[00:00.000 --> 00:04.860]  Hi everyone. Today we're going to be talking about redefining patient safety in the digital era.
[00:05.300 --> 00:10.680]  My name is Dina Mendelsohn. I'm Director of Health Policy and Data Governance at ElectroLabs.
[00:11.160 --> 00:15.520]  And I'm Jen Goldsack. I'm the Executive Director of the Digital Medicine Society.
[00:15.520 --> 00:21.640]  When Diane Diller, a woman featured in a 2019 Washington Post news article,
[00:21.640 --> 00:27.340]  downloaded the privacy tracking app Ovia, she used it for much the same reason as the app's
[00:27.340 --> 00:32.550]  10 million other viewers, to track her pregnancy and the health of her baby.
[00:33.060 --> 00:37.640]  She did not intend for that information to be shared with her employer, but that's exactly
[00:37.640 --> 00:43.200]  what happened. Think about what's involved with making a baby. Think about how you feel if your
[00:43.200 --> 00:48.640]  boss got the details. It's not just embarrassing for women, it puts them at risk for pregnancy
[00:48.640 --> 00:55.680]  discrimination and adverse effects in the workplace. But first, some level setting.
[00:56.320 --> 01:00.480]  Jen will walk you through exactly what we're talking about when we talk about biometric
[01:00.480 --> 01:07.100]  monitoring technologies. She'll also explain why, despite a whole DEFCON talk designed to
[01:07.100 --> 01:12.000]  point down the safety risks of these products, we still believe that these technologies are
[01:12.000 --> 01:19.500]  critical for patient care and clinical research. Jen will also cover our biometric ethics portion
[01:19.500 --> 01:26.540]  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 --> 01:37.480]  Fantastic. Thanks, Dina. So let's dive in and think about why healthcare is different in the
[01:37.480 --> 01:42.200]  digital age and why digital health at all. If we look at the financial information,
[01:42.200 --> 01:48.300]  we see huge possibilities, huge promise, and a lot of noise in Silicon Valley about the value,
[01:48.300 --> 01:54.080]  the financial value of this new and emerging industry. And in fact, even throughout the
[01:54.080 --> 01:59.100]  course of the pandemic, the first half of 2020 yielded some of the greatest investments in
[01:59.100 --> 02:05.540]  digital health. So is it all about the money? Absolutely not. I think that the financial
[02:05.540 --> 02:10.500]  investments that we've seen are a product of and perhaps an indicator for, but certainly aren't
[02:10.500 --> 02:16.500]  the reason that we're passionately pursuing the safe, effective, ethical, and equitable use of
[02:16.500 --> 02:22.560]  digital health technologies. Let's think about the healthcare environment that we've been in
[02:22.560 --> 02:26.980]  for the last few decades. Let's think about some of the persistent and pervasive problems
[02:26.980 --> 02:34.840]  that as a community, and not just as an industry, as a whole population that we face as a result of
[02:34.840 --> 02:42.880]  these challenges in healthcare. So in 2018, US household spending topped a trillion dollars.
