WEBVTT 00:00:00.809 --> 00:00:02.270 I'm going to talk to you today 00:00:02.294 --> 00:00:05.777 about the design of medical technology for low-resource settings. 00:00:05.801 --> 00:00:08.154 I study health systems in these countries. 00:00:08.178 --> 00:00:10.093 And one of the major gaps in care, 00:00:10.117 --> 00:00:11.776 almost across the board, 00:00:11.800 --> 00:00:13.967 is access to safe surgery. 00:00:13.991 --> 00:00:16.650 Now one of the major bottlenecks that we've found 00:00:16.674 --> 00:00:19.909 that's sort of preventing both the access in the first place, 00:00:19.933 --> 00:00:23.369 and the safety of those surgeries that do happen, is anesthesia. 00:00:23.846 --> 00:00:26.238 And actually, it's the model that we expect to work 00:00:26.262 --> 00:00:28.961 for delivering anesthesia in these environments. NOTE Paragraph 00:00:29.620 --> 00:00:33.473 Here, we have a scene that you would find in any operating room across the US, 00:00:33.497 --> 00:00:34.974 or any other developed country. 00:00:34.998 --> 00:00:36.185 In the background there 00:00:36.209 --> 00:00:38.780 is a very sophisticated anesthesia machine. 00:00:38.804 --> 00:00:42.653 And this machine is able to enable surgery and save lives 00:00:42.677 --> 00:00:45.976 because it was designed with this environment in mind. 00:00:46.329 --> 00:00:49.261 In order to operate, this machine needs a number of things 00:00:49.285 --> 00:00:51.185 that this hospital has to offer. 00:00:51.209 --> 00:00:54.577 It needs an extremely well-trained anesthesiologist 00:00:54.601 --> 00:00:57.052 with years of training with complex machines 00:00:57.076 --> 00:00:59.497 to help her monitor the flows of the gas 00:00:59.521 --> 00:01:02.084 and keep her patients safe and anesthetized 00:01:02.108 --> 00:01:03.559 throughout the surgery. 00:01:03.583 --> 00:01:06.350 It's a delicate machine running on computer algorithms, 00:01:06.374 --> 00:01:09.592 and it needs special care, TLC, to keep it up and running, 00:01:09.616 --> 00:01:11.474 and it's going to break pretty easily. 00:01:11.498 --> 00:01:14.410 And when it does, it needs a team of biomedical engineers 00:01:14.434 --> 00:01:17.743 who understand its complexities, can fix it, can source the parts 00:01:17.767 --> 00:01:19.999 and keep it saving lives. NOTE Paragraph 00:01:20.688 --> 00:01:22.222 It's a pretty expensive machine. 00:01:22.246 --> 00:01:24.887 It needs a hospital whose budget can allow it 00:01:24.911 --> 00:01:29.805 to support one machine costing upwards of 50 or $100,000. 00:01:30.296 --> 00:01:32.195 And perhaps most obviously, 00:01:32.219 --> 00:01:33.733 but also most importantly -- 00:01:33.757 --> 00:01:36.593 and the path to concepts that we've heard about 00:01:36.617 --> 00:01:37.903 kind of illustrates this -- 00:01:37.927 --> 00:01:43.073 it needs infrastructure that can supply an uninterrupted source of electricity, 00:01:43.097 --> 00:01:46.109 of compressed oxygen, and other medical supplies 00:01:46.133 --> 00:01:50.411 that are so critical to the functioning of this machine. 00:01:50.435 --> 00:01:53.734 In other words, this machine requires a lot of stuff 00:01:53.758 --> 00:01:55.731 that this hospital cannot offer. NOTE Paragraph 00:01:56.332 --> 00:01:59.352 This is the electrical supply for a hospital in rural Malawi. 00:02:00.153 --> 00:02:01.314 In this hospital, 00:02:01.338 --> 00:02:04.009 there is one person qualified to deliver anesthesia, 00:02:04.033 --> 00:02:05.185 and she's qualified 00:02:05.209 --> 00:02:09.785 because she has 12, maybe 18 months of training in anesthesia. 00:02:09.809 --> 00:02:12.056 In the hospital and in the entire region 00:02:12.080 --> 00:02:14.087 there's not a single biomedical engineer. 