Speaker 1: This is a very real problem that directly affects millions
Speaker 1: of people around the world. If we expand that to
Speaker 1: look at the indirect effects, such as how disparity creates
Speaker 1: enormous stress on communities around the world, we're talking about
Speaker 1: billions of people who are impacted by this issue. And
Speaker 1: for me at least, this was a really big problem
Speaker 1: where using technology wasn't an apparent path. If you were
Speaker 1: to ask me how technology could help address an issue
Speaker 1: like the disparity among different populations when it comes to
Speaker 1: health care access, I would be at a loss. But
Speaker 1: as it turns out, technology can play an important role
Speaker 1: in that effort. As we'll learn, tech is really one
Speaker 1: piece of it. Real solutions to eliminating disparity will require
Speaker 1: much more than technology. I spoke with Dr q Ree,
Speaker 1: Chief Health off Sir at IBM and Dr Irene don
Speaker 1: Qua Mullen, Deputy Chief Health Officer IBM Watson Health about
Speaker 1: this issue. Both doctors have dedicated an enormous amount of
Speaker 1: time and effort as positions and data experts to create
Speaker 1: a more equitable access to health services across all communities.
Speaker 1: They helped me get a deeper understanding of the challenges
Speaker 1: we face, how they impact millions of people, and the
Speaker 1: way technology plays a part in addressing the problem. Thank
Speaker 1: you both for joining me today. We have a lot
Speaker 1: of ground to cover and a big topic to talk about,
Speaker 1: but before we really dive into that, I wanted to
Speaker 1: hear a little bit about your personal story, about your
Speaker 1: journey and how you got to where you are today
Speaker 1: and your personal reflections upon the really big challenge of
Speaker 1: disparities and access to health and health care services. Dr Rey,
Speaker 1: would you care to share a little bit of your
Speaker 1: background owned and your personal experience. Sure, now, I appreciate that.
Speaker 1: So I currently serve as the chief Health Officer for
Speaker 1: IBM and Watson Health. I'm a physician by training and
Speaker 1: also UM have some background in in health policy. But
Speaker 1: if I were to reflect on how my journey in
Speaker 1: health and healthcare started, in some ways, it might have
Speaker 1: started since I was born. UM. I was born in Soul, Korea.
Speaker 1: My I was the eldest child of of my generation
Speaker 1: and UM I got very sick at a very young age.
Speaker 1: When I was several months old, I was having UM
Speaker 1: what was known as failure to thrive and I wasn't
Speaker 1: able to gain weight and the the health care system
Speaker 1: at the time, UM wasn't able to find a solution,
Speaker 1: and my my parents, UM we're told as go go home,
Speaker 1: and and likely that I wasn't going to UM make it,
Speaker 1: and so UM, in a fascinating way, things things changed.
Speaker 1: I was able to gain weight, and my mother, who
Speaker 1: was a nurse, UM, you know uh uh supported my
Speaker 1: my growth. And then we immigrated to the US, a
Speaker 1: country of extraordinary opportunity to to start a new life
Speaker 1: with my dad who's an economist in the World Bank,
Speaker 1: and my mom is a nurse. And UM was fortunate
Speaker 1: enough as an immigrant to to really have a supportive family,
Speaker 1: plus an extraordinary education that helped me recognize, you know,
Speaker 1: the value of health and and the role that we
Speaker 1: could play UM in advancing and improving the health of populations.
Speaker 1: I trained as a physician in internal medicine and pediatrics
Speaker 1: to take care of families. I had the the good
Speaker 1: fortune of taking care of a lot of families, many
Speaker 1: of whom were immigrant families UH in d c. And Baltimore,
Speaker 1: and many from communities of color and poverty. And then
Speaker 1: UM had the good fortune to work in the federal
Speaker 1: government as a health policymaker and look at health disparities
Speaker 1: and the challenges of health and healthcare across the country domestically,
Speaker 1: and even play a small role in the health policy
Speaker 1: around the Affordable Care Act, which played a very significant
Speaker 1: role in expanding care for underserved populations. And now have
Speaker 1: the good fortune nearly a decade working for IBM and
Speaker 1: looking at global public health and and looking at ways
Speaker 1: in which data, analytics and AI can support the health
Speaker 1: of the populations of the clients and partners we serve.
Speaker 1: Fascinating a doctor don Qua Mullin, can you tell us
Speaker 1: a little bit about your background and your journey. Yes, absolutely,
Speaker 1: um so I also a Service Deputy Chief Health Officer
Speaker 1: UM at IBM Watson Health and Chief Health Equity Officer,
Speaker 1: and I have primary responsibility for science, data and evidence
Speaker 1: research and evaluation. And I also as Chief Health Equity
Speaker 1: Officer UM basically helps to ensure AH equity, health, health equity,
Speaker 1: diversity and inclusion UM working with Q and the brilliant
Speaker 1: team at IBM Watson Health. In terms of my journey,
Speaker 1: am I grew up in Ghana. I knew a woman
Speaker 1: at our heart who was also called Irene Um. She
Speaker 1: was a dentist UH and I actually called an anti
Speaker 1: Irene even though there were no relation because she was
Speaker 1: At that time, there were very few women doctors in
Speaker 1: Ghana that I knew, and I was really inspired by
Speaker 1: hair so Um. To be honest, I was also motivated
Speaker 1: by the idea of being thought as someone smart, intelligent, caring,
Speaker 1: and a dedicated physician who was also a woman. So
Speaker 1: I really really wanted to have those qualities that I
Speaker 1: saw in in anti Irene. Um. In addition to growing
Speaker 1: up in Ghana, which was which is quite different right
Speaker 1: from the US, there was a lot of illness that
Speaker 1: I saw that were chronic um and diseases that were
Speaker 1: easily preventable with either vaccination or it's cleaning and early detection. UM.
