the discoveries 41 00:02:06,600 --> 00:02:08,639 that have flown from that line of thinking. 42 00:02:09,639 --> 00:02:14,776 So the test failures, the exceptions, the outliers 43 00:02:14,800 --> 00:02:19,360 teach us what we don't know and lead us to something new. 44 00:02:20,000 --> 00:02:23,200 This is how science moves forward. This is how science learns. 45 00:02:23,840 --> 00:02:26,096 Sometimes in the media, and even more rarely, 46 00:02:26,120 --> 00:02:28,536 but sometimes even scientists will say 47 00:02:28,560 --> 00:02:31,320 that something or other has been scientifically proven. 48 00:02:31,880 --> 00:02:36,456 But I hope that you understand that science never proves anything 49 00:02:36,480 --> 00:02:38,360 definitively forever. 50 00:02:39,520 --> 00:02:43,336 Hopefully science remains curious enough 51 00:02:43,360 --> 00:02:44,776 to look for 52 00:02:44,800 --> 00:02:46,776 and humble enough to recognize 53 00:02:46,800 --> 00:02:48,296 when we have found 54 00:02:48,320 --> 00:02:50,016 the next outlier, 55 00:02:50,040 --> 00:02:51,536 the next exception, 56 00:02:51,560 --> 00:02:53,856 which, like Jupiter's moons, 57 00:02:53,880 --> 00:02:56,480 teaches us what we don't actually know. 58 00:02:57,160 --> 00:02:59,696 We're going to change gears here for a second. 59 00:02:59,720 --> 00:03:01,656 The caduceus, or the symbol of medicine, 60 00:03:01,680 --> 00:03:04,136 means a lot of different things to different people, 61 00:03:04,160 --> 00:03:06,416 but most of our public discourse on medicine 62 00:03:06,440 --> 00:03:09,216 really turns it into an engineering problem. 63 00:03:09,240 --> 00:03:10,976 We have the hallways of Congress, 64 00:03:11,000 --> 00:03:15,000 and the boardrooms of insurance companies that try to figure out how to pay for it. 65 00:03:15,680 --> 00:03:17,296 The ethicists and epidemiologists 66 00:03:17,320 --> 00:03:20,016 try to figure out how best to distribute medicine, 67 00:03:20,040 --> 00:03:22,696 and the hospitals and physicians are absolutely obsessed 68 00:03:22,720 --> 00:03:24,656 with their protocols and checklists, 69 00:03:24,680 --> 00:03:28,216 trying to figure out how best to safely apply medicine. 70 00:03:28,240 --> 00:03:30,360 These are all good things. 71 00:03:30,960 --> 00:03:33,696 However, they also all assume 72 00:03:33,720 --> 00:03:35,696 at some level 73 00:03:35,720 --> 00:03:38,240 that the textbook of medicine is closed. 74 00:03:39,160 --> 00:03:41,656 We start to measure the quality of our health care 75 00:03:41,680 --> 00:03:44,216 by how quickly we can access it. 76 00:03:44,240 --> 00:03:46,336 It doesn't surprise me that in this climate, 77 00:03:46,360 --> 00:03:49,176 many of our institutions for the provision of health care 78 00:03:49,200 --> 00:03:51,696 start to look a heck of a lot like Jiffy Lube. 79 00:03:51,720 --> 00:03:54,296 (Laughter) 80 00:03:54,320 --> 00:03:58,256 The only problem is that when I graduated from medical school, 81 00:03:58,280 --> 00:04:00,336 I didn't get one of those little doohickeys 82 00:04:00,360 --> 00:04:02,736 that your mechanic has to plug into your car 83 00:04:02,760 --> 00:04:05,136 and find out exactly what's wrong with it, 84 00:04:05,160 --> 00:04:07,256 because the textbook of medicine 85 00:04:07,280 --> 00:04:08,800 is not closed. 