[02:42.880 --> 02:47.780]  We know that healthcare spending writ large here in the US is over $3 trillion,
[02:48.400 --> 02:53.160]  but kitchen table conversations, what folks were individually being asked to write a check for
[02:53.160 --> 03:00.380]  to preserve their own health was over $1 trillion. Let's put that into context. $3 trillion,
[03:00.380 --> 03:05.620]  total healthcare spending here in the US, it's more than the GDP of France. This is an enormous
[03:05.620 --> 03:12.020]  industry and we are paying a price for it that we cannot afford. And despite all of this
[03:12.020 --> 03:19.020]  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 --> 03:28.940]  In fact, the number one reason that most Americans file for bankruptcy is healthcare
[03:28.940 --> 03:34.080]  costs. And the other week I learned it's the number two reason cited these days in divorce
[03:34.080 --> 03:39.360]  proceedings. It's the stress and the strain and the financial implications of a healthcare system
[03:39.360 --> 03:45.640]  that is absolutely unsustainable. And despite all of this, we still have these catastrophic
[03:45.640 --> 03:51.720]  diseases and illnesses that we are in no place to try and treat. There is not a single disease
[03:51.720 --> 03:59.080]  modifying treatment available for Alzheimer's and there's certainly no cure. Interestingly,
[03:59.080 --> 04:04.380]  for folks who don't know, the gold standard that we use in evaluating Alzheimer's, whether it's a
[04:04.380 --> 04:08.660]  loved one that you're helping get treatment for, or whether it's in a clinical trial setting,
[04:08.660 --> 04:14.840]  is a document for the ADAS blog. It's a 30 something page paper document that physicians
[04:14.840 --> 04:21.720]  fill out. It's a blunt instrument that's helping us preserve the status quo. And in the absence of
[04:21.720 --> 04:27.120]  technology, we're really going to struggle to make progress. And the challenge is, even when we do
[04:27.120 --> 04:35.480]  have terrific interventions and treatments for chronic diseases, such as diabetes, one in four
[04:35.480 --> 04:39.960]  diabetics in the US ration their insulin because they can't afford to pay for it. This is an
[04:39.960 --> 04:47.100]  unsustainable status quo that we're in today. We have our warfighters coming home from service
[04:47.690 --> 04:54.120]  and due to PTSD that we cannot treat when they're in rural areas. There's a really terrible
[04:54.120 --> 05:00.820]  maldistribution of folks who can help them and the patients in need. Our American heroes are
[05:00.820 --> 05:07.060]  dying for preventable reasons. And finally, even the clinicians who are at the front lines
[05:07.800 --> 05:13.180]  have suicide rates at the highest possible level. This is a system that is broken for absolutely
[05:13.180 --> 05:18.000]  everyone involved. And so I would say to you that we're not here to talk about technology today
[05:18.000 --> 05:22.300]  because it's cool. 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 --> 05:37.120]  So what we want to discuss today with this idea of a new definition of patient safety is for all
[05:37.120 --> 05:43.080]  of the promise that these technologies have, there are new risks that we need to be eyes wide open to
[05:43.080 --> 05:48.220]  to make sure that we aren't creating a new laundry list of difficulties in the digital era of health
[05:48.220 --> 05:54.400]  care. So let's actually talk about for a hot second what we mean when we talk about digital
[05:54.400 --> 06:02.600]  health. As I said, the industry is enormous. At some point we envisage digital health being a bit
[06:02.600 --> 06:06.880]  like computers in business. They're going to be ubiquitous. So if we're talking about a three
[06:06.880 --> 06:11.200]  trillion dollar industry, where are we putting the different digital components? So we would
[06:11.200 --> 06:16.360]  offer up a definition that the use of digital and the support of improved lives or improved health
[06:16.360 --> 06:20.960]  all fits into the bucket of digital health. And that includes things like communications
[06:20.960 --> 06:26.180]  technologies, record keeping systems, so on and so forth. Within that, there's a more specific
[06:26.180 --> 06:33.900]  category of digital medicine products, which both measure and intervene in the service of health.
[06:33.900 --> 06:41.340]  So that may be sensor technologies, that may be algorithms, that may be different tools and
[06:41.340 --> 06:48.380]  solutions that support the administration of active molecules and traditional devices.
[06:48.380 --> 06:53.220]  And then there's a very specific subset of the field that we would describe as digital therapeutics,
[06:53.220 --> 06:58.440]  where the software itself is the intervention. That's a new and rapidly growing field and I
[06:58.440 --> 07:03.660]  think an important component for us to keep in mind. For the purposes of mine and Dina's thought
[07:03.660 --> 07:09.120]  today, we are going to focus on biometric monitoring technologies or biometrics. And we define those
[07:09.120 --> 07:14.760]  specifically as connected digital medicine tools and ones that rely upon a sensor for data capture
[07:14.760 --> 07:19.320]  and a single or a suite of algorithms for processing that information
[07:19.320 --> 07:24.020]  to give us measures of a person's health status.
[07:25.300 --> 07:31.420]  And why are we so interested in these biometrics? This is a great visual that I like to show.