Speaker 1: I actually remember getting moms. I remember, UM. I don't
Speaker 1: remember getting measles, but I was told I had measles
Speaker 1: as a child. Um. You know, a health care system
Speaker 1: was was overburdened, health care was rationed and I and
Speaker 1: I experienced and I saw all of this. But I
Speaker 1: was also drawn by this opportunity to pursue a deeper
Speaker 1: um scientific understanding of the human body, right the physiology
Speaker 1: of the disease, why it occurs, UM and UM I
Speaker 1: sort of really knew that there was disease outside of
Speaker 1: just UM clinical care because of what I saw with
Speaker 1: you know, lack of nutrition and hydration UM in in
Speaker 1: growing up, and so as I entered I came here
Speaker 1: UM actually for college after I finished high school UM I,
Speaker 1: and when I entered medical school and residency and learn
Speaker 1: more about determinants of health, it was sort of on
Speaker 1: aha moment and UM in medical school, I went into
Speaker 1: public health as well, so I did a double public
Speaker 1: health medicine degree and UM MY and becoming a primary
Speaker 1: care physician UM was what I wanted to do. And
Speaker 1: I realized really, yes, I wanted to care for vulnerable
Speaker 1: and socially disadvantage populations. I wanted to be more compassionate,
Speaker 1: you know, listen and understanding and value UM their culture
Speaker 1: and beliefs. UM. But but I also had that motivation
Speaker 1: about changing the way medicine was always focused on clinical
Speaker 1: care in the US, you know, seeing the sick chronically ill,
Speaker 1: to focus on also addressing determinants and disparities and and
Speaker 1: supporting interventions around what we know as social determinants, and
Speaker 1: you know, both need to work together. So I had
Speaker 1: do you just like UM Dr v i UM worked
Speaker 1: in public health and also had the opportunity to work
Speaker 1: at the National Institutes of Health the health care side.
Speaker 1: Can you talk a bit about what it is IBM
Speaker 1: is doing in that space, what are your teams actually pursuing.
Speaker 1: Health is so foundational and essential to the value proposition
Speaker 1: that I hope and I believe IBM has played and
Speaker 1: will play during this crisis and beyond UM. If you
Speaker 1: think about UM information, data, analytics, and and and the
Speaker 1: opportunities around artificial intelligence and machine learning and analytics and
Speaker 1: predictive analytics UM, there's such an important role to address
Speaker 1: health UM for the what I would call the multiple
Speaker 1: stakeholders in a health ecosystem. If you think about how
Speaker 1: data and even care or money flows in healthcare, which
Speaker 1: in the US represents one in five dollars and in
Speaker 1: most developed countries one in ten dollars and in most
Speaker 1: developing countries one and twenty. The the nature of health
Speaker 1: and health care is that it typically you've got a patient,
Speaker 1: a citizen, a consumer who comes in with a challenge
Speaker 1: on an issue. UM. We know that of that spend
Speaker 1: of that challenge in terms of costs is related to
Speaker 1: chronic diseases like diabetes, like heart disease, like asthma, like COPD,
Speaker 1: like depression, like arthritis, like cancer. And there is a
Speaker 1: encounter that I that Irene had, you know, have the
Speaker 1: good fortunate as physicians to take care of in that
Speaker 1: privileged moment to take care of a patient you know,
Speaker 1: and and and and offer support in those short you know,
Speaker 1: five to ten minutes sometimes twenty minutes conversations and interactions,
Speaker 1: and and that data flows in a certain way. It
Speaker 1: flows to a pay er a health plan. It flows
Speaker 1: to an employer who often is the one who pays
Speaker 1: those bills for for their workforce and their family members.
Speaker 1: It flows potentially to a farmer company as they think
Speaker 1: about studies and trials um. It flows to a government
Speaker 1: if you think about all the testing that's happening with
Speaker 1: COVID nineteen now and and and the challenges of contact
Speaker 1: tracing and treatment in isolation and quarantining. So there's an
Speaker 1: ecosystem here as it relates to health and the impact
Speaker 1: that health has on has on you know, people, communities, families,
Speaker 1: and the role that data analytics and AI and the
Speaker 1: expertise of people at IBM who you know, are experts
Speaker 1: in data science, are expert into and computing, our experts
Speaker 1: into you know, Watson and machine learning to bring those
Speaker 1: worlds together of tech and health and healthcare. I mean,
Speaker 1: what better endeavor than to try to improve the health
Speaker 1: of populations. Fantastic And this kind of also brings us
Speaker 1: to the discussion at hand for today. This is a
Speaker 1: huge topic disparity in access to healthcare, to health services,
Speaker 1: to health information, and that it has as of itself.
