What does a $100 million public health data revolution look like?

Summary

The speaker discusses the importance of real-time health data in managing complex systems, exemplified by Rio de Janeiro's smart city initiative. They introduce a global health data tool, created by 500 experts over five years, which provides insights into disease patterns by age, sex, and locality for 187 countries. The tool reveals a shift from child mortality to non-communicable diseases in aging populations, with significant variations across countries. It also identifies leading risk factors like diet and smoking in the U.S., emphasizing the tool's potential to transform population health by learning from global patterns.

Takeaways

• 🚗 The speaker uses the metaphor of getting to a destination, emphasizing the importance of clear information, roadmaps, and anticipating obstacles for success.
• 🏙️ The evolution of smart cities like Rio de Janeiro, which gather real-time data to manage complex systems, is highlighted as a model for efficient responses in large cities.
• 🌍 Over 500 experts from 50 countries have compiled global health data covering more than 1,000 clinical outcomes for 187 countries over two decades, providing invaluable insights.
• 📊 From 1990 to 2010, the world saw significant progress in reducing child mortality and shifting the burden of disease to older populations, especially heart disease and cancer.
• 👶 While deaths have decreased, premature mortality in children remains a large issue, with neonatal causes, diarrhea, pneumonia, and malaria still prominent in many areas.
• 🧠 Mental and musculoskeletal disorders, along with hearing and vision loss, are significant contributors to global health problems, even though they do not cause direct mortality.
• 🌍 The burden of disease varies greatly by region, with West Africa facing primarily communicable diseases and China having transitioned to non-communicable diseases like heart disease and cancer.
• 📉 China has made remarkable progress in reducing communicable diseases by 80% since 1990, although it faces rising challenges from ischemic heart disease, offering lessons for other nations.
• 🍽️ Risk factors like diet, smoking, obesity, and high blood pressure dominate health loss in the U.S., highlighting lifestyle changes as critical to improving overall health.
• 🔬 The project combines data, science, and visualization tools to give everyone—not just specialists—access to a deep understanding of global health patterns, helping to improve public health at the community level.

Q & A

What is the key message of the speaker's introduction regarding reaching a destination?

The speaker emphasizes the importance of knowing how to reach a destination, including factors such as means of transport, clarity of the destination, potential obstacles, and tools to navigate the route. This analogy introduces the complexity of managing systems, particularly in health and first-response contexts.

What is the role of smart cities in first-response management, as explained in the transcript?

Smart cities, like Rio de Janeiro, gather real-time data to manage complex systems such as first-response services. This allows the city to handle emerging problems more effectively and ensure timely responses to emergencies.

What significant health data collection project does the speaker mention?

The speaker mentions a project involving 500 people from 50 countries who, over five years, compiled health data on more than 1,000 clinical outcomes for 187 countries. This dataset spans two decades and provides insights into global health patterns, including progress made in various health conditions.

What are the key insights from global child mortality trends between 1990 and 2010?

Between 1990 and 2010, global child mortality decreased significantly from 12 million to 7 million deaths. There was also a shift in the age distribution of deaths, with more people living to age 80 or older, showing global health improvements over time.

Why does the speaker emphasize premature mortality when discussing global health?

The speaker highlights premature mortality to emphasize that not all deaths are equal in terms of life years lost. For example, a death at age five results in more years of lost potential life compared to a death at age 95. This concept helps better understand the broader impact of early deaths.

What are some of the major health issues affecting young adults globally, according to the transcript?

Major health issues affecting young adults include HIV/AIDS, tuberculosis, road accidents, homicide, and suicide. These conditions contribute significantly to premature mortality in this age group.

What does the speaker mean by 'what ails you globally isn't actually what kills you'?

The speaker is referring to the distinction between conditions that cause death and those that cause non-fatal health problems. While conditions like heart disease and cancer may be leading causes of death, mental disorders, musculoskeletal disorders, and sensory impairments (e.g., vision and hearing loss) are major contributors to global health problems that don't necessarily result in death.

How has the burden of disease in China shifted between 1990 and 2010?

In 1990, 25% of the disease burden in China was from communicable diseases. By 2010, this figure dropped significantly, and non-communicable diseases such as heart disease, cancer, and mental disorders now account for 80% of the disease burden. This reflects China's success in reducing infectious diseases but highlights new challenges with non-communicable diseases.

What are some of the leading risk factors for health loss in the United States?

In the United States, the leading risk factors for health loss are poor diet, smoking, obesity, high blood pressure, high blood sugar, physical inactivity, and alcohol use. These factors contribute significantly to the country's overall health burden.