86 00:04:09,320 --> 00:04:11,160 Medicine is science. 87 00:04:11,560 --> 00:04:14,240 Medicine is knowledge in process. 88 00:04:15,280 --> 00:04:16,656 We make an observation, 89 00:04:16,680 --> 00:04:18,815 we guess an explanation of that observation, 90 00:04:18,839 --> 00:04:21,456 and then we make a prediction that we can test. 91 00:04:21,480 --> 00:04:25,056 Now, the testing ground of most predictions in medicine 92 00:04:25,080 --> 00:04:26,616 is populations. 93 00:04:26,640 --> 00:04:30,216 And you may remember from those boring days in biology class 94 00:04:30,240 --> 00:04:32,416 that populations tend to distribute 95 00:04:32,440 --> 00:04:33,656 around a mean 96 00:04:33,680 --> 00:04:35,536 as a Gaussian or a normal curve. 97 00:04:35,560 --> 00:04:37,216 Therefore, in medicine, 98 00:04:37,240 --> 00:04:40,456 after we make a prediction from a guessed explanation, 99 00:04:40,480 --> 00:04:42,360 we test it in a population. 100 00:04:43,320 --> 00:04:46,256 That means that what we know in medicine, 101 00:04:46,280 --> 00:04:48,536 our knowledge and our know-how, 102 00:04:48,560 --> 00:04:50,816 comes from populations 103 00:04:50,840 --> 00:04:53,616 but extends only as far 104 00:04:53,640 --> 00:04:55,376 as the next outlier, 105 00:04:55,400 --> 00:04:56,616 the next exception, 106 00:04:56,640 --> 00:04:58,376 which, like Jupiter's moons, 107 00:04:58,400 --> 00:05:00,800 will teach us what we don't actually know. 108 00:05:02,080 --> 00:05:03,416 Now, I am a surgeon 109 00:05:03,440 --> 00:05:05,856 who looks after patients with sarcoma. 110 00:05:05,880 --> 00:05:08,080 Sarcoma is a very rare form of cancer. 111 00:05:08,720 --> 00:05:10,760 It's the cancer of flesh and bones. 112 00:05:11,240 --> 00:05:15,576 And I would tell you that every one of my patients is an outlier, 113 00:05:15,600 --> 00:05:16,800 is an exception. 114 00:05:18,000 --> 00:05:21,216 There is no surgery I have ever performed for a sarcoma patient 115 00:05:21,240 --> 00:05:25,496 that has ever been guided by a randomized controlled clinical trial, 116 00:05:25,520 --> 00:05:29,240 what we consider the best kind of population-based evidence in medicine. 117 00:05:30,400 --> 00:05:32,696 People talk about thinking outside the box, 118 00:05:32,720 --> 00:05:35,456 but we don't even have a box in sarcoma. 119 00:05:35,480 --> 00:05:38,816 What we do have as we take a bath in the uncertainty 120 00:05:38,840 --> 00:05:42,976 and unknowns and exceptions and outliers that surround us in sarcoma 121 00:05:43,000 --> 00:05:47,536 is easy access to what I think are those two most important values 122 00:05:47,560 --> 00:05:49,096 for any science: 123 00:05:49,120 --> 00:05:51,320 humility and curiosity. 124 00:05:52,000 --> 00:05:54,296 Because if I am humble and curious, 125 00:05:54,320 --> 00:05:56,616 when a patient asks me a question, 126 00:05:56,640 --> 00:05:58,080 and I don't know the answer, 127 00:05:58,920 --> 00:06:00,136 I'll ask a colleague 128 00:06:00,160 --> 00:06:03,176 who may have a similar albeit distinct patient with sarcoma. 129 00:06:03,200 --> 00:06:05,896 We'll even establish international collaborations. 130 00:06:05,920 --> 00:06:09,056 Those patients will start to talk to each other through chat rooms 131 00:06:09,080 --> 00:06:10,280 and support groups. 