Speaker 1: It's it's such an enormous thing and it has so
Speaker 1: many facets. It's challenging to talk about because there are
Speaker 1: so many different ways we could go at it. We
Speaker 1: could look at it along aspects of socio economic levels, regions,
Speaker 1: we could look at it by race, and it is
Speaker 1: a complicated issue. Can you talk a little bit about
Speaker 1: the overall concept of health disparity. We have a challenge
Speaker 1: globally domad e stickally in communities all across this country
Speaker 1: and all across the globe where there are members of
Speaker 1: our family who are ill, who suffer disproportionately from illness
Speaker 1: from those chronic diseases like diabetes, like heart disease, like cancer,
Speaker 1: like asthma, like depression, And we have an opportunity and
Speaker 1: responsibility in terms of our values to find ways to
Speaker 1: bring those folks back to better health. And unfortunately, many
Speaker 1: of the factors that represent how those family members are
Speaker 1: ill are are are based on risk factors that are
Speaker 1: associated with things like race or ethnicity, or sexual orientation
Speaker 1: or socio economic status or you know, education or employment.
Speaker 1: And so it's so essential for us to to to
Speaker 1: think about this as a society, to think about the
Speaker 1: values that we believe are essential for us to be
Speaker 1: you know, you know, to support our family members, but
Speaker 1: also you know, create a dynamic where we we we
Speaker 1: we bring those those health disparity populations back up in
Speaker 1: terms of health. So that's how I you know, simplified
Speaker 1: or think about it in terms of health disparities. And
Speaker 1: to me, equity represents that hope that all members of
Speaker 1: our family are are healthy and how do we achieve that? Yes,
Speaker 1: and I can add to UM the concept of health
Speaker 1: disparities and and even share a story UM as an example.
Speaker 1: So there are health differences and their health disparities, and
Speaker 1: when we the health difference for example, a health difference
Speaker 1: for example is UM the elderly population having more you know, diseases,
Speaker 1: or morbidity than the younger population. Right, So that's that's
Speaker 1: a health difference. And when we talk about health disparities,
Speaker 1: we are referring to that particular type of health difference
Speaker 1: that is linked with a social or economic or environmental disadvantage.
Speaker 1: So UM, in terms of address and health disparities, we
Speaker 1: try to understand the root causes of why they exist
Speaker 1: because they are complex. UM. Disease and illness are complex,
Speaker 1: not just from one factor or due to one single factor,
Speaker 1: but due to multiple structural policy decisions that we make
Speaker 1: as a society. UM. For example, having access to clean,
Speaker 1: safe and healthy environment, having access to healthy food UM,
Speaker 1: and overall UM not being breadened by everyday stresses. UM.
Speaker 1: There's there's a lot of stress from being for low
Speaker 1: income or unemployed UM. And so the stresses that are
Speaker 1: experienced disproportionately as he was mentioning by people with social
Speaker 1: disadvantage or by those who have experienced racism or discrimination
Speaker 1: UM are all as impact health and and are seen
Speaker 1: as health disparities. And so solutions for health disparities are
Speaker 1: not always just medical or clinical UM. And I and
Speaker 1: in terms of a story that I wanted to share,
Speaker 1: UM sort of a close and personalities around racial disparities
Speaker 1: in maternal UM and infant health or pre timbers or
Speaker 1: infant mortality. I think, UM, you know, there's a lot
Speaker 1: of literature and scientific evidence UM around the huge, huge
Speaker 1: disparity GAS between African American UM blacks and white um
Speaker 1: in in in maternal mortality, in infan mortality UM as
Speaker 1: well as pre timbers UM or premature new natal birds.
Speaker 1: There's ample evidence from studies that show that cettain maternal
Speaker 1: risk factors UM that explained these disparities are mostly from
Speaker 1: racism or racial disparities, and the experience of systemic racial bias,
Speaker 1: not not just raise itself, can compromise health UM in
Speaker 1: In Ghana, infant mortality was was high, I mean, and
Speaker 1: it was seen mostly with women from loyal socio economic
Speaker 1: status or regions with very very poor health care infrastructure.
Speaker 1: But however, in the US, in the United States UM
Speaker 1: in fun mortality or blacks, US blacks across all socio
Speaker 1: economic status have poor maternal health outcomes and infant mortality
Speaker 1: outcomes compared to their UM white counterparts, even in the
Speaker 1: same socio economic status UM. And in fact, there's a
Speaker 1: study that showed that Black woman with a higher education
Speaker 1: like college level or graduate level degree have similar rates
Speaker 1: compared to similar rates to whites who only have a
Speaker 1: high school education in terms of UM in fun mortality.
Speaker 1: So a lot of African American families, for example, I mean,
Speaker 1: so this is all due to UM, some underlying systemic
Speaker 1: UM or determinants or social determinants of health. UM. And
Speaker 1: of course there's ongoing research to really tease out UM
Speaker 1: why that is the case. And I myself, you know,
Speaker 1: surprisingly experienced the high risk pregnancy. UM. I had a
Speaker 1: pretember UM and I thought I was doing everything right.