00:02:14.111 --> 00:02:15.680 So when this machine breaks, 00:02:15.704 --> 00:02:17.913 the machines that they have to work with break, 00:02:17.937 --> 00:02:19.706 they've got to try and figure it out, 00:02:19.730 --> 00:02:22.022 but most of the time, that's the end of the road. 00:02:22.046 --> 00:02:24.263 Those machines go the proverbial junkyard. 00:02:24.287 --> 00:02:26.616 And the price tag of the machine that I mentioned 00:02:26.640 --> 00:02:28.701 could represent maybe a quarter or a third 00:02:28.725 --> 00:02:31.537 of the annual operating budget for this hospital. NOTE Paragraph 00:02:32.580 --> 00:02:35.964 And finally, I think you can see that infrastructure is not very strong. 00:02:35.988 --> 00:02:38.662 This hospital is connected to a very weak power grid, 00:02:38.686 --> 00:02:40.468 one that goes down frequently. 00:02:40.492 --> 00:02:43.038 So it runs frequently, the entire hospital, 00:02:43.062 --> 00:02:44.485 just on a generator. 00:02:44.509 --> 00:02:46.665 And you can imagine, the generator breaks down 00:02:46.689 --> 00:02:48.001 or runs out of fuel. 00:02:48.361 --> 00:02:50.388 And the World Bank sees this 00:02:50.412 --> 00:02:53.943 and estimates that a hospital in this setting in a low-income country 00:02:53.967 --> 00:02:57.043 can expect up to 18 power outages per month. 00:02:58.658 --> 00:03:01.851 Similarly, compressed oxygen and other medical supplies 00:03:01.875 --> 00:03:03.057 are really a luxury, 00:03:03.081 --> 00:03:06.363 and can often be out of stock for months or even a year. NOTE Paragraph 00:03:06.387 --> 00:03:09.551 So it seems crazy, but the model that we have right now 00:03:09.575 --> 00:03:11.780 is taking those machines that were designed 00:03:11.804 --> 00:03:14.087 for that first environment that I showed you 00:03:14.111 --> 00:03:17.975 and donating or selling them to hospitals in this environment. 00:03:18.861 --> 00:03:20.437 It's not just inappropriate, 00:03:20.461 --> 00:03:22.999 it becomes really unsafe. NOTE Paragraph 00:03:23.516 --> 00:03:25.438 One of our partners at Johns Hopkins 00:03:25.462 --> 00:03:29.641 was observing surgeries in Sierra Leone about a year ago. 00:03:30.225 --> 00:03:33.558 And the first surgery of the day happened to be an obstetrical case. 00:03:33.582 --> 00:03:36.565 A woman came in, she needed an emergency C-section 00:03:36.589 --> 00:03:39.318 to save her life and the life of her baby. 00:03:39.805 --> 00:03:41.759 And everything began pretty auspiciously. 00:03:41.783 --> 00:03:44.036 The surgeon was on call and scrubbed in. 00:03:44.060 --> 00:03:45.348 The nurse was there. 00:03:45.372 --> 00:03:48.233 She was able to anesthetize her quickly, and it was important 00:03:48.257 --> 00:03:50.593 because of the emergency nature of the situation. 00:03:50.617 --> 00:03:52.334 And everything began well 00:03:52.358 --> 00:03:54.430 until the power went out. 00:03:55.773 --> 00:03:57.597 And now in the middle of this surgery, 00:03:57.621 --> 00:04:00.690 the surgeon is racing against the clock to finish his case, 00:04:00.714 --> 00:04:03.066 which he can do -- he's got a headlamp. 00:04:03.090 --> 00:04:07.151 But the nurse is literally running around a darkened operating theater 00:04:07.175 --> 00:04:10.130 trying to find anything she can use to anesthetize her patient, 00:04:10.154 --> 00:04:11.843 to keep her patient asleep. 00:04:11.867 --> 00:04:14.750 Because her machine doesn't work when there's no power. 00:04:15.437 --> 00:04:18.491 This routine surgery that many of you have probably experienced, 00:04:18.515 --> 00:04:22.989 and others are probably the product of, has now become a tragedy. 00:04:23.655 --> 00:04:26.391 And what's so frustrating is this is not a singular event; 00:04:26.415 --> 00:04:28.914 this happens across the developing world. 