132 00:06:10,800 --> 00:06:14,376 It's through this kind of humbly curious communication 133 00:06:14,400 --> 00:06:17,960 that we begin to try and learn new things. 134 00:06:19,240 --> 00:06:21,296 As an example, this is a patient of mine 135 00:06:21,320 --> 00:06:23,000 who had a cancer near his knee. 136 00:06:23,480 --> 00:06:25,856 Because of humbly curious communication 137 00:06:25,880 --> 00:06:27,976 in international collaborations, 138 00:06:28,000 --> 00:06:32,536 we have learned that we can repurpose the ankle to serve as the knee 139 00:06:32,560 --> 00:06:34,816 when we have to remove the knee with the cancer. 140 00:06:34,840 --> 00:06:37,680 He can then wear a prosthetic and run and jump and play. 141 00:06:38,360 --> 00:06:41,376 This opportunity was available to him 142 00:06:41,400 --> 00:06:44,176 because of international collaborations. 143 00:06:44,200 --> 00:06:45,896 It was desirable to him 144 00:06:45,920 --> 00:06:48,880 because he had contacted other patients who had experienced it. 145 00:06:49,920 --> 00:06:53,976 And so exceptions and outliers in medicine 146 00:06:54,000 --> 00:06:57,960 teach us what we don't know, but also lead us to new thinking. 147 00:06:59,080 --> 00:07:00,936 Now, very importantly, 148 00:07:00,960 --> 00:07:04,816 all the new thinking that outliers and exceptions lead us to in medicine 149 00:07:04,840 --> 00:07:08,200 does not only apply to the outliers and exceptions. 150 00:07:08,920 --> 00:07:12,096 It is not that we only learn from sarcoma patients 151 00:07:12,120 --> 00:07:14,080 ways to manage sarcoma patients. 152 00:07:14,920 --> 00:07:16,976 Sometimes, the outliers 153 00:07:17,000 --> 00:07:18,696 and the exceptions 154 00:07:18,720 --> 00:07:21,960 teach us things that matter quite a lot to the general population. 155 00:07:23,360 --> 00:07:25,216 Like a tree standing outside a forest, 156 00:07:25,240 --> 00:07:29,256 the outliers and the exceptions draw our attention 157 00:07:29,280 --> 00:07:33,616 and lead us into a much greater sense of perhaps what a tree is. 158 00:07:33,640 --> 00:07:36,136 We often talk about losing the forests for the trees, 159 00:07:36,160 --> 00:07:37,976 but one also loses a tree 160 00:07:38,000 --> 00:07:39,520 within a forest. 161 00:07:41,000 --> 00:07:42,856 But the tree that stands out by itself 162 00:07:42,880 --> 00:07:45,776 makes those relationships that define a tree, 163 00:07:45,800 --> 00:07:49,616 the relationships between trunk and roots and branches, 164 00:07:49,640 --> 00:07:50,880 much more apparent. 165 00:07:51,360 --> 00:07:53,056 Even if that tree is crooked 166 00:07:53,080 --> 00:07:56,056 or even if that tree has very unusual relationships 167 00:07:56,080 --> 00:07:58,376 between trunk and roots and branches, 168 00:07:58,400 --> 00:08:01,096 it nonetheless draws our attention 169 00:08:01,120 --> 00:08:03,016 and allows us to make observations 170 00:08:03,040 --> 00:08:05,280 that we can then test in the general population. 171 00:08:06,000 --> 00:08:07,976 I told you that sarcomas are rare. 172 00:08:08,000 --> 00:08:10,640 They make up about one percent of all cancers. 173 00:08:11,280 --> 00:08:15,240 You also probably know that cancer is considered a genetic disease. 174 00:08:15,840 --> 00:08:19,176 By genetic disease we mean that cancer is caused by oncogenes 175 00:08:19,200 --> 00:08:20,576 that are turned on in cancer 176 00:08:20,600 --> 00:08:23,640 and tumor suppressor genes that are turned off to cause cancer. 