[07:31.480 --> 07:36.440]  If we think about how we deliver health care in current state, if we think about how we do
[07:36.440 --> 07:41.320]  clinical research, we're relying on these really isolated data snapshots that you see at the top
[07:41.320 --> 07:47.020]  of the graph. The possibility created by these biometric monitoring technologies is that we can
[07:47.020 --> 07:54.440]  have a much greater, a much more holistic look at a patient's lived experience with and without
[07:54.440 --> 07:59.260]  disease, with or without a given treatment. And that's why we're so keen to focus on this,
[07:59.260 --> 08:04.180]  because we see this as sort of the tip of the sphere in really addressing some of those really
[08:04.180 --> 08:11.080]  pressing health care challenges that I shared with you earlier. And this is a bit of a silly
[08:11.080 --> 08:17.760]  cartoon, but I don't... because it's important to have some levity. But I wanted to talk about
[08:17.760 --> 08:26.740]  how decision making actually works in health care today. Oftentimes we think about a risk-benefit
[08:26.740 --> 08:32.460]  analysis. It's wrong to say that we don't tolerate risk. It's wrong to say that we don't tolerate
[08:32.460 --> 08:38.080]  safety issues. And I think chemotherapy might be a really good example. For anyone who has
[08:38.080 --> 08:44.040]  battled cancer themselves or has sort of been on the journey with a loved one, we all know that the
[08:44.560 --> 08:52.220]  side effects of chemotherapy is often awful, from hair loss to devastating sort of sickness to
[08:52.220 --> 08:57.920]  weight loss, so on and so forth. There is a risk-benefit calculation that goes into the
[08:57.920 --> 09:02.280]  approval and prescription of those drugs. If we are in a fight to save your life, we are going
[09:02.280 --> 09:07.880]  to tolerate some safety issues, some quality of life issues, because there's a lot at stake.
[09:08.080 --> 09:13.680]  Now, we would never apply that same risk-benefit to a treatment for a common cold, for example. We
[09:13.680 --> 09:17.640]  can't treat a common cold, which we could. We might be having more luck for coronavirus, but
[09:17.640 --> 09:22.360]  there are certainly some drugs out there that can help you with the symptoms of a snotty nose, of a
[09:22.360 --> 09:28.900]  sore throat. We would not tolerate any safety issues from those sorts of drugs. Why? Because
[09:28.900 --> 09:34.520]  the risk of the cold is low. Few people are going to have any more serious issues than some pretty
[09:34.520 --> 09:39.180]  unpleasant symptoms for a few days. So it all comes down to that risk-benefit. The benefit of
[09:39.280 --> 09:44.700]  a chemotherapy is we can save your life. So we tolerate higher risks. The benefit of a common
[09:44.700 --> 09:48.980]  cold drug is a little more comfort for a few days. We aren't going to expose you to any additional
[09:48.980 --> 09:54.720]  safety risks. And so I thought that might be a really good way just to sort of ground our
[09:54.720 --> 10:01.980]  conversation of decision-making in healthcare and why and how we might tolerate safety risk
[10:01.980 --> 10:08.840]  to an individual. And so Dina and I are going to be handing off to each other. I'm going to talk
[10:08.840 --> 10:16.440]  briefly before I hand back to Dina about biomedical ethics. This is a huge topic,
[10:16.440 --> 10:23.680]  an emerging and important topic. And certainly I'm not an expert, but there are some themes that we
[10:23.680 --> 10:28.720]  should all be aware of. And there is some groundwork that we should have a common understanding of
[10:28.720 --> 10:32.700]  before we think about how digital affects healthcare.
[10:33.220 --> 10:39.860]  So for healthcare practice to be considered ethical, it has to sort of reflect four
[10:39.860 --> 10:46.220]  principles. The first is autonomy, where individuals have autonomy of thought and
[10:46.220 --> 10:50.380]  intention when they're making decisions. And a really good example of this is in the informed
[10:50.380 --> 10:55.320]  consent process. So if you're entering into a search, you need to know all of the risks and
[10:55.320 --> 10:59.820]  potential benefits. You need to truly understand them. And then you're asked to provide a written
[10:59.820 --> 11:06.140]  consent. This is also the same for anyone who's had surgery, for example. You always have an
[11:06.140 --> 11:11.220]  informed consent before you go into surgery. You need to know the risks and you need to knowingly
[11:11.220 --> 11:19.340]  opt in to participating in healthcare. Justice, I think, is really important. It helps us think
[11:19.340 --> 11:25.100]  about the burdens and benefits being distributed equally. So let's think about that in the context
[11:25.100 --> 11:31.020]  of digital. Let's think about if we start to implement the use of these biometric monitoring
[11:31.020 --> 11:38.320]  technologies, are we ensuring justice for folks who don't have access to broadband? Are we ensuring
[11:38.320 --> 11:45.080]  justice for folks who can't purchase them out of their own pocket? And then how about, you know,
[11:45.080 --> 11:51.240]  when we start to do research using these things, if we find great outcomes using digital technologies,
[11:51.240 --> 11:56.640]  can those be broadly applied to the full population if we aren't able to get everyone
[11:56.640 --> 12:03.200]  access to these tools? Beneficence, which is a word I often stumble over, so I nailed it today.
