WEBVTT 00:00.000 --> 00:00.920 Hi everyone. 00:00.920 --> 00:04.860 Today we're going to be talking about redefining patient safety in the digital era. 00:05.300 --> 00:07.060 My name is Dina Mendelsohn. 00:07.060 --> 00:10.680 I'm Director of Health Policy and Data Governance at ElectroLabs. 00:11.160 --> 00:12.460 And I'm Jen Goldsack. 00:12.460 --> 00:15.520 I'm the Executive Director of the Digital Medicine Society. 00:15.520 --> 00:32.550 When Diane Diller, a woman featured in a 2019 Washington Post news article, downloaded the privacy tracking app Ovia, she used it for much the same reason as the app's 10 million other viewers, to track her pregnancy and the health of her baby. 00:33.060 --> 00:38.760 She did not intend for that information to be shared with her employer, but that's exactly what happened. 00:39.080 --> 00:41.960 Think about what's involved with making a baby. 00:42.000 --> 00:44.700 Think about how you feel if your boss got the details. 00:45.300 --> 00:52.120 It's not just embarrassing for women, it puts them at risk for pregnancy discrimination and adverse effects in the workplace. 00:53.320 --> 00:55.680 But first, some level setting. 00:56.320 --> 01:02.240 Jen will walk you through exactly what we're talking about when we talk about biometric monitoring technologies. 01:02.240 --> 01:15.520 She'll also explain why, despite a whole DEFCON talk designed to point down the safety risks of these products, we still believe that these technologies are critical for patient care and clinical research. 01:15.660 --> 01:26.540 Jen will also cover our biometric ethics portion before talking it to me to discuss the shaky ground for data rights in the United States. 01:26.540 --> 01:31.680 After that, we'll get to the fun stuff, if you consider serious safety violations to be fun. 01:32.040 --> 01:32.860 Fantastic. 01:32.860 --> 01:33.920 Thanks, Dina. 01:33.920 --> 01:40.180 So let's dive in and think about why healthcare is different in the digital age and why digital health at all. 01:40.180 --> 01:52.140 If we look at the financial information, we see huge possibilities, huge promise, and a lot of noise in Silicon Valley about the value, the financial value of this new and emerging industry. 01:52.360 --> 02:00.180 And in fact, even throughout the course of the pandemic, the first half of 2020 yielded some of the greatest investments in digital health. 02:00.180 --> 02:02.720 So is it all about the money? 02:02.820 --> 02:03.940 Absolutely not. 02:03.940 --> 02:18.380 I think that the financial investments that we've seen are a product of and perhaps an indicator for, but certainly aren't the reason that we're passionately pursuing the safe, effective, ethical, and equitable use of digital health technologies. 02:18.660 --> 02:23.920 Let's think about the healthcare environment that we've been in for the last few decades. 02:23.920 --> 02:36.660 Let's think about some of the persistent and pervasive problems that as a community, and not just as an industry, as a whole population that we face as a result of these challenges in healthcare. 02:36.940 --> 02:42.880 So in 2018, US household spending topped a trillion dollars. 02:42.880 --> 02:56.280 We know that healthcare spending writ large here in the US is over $3 trillion, but kitchen table conversations, what folks were individually being asked to write a check for to preserve their own health was over $1 trillion. 02:56.980 --> 02:59.180 Let's put that into context. 02:59.260 --> 03:04.700 $3 trillion, total healthcare spending here in the US, it's more than the GDP of France. 03:04.700 --> 03:09.760 This is an enormous industry and we are paying a price for it that we cannot afford. 03:10.680 --> 03:19.020 And despite all of this investment, our workforce here in the US is dying higher rates than any other developed country. 03:19.020 --> 03:23.680 We're paying out of the nose for healthcare and we are not getting high quality in return. 03:23.680 --> 03:29.520 In fact, the number one reason that most Americans file for bankruptcy is healthcare costs. 03:29.520 --> 03:35.040 And the other week I learned it's the number two reason cited these days in divorce proceedings. 03:35.040 --> 03:41.740 It's the stress and the strain and the financial implications of a healthcare system that is absolutely unsustainable. 03:42.140 --> 03:50.500 And despite all of this, we still have these catastrophic diseases and illnesses that we are in no place to try and treat. 