177 00:08:24,160 --> 00:08:26,576 You might think that we learned about oncogenes 178 00:08:26,600 --> 00:08:28,816 and tumor suppressor genes from common cancers 179 00:08:28,840 --> 00:08:30,816 like breast cancer and prostate cancer 180 00:08:30,840 --> 00:08:32,336 and lung cancer, 181 00:08:32,360 --> 00:08:33,559 but you'd be wrong. 182 00:08:34,000 --> 00:08:36,895 We learned about oncogenes and tumor suppressor genes 183 00:08:36,919 --> 00:08:38,135 for the first time 184 00:08:38,159 --> 00:08:41,600 in that itty-bitty little one percent of cancers called sarcoma. 185 00:08:42,760 --> 00:08:45,336 In 1966, Peyton Rous got the Nobel Prize 186 00:08:45,360 --> 00:08:47,376 for realizing that chickens 187 00:08:47,400 --> 00:08:50,520 had a transmissible form of sarcoma. 188 00:08:51,260 --> 00:08:54,096 Thirty years later, Harold Varmus and Mike Bishop discovered 189 00:08:54,120 --> 00:08:56,656 what that transmissible element was. 190 00:08:56,680 --> 00:08:58,256 It was a virus 191 00:08:58,280 --> 00:08:59,696 carrying a gene, 192 00:08:59,720 --> 00:09:01,160 the src oncogene. 193 00:09:01,880 --> 00:09:05,536 Now, I will not tell you that src is the most important oncogene. 194 00:09:05,560 --> 00:09:06,776 I will not tell you 195 00:09:06,800 --> 00:09:10,296 that src is the most frequently turned on oncogene in all of cancer. 196 00:09:10,320 --> 00:09:12,760 But it was the first oncogene. 197 00:09:13,960 --> 00:09:16,296 The exception, the outlier 198 00:09:16,320 --> 00:09:18,840 drew our attention and led us to something 199 00:09:19,520 --> 00:09:23,560 that taught us very important things about the rest of biology. 200 00:09:24,880 --> 00:09:28,976 Now, TP53 is the most important tumor suppressor gene. 201 00:09:29,000 --> 00:09:31,736 It is the most frequently turned off tumor suppressor gene 202 00:09:31,760 --> 00:09:33,560 in almost every kind of cancer. 203 00:09:34,360 --> 00:09:36,656 But we didn't learn about it from common cancers. 204 00:09:36,680 --> 00:09:39,096 We learned about it when doctors Li and Fraumeni 205 00:09:39,120 --> 00:09:40,696 were looking at families, 206 00:09:40,720 --> 00:09:42,736 and they realized that these families 207 00:09:42,760 --> 00:09:45,280 had way too many sarcomas. 208 00:09:45,920 --> 00:09:47,696 I told you that sarcoma is rare. 209 00:09:47,720 --> 00:09:50,896 Remember that a one in a million diagnosis, 210 00:09:50,920 --> 00:09:53,056 if it happens twice in one family, 211 00:09:53,080 --> 00:09:55,480 is way too common in that family. 212 00:09:56,640 --> 00:09:59,336 The very fact that these are rare 213 00:09:59,360 --> 00:10:00,800 draws our attention 214 00:10:01,760 --> 00:10:04,000 and leads us to new kinds of thinking. 215 00:10:05,480 --> 00:10:06,936 Now, many of you may say, 216 00:10:06,960 --> 00:10:08,496 and may rightly say, 217 00:10:08,520 --> 00:10:10,416 that yeah, Kevin, that's great, 218 00:10:10,440 --> 00:10:12,496 but you're not talking about a bird's wing. 219 00:10:12,520 --> 00:10:16,000 You're not talking about moons floating around some planet Jupiter. 220 00:10:16,520 --> 00:10:18,056 This is a person. 221 00:10:18,080 --> 00:10:21,336 This outlier, this exception, may lead to the advancement of science, 222 00:10:21,360 --> 00:10:22,560 but this is a person. 