00:04:28.938 --> 00:04:31.891 35 million surgeries are attempted every year 00:04:31.915 --> 00:04:33.511 without safe anesthesia. NOTE Paragraph 00:04:34.210 --> 00:04:37.122 My colleague, Dr. Paul Fenton, was living this reality. 00:04:37.146 --> 00:04:38.976 He was the chief of anesthesiology 00:04:39.000 --> 00:04:41.500 in a hospital in Malawi, a teaching hospital. 00:04:42.028 --> 00:04:43.522 He went to work every day 00:04:43.546 --> 00:04:45.514 in an operating theater like this one, 00:04:45.538 --> 00:04:48.677 trying to deliver anesthesia and teach others how to do so 00:04:48.701 --> 00:04:49.976 using that same equipment 00:04:50.000 --> 00:04:54.311 that became so unreliable, and frankly unsafe, in his hospital. 00:04:55.039 --> 00:04:56.819 And after umpteen surgeries 00:04:56.843 --> 00:04:59.411 and, you can imagine, really unspeakable tragedy, 00:04:59.435 --> 00:05:01.777 he just said, "That's it. I'm done. That's enough. 00:05:01.801 --> 00:05:03.871 There has to be something better." 00:05:04.229 --> 00:05:05.776 He took a walk down the hall 00:05:05.800 --> 00:05:09.231 to where they threw all those machines that had just crapped out on them, 00:05:09.255 --> 00:05:10.932 I think that's the scientific term, 00:05:10.956 --> 00:05:12.298 and he started tinkering. 00:05:12.322 --> 00:05:14.675 He took one part from here and another from there, 00:05:14.699 --> 00:05:17.281 and he tried to come up with a machine that would work 00:05:17.305 --> 00:05:18.933 in the reality that he was facing. NOTE Paragraph 00:05:18.957 --> 00:05:20.171 And what he came up with: 00:05:20.195 --> 00:05:21.518 was this guy. 00:05:21.542 --> 00:05:25.079 The prototype for the Universal Anesthesia Machine -- 00:05:25.103 --> 00:05:28.400 a machine that would work and anesthetize his patients 00:05:28.424 --> 00:05:31.999 no matter the circumstances that his hospital had to offer. 00:05:32.519 --> 00:05:34.000 Here it is, back at home 00:05:34.024 --> 00:05:37.453 at that same hospital, developed a little further, 12 years later, 00:05:37.477 --> 00:05:40.657 working on patients from pediatrics to geriatrics. NOTE Paragraph 00:05:41.137 --> 00:05:43.907 Let me show you a little bit about how this machine works. 00:05:43.931 --> 00:05:45.809 Voila! 00:05:46.452 --> 00:05:47.659 Here she is. 00:05:47.683 --> 00:05:48.927 When you have electricity, 00:05:48.951 --> 00:05:51.969 everything in this machine begins in the base. 00:05:51.993 --> 00:05:54.590 There's a built-in oxygen concentrator down there. 00:05:54.614 --> 00:05:57.743 Now you've heard me mention oxygen a few times at this point. 00:05:57.767 --> 00:06:01.555 Essentially, to deliver anesthesia, you want as pure oxygen as possible, 00:06:01.579 --> 00:06:05.002 because eventually you're going to dilute it, essentially, with the gas. 00:06:05.026 --> 00:06:07.462 And the mixture that the patient inhales 00:06:07.486 --> 00:06:09.797 needs to be at least a certain percentage oxygen 00:06:09.821 --> 00:06:11.507 or else it can become dangerous. 00:06:11.531 --> 00:06:13.449 But so in here when there's electricity, 00:06:13.473 --> 00:06:16.348 the oxygen concentrator takes in room air. 00:06:16.372 --> 00:06:19.651 Now we know room air is gloriously free, 00:06:19.675 --> 00:06:20.976 it is abundant, 00:06:21.000 --> 00:06:22.999 and it's already 21 percent oxygen. 00:06:23.436 --> 00:06:27.113 So all this concentrator does is take that room air in, filter it 00:06:27.137 --> 00:06:30.957 and send 95 percent pure oxygen up and across here, 00:06:30.981 --> 00:06:33.187 where it mixes with the anesthetic agent. NOTE Paragraph 00:06:33.743 --> 00:06:37.367 Now before that mixture hits the patient's lungs, 00:06:37.391 --> 00:06:39.605 it's going to pass by here -- you can't see it, 00:06:39.629 --> 00:06:41.411 but there's an oxygen sensor here -- 00:06:41.435 --> 00:06:45.640 that's going to read out on this screen the percentage of oxygen being delivered. 