[12:03.200 --> 12:09.340]  That's like a sort of net good and a bit of a sore point for me right now. The intent of
[12:09.340 --> 12:14.140]  doing good for the individuals and populations involved. So for example, wear your mask during
[12:14.140 --> 12:20.100]  COVID. That is a nice move there. It's a pretty sensible no-brainer, in my opinion at least.
[12:20.100 --> 12:27.420]  And then the last one, crikey, another one I often stumble over, non-maleficence doesn't harm
[12:27.420 --> 12:34.240]  the individual or others in society. And this goes back to that really important principle of harm in
[12:34.240 --> 12:39.140]  the context of benefit. This is never a black and white decision and we always have to think about
[12:39.140 --> 12:46.120]  context. Again, there are some examples from COVID I'm sure sort of come quickly to mind for folks.
[12:46.120 --> 12:53.920]  And the way this is codified in the training of physicians at least is the Hippocratic Oath. So
[12:54.420 --> 13:00.860]  all graduating physicians swear the Hippocratic Oath when they finally get done with and declare
[13:00.860 --> 13:05.620]  victory on their passage through medical school. What's important to know about the Hippocratic
[13:05.620 --> 13:11.740]  Oath is it never actually says, but first do no harm. That is not present in the Hippocratic Oath.
[13:11.740 --> 13:16.100]  And I think I'm going to probably bore everyone, but it's really important. It comes back to this
[13:16.100 --> 13:23.680]  idea of risk-benefit and that's codified in the Hippocratic Oath. It's much closer to the ethical
[13:23.680 --> 13:29.920]  principles than it is first do no harm. And something we follow at the Digital Medicine
[13:29.920 --> 13:34.560]  Society and something I know that Dina and I talk about often is the great work done by Iron
[13:34.560 --> 13:42.820]  Recovery. Members of this community have really thought carefully about the new risks associated
[13:42.820 --> 13:49.280]  with security when we're starting to use connected devices either for monitoring or
[13:49.280 --> 13:56.260]  for healthcare intervention. And what we'll talk a little bit about today is if this community has
[13:56.260 --> 14:03.560]  extrapolated a vision for harm and a risk-benefit analysis to include security considerations,
[14:03.560 --> 14:08.560]  what are the other considerations that we need to be thinking about as we move into this digital
[14:08.560 --> 14:13.220]  era of healthcare? And with that, Dina, I'll hand it back to you.
[14:13.580 --> 14:19.160]  Thanks, Jen. I'm going to dive right into Health Policy 101, where we're going to start first by
[14:19.160 --> 14:24.660]  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 --> 14:35.460]  Can you have this information? Yes, you can have it. No, you can't have it.
[14:35.460 --> 14:40.560]  But as we get further into data rights and data governance, we start to realize that the
[14:40.560 --> 14:47.500]  question isn't as much yes or no, but it's more about context and who. So, when we talk about
[14:47.500 --> 14:53.200]  data rights as opposed to privacy, the choice to share or not to share our data is context-specific
[14:53.200 --> 14:58.520]  and varied by the individual. A woman may feel comfortable having her reproductive health staff
[14:58.520 --> 15:03.140]  share information with her partner or her healthcare provider. She probably won't feel
[15:03.140 --> 15:07.340]  comfortable having that information shared with her boss. Or maybe she will. Maybe that's something
[15:07.340 --> 15:12.820]  that should be up to her. And so that's why we're moving the conversation from one that uses the
[15:12.820 --> 15:19.800]  word privacy to one that's talking about data rights. As it is, our healthcare system has
[15:19.800 --> 15:25.880]  strong protections for patient biospecimens like blood or glucose data. But protections are murkier
[15:25.880 --> 15:30.680]  when it comes to digital specimens. The same can be said of data created by health apps,
[15:30.680 --> 15:35.100]  fitness trackers, and all the other kinds of biomeths that we're talking about today.