223 00:10:24,280 --> 00:10:25,896 And all I can say 224 00:10:25,920 --> 00:10:28,280 is that I know that all too well. 225 00:10:29,760 --> 00:10:33,160 I have conversations with these patients with rare and deadly diseases. 226 00:10:33,800 --> 00:10:35,736 I write about these conversations. 227 00:10:35,760 --> 00:10:38,056 These conversations are terribly fraught. 228 00:10:38,080 --> 00:10:39,896 They're fraught with horrible phrases 229 00:10:39,920 --> 00:10:43,160 like "I have bad news" or "There's nothing more we can do." 230 00:10:43,760 --> 00:10:46,960 Sometimes these conversations turn on a single word: 231 00:10:47,760 --> 00:10:48,960 "terminal." 232 00:10:52,920 --> 00:10:55,840 Silence can also be rather uncomfortable. 233 00:10:57,360 --> 00:10:59,936 Where the blanks are in medicine 234 00:10:59,960 --> 00:11:01,816 can be just as important 235 00:11:01,840 --> 00:11:04,080 as the words that we use in these conversations. 236 00:11:05,080 --> 00:11:06,616 What are the unknowns? 237 00:11:06,640 --> 00:11:08,840 What are the experiments that are being done? 238 00:11:09,680 --> 00:11:11,376 Do this little exercise with me. 239 00:11:11,400 --> 00:11:14,616 Up there on the screen, you see this phrase, "no where." 240 00:11:14,640 --> 00:11:15,920 Notice where the blank is. 241 00:11:16,680 --> 00:11:19,880 If we move that blank one space over 242 00:11:20,640 --> 00:11:22,216 "no where" 243 00:11:22,240 --> 00:11:24,936 becomes "now here," 244 00:11:24,960 --> 00:11:26,856 the exact opposite meaning, 245 00:11:26,880 --> 00:11:29,080 just by shifting the blank one space over. 246 00:11:31,680 --> 00:11:33,256 I'll never forget the night 247 00:11:33,280 --> 00:11:35,520 that I walked into one of my patients' rooms. 248 00:11:36,280 --> 00:11:37,936 I had been operating long that day 249 00:11:37,960 --> 00:11:39,976 but I still wanted to come and see him. 250 00:11:40,000 --> 00:11:43,200 He was a boy I had diagnosed with a bone cancer a few days before. 251 00:11:43,840 --> 00:11:46,896 He and his mother had been meeting with the chemotherapy doctors 252 00:11:46,920 --> 00:11:48,136 earlier that day, 253 00:11:48,160 --> 00:11:51,136 and he had been admitted to the hospital to begin chemotherapy. 254 00:11:51,160 --> 00:11:53,336 It was almost midnight when I got to his room. 255 00:11:53,360 --> 00:11:55,536 He was asleep, but I found his mother 256 00:11:55,560 --> 00:11:57,136 reading by flashlight 257 00:11:57,160 --> 00:11:58,616 next to his bed. 258 00:11:58,640 --> 00:12:01,440 She came out in the hall to chat with me for a few minutes. 259 00:12:02,280 --> 00:12:04,376 It turned out that what she had been reading 260 00:12:04,400 --> 00:12:06,576 was the protocol that the chemotherapy doctors 261 00:12:06,600 --> 00:12:07,840 had given her that day. 262 00:12:08,200 --> 00:12:09,440 She had memorized it. 263 00:12:11,200 --> 00:12:14,736 She said, "Dr. Jones, you told me 264 00:12:14,760 --> 00:12:16,936 that we don't always win 265 00:12:16,960 --> 00:12:18,240 with this type of cancer, 266 00:12:19,680 --> 00:12:23,160 but I've been studying this protocol, and I think I can do it. 267 00:12:23,960 --> 00:12:27,536 I think I can comply with these very difficult treatments. 