00:06:46.284 --> 00:06:48.258 Now if you don't have power, 00:06:48.282 --> 00:06:51.888 or, God forbid, the power cuts out in the middle of a surgery, 00:06:51.912 --> 00:06:54.256 this machine transitions automatically, 00:06:54.280 --> 00:06:56.029 without even having to touch it, 00:06:56.053 --> 00:06:58.384 to drawing in room air from this inlet. NOTE Paragraph 00:06:58.805 --> 00:07:00.141 Everything else is the same. 00:07:00.165 --> 00:07:01.761 The only difference is that now 00:07:01.785 --> 00:07:04.999 you're only working with 21 percent oxygen. 00:07:05.406 --> 00:07:08.227 Now that used to be a dangerous guessing game, 00:07:08.251 --> 00:07:10.637 because you only knew if you gave too little oxygen 00:07:10.661 --> 00:07:12.037 once something bad happened. 00:07:12.061 --> 00:07:14.774 But we've put a long-life battery backup on here. 00:07:14.798 --> 00:07:16.992 This is the only part that's battery backed up. 00:07:17.016 --> 00:07:20.421 But this gives control to the provider, whether there's power or not, 00:07:20.445 --> 00:07:22.038 because they can adjust the flows 00:07:22.062 --> 00:07:26.030 based on the percentage of oxygen they see that they're giving the patient. NOTE Paragraph 00:07:26.054 --> 00:07:29.399 In both cases, whether you have power or not, 00:07:29.423 --> 00:07:31.463 sometimes the patient needs help breathing. 00:07:31.487 --> 00:07:34.688 It's just a reality of anesthesia, the lungs can be paralyzed. 00:07:34.712 --> 00:07:36.796 And so we've just added this manual bellows. 00:07:36.820 --> 00:07:39.811 We've seen surgeries for three or four hours 00:07:39.835 --> 00:07:41.693 to ventilate the patient on this. NOTE Paragraph 00:07:42.424 --> 00:07:45.412 So it's a straightforward machine. 00:07:45.436 --> 00:07:48.341 I shudder to say simple; it's straightforward. 00:07:48.936 --> 00:07:50.837 And it's by design. 00:07:50.861 --> 00:07:56.061 You do not need to be a highly trained, specialized anesthesiologist 00:07:56.085 --> 00:07:57.256 to use this machine, 00:07:57.280 --> 00:08:00.032 which is good because, in these rural district hospitals, 00:08:00.056 --> 00:08:02.651 you're not going to get that level of training. 00:08:02.675 --> 00:08:05.803 It's also designed for the environment that it will be used in. NOTE Paragraph 00:08:05.827 --> 00:08:07.604 This is an incredibly rugged machine. 00:08:07.628 --> 00:08:11.083 It has to stand up to the heat and the wear and tear 00:08:11.107 --> 00:08:14.225 that happens in hospitals in these rural districts. 00:08:14.249 --> 00:08:16.644 And so it's not going to break very easily, 00:08:16.668 --> 00:08:19.942 but if it does, virtually every piece in this machine 00:08:19.966 --> 00:08:21.976 can be swapped out and replaced 00:08:22.000 --> 00:08:23.994 with a hex wrench and a screwdriver. 00:08:25.750 --> 00:08:28.010 And finally, it's affordable. 00:08:28.034 --> 00:08:31.687 This machine comes in at an eighth of the cost 00:08:31.711 --> 00:08:34.789 of the conventional machine that I showed you earlier. 00:08:34.813 --> 00:08:39.301 So in other words, what we have here is a machine that can enable surgery 00:08:39.325 --> 00:08:40.497 and save lives, 00:08:40.521 --> 00:08:43.511 because it was designed for its environment, 00:08:43.535 --> 00:08:45.953 just like the first machine I showed you. NOTE Paragraph 00:08:45.977 --> 00:08:47.981 But we're not content to stop there. 00:08:48.005 --> 00:08:49.180 Is it working? 