03:50.500 --> 03:58.320 There is not a single disease modifying treatment available for Alzheimer's and there's certainly no cure. 03:58.320 --> 04:11.040 Interestingly, for folks who don't know, the gold standard that we use in evaluating Alzheimer's, whether it's a loved one that you're helping get treatment for, or whether it's in a clinical trial setting, is a document for the ADAS blog. 04:11.040 --> 04:15.540 It's a 30 something page paper document that physicians fill out. 04:15.540 --> 04:20.900 It's a blunt instrument that's helping us preserve the status quo. 04:20.900 --> 04:24.620 And in the absence of technology, we're really going to struggle to make progress. 04:24.860 --> 04:39.460 And the challenge is, even when we do have terrific interventions and treatments for chronic diseases, such as diabetes, one in four diabetics in the US ration their insulin because they can't afford to pay for it. 04:39.460 --> 04:43.580 This is an unsustainable status quo that we're in today. 04:43.800 --> 04:52.160 We have our warfighters coming home from service and due to PTSD that we cannot treat when they're in rural areas. 04:52.160 --> 04:59.060 There's a really terrible maldistribution of folks who can help them and the patients in need. 04:59.060 --> 05:03.460 Our American heroes are dying for preventable reasons. 05:03.700 --> 05:10.720 And finally, even the clinicians who are at the front lines have suicide rates at the highest possible level. 05:10.720 --> 05:14.680 This is a system that is broken for absolutely everyone involved. 05:14.720 --> 05:18.900 And so I would say to you that we're not here to talk about technology today because it's cool. 05:18.900 --> 05:22.300 We're not here to talk about technology because there's a ton of money in it. 05:22.300 --> 05:27.240 We are passionate about the use of these technologies to try and solve these problems. 05:27.240 --> 05:31.400 They're not going to be a silver bullet, but we believe that they can make a difference. 05:31.440 --> 05:48.920 So what we want to discuss today with this idea of a new definition of patient safety is for all of the promise that these technologies have, there are new risks that we need to be eyes wide open to to make sure that we aren't creating a new laundry list of difficulties in the digital era of health care. 05:49.500 --> 05:55.320 So let's actually talk about for a hot second what we mean when we talk about digital health. 05:55.360 --> 05:58.260 As I said, the industry is enormous. 05:58.260 --> 06:04.140 At some point we envisage digital health being a bit like computers in business. 06:04.140 --> 06:05.720 They're going to be ubiquitous. 06:05.720 --> 06:10.560 So if we're talking about a three trillion dollar industry, where are we putting the different digital components? 06:10.720 --> 06:19.100 So we would offer up a definition that the use of digital and the support of improved lives or improved health all fits into the bucket of digital health. 06:19.100 --> 06:24.460 And that includes things like communications technologies, record keeping systems, so on and so forth. 06:24.460 --> 06:33.900 Within that, there's a more specific category of digital medicine products, which both measure and intervene in the service of health. 06:33.900 --> 06:48.380 So that may be sensor technologies, that may be algorithms, that may be different tools and solutions that support the administration of active molecules and traditional devices. 06:48.380 --> 06:56.060 And then there's a very specific subset of the field that we would describe as digital therapeutics, where the software itself is the intervention. 06:56.240 --> 07:01.020 That's a new and rapidly growing field and I think an important component for us to keep in mind. 07:01.020 --> 07:08.220 For the purposes of mine and Dina's thought today, we are going to focus on biometric monitoring technologies or biometrics. 07:08.220 --> 07:24.020 And we define those specifically as connected digital medicine tools and ones that rely upon a sensor for data capture and a single or a suite of algorithms for processing that information to give us measures of a person's health status. 07:25.300 --> 07:28.800 And why are we so interested in these biometrics? 