268 00:12:27,560 --> 00:12:30,536 I'm going to quit my job. I'm going to move in with my parents. 269 00:12:30,560 --> 00:12:32,520 I'm going to keep my baby safe." 270 00:12:35,320 --> 00:12:36,520 I didn't tell her. 271 00:12:37,840 --> 00:12:40,760 I didn't stop to correct her thinking. 272 00:12:41,680 --> 00:12:43,936 She was trusting in a protocol 273 00:12:43,960 --> 00:12:47,176 that even if complied with, 274 00:12:47,200 --> 00:12:49,600 wouldn't necessarily save her son. 275 00:12:51,960 --> 00:12:53,160 I didn't tell her. 276 00:12:54,360 --> 00:12:55,760 I didn't fill in that blank. 277 00:12:57,080 --> 00:12:59,056 But a year and a half later 278 00:12:59,080 --> 00:13:01,800 her boy nonetheless died of his cancer. 279 00:13:03,400 --> 00:13:04,720 Should I have told her? 280 00:13:05,360 --> 00:13:07,616 Now, many of you may say, "So what? 281 00:13:07,640 --> 00:13:08,896 I don't have sarcoma. 282 00:13:08,920 --> 00:13:10,816 No one in my family has sarcoma. 283 00:13:10,840 --> 00:13:12,296 And this is all fine and well, 284 00:13:12,320 --> 00:13:15,016 but it probably doesn't matter in my life." 285 00:13:15,040 --> 00:13:16,296 And you're probably right. 286 00:13:16,320 --> 00:13:19,000 Sarcoma may not matter a whole lot in your life. 287 00:13:21,040 --> 00:13:23,376 But where the blanks are in medicine 288 00:13:23,400 --> 00:13:24,720 does matter in your life. 289 00:13:26,520 --> 00:13:28,816 I didn't tell you one dirty little secret. 290 00:13:28,840 --> 00:13:33,216 I told you that in medicine, we test predictions in populations, 291 00:13:33,240 --> 00:13:34,496 but I didn't tell you, 292 00:13:34,520 --> 00:13:36,736 and so often medicine never tells you 293 00:13:36,760 --> 00:13:39,616 that every time an individual 294 00:13:39,640 --> 00:13:41,736 encounters medicine, 295 00:13:41,760 --> 00:13:45,800 even if that individual is firmly embedded in the general population, 296 00:13:47,360 --> 00:13:49,736 neither the individual nor the physician knows 297 00:13:49,760 --> 00:13:52,440 where in that population the individual will land. 298 00:13:53,040 --> 00:13:55,736 Therefore, every encounter with medicine 299 00:13:55,760 --> 00:13:57,200 is an experiment. 300 00:13:57,920 --> 00:13:59,936 You will be a subject 301 00:13:59,960 --> 00:14:01,640 in an experiment. 302 00:14:02,560 --> 00:14:07,400 And the outcome will be either a better or a worse result for you. 303 00:14:08,320 --> 00:14:10,336 As long as medicine works well, 304 00:14:10,360 --> 00:14:13,376 we're fine with fast service, 305 00:14:13,400 --> 00:14:16,840 bravado, brimmingly confident conversations. 306 00:14:17,720 --> 00:14:19,376 But when things don't work well, 307 00:14:19,400 --> 00:14:21,240 sometimes we want something different. 308 00:14:22,520 --> 00:14:25,800 A colleague of mine removed a tumor from a patient's limb. 309 00:14:26,920 --> 00:14:28,736 He was concerned about this tumor. 310 00:14:28,760 --> 00:14:31,776 In our physician conferences, he talked about his concern 311 00:14:31,800 --> 00:14:33,216 that this was a type of tumor 312 00:14:33,240 --> 00:14:35,800 that had a high risk for coming back in the same limb. 313 00:14:36,680 --> 00:14:38,656 But his conversations with the patient 314 00:14:38,680 --> 00:14:40,776 were exactly what a patient might want: 315 00:14:40,800 --> 00:14:42,056 brimming with confidence. 