[15:35.520 --> 15:41.020]  Now, as Jen said a bunch of times, and I'll reiterate, wearables, health apps, and in-home
[15:41.020 --> 15:48.380]  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 --> 16:00.020]  The digital health information that folks generate may threaten both their health and their financial
[16:00.020 --> 16:04.340]  welfare. And that's why we think it's so important that we're talking about it today.
[16:07.180 --> 16:14.080]  In the United States, legal protections are limited for data rights. U.S. laws do not have
[16:14.080 --> 16:19.580]  explicit regulations that give consumers full control over how their data is collected, used,
[16:19.580 --> 16:25.360]  or shared. There also really aren't rules about when we have to delete that information and what
[16:25.360 --> 16:31.800]  exactly that means. Instead, data rights are limited to a pathway of protection, which is
[16:31.800 --> 16:36.660]  basically a combination of the HIPAA privacy rule, which was never intended to be a comprehensive
[16:36.660 --> 16:44.860]  health privacy law, the FTC Act Section 5, which was drafted a long time before biomeths came
[16:44.860 --> 16:51.260]  around, and state laws, which are effectively the ultimate pathway of protection for consumers
[16:51.820 --> 16:56.320]  because you really don't know what protections you have unless you're a legal expert or an
[16:56.320 --> 17:04.700]  extremely well-informed consumer. So now we're moving on to redefining safety in the digital
[17:04.700 --> 17:10.060]  era. And first, I'm going to give a kind of broad description of all the different
[17:10.060 --> 17:16.820]  safety issues that Jen and I are concerned about. We've seen enough headlines to know
[17:16.820 --> 17:22.540]  that there's a problem with how our data is being collected, used, and shared. When we see headlines
[17:22.540 --> 17:28.720]  like these, for many of us, it feels wrong. It feels gross. Jen and I want to explore that feeling
[17:28.720 --> 17:35.620]  and have more technologists, clinicians, lawmakers, and the public talking about why this feels wrong.
[17:35.740 --> 17:41.680]  The answer is that it feels wrong because it's not safe. Women's jobs are not safe when their
[17:41.680 --> 17:47.480]  employer has access to their pregnancy information or plans to become pregnant. We're not safe when
[17:47.480 --> 17:53.500]  our insurer makes life or death decisions about our access to care based on data that may not even
[17:53.500 --> 17:59.380]  be right. In this section of the talk, Jen and I will walk you through a handful of data risks and
[17:59.380 --> 18:05.280]  related harms, not to say that technology is bad or should be avoided, but to start the conversation
[18:05.280 --> 18:15.000]  around data rights as an issue of patient safety. Connected health technologies have the power to do
[18:15.000 --> 18:20.400]  more than embarrass. The data it creates can impact how individuals experience day-to-day
[18:20.400 --> 18:28.160]  living and the world around them. When you share information, either passively or actively,
[18:28.160 --> 18:35.140]  you create information about yourself. One key way that data is used is by data brokers or data
[18:35.140 --> 18:41.820]  aggregators. Certainly not all data manipulation accomplished by data aggregators is harmful.
[18:42.500 --> 18:49.600]  However, data packets as a sort of health score can affect individuals' access to insurance,
[18:49.600 --> 18:55.220]  while the algorithms behind those scores are hidden and could include inaccurate information.
[18:56.020 --> 19:00.740]  Now, some of you may be thinking in your head that the Affordable Care Act means that these
[19:00.740 --> 19:05.840]  scores don't affect our access to insurance, but that's really only limited to health insurance.