07:28.800 --> 07:31.420 This is a great visual that I like to show. 07:31.480 --> 07:42.300 If we think about how we deliver health care in current state, if we think about how we do clinical research, we're relying on these really isolated data snapshots that you see at the top of the graph. 07:42.500 --> 07:57.240 The possibility created by these biometric monitoring technologies is that we can have a much greater, a much more holistic look at a patient's lived experience with and without disease, with or without a given treatment. 07:57.240 --> 08:07.640 And that's why we're so keen to focus on this, because we see this as sort of the tip of the sphere in really addressing some of those really pressing health care challenges that I shared with you earlier. 08:09.100 --> 08:15.520 And this is a bit of a silly cartoon, but I don't... because it's important to have some levity. 08:15.520 --> 08:22.940 But I wanted to talk about how decision making actually works in health care today. 08:22.940 --> 08:27.240 Oftentimes we think about a risk-benefit analysis. 08:27.460 --> 08:30.600 It's wrong to say that we don't tolerate risk. 08:30.600 --> 08:33.400 It's wrong to say that we don't tolerate safety issues. 08:33.400 --> 08:36.640 And I think chemotherapy might be a really good example. 08:36.700 --> 08:54.240 For anyone who has battled cancer themselves or has sort of been on the journey with a loved one, we all know that the side effects of chemotherapy is often awful, from hair loss to devastating sort of sickness to weight loss, so on and so forth. 08:54.600 --> 08:59.860 There is a risk-benefit calculation that goes into the approval and prescription of those drugs. 08:59.860 --> 09:07.880 If we are in a fight to save your life, we are going to tolerate some safety issues, some quality of life issues, because there's a lot at stake. 09:08.080 --> 09:13.580 Now, we would never apply that same risk-benefit to a treatment for a common cold, for example. 09:13.580 --> 09:15.400 We can't treat a common cold, which we could. 09:15.400 --> 09:23.140 We might be having more luck for coronavirus, but there are certainly some drugs out there that can help you with the symptoms of a snotty nose, of a sore throat. 09:23.140 --> 09:27.700 We would not tolerate any safety issues from those sorts of drugs. 09:27.700 --> 09:28.340 Why? 09:28.340 --> 09:31.080 Because the risk of the cold is low. 09:31.260 --> 09:36.260 Few people are going to have any more serious issues than some pretty unpleasant symptoms for a few days. 09:36.260 --> 09:38.580 So it all comes down to that risk-benefit. 09:38.580 --> 09:41.260 The benefit of a chemotherapy is we can save your life. 09:41.260 --> 09:43.180 So we tolerate higher risks. 09:43.180 --> 09:46.980 The benefit of a common cold drug is a little more comfort for a few days. 09:46.980 --> 09:50.220 We aren't going to expose you to any additional safety risks. 09:50.520 --> 10:03.420 And so I thought that might be a really good way just to sort of ground our conversation of decision-making in healthcare and why and how we might tolerate safety risk to an individual. 10:04.860 --> 10:08.300 And so Dina and I are going to be handing off to each other. 10:08.300 --> 10:13.720 I'm going to talk briefly before I hand back to Dina about biomedical ethics. 10:13.720 --> 10:19.000 This is a huge topic, an emerging and important topic. 10:19.000 --> 10:25.420 And certainly I'm not an expert, but there are some themes that we should all be aware of. 10:25.420 --> 10:32.700 And there is some groundwork that we should have a common understanding of before we think about how digital affects healthcare. 10:33.220 --> 10:40.620 So for healthcare practice to be considered ethical, it has to sort of reflect four principles. 10:40.620 --> 10:48.220 The first is autonomy, where individuals have autonomy of thought and intention when they're making decisions. 10:48.220 --> 10:51.620 And a really good example of this is in the informed consent process. 10:51.620 --> 10:56.500 So if you're entering into a search, you need to know all of the risks and potential benefits. 10:56.500 --> 10:58.080 You need to truly understand them. 10:58.080 --> 11:00.900 And then you're asked to provide a written consent. 11:01.160 --> 11:04.940 This is also the same for anyone who's had surgery, for example. 11:04.940 --> 11:08.200 You always have an informed consent before you go into surgery. 11:08.200 --> 11:14.620 You need to know the risks and you need to knowingly opt in to participating in healthcare. 