Speaker 1: I mean, for myself, I was eating well. I thought
Speaker 1: being educated put me at least risk for any adverse outcomes. UM.
Speaker 1: Deadly in Ghana, it would have so UM, you know,
Speaker 1: being in the u United States environment, being in this
Speaker 1: probably you know, I'm not saying, I'm not sure exactly
Speaker 1: what calls it, but you know, I, as an example,
Speaker 1: was quite surprised. Um. Of course everything has turned out fine.
Speaker 1: My daughter is will turn eighteen at the end of
Speaker 1: this month, and UM, she's off to college. So it's
Speaker 1: think think everything works out, work down well. So that's
Speaker 1: sort of my story that I wanted to share UM
Speaker 1: that yes, you know, this is an example of the disparities.
Speaker 1: And I believe it's safe to ay that the current
Speaker 1: COVID nineteen crisis has really highlighted disparities in a lot
Speaker 1: of ways. That we've seen this play out tragically with
Speaker 1: the response to to COVID nineteen within certain communities. How
Speaker 1: has COVID nineteen impacted or affected this issue? Oh goodness, UM,
Speaker 1: COVID has definitely shaped our world. UM. It has exposed
Speaker 1: huge inequalities and health UM in healthcare UM, the burden
Speaker 1: of underlying disease and access outcomes UM from from COVID nineteen.
Speaker 1: What we see and then hearing actually from the front
Speaker 1: lines are UM glaring inequalities not only in the US,
Speaker 1: but also globally. UM. In the United States, we're actually
Speaker 1: seen the spread is from COVID across race as well race, ethnicity,
Speaker 1: and geography, right, so mostly UM along socio economic lines. UM.
Speaker 1: The disparities that we're seeing are in you know, testing
Speaker 1: rates and infection, severe disease, illness, UM, hospitalization and even
Speaker 1: I see you UM outcomes And so basically what we're
Speaker 1: seeing is something really structural and systemic. In addition to
Speaker 1: what we know are higher COOL mobilities in low sitio
Speaker 1: economic status UM minorities as well as with with racio
Speaker 1: ethnic minorities or people from communities of color. UM. We've
Speaker 1: come to find out that it's also UM higher among
Speaker 1: language minorities. So the COVID positive cases or infection UM
Speaker 1: is not also only occurring along racial ethnic clients, but
Speaker 1: UM also according to the we see that along the
Speaker 1: impact of we've seen the impact of racial segregation, I
Speaker 1: would say, UM, working class UM, the lack of home
Speaker 1: ownership or wealth, and how people living in these communities
Speaker 1: really are impacted by the labor market right UM. These
Speaker 1: are we've seen individuals who really have to go to work,
Speaker 1: you know that to pay their bills, leading to higher
Speaker 1: exposure dr read What are some of the most challenging
Speaker 1: racial and ethnic disparities in public health and health care
Speaker 1: as you see it? One quick truth to recognize is
Speaker 1: that health is so much more than health care. That
Speaker 1: doesn't mean health care isn't essentially it is, but if
Speaker 1: you think about the determinants that play a role in
Speaker 1: health outcomes, it's almost you could think one, two, three, four,
Speaker 1: which adds up to UM. The the broader recognition. When
Speaker 1: you talk about disparities and inequities, you have to recognize
Speaker 1: the ten percent which is clinical genomics and and and
Speaker 1: some of that's connected to this this common history UM.
Speaker 1: You know, family history of chronic diseases makes you a
Speaker 1: higher risk of having a chronic disease, so UM. And
Speaker 1: then the thirty social, environmental, and behavioral and so so
Speaker 1: many of our communities are challenged where the statement that
Speaker 1: your zip code is more important than your genetic code
Speaker 1: is really true. Place matters, UM. You can in the
Speaker 1: same we use this UM reference in in d C.
Speaker 1: When I worked serving and underserved communities in DC. You know,
Speaker 1: you could go on the metro and you can go
Speaker 1: from one stop to another stop and literally span twenty
Speaker 1: to thirty years of life expectancy. So I want to
Speaker 1: highlight that. So when you look across almost every health condition,
Speaker 1: there are disparities that exists, and there's opportunities for equity.