[19:05.840 --> 19:09.980]  When you think about all the different ways that a person might want to financially protect
[19:09.980 --> 19:15.240]  themselves or their family, that includes life insurance, disability insurance,
[19:15.240 --> 19:20.280]  and long-term care insurance, to name a few. And all of those are allowed to use information
[19:20.280 --> 19:26.460]  created by these data aggregators. For decades, we've allowed insurers to determine our access
[19:26.460 --> 19:32.140]  to insurance based on genuine medical information. Now, assumptions based on
[19:32.140 --> 19:38.220]  unconsented data from opaque algorithms are changing how traditional underwriting is done,
[19:38.220 --> 19:43.000]  making it challenging for some to purchase insurance at a price that they can afford,
[19:43.000 --> 19:45.940]  or even being denied insurance at all.
[19:47.580 --> 19:52.660]  I don't need data can also impact lending and housing decisions. Studies
[19:52.660 --> 19:58.280]  from the American University Center for Digital Democracy and the National Bureau of Economic
[19:58.280 --> 20:03.580]  Research both report that consumer health data can be combined by data aggregators
[20:03.580 --> 20:09.800]  and used to profile and discriminate in the context of employment, education, insurance,
[20:09.800 --> 20:16.640]  social services, criminal justice, and finance. Clinicians and researchers may not be aware of
[20:16.640 --> 20:22.960]  how digital data can result in discrimination in these areas. Neither may you. But this type
[20:22.960 --> 20:31.720]  of data manipulation can be done as a proxy to circumvent the U.S. Equal Credit Opportunities
[20:31.720 --> 20:37.080]  Act. And it's not something that's going to be done transparently. 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 --> 20:52.680]  Wearables that measure physical activity use technology that identify an individual's precise
[20:52.680 --> 20:58.780]  movements. While this data is rich information for legitimate use, it can also be used for
[20:58.780 --> 21:02.260]  surveillance. And this is particularly problematic for people of color
[21:02.260 --> 21:06.720]  who are disproportionately the subject of undisclosed surveillance, data collection,
[21:06.720 --> 21:13.700]  and monitoring. There's other ways, of course, that even well-intended technology
[21:13.700 --> 21:20.200]  can cause tangible harm to users. Have you ever had that trouble falling asleep,
[21:20.200 --> 21:25.260]  trying to relax and to rest, and all you can think about is the fact that you can't fall asleep?
[21:25.260 --> 21:30.940]  You keep checking the clock and you're still awake? Now, imagine an insomniac using a sleep
[21:30.940 --> 21:37.440]  sensor to address sleep issues who, instead of getting helpful data and perhaps better rest,
[21:37.440 --> 21:42.940]  instead spends the night anxious and losing sleep over sleep data and ended up worse than
[21:42.940 --> 21:49.600]  they started. There's actually a term for this kind of harm. It's called othosomnia.
[21:49.780 --> 21:55.200]  And I'm pretty excited I just pronounced it right. Technology can also cause clinical harm.
[21:55.260 --> 22:01.760]  Known as e-iatrogenic harm, this type of injury can occur when errors in the data collection
[22:01.760 --> 22:08.980]  by biomeds goes unnoticed. And finally, I'll point out that the use of technology in a trial
[22:08.980 --> 22:15.300]  can inadvertently skew results. How participants are recruited over technology can be deeply
[22:15.300 --> 22:21.600]  problematic, as can be technology used as an incentive to participate in a trial.
[22:21.600 --> 22:26.900]  Similarly, deploying technology that cannot measure all participants with equal accuracy
[22:26.900 --> 22:32.540]  will skew data results, even if it appears as if there's an appropriate sample miss.
[22:34.540 --> 22:39.900]  And finally here, some people, including former president candidate Andrew Yang,
[22:39.900 --> 22:44.920]  think that solutions to tech companies profiting off of individual data and collecting and sharing
[22:44.920 --> 22:50.600]  it freely is to make that data cost something and give individuals a cut of the money.
[22:51.600 --> 22:56.660]  While that does play into the idea of data rights and giving individual control,
[22:56.660 --> 23:01.660]  this practice, which is commonly called data, or this idea, which is commonly called digital
[23:01.660 --> 23:08.560]  dividends, for data rights advocates like me, this amounts to pay for privacy. Survey after
[23:08.560 --> 23:13.720]  survey shows that consumers want more control over their private information, and they don't
[23:13.720 --> 23:21.000]  want their information monetized. Yet ideas like this keep coming up. When digital dividends was
[23:21.000 --> 23:27.080]  on the docket in Oregon in 2019, and I was serving as senior policy counsel for Consumer Reports,
[23:27.080 --> 23:32.600]  I wrote to lawmakers on behalf of Consumer Reports to explain why we oppose such a bill.