11:15.420 --> 11:18.300 Justice, I think, is really important. 11:18.460 --> 11:22.780 It helps us think about the burdens and benefits being distributed equally. 11:22.780 --> 11:25.960 So let's think about that in the context of digital. 11:25.960 --> 11:37.780 Let's think about if we start to implement the use of these biometric monitoring technologies, are we ensuring justice for folks who don't have access to broadband? 11:37.780 --> 11:41.920 Are we ensuring justice for folks who can't purchase them out of their own pocket? 11:42.340 --> 11:58.480 And then how about, you know, when we start to do research using these things, if we find great outcomes using digital technologies, can those be broadly applied to the full population if we aren't able to get everyone access to these tools? 11:58.540 --> 12:03.200 Beneficence, which is a word I often stumble over, so I nailed it today. 12:03.200 --> 12:08.560 That's like a sort of net good and a bit of a sore point for me right now. 12:08.560 --> 12:11.760 The intent of doing good for the individuals and populations involved. 12:11.760 --> 12:14.780 So for example, wear your mask during COVID. 12:14.780 --> 12:16.620 That is a nice move there. 12:16.620 --> 12:20.100 It's a pretty sensible no-brainer, in my opinion at least. 12:20.100 --> 12:30.440 And then the last one, crikey, another one I often stumble over, non-maleficence doesn't harm the individual or others in society. 12:30.520 --> 12:35.580 And this goes back to that really important principle of harm in the context of benefit. 12:35.580 --> 12:40.120 This is never a black and white decision and we always have to think about context. 12:40.120 --> 12:46.120 Again, there are some examples from COVID I'm sure sort of come quickly to mind for folks. 12:46.120 --> 12:53.700 And the way this is codified in the training of physicians at least is the Hippocratic Oath. 12:53.700 --> 13:03.420 So all graduating physicians swear the Hippocratic Oath when they finally get done with and declare victory on their passage through medical school. 13:03.420 --> 13:08.960 What's important to know about the Hippocratic Oath is it never actually says, but first do no harm. 13:08.960 --> 13:11.740 That is not present in the Hippocratic Oath. 13:11.740 --> 13:15.280 And I think I'm going to probably bore everyone, but it's really important. 13:15.280 --> 13:22.020 It comes back to this idea of risk-benefit and that's codified in the Hippocratic Oath. 13:22.020 --> 13:26.600 It's much closer to the ethical principles than it is first do no harm. 13:27.060 --> 13:35.660 And something we follow at the Digital Medicine Society and something I know that Dina and I talk about often is the great work done by Iron Recovery. 13:35.920 --> 13:51.140 Members of this community have really thought carefully about the new risks associated with security when we're starting to use connected devices either for monitoring or for healthcare intervention. 13:51.180 --> 14:09.900 And what we'll talk a little bit about today is if this community has extrapolated a vision for harm and a risk-benefit analysis to include security considerations, what are the other considerations that we need to be thinking about as we move into this digital era of healthcare? 14:10.140 --> 14:13.220 And with that, Dina, I'll hand it back to you. 14:13.580 --> 14:14.580 Thanks, Jen. 14:14.580 --> 14:24.660 I'm going to dive right into Health Policy 101, where we're going to start first by explaining the difference between privacy and data rights, so we don't lose anybody from the top. 14:26.560 --> 14:31.100 What we've always thought about is privacy tended to be something as a yes or no. 14:31.100 --> 14:32.820 Can you have this information? 14:32.900 --> 14:33.980 Yes, you can have it. 14:33.980 --> 14:35.460 No, you can't have it. 14:35.460 --> 14:46.260 But as we get further into data rights and data governance, we start to realize that the question isn't as much yes or no, but it's more about context and who. 14:46.260 --> 14:55.100 So, when we talk about data rights as opposed to privacy, the choice to share or not to share our data is context-specific and varied by the individual. 14:55.240 --> 15:02.020 A woman may feel comfortable having her reproductive health staff share information with her partner or her healthcare provider. 