316 00:14:42,080 --> 00:14:45,096 He said, "I got it all and you're good to go." 317 00:14:45,120 --> 00:14:46,856 She and her husband were thrilled. 318 00:14:46,880 --> 00:14:50,960 They went out, celebrated, fancy dinner, opened a bottle of champagne. 319 00:14:52,040 --> 00:14:54,336 The only problem was a few weeks later, 320 00:14:54,360 --> 00:14:57,456 she started to notice another nodule in the same area. 321 00:14:57,480 --> 00:15:01,616 It turned out he hadn't gotten it all, and she wasn't good to go. 322 00:15:01,640 --> 00:15:04,480 But what happened at this juncture absolutely fascinates me. 323 00:15:05,200 --> 00:15:06,816 My colleague came to me and said, 324 00:15:06,840 --> 00:15:09,560 "Kevin, would you mind looking after this patient for me?" 325 00:15:10,240 --> 00:15:13,456 I said, "Why, you know the right thing to do as well as I do. 326 00:15:13,480 --> 00:15:15,096 You haven't done anything wrong." 327 00:15:15,120 --> 00:15:19,600 He said, "Please, just look after this patient for me." 328 00:15:21,200 --> 00:15:22,736 He was embarrassed -- 329 00:15:22,760 --> 00:15:24,160 not by what he had done, 330 00:15:25,154 --> 00:15:27,080 but by the conversation that he had had, 331 00:15:27,760 --> 00:15:29,200 by the overconfidence. 332 00:15:30,600 --> 00:15:33,216 So I performed a much more invasive surgery 333 00:15:33,240 --> 00:15:36,376 and had a very different conversation with the patient afterwards. 334 00:15:36,400 --> 00:15:38,736 I said, "Most likely I've gotten it all 335 00:15:38,760 --> 00:15:41,176 and you're most likely good to go, 336 00:15:41,200 --> 00:15:44,360 but this is the experiment that we're doing. 337 00:15:45,040 --> 00:15:47,056 This is what you're going to watch for. 338 00:15:47,080 --> 00:15:48,976 This is what I'm going to watch for. 339 00:15:49,000 --> 00:15:52,936 And we're going to work together to find out if this surgery will work 340 00:15:52,960 --> 00:15:54,280 to get rid of your cancer." 341 00:15:54,920 --> 00:15:56,856 I can guarantee you, she and her husband 342 00:15:56,880 --> 00:15:59,800 did not crack another bottle of champagne after talking to me. 343 00:16:01,600 --> 00:16:04,456 But she was now a scientist, 344 00:16:04,480 --> 00:16:07,840 not only a subject in her experiment. 345 00:16:09,960 --> 00:16:11,576 And so I encourage you 346 00:16:11,600 --> 00:16:15,056 to seek humility and curiosity 347 00:16:15,080 --> 00:16:16,280 in your physicians. 348 00:16:16,760 --> 00:16:19,736 Almost 20 billion times each year, 349 00:16:19,760 --> 00:16:23,696 a person walks into a doctor's office, 350 00:16:23,720 --> 00:16:26,000 and that person becomes a patient. 351 00:16:27,320 --> 00:16:30,840 You or someone you love will be that patient sometime very soon. 352 00:16:31,840 --> 00:16:33,480 How will you talk to your doctors? 353 00:16:34,640 --> 00:16:35,840 What will you tell them? 354 00:16:36,760 --> 00:16:38,280 What will they tell you? 355 00:16:40,600 --> 00:16:42,816 They cannot tell you 356 00:16:42,840 --> 00:16:44,360 what they do not know, 357 00:16:45,560 --> 00:16:49,120 but they can tell you when they don't know 358 00:16:50,280 --> 00:16:51,640 if only you'll ask. 359 00:16:52,160 --> 00:16:55,000 So please, join the conversation. 360 00:16:56,200 --> 00:16:57,416 Thank you. 361 00:16:57,440 --> 00:17:00,308 (Applause)