Speaker 1: And it requires requires us to understand the determinants. It
Speaker 1: requires us to bring in the right data and then
Speaker 1: to influence the decision makers. So I'm on this three
Speaker 1: D commission, we call it Determinants Data Decisions that's sponsored
Speaker 1: by the Rockefeller Foundation and UM and the School Public
Speaker 1: Health at BEU. And this is very important to think
Speaker 1: about because we've we've got an opportunity now with COVID
Speaker 1: and all the data and the determinants science we know
Speaker 1: to influence decisions in the disparities that exist in public
Speaker 1: health and healthcare. UM. COVID is making us more aware
Speaker 1: of mental illness, their disparities there UM in depression and
Speaker 1: anxiety disorders and psychotic disorders and addictions that exists that
Speaker 1: need to be addressed and flatten those curves have to
Speaker 1: be flattened as well, there are chronic disease curves that
Speaker 1: need to be flattened. UM. That's worsening, especially for communities
Speaker 1: of color and poverty. So you know, all the chronic
Speaker 1: diseases of already referenced from diabetes, are heart disease to
Speaker 1: asthma to SELPD, to depression, to arthritis to cancer. And
Speaker 1: then the other curve that we have to really address
Speaker 1: and and be really you know, open about, is the
Speaker 1: curve of inequities and the role of structural racism and
Speaker 1: discrimination in our in our systems, and how can we
Speaker 1: address that UM and really invest in diversity and inclusion
Speaker 1: and equity so UM. I mean, there's so much opportunity
Speaker 1: here for us to take this moment with COVID nineteen
Speaker 1: to be upfront about what we have, what we need
Speaker 1: to do, and what we want to build in terms
Speaker 1: of the health system of the future. It sounds like
Speaker 1: there's a great deal of work to be done. I'm
Speaker 1: very curious to learn more about what it is that
Speaker 1: IBM and more specifically what IBM what's in health are
Speaker 1: doing in an effort to try and address these challenges.
Speaker 1: I mean, clearly, this is something bigger than what is
Speaker 1: going to take you know, a tech solution. Dr you
Speaker 1: mentioned that earlier, it's going to require a lot of
Speaker 1: different work. But what is IBMS peace in this What
Speaker 1: are what are you guys doing in your efforts to
Speaker 1: kind of address the issue of health disparity. So we
Speaker 1: see r ole by leveraging technology, but ultimately by by
Speaker 1: looking at trust. I think so much of health and
Speaker 1: healthcare is still foundationally about relationships and trust, and so
Speaker 1: as you think about a journey with IBM, it is
Speaker 1: working with life science companies, hospitals, health systems, governments, um
Speaker 1: and employers and businesses and health plans in a partnership
Speaker 1: with what I would call shared expertise. You know, some
Speaker 1: of the brightest minds and the smartest minds who are
Speaker 1: very global and very diverse across the globe in data
Speaker 1: science and AI and health and healthcare, like like we've
Speaker 1: got with Dr Danko Mullen and and others on our
Speaker 1: our team to work with those other partners and clients
Speaker 1: and to evolve that shared expertise into conversations about data.
Speaker 1: How do we connect these unique data sets, How do
Speaker 1: we protect these data sets because so much about data
Speaker 1: is about trust UM, And then how do we bring
Speaker 1: them together and apply analytics and artificial intelligence and advanced
Speaker 1: analytics to bring insights that better predict, that better personalized,
Speaker 1: and that better prevents bad outcomes and promote good outcomes.
Speaker 1: And so, you know, we're very proud of the work
Speaker 1: we've done with so many different clients to deliver that
Speaker 1: value and that shared expertise UM and those insights from
Speaker 1: the data, analytics and AI. Dr don Komlin, I have
Speaker 1: a question for you about data and analytics. I mean,
Speaker 1: we we know that data is important, but obviously data
Speaker 1: doesn't matter so much unless you're able to do something
Speaker 1: actionable with it. So, how can organizations actually apply data
Speaker 1: and analytics to make better decisions or to create better
Speaker 1: outcomes for themselves? What are some actual processes that you
Speaker 1: look at. Data is actually a very powerful tool UM.
Speaker 1: I've heard someone saying how data is actually a lifeline. UM.
Speaker 1: It's it's very important. And so organizations can definitely you know,
Speaker 1: incorporated health equity UM lens when applying data and analytics,
Speaker 1: especially for decision making UM, in order to really see
Speaker 1: improved outcomes or or better outcomes UM. And they of
Speaker 1: course they also need to ensure that while using the
Speaker 1: data that we are addressing any transparency UM bias as
Speaker 1: well as UM ethical issues that are usually at the
Speaker 1: core of UM data use. UH. You know, in terms
Speaker 1: of our even the current strategy to address COVID response
Speaker 1: M recovery and even preparedness for for a potential wave
Speaker 1: or increase in cases, we really need sort of a
Speaker 1: considered coordinated effort using accurate data or complete data UM
Speaker 1: that that is informed by UM health equity and integrated
Speaker 1: into all of our all of our policies, all of
Speaker 1: our interventions UM in scientific evidence. So I would basically
Speaker 1: UM say that the use of data for and technology
Speaker 1: for we're feel good. UM. It's what organizations UM need
Speaker 1: and so that we can make better informed decisions and
Speaker 1: produce better outcomes as well as at risk of health
Speaker 1: disparity scale. We've talked a lot about what IBM is doing,
Speaker 1: and I know there are a lot of people out there,
Speaker 1: whether they are currently having issues accessing health services, maybe
Speaker 1: they've been affected by disparity. Do you have any advice
Speaker 1: for people who want to work to eliminate health disparities?
Speaker 1: What can the average person do that can be helpful.
Speaker 1: It starts with your people, UM, as I was saying,
Speaker 1: and the diversity that you need to respect amongst your people. UM.