15:02.080 --> 15:05.520 She probably won't feel comfortable having that information shared with her boss. 15:05.520 --> 15:06.700 Or maybe she will. 15:06.700 --> 15:08.600 Maybe that's something that should be up to her. 15:08.680 --> 15:15.880 And so that's why we're moving the conversation from one that uses the word privacy to one that's talking about data rights. 15:17.540 --> 15:24.260 As it is, our healthcare system has strong protections for patient biospecimens like blood or glucose data. 15:24.260 --> 15:27.760 But protections are murkier when it comes to digital specimens. 15:28.040 --> 15:35.100 The same can be said of data created by health apps, fitness trackers, and all the other kinds of biomeths that we're talking about today. 15:35.520 --> 15:48.380 Now, as Jen said a bunch of times, and I'll reiterate, wearables, health apps, and in-home sensors offer great promise for portable, accessible, equitable, high-quality care. 15:48.640 --> 15:53.480 But in the modern era, data rights have become a safety issue that extends beyond the body. 15:53.980 --> 16:00.940 The digital health information that folks generate may threaten both their health and their financial welfare. 16:01.040 --> 16:04.340 And that's why we think it's so important that we're talking about it today. 16:07.180 --> 16:12.040 In the United States, legal protections are limited for data rights. 16:12.120 --> 16:12.460 U.S. 16:12.460 --> 16:20.700 laws do not have explicit regulations that give consumers full control over how their data is collected, used, or shared. 16:20.740 --> 16:26.980 There also really aren't rules about when we have to delete that information and what exactly that means. 16:27.060 --> 16:45.760 Instead, data rights are limited to a pathway of protection, which is basically a combination of the HIPAA privacy rule, which was never intended to be a comprehensive health privacy law, the FTC Act Section 5, which was drafted a long time before biomeths came around, 16:45.760 --> 16:58.440 and state laws, which are effectively the ultimate pathway of protection for consumers because you really don't know what protections you have unless you're a legal expert or an extremely well-informed consumer. 17:01.000 --> 17:05.620 So now we're moving on to redefining safety in the digital era. 17:05.720 --> 17:12.840 And first, I'm going to give a kind of broad description of all the different safety issues that Jen and I are concerned about. 17:14.780 --> 17:20.940 We've seen enough headlines to know that there's a problem with how our data is being collected, used, and shared. 17:21.180 --> 17:25.120 When we see headlines like these, for many of us, it feels wrong. 17:25.120 --> 17:26.480 It feels gross. 17:26.960 --> 17:35.620 Jen and I want to explore that feeling and have more technologists, clinicians, lawmakers, and the public talking about why this feels wrong. 17:35.740 --> 17:39.380 The answer is that it feels wrong because it's not safe. 17:39.740 --> 17:46.120 Women's jobs are not safe when their employer has access to their pregnancy information or plans to become pregnant. 17:46.320 --> 17:54.620 We're not safe when our insurer makes life or death decisions about our access to care based on data that may not even be right. 17:54.960 --> 18:08.940 In this section of the talk, Jen and I will walk you through a handful of data risks and related harms, not to say that technology is bad or should be avoided, but to start the conversation around data rights as an issue of patient safety. 18:12.300 --> 18:16.340 Connected health technologies have the power to do more than embarrass. 18:16.340 --> 18:23.400 The data it creates can impact how individuals experience day-to-day living and the world around them. 18:23.980 --> 18:31.120 When you share information, either passively or actively, you create information about yourself. 18:31.520 --> 18:36.480 One key way that data is used is by data brokers or data aggregators. 18:36.580 --> 18:41.820 Certainly not all data manipulation accomplished by data aggregators is harmful. 18:42.500 --> 18:55.220 However, data packets as a sort of health score can affect individuals' access to insurance, while the algorithms behind those scores are hidden and could include inaccurate information. 18:56.020 --> 19:05.840 Now, some of you may be thinking in your head that the Affordable Care Act means that these scores don't affect our access to insurance, but that's really only limited to health insurance. 