[23:32.700 --> 23:38.780]  In essence, data dividends turn the basic right of privacy into a luxury out of reach for lower
[23:38.780 --> 23:45.180]  income individuals. Further, those who sell their data would receive compensation for something that
[23:45.180 --> 23:51.980]  can't realistically be appraised, or is lost fully reimbursed. Now I'm going to turn it to Jen,
[23:51.980 --> 23:58.940]  who can help us think more about the safety risks with data rights. Fantastic. Thanks, Dina. And I
[23:58.940 --> 24:07.360]  think in terms of recognizing the broad swath of risks associated with sort of data rights
[24:07.360 --> 24:13.440]  and safety, I always turn to you as the expert on this. 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 --> 24:23.740]  And I think a lot about equity and access. And I've got two graphs up there on the screen.
[24:23.740 --> 24:27.200]  They're a little small, so let me explain them to you. The one on the left is from the Dartmouth
[24:27.920 --> 24:35.600]  Atlas of Health. And this is an example of a specific health outcome. So red is good.
[24:35.860 --> 24:40.740]  In this case, that means that individuals with diabetes are actually getting the necessary
[24:40.740 --> 24:47.220]  vision screening to make sure that their diabetes doesn't actually lead to vision impairment and
[24:47.220 --> 24:51.920]  ultimately blindness. So we can see up there in New England, they're doing a great job.
[24:51.920 --> 24:58.340]  And in certain areas of the Midwest, dark green color is where that kind of screening is not
[24:58.340 --> 25:04.080]  happening at all. Individuals with diabetes are not getting high quality care. On the right hand
[25:04.080 --> 25:10.240]  side, you can see a map of households without internet. And there it's the red color that's
[25:10.240 --> 25:16.040]  showing that there is not great internet access and blue that there is. So let's think about,
[25:16.040 --> 25:21.080]  there's a really interesting new product on the market for the IDXDR, which is a tool that doesn't
[25:21.080 --> 25:26.300]  require a physician. It's a simple camera. It takes a picture of your retina and it looks to
[25:26.300 --> 25:32.380]  see whether diabetes patients are struggling with imminent risk of their vision. If we're relying
[25:32.380 --> 25:37.240]  on the internet to administer that, we can see that in New England already, they have great
[25:37.240 --> 25:42.280]  outcomes and that's the place with some of the best internet. Yet, if you look at Texas, they're
[25:42.280 --> 25:47.560]  suffering with some really poor health outcomes and most of those households don't have internet.
[25:47.560 --> 25:53.000]  So I come back to this idea of, are we going to use these digital tools to ameliorate some of the
[25:53.000 --> 25:58.580]  disparities in access to care, some of the disparities in health outcomes, or are we going to
[25:58.580 --> 26:03.940]  unfortunately widen that gap between the healthy and the sick, 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 --> 26:15.280]  We also intentionally, because otherwise I think it gets overwhelming very quickly,
[26:15.280 --> 26:19.880]  focused on violence. But I do want to draw attention to the fact that this digital era of
[26:19.880 --> 26:26.840]  health goes well beyond those remote monitoring technologies that rely on those either fixed
[26:26.840 --> 26:33.260]  point or wearable sensors. There's been instances of using sort of care decision tools
[26:33.260 --> 26:40.540]  that were actually incorporating bias into care outreach. There have been other instances
[26:41.540 --> 26:49.080]  where we're actually defining whole new tracks of data as being important to health. And I'll
[26:49.080 --> 26:53.520]  give you an example. There was this phenomenal study that was done by some researchers at
[26:53.520 --> 27:00.480]  Microsoft. 15% of pancreatic cancer patients can be identified by nothing more than their web
[27:00.480 --> 27:08.160]  searches. Dina summarized the pretty loose and pretty narrow privacy regulations. Certainly
[27:08.160 --> 27:13.200]  nothing extends to your browser history. Let's think about how this plays out. This is phenomenal
[27:13.200 --> 27:18.560]  if we think about your only hope in beating pancreatic cancer being an early diagnosis.