Speaker 1: It also then goes to what I would call the
Speaker 1: data and the nature in which you collect data, how
Speaker 1: you build trust, and the diversity of your data sets
Speaker 1: and the transparency you have about your data, but also
Speaker 1: the protections you have, the privacy protections because as I
Speaker 1: said earlier, you can't you can't you can't trust data
Speaker 1: or share data. You don't share data with people you
Speaker 1: don't trust. So that's a very key piece I think
Speaker 1: in this this clash between the culture of tech and
Speaker 1: healthcare and public health. You need companies that you can
Speaker 1: trust who will protect and secure that data, and that
Speaker 1: our values based. It then is about analytics, and we
Speaker 1: were very proud to be doing analytics that support what
Speaker 1: I would call this concept of equity dashboards, where people
Speaker 1: can see the disparities that exist in the populations they serve,
Speaker 1: whether you're a hospital, whether you're an employer, whether you're
Speaker 1: a health plan, whether you're a government UM. And then
Speaker 1: the last piece is AI, and I think ethical, transparent,
Speaker 1: and equitable AI is going to be so essential. Many
Speaker 1: companies want to create what I would call a black
Speaker 1: box for AI, and you know, you know, we believe
Speaker 1: that you need transparency. UM. You need to know who
Speaker 1: trains these AI systems because in many ways, the biases
Speaker 1: that they may have might be continued or extrapolated if
Speaker 1: you're not transparent. And people need to know how they're trained,
Speaker 1: they need to know the data sets they're trained on,
Speaker 1: and they need to recognize the limitations of AI. And
Speaker 1: we've always suggested that the value prop is not humans
Speaker 1: or AI, it's humans plus AI to make better decisions.
Speaker 1: And a part of making those better decisions is to
Speaker 1: reduce the role of bias UH in those decisions by
Speaker 1: by taking advantage the best of technology and the best
Speaker 1: of human expertise together. Do you have advice for people
Speaker 1: who want to work to eliminate health disparities? What can
Speaker 1: the average person do that can be helpful. What I
Speaker 1: love about IBM as a company and in our role
Speaker 1: we have in society is we can catalyze these conversations
Speaker 1: as we're doing today. And so there's so much anyone
Speaker 1: can do to address health disparities and health inequities. Number One,
Speaker 1: you you educate yourself, You make yourself aware UM as
Speaker 1: it relates to the challenges as relates to you know,
Speaker 1: the members of a community that are are facing these
Speaker 1: disparities and and and and to me, I'm a big
Speaker 1: believer in we uh, you know, and how we think
Speaker 1: about our society and and and UM data brings people
Speaker 1: together in many ways. UM and and analytics and and
Speaker 1: companies like IBM can play an important role in that.
Speaker 1: So think about, you know, educating yourself about these disparities
Speaker 1: that exist, learn about them, and think about how you
Speaker 1: can bring attention to that UM and and and more
Speaker 1: knowledge and awareness. UH. A lot of this starts with
Speaker 1: with what I call data and trust. It's it's it's
Speaker 1: this idea. If you think about part of this journey
Speaker 1: starts with how the data is collected. When you're in
Speaker 1: UM a hospital, or you're you're an employer, and where
Speaker 1: you're in the census, and you you share data about
Speaker 1: yourself and and you're transparent about maybe you're limited English proficiency,
Speaker 1: or you're transparent about your race, ethnicity, or your country
Speaker 1: of origin. You're transparent about you know, topics like sexual orientation.
Speaker 1: These these factors play a very important role in the
Speaker 1: future of reducing those disparities. If the data isn't collected
Speaker 1: accurately and then the disparities aren't identified, and then you
Speaker 1: can't close those gaps. So there's a big conversation about
Speaker 1: trust and how you how data is shared and how
Speaker 1: it's used. And you should be comfortable asking those questions
Speaker 1: like what is this data for and how's it being used,
Speaker 1: but but challenging that you know, hopefully that you're willing
Speaker 1: to share that data. UM. In my view, whenever we
Speaker 1: analyze anything, I mean, you should look at disparities. You
Speaker 1: should look at factors of race and socio economic status.
Speaker 1: When you're running reports, when you're doing whatever you do,
Speaker 1: you know, ask that question. You know, we know, for example,
Speaker 1: blacks make fifty nine cents you know, compared to whites
Speaker 1: in terms of income. We know that in terms of wealth,
Speaker 1: they make ten cents for every dollar of wealth that
Speaker 1: a person who's white makes. You know, we I know
Speaker 1: my daughters, you know, when they grow up there, you
Speaker 1: know right now they're competing in an environment where they'll
Speaker 1: make seventy cents on the dollar that a man will make.