19:05.840 --> 19:17.520 When you think about all the different ways that a person might want to financially protect themselves or their family, that includes life insurance, disability insurance, and long-term care insurance, to name a few. 19:17.520 --> 19:22.780 And all of those are allowed to use information created by these data aggregators. 19:22.920 --> 19:30.180 For decades, we've allowed insurers to determine our access to insurance based on genuine medical information. 19:30.360 --> 19:45.940 Now, assumptions based on unconsented data from opaque algorithms are changing how traditional underwriting is done, making it challenging for some to purchase insurance at a price that they can afford, or even being denied insurance at all. 19:47.580 --> 19:51.880 I don't need data can also impact lending and housing decisions. 19:52.000 --> 20:08.280 Studies from the American University Center for Digital Democracy and the National Bureau of Economic Research both report that consumer health data can be combined by data aggregators and used to profile and discriminate in the context of employment, 20:08.280 --> 20:13.920 education, insurance, social services, criminal justice, and finance. 20:14.140 --> 20:20.360 Clinicians and researchers may not be aware of how digital data can result in discrimination in these areas. 20:20.840 --> 20:22.380 Neither may you. 20:22.440 --> 20:30.440 But this type of data manipulation can be done as a proxy to circumvent the U.S. 20:30.440 --> 20:32.580 Equal Credit Opportunities Act. 20:32.620 --> 20:35.680 And it's not something that's going to be done transparently. 20:35.760 --> 20:37.080 However, it happens. 20:37.080 --> 20:40.680 And that's a serious safety risk that we should all be aware of and consider. 20:43.140 --> 20:47.340 Additionally, geolocation information can be used for surveillance. 20:47.700 --> 20:53.820 Wearables that measure physical activity use technology that identify an individual's precise movements. 20:54.020 --> 20:59.400 While this data is rich information for legitimate use, it can also be used for surveillance. 20:59.400 --> 21:07.960 And this is particularly problematic for people of color who are disproportionately the subject of undisclosed surveillance, data collection, and monitoring. 21:10.260 --> 21:16.640 There's other ways, of course, that even well-intended technology can cause tangible harm to users. 21:17.480 --> 21:25.260 Have you ever had that trouble falling asleep, trying to relax and to rest, and all you can think about is the fact that you can't fall asleep? 21:25.260 --> 21:28.540 You keep checking the clock and you're still awake? 21:28.680 --> 21:44.060 Now, imagine an insomniac using a sleep sensor to address sleep issues who, instead of getting helpful data and perhaps better rest, instead spends the night anxious and losing sleep over sleep data and ended up worse than they started. 21:44.140 --> 21:47.060 There's actually a term for this kind of harm. 21:47.080 --> 21:49.600 It's called othosomnia. 21:49.780 --> 21:52.500 And I'm pretty excited I just pronounced it right. 21:52.660 --> 21:55.200 Technology can also cause clinical harm. 21:55.260 --> 22:04.840 Known as e-iatrogenic harm, this type of injury can occur when errors in the data collection by biomeds goes unnoticed. 22:05.280 --> 22:11.960 And finally, I'll point out that the use of technology in a trial can inadvertently skew results. 22:11.960 --> 22:21.600 How participants are recruited over technology can be deeply problematic, as can be technology used as an incentive to participate in a trial. 22:21.600 --> 22:32.540 Similarly, deploying technology that cannot measure all participants with equal accuracy will skew data results, even if it appears as if there's an appropriate sample miss. 22:34.540 --> 22:50.600 And finally here, some people, including former president candidate Andrew Yang, think that solutions to tech companies profiting off of individual data and collecting and sharing it freely is to make that data cost something and give individuals a cut of the money. 22:51.600 --> 23:07.560 While that does play into the idea of data rights and giving individual control, this practice, which is commonly called data, or this idea, which is commonly called digital dividends, for data rights advocates like me, this amounts to pay for privacy. 