00:08:49.204 --> 00:08:51.786 Is this the design that's going to work in place? 00:08:51.810 --> 00:08:53.577 Well, we've seen good results so far. 00:08:53.601 --> 00:08:56.986 This is in 13 hospitals in four countries, 00:08:57.010 --> 00:09:00.943 and since 2010, we've done well over 2,000 surgeries 00:09:00.967 --> 00:09:03.200 with no clinically adverse events. 00:09:03.540 --> 00:09:04.707 So we're thrilled. 00:09:04.731 --> 00:09:09.153 This really seems like a cost-effective, scalable solution 00:09:09.177 --> 00:09:11.210 to a problem that's really pervasive. 00:09:11.698 --> 00:09:13.298 But we still want to be sure 00:09:13.322 --> 00:09:15.739 that this is the most effective and safe device 00:09:15.763 --> 00:09:17.820 that we can be putting into hospitals. NOTE Paragraph 00:09:17.844 --> 00:09:20.368 So to do that, we've launched a number of partnerships 00:09:20.392 --> 00:09:21.878 with NGOs and universities, 00:09:21.902 --> 00:09:24.551 to gather data on the user interface, 00:09:24.575 --> 00:09:26.767 on the types of surgeries it's appropriate for, 00:09:26.791 --> 00:09:29.178 and ways we can enhance the device itself. 00:09:29.202 --> 00:09:31.856 One of those partnerships is with Johns Hopkins 00:09:31.880 --> 00:09:33.253 just here in Baltimore. 00:09:33.277 --> 00:09:37.555 They have a really cool anesthesia simulation lab out in Baltimore. 00:09:37.579 --> 00:09:39.460 So we're taking this machine 00:09:39.484 --> 00:09:43.058 and recreating some of the operating theater crises 00:09:43.082 --> 00:09:44.589 that this machine might face 00:09:44.613 --> 00:09:46.976 in one of the hospitals that it's intended for, 00:09:47.000 --> 00:09:49.124 and in a contained, safe environment, 00:09:49.148 --> 00:09:50.865 evaluating its effectiveness. 00:09:51.347 --> 00:09:54.979 We're then able to compare the results from that study 00:09:55.003 --> 00:09:56.423 with real-world experience, 00:09:56.447 --> 00:09:58.644 because we're putting two of these in hospitals 00:09:58.668 --> 00:10:00.819 that Johns Hopkins works with in Sierra Leone, 00:10:00.843 --> 00:10:03.957 including the hospital where that emergency C-section happened. NOTE Paragraph 00:10:05.385 --> 00:10:08.513 So I've talked a lot about anesthesia, and I tend to do that. 00:10:08.537 --> 00:10:12.629 I think it is incredibly fascinating and an important component of health. 00:10:12.653 --> 00:10:15.284 And it really seems peripheral, we never think about it, 00:10:15.308 --> 00:10:17.512 until we don't have access to it, 00:10:17.536 --> 00:10:19.498 and then it becomes a gatekeeper. 00:10:19.522 --> 00:10:21.491 Who gets surgery and who doesn't? 00:10:21.824 --> 00:10:24.554 Who gets safe surgery and who doesn't? 00:10:25.216 --> 00:10:27.679 But you know, it's just one of so many ways 00:10:27.703 --> 00:10:30.810 that design, appropriate design, 00:10:30.834 --> 00:10:32.810 can have an impact on health outcomes. 00:10:33.318 --> 00:10:35.437 If more people in the health-delivery space 00:10:35.461 --> 00:10:39.030 really working on some of these challenges in low-income countries 00:10:39.054 --> 00:10:42.707 could start their design process, their solution search, 00:10:42.731 --> 00:10:44.669 from outside of that proverbial box 00:10:44.693 --> 00:10:46.631 and inside of the hospital -- 00:10:46.655 --> 00:10:48.486 In other words, if we could design 00:10:48.510 --> 00:10:51.701 for the environment that exists in so many parts of the world, 00:10:51.725 --> 00:10:54.134 rather than the one that we wished existed -- 00:10:54.158 --> 00:10:56.324 we might just save a lot of lives. NOTE Paragraph 00:10:56.787 --> 00:10:58.255 Thank you very much. NOTE Paragraph 00:10:58.279 --> 00:11:02.714 (Applause)