Speaker 1: So if you don't include equity in your analytics, and
Speaker 1: you don't include these factors, then in some ways you
Speaker 1: you you're oblivious to the problem or the gaps that
Speaker 1: you want to reduce. So we should ask and demand
Speaker 1: to have those measures, you know, analyze and tracked, and
Speaker 1: then ask questions about the root cause and how do
Speaker 1: we reduce those gaps. Um I also believe so much
Speaker 1: in the diversity of people. Like think about your own team,
Speaker 1: think about the people you interact with, Think about how
Speaker 1: you recruit your people, how you retain people. You know,
Speaker 1: how are you thinking about diversity? Um in in in
Speaker 1: your in your processes of of who you listen to
Speaker 1: and who you recruit, who you retain. You know, I'm
Speaker 1: a big believer in diversity and we're very proud at
Speaker 1: IBM for was it twenty seven years being leader in
Speaker 1: patents in the US? I mean twenty seven years in
Speaker 1: a row being number one in patents and I am
Speaker 1: a strong believer. A big source of that ability to
Speaker 1: be leader in patents and that type of creativity is diversity.
Speaker 1: And so many studies have shown that diversity breeds innovation.
Speaker 1: And there's an r O I attached to being diverse.
Speaker 1: So I would ask each of you to challenge yourself
Speaker 1: to to think about the community and the people you're
Speaker 1: with and how do you embrace diversity and whatever you do.
Speaker 1: Dr Dougua Mullen, would you like to chime in about
Speaker 1: this about what the average person can do to address disparity.
Speaker 1: Health disparities are costly. I'm not sure if everyone realizes
Speaker 1: UM and the and it's caused by a lot of
Speaker 1: you know, determinants of healthy UM. It's also caused by
Speaker 1: the fact that data UM that we are promoting or
Speaker 1: working on is sometimes not complete or not accurate UM.
Speaker 1: So in terms of you know, companies or individuals, I
Speaker 1: think we should awareness is it's key and helping to
Speaker 1: drive and address inequalities by UM, you know, promoting and
Speaker 1: having a health equity lens and promoting UM data and
Speaker 1: and analytics or artificial intelligence for for social good or
Speaker 1: ensuring that we're all building technologies or working on solutions
Speaker 1: that voll ensure the benefits for everyone and that unfairly
Speaker 1: disadvantage other populations would help UM. And and we've seen
Speaker 1: that this pandemic has actually resulted in you know, a
Speaker 1: recession and a loss of economic livelihoods UM for a
Speaker 1: lot of people. And so what we really need to
Speaker 1: also look at is sporting UM programs, building up these
Speaker 1: programs and interventional efforts that would really improve the economic
Speaker 1: resiliency UM or or social capital, especially for despreading populations UM,
Speaker 1: marginalized or under resource communities that have been really hard
Speaker 1: hips UM. You know, it's hard to imagine how we
Speaker 1: we could recover. I mean, there's been a number of
Speaker 1: communities that have been left behind, for example, by the
Speaker 1: digital UM and AI UM revolution, and so really helping
Speaker 1: I mean with resources or UM technologies can help. I mean,
Speaker 1: for example, schools education is a really strong determinant of
Speaker 1: health and school education and cater UM these technologies for
Speaker 1: black and brown communities that are in you know, socially
Speaker 1: disadvantage communities may not always have to uh technology or computers. UM.
Speaker 1: And so assisting with that, and this displays a larger
Speaker 1: role in addressing, UM, a larger role in sort of
Speaker 1: understanding these systemic or structural inequities. UM. Until helping with
Speaker 1: that is really key. UM. I think as individuals. I mean,
Speaker 1: I'm really pleased that we are having this conversation UM
Speaker 1: around UM equity. Uh. You know, health disporities have asisted
Speaker 1: for really long in the United States, UM, I mean
Speaker 1: around the world as well. But I am I'm sort
Speaker 1: of pleased with a with a conversation that's ongoing. So
Speaker 1: if health disporities have existed for long, and we know
Speaker 1: some of the root causes and promising interventions, we need
Speaker 1: to ask yourself, you know, what are we contributing to
Speaker 1: that legacy or the science right now? UM. You know
Speaker 1: in the past, we would often say, oh, nothing can
Speaker 1: be done about it, UM, you know, and what could
Speaker 1: we do? And it's and so I think we're at
Speaker 1: the right time in our history where a lot of
Speaker 1: people are now caring more about inequalities, about racial justice. UM,
Speaker 1: We're beginning to really address these difficult things and and
Speaker 1: just talking about it, you know, UM, asking questions and
Speaker 1: having that dialogue is is a great start. I mean
Speaker 1: I'm inspired by uh, you know, the current movement Black
Speaker 1: Lives Matter UM and and I think that that helps basically,
Speaker 1: I mean, where people can start talking about the people
Speaker 1: can look at you know, how can you we can
Speaker 1: leverage our skills, UM and expertise and for the benefit
Speaker 1: of everyone. I mean, I think playing all of us
Speaker 1: playing our part in leveraging our skills and looking um
Speaker 1: beyond competition, collaborating in our own space for the benefit
Speaker 1: of everyone. Help. I could not agree more. I mean,
Speaker 1: I feel that we are entering into a time where
Speaker 1: more and more people are either realizing the realities that
Speaker 1: have been in place forever but or or effectively forever
Speaker 1: for all of our lifetimes. But maybe they weren't aware