23:08.020 --> 23:15.720 Survey after survey shows that consumers want more control over their private information, and they don't want their information monetized. 23:15.720 --> 23:18.720 Yet ideas like this keep coming up. 23:19.320 --> 23:32.600 When digital dividends was on the docket in Oregon in 2019, and I was serving as senior policy counsel for Consumer Reports, I wrote to lawmakers on behalf of Consumer Reports to explain why we oppose such a bill. 23:32.700 --> 23:40.400 In essence, data dividends turn the basic right of privacy into a luxury out of reach for lower income individuals. 23:40.600 --> 23:49.680 Further, those who sell their data would receive compensation for something that can't realistically be appraised, or is lost fully reimbursed. 23:50.380 --> 23:56.320 Now I'm going to turn it to Jen, who can help us think more about the safety risks with data rights. 23:56.520 --> 23:57.260 Fantastic. 23:57.260 --> 23:58.320 Thanks, Dina. 23:58.320 --> 24:10.760 And I think in terms of recognizing the broad swath of risks associated with sort of data rights and safety, I always turn to you as the expert on this. 24:10.760 --> 24:13.440 So appreciate you taking the lead there. 24:13.440 --> 24:17.760 I want to talk about some of the other principles that we touched on too. 24:17.980 --> 24:21.240 And I think a lot about equity and access. 24:21.240 --> 24:23.740 And I've got two graphs up there on the screen. 24:23.740 --> 24:25.680 They're a little small, so let me explain them to you. 24:25.680 --> 24:29.500 The one on the left is from the Dartmouth Atlas of Health. 24:29.560 --> 24:34.100 And this is an example of a specific health outcome. 24:34.100 --> 24:35.600 So red is good. 24:35.860 --> 24:48.300 In this case, that means that individuals with diabetes are actually getting the necessary vision screening to make sure that their diabetes doesn't actually lead to vision impairment and ultimately blindness. 24:48.300 --> 24:51.920 So we can see up there in New England, they're doing a great job. 24:51.920 --> 24:59.580 And in certain areas of the Midwest, dark green color is where that kind of screening is not happening at all. 24:59.640 --> 25:03.040 Individuals with diabetes are not getting high quality care. 25:03.180 --> 25:08.500 On the right hand side, you can see a map of households without internet. 25:08.600 --> 25:14.680 And there it's the red color that's showing that there is not great internet access and blue that there is. 25:14.680 --> 25:22.500 So let's think about, there's a really interesting new product on the market for the IDXDR, which is a tool that doesn't require a physician. 25:22.520 --> 25:23.680 It's a simple camera. 25:23.680 --> 25:31.340 It takes a picture of your retina and it looks to see whether diabetes patients are struggling with imminent risk of their vision. 25:31.480 --> 25:40.500 If we're relying on the internet to administer that, we can see that in New England already, they have great outcomes and that's the place with some of the best internet. 25:40.500 --> 25:47.560 Yet, if you look at Texas, they're suffering with some really poor health outcomes and most of those households don't have internet. 25:47.560 --> 26:02.400 So I come back to this idea of, are we going to use these digital tools to ameliorate some of the disparities in access to care, some of the disparities in health outcomes, or are we going to unfortunately widen that gap between the healthy and the sick, 26:02.400 --> 26:03.940 between the rich and the poor? 26:03.940 --> 26:09.160 That's something that we have to keep front of mind and I would argue is a safety issue. 26:09.900 --> 26:16.520 We also intentionally, because otherwise I think it gets overwhelming very quickly, focused on violence. 26:16.520 --> 26:28.960 But I do want to draw attention to the fact that this digital era of health goes well beyond those remote monitoring technologies that rely on those either fixed point or wearable sensors. 26:29.160 --> 26:38.780 There's been instances of using sort of care decision tools that were actually incorporating bias into care outreach. 26:38.780 --> 26:48.860 There have been other instances where we're actually defining whole new tracks of data as being important to health. 26:48.860 --> 26:50.140 And I'll give you an example. 26:50.140 --> 26:54.600 There was this phenomenal study that was done by some researchers at Microsoft. 26:54.620 --> 27:01.420 15% of pancreatic cancer patients can be identified by nothing more than their web searches. 