[27:18.560 --> 27:24.000]  If we can harness that information, this is a huge win. It's great for saving lives. But let's
[27:24.000 --> 27:28.480]  think back to some of the examples that Dina shared with us. What if instead of this information going
[27:28.480 --> 27:32.960]  to your doctor or someone who would reach out to you to say, hey, I think you're at risk and I
[27:32.960 --> 27:38.280]  think we can save your life if we act now, what if instead it goes to an employment agency? What if
[27:38.280 --> 27:43.160]  instead it goes to a life insurance company? What if instead it goes to a mortgage lender?
[27:43.380 --> 27:49.000]  There is the possibility here of phenomenal improvements in the way that we care for humans
[27:49.000 --> 27:55.940]  and the cost at which we do it. There is also really quite terrifying risk about how we use
[27:55.940 --> 28:02.980]  this information and the harms that individuals could suffer. And I have a bit of a flair for
[28:02.980 --> 28:09.980]  the dramatic and I'm very willing to cop to that one. But I don't think it's an overstatement to
[28:09.980 --> 28:16.480]  think about these violence and in fact digital health writ large. Are we going to weaponize it
[28:16.480 --> 28:23.420]  or are we going to use it as a tool? Are we going to use it as a way to do low-cost outreach to
[28:23.420 --> 28:28.700]  deliver personalized medicine to be as inclusive as we ever have been in the history of healthcare
[28:28.700 --> 28:34.440]  and hopefully better? Or are we going to use it to double down on the surveillance economy?
[28:34.440 --> 28:40.380]  Are we going to use it to increase the disparities in care across different races, across different
[28:40.380 --> 28:46.980]  socioeconomic status? And I think that means in order to address this, we one, have to be
[28:46.980 --> 28:52.860]  very intentional and two, as we discussed, we really do need to think about a new definition
[28:52.860 --> 28:59.260]  for patient safety in the digital era. And the definition of patient safety that the World Health
[28:59.260 --> 29:04.380]  Organization has proposed is up here on your screen. It's a lot of text, but what you can see
[29:04.380 --> 29:10.580]  is we're thinking mostly about the absence of preventable harm, reducing risk wherever possible,
[29:10.840 --> 29:16.880]  and collective notions given current knowledge, resources available, and the context of pain.
[29:17.060 --> 29:22.520]  So in fact when we talk about redefining patient safety, I think this definition holds up quite
[29:22.520 --> 29:27.220]  well. What we really need to do and what was done very well by the Hippocratic Oath,
[29:27.220 --> 29:32.020]  the Connected Medical Devices, and I am the Cavalry, is thinking about what is given current
[29:32.020 --> 29:37.720]  knowledge? What are our resources available? And what is the context of care? As we move from data
[29:37.720 --> 29:43.940]  in a manila folder in a file cabinet, delivered in a healthcare environment to the use of these
[29:43.940 --> 29:49.180]  environments, the use of search histories, the dependence on the internet to get information
[29:49.180 --> 29:54.820]  and to administer cures, how do we use our current knowledge about the risk? How do we
[29:54.820 --> 30:00.360]  use the resources available and how do we think about the context of care being now 24-7 because
[30:00.360 --> 30:05.460]  it's tracking your Google searches, because it's tracking your smartwatch? It's not necessarily
[30:05.460 --> 30:11.560]  that this definition needs to change, but we need to think about how we advance what we know
[30:11.560 --> 30:20.180]  in this community about harms due to connectivity to the internet. And we'd love to learn from you
[30:20.180 --> 30:25.680]  guys during the Q&A about your thoughts, your ideas, and any feedback on anything we've missed
[30:25.680 --> 30:33.440]  and how we can advance this agenda to saving lives, to reducing preventable harms as we move
[30:33.440 --> 30:39.100]  into this digital era of health. Thank you so much. And Dina, thank you for being such a wonderful
[30:39.100 --> 30:43.180]  co-presenter. I look forward to some great discussion. Thank you. This has been great.