Speaker 1: of them because they'd never directly experienced them, or they're
Speaker 1: they're acknowledging them. Perhaps they were at least subconsciously aware
Speaker 1: but had not truly reflected upon it. We're starting to
Speaker 1: see that change. I am also, like you, inspired by that,
Speaker 1: and I am determined to do whatever I can in
Speaker 1: my role as a voice of the media to continue
Speaker 1: that conversation and to carry it forward, to make sure
Speaker 1: people are still talking about this and thinking about this
Speaker 1: and thinking about the aspects of the challenges that they
Speaker 1: can rise to meet, and and why other ways we
Speaker 1: can look to help others and to really, through helping others,
Speaker 1: help everyone. I was wondering, Dr don Quamalen, if there
Speaker 1: were any stories you could share about the work that
Speaker 1: your team has done during the pandemic that you you're
Speaker 1: particularly proud of. IBM has developed there's a website aimed
Speaker 1: specifically for all COVID nineteen researchers and so it allows
Speaker 1: users to upload information from electronic medical records or from
Speaker 1: draft trials, UM or other sources and use these algorithms
Speaker 1: to uncover new findings. Um AND and the side to
Speaker 1: set up so that users can also keep their data
Speaker 1: private um AND AND or share it as long as
Speaker 1: UM they have privacy laws in place. But but I
Speaker 1: hope is that the site that has been developed allows
Speaker 1: researchers a around the world too collaborate and gain a
Speaker 1: better insight into the understanding of the virus and how
Speaker 1: it's um how it reacts in different populations UM and
Speaker 1: you know, apart from the disparities that we're seeing UM
Speaker 1: and and really have precise UM treatment. I mean, so
Speaker 1: this that there is that there's also UM. The clinical
Speaker 1: development journey is really extensive UM. But we are looking
Speaker 1: at ways in which we can accelerate UM research and
Speaker 1: using the cloud based technology at IBM and and and
Speaker 1: streamlining data collection UM or its integration or standardization, especially
Speaker 1: through the clinical trial process and vaccine development. We want
Speaker 1: to make sure that it's inclusive and everyone UM and
Speaker 1: it's safe for all populations UM. So those are some
Speaker 1: of the ongoing work UM AND and some of it
Speaker 1: that we hope to publish soon. But I would say,
Speaker 1: you know, this collaboration, this website UM specifically for researchers
Speaker 1: and especially to conduct equity work and look at electronic
Speaker 1: health records UM and data has been UM really helpful.
Speaker 1: So I find that extremely inspiring and I love learning
Speaker 1: more about this because when we hear about on the news,
Speaker 1: we typically hear about things in the context of doctors
Speaker 1: are working on this, scientists are studying it, but it
Speaker 1: tends to be at that level and we don't get
Speaker 1: a deeper appreciation for what that actually means, what is
Speaker 1: going into that process. What does it mean to analyze
Speaker 1: the effects of COVID nineteen, or potential treatments for COVID nineteen,
Speaker 1: or looking at even the spread of COVID nineteen and
Speaker 1: how it spreads. So learning a little bit more about
Speaker 1: that gives me a much deeper appreciation for the work
Speaker 1: that that you and others that IBM are doing in
Speaker 1: an effort to really address not just the COVID nineteen crisis,
Speaker 1: but the overall challenge of providing health services, making sure
Speaker 1: that you help others to provide health services to address
Speaker 1: the issues of health disparity. One thing that became clear
Speaker 1: in my conversation with doctors Re and don Qua Mullen
Speaker 1: is that we can't really begin to address a problem
Speaker 1: like disparity in health care access without data. To form solutions,
Speaker 1: we first have to really understand the problem. Without that step,
Speaker 1: any solution we attempt is bound to be insufficient to
Speaker 1: me in our needs. It is therefore critical to have
Speaker 1: sophisticated systems in place to collect information and to analyze it.
Speaker 1: That's where the technology really comes in. We can lean
Speaker 1: on tech to sift through information so that we can
Speaker 1: glean insight from those findings. Cognitive systems can help guide
Speaker 1: us to potential approaches that are more likely to have
Speaker 1: a real impact and steer us away from actions that
Speaker 1: might intuitively seem helpful but in reality have very little effect.
Speaker 1: And as I learned, time is a critical component when
Speaker 1: you're talking about health. To learn more about how IBM
Speaker 1: is responding to COVID nineteen, including information that business leaders
Speaker 1: can use to form their response plans and guide decision making,
Speaker 1: visit IBM dot com slash impact slash COVID Dash nineteen.
Speaker 1: I want to thank doctors Re and Donqua Mullin once
Speaker 1: again for coming on a show and sharing their time
Speaker 1: with me. I found it incredibly informative, and I hope
Speaker 1: you did too. Make certain you check out all of
Speaker 1: our past episodes of smart Talks. You can find those
Speaker 1: past episodes in the Tech Stuff feed and the Stuff
Speaker 1: to Blow your Mind feed. We've had a chance to
Speaker 1: talk to lots of incredible people who are using technology
Speaker 1: in really interesting ways, so make sure you go back
Speaker 1: and listen to those episodes as well. Thank you so much.
Speaker 1: Text Stuff is an I Heart Radio production. For more
Speaker 1: podcasts from My Heart Radio, visit the I heart Radio app,
Speaker 1: Apple podcasts, or wherever you listen to your favorite shows.