27:01.540 --> 27:07.620 Dina summarized the pretty loose and pretty narrow privacy regulations. 27:07.700 --> 27:10.380 Certainly nothing extends to your browser history. 27:10.380 --> 27:12.140 Let's think about how this plays out. 27:12.140 --> 27:18.560 This is phenomenal if we think about your only hope in beating pancreatic cancer being an early diagnosis. 27:18.560 --> 27:21.620 If we can harness that information, this is a huge win. 27:21.620 --> 27:23.500 It's great for saving lives. 27:23.500 --> 27:26.360 But let's think back to some of the examples that Dina shared with us. 27:26.360 --> 27:38.080 What if instead of this information going to your doctor or someone who would reach out to you to say, hey, I think you're at risk and I think we can save your life if we act now, what if instead it goes to an employment agency? 27:38.080 --> 27:40.700 What if instead it goes to a life insurance company? 27:40.700 --> 27:43.160 What if instead it goes to a mortgage lender? 27:43.380 --> 27:50.640 There is the possibility here of phenomenal improvements in the way that we care for humans and the cost at which we do it. 27:50.640 --> 28:01.180 There is also really quite terrifying risk about how we use this information and the harms that individuals could suffer. 28:01.600 --> 28:07.740 And I have a bit of a flair for the dramatic and I'm very willing to cop to that one. 28:07.740 --> 28:15.220 But I don't think it's an overstatement to think about these violence and in fact digital health writ large. 28:15.220 --> 28:18.240 Are we going to weaponize it or are we going to use it as a tool? 28:18.240 --> 28:31.480 Are we going to use it as a way to do low-cost outreach to deliver personalized medicine to be as inclusive as we ever have been in the history of healthcare and hopefully better? 28:31.480 --> 28:34.440 Or are we going to use it to double down on the surveillance economy? 28:34.440 --> 28:41.860 Are we going to use it to increase the disparities in care across different races, across different socioeconomic status? 28:41.860 --> 28:55.780 And I think that means in order to address this, we one, have to be very intentional and two, as we discussed, we really do need to think about a new definition for patient safety in the digital era. 28:56.500 --> 29:02.240 And the definition of patient safety that the World Health Organization has proposed is up here on your screen. 29:02.240 --> 29:16.880 It's a lot of text, but what you can see is we're thinking mostly about the absence of preventable harm, reducing risk wherever possible, and collective notions given current knowledge, resources available, and the context of pain. 29:17.060 --> 29:23.240 So in fact when we talk about redefining patient safety, I think this definition holds up quite well. 29:23.240 --> 29:32.500 What we really need to do and what was done very well by the Hippocratic Oath, the Connected Medical Devices, and I am the Cavalry, is thinking about what is given current knowledge? 29:32.500 --> 29:34.300 What are our resources available? 29:34.300 --> 29:36.320 And what is the context of care? 29:36.320 --> 29:54.380 As we move from data in a manila folder in a file cabinet, delivered in a healthcare environment to the use of these environments, the use of search histories, the dependence on the internet to get information and to administer cures, how do we use our current knowledge about the risk? 29:54.380 --> 30:04.200 How do we use the resources available and how do we think about the context of care being now 24-7 because it's tracking your Google searches, because it's tracking your smartwatch? 30:04.200 --> 30:17.520 It's not necessarily that this definition needs to change, but we need to think about how we advance what we know in this community about harms due to connectivity to the internet. 30:17.520 --> 30:35.620 And we'd love to learn from you guys during the Q&A about your thoughts, your ideas, and any feedback on anything we've missed and how we can advance this agenda to saving lives, to reducing preventable harms as we move into this digital era of health. 30:35.740 --> 30:37.000 Thank you so much. 30:37.000 --> 30:39.900 And Dina, thank you for being such a wonderful co-presenter. 30:39.900 --> 30:41.660 I look forward to some great discussion. 30:41.680 --> 30:42.260 Thank you. 30:42.260 --> 30:43.180 This has been great.