What are the three main takeaways the speaker wants the audience to remember about global health data and tools?

The speaker's three main takeaways are: (1) The tools allow us to ask new and insightful questions about global health; (2) We can learn from both successes and failures across the world to improve health outcomes; and (3) These tools empower everyone, not just specialists, to engage in improving health globally.

Outlines

00:00

🚑 The Role of Data in First Response and Global Health

The speaker opens by asking the audience to consider the importance of information in reaching a destination, particularly in emergency responses within large cities. He introduces the concept of smart cities, such as Rio de Janeiro, where real-time data is used to manage emergencies. The discussion then shifts to a global scale, focusing on health systems and how data collection over the last two decades—covering thousands of clinical outcomes for 187 countries—has provided insights into disease patterns. The speaker highlights the availability of this data online and emphasizes the progress in reducing child mortality between 1990 and 2010.

05:03

📊 Premature Mortality and Health Complexity

The speaker dives deeper into the issue of premature mortality, explaining how years of life lost is a better measure than just counting deaths. He illustrates the burden of diseases like diarrhea, pneumonia, and malaria, particularly in children, but also brings attention to young adult mortality from causes like HIV and road accidents. He emphasizes that health is more than avoiding death, mentioning that diseases such as mental disorders, musculoskeletal issues, and vision loss contribute significantly to the global health burden. The discussion moves toward country-specific health challenges, showing how non-communicable diseases have become more prevalent in countries like China.

10:06

📉 Tracking Changes in Disease Burden Over Time

The speaker introduces a ranked list comparing health loss in China from 1990 to 2010, showing the dramatic reduction in communicable diseases like tuberculosis and pneumonia, alongside a rise in ischemic heart disease. This comparison underscores the significant epidemiological shift in China over two decades. The speaker stresses that these trends offer lessons for both China and other developing nations on managing health transitions and emphasizes the value of understanding specific diseases for targeted health interventions.

🛡️ The Impact of Risk Factors on Health

The speaker shifts to the topic of risk factors, presenting the U.S. as a case study. He lists diet, smoking, obesity, high blood pressure, and physical inactivity as the leading contributors to health loss. The speaker reiterates the importance of using data to explore risk factors and health outcomes in different populations, encouraging the audience to explore these tools themselves. He introduces the idea that these risk factors can be modified both individually and at the community level to improve public health outcomes.

🌍 The Power of Data in Global Health Improvement

The speaker recounts a personal story about his parents' work in healthcare, which inspired his career in understanding global health patterns. He reflects on the challenges of synthesizing health data from various sources and regions, emphasizing the need for robust science to account for biases and inconsistencies in data collection. He celebrates the emergence of data scientists and advanced visualization tools that now make this complex data accessible to everyone, enabling better health interventions worldwide.

🏥 Lessons from Life Expectancy Disparities

The speaker concludes with a powerful illustration of health disparities within the U.S., showing that life expectancy can vary by up to 12 years depending on the county. He uses this disparity to emphasize the potential for health improvement by studying successful health interventions in different communities and regions. He advocates for a collective effort to use data to ask new questions, learn from global successes and failures, and empower everyone to contribute to better health outcomes, not just specialists.

Keywords

💡Smart Cities

Smart cities are urban areas that use technology and real-time data to manage resources and services more effectively. In the video, Rio de Janeiro is highlighted as a smart city where real-time data helps manage first responders and urban systems, ensuring quicker responses to problems. This concept is used to draw parallels with global health systems, emphasizing the importance of data for effective management.

💡Global Health Data

Global health data refers to the collection of health-related information from different countries, allowing for the analysis of diseases, clinical outcomes, and health trends. The speaker mentions a massive effort to compile health data from 50 countries over 20 years, providing insights into disease patterns and helping to inform health policies worldwide.

💡Premature Mortality

Premature mortality refers to deaths that occur before the expected age, often due to preventable causes. The video discusses the global agenda to tackle premature deaths, especially in children, and the progress made in reducing child mortality from diseases like pneumonia and diarrhea between 1990 and 2010. Premature mortality is used to emphasize the importance of early intervention and healthcare improvement.

💡Non-communicable Diseases (NCDs)

Non-communicable diseases are medical conditions not caused by infectious agents, such as heart disease, cancer, and mental health disorders. The video highlights the growing burden of NCDs in countries like China and the US, where heart disease and cancer are major causes of health loss. It contrasts these with communicable diseases, which are declining in some regions.

💡Communicable Diseases

Communicable diseases are illnesses caused by infectious agents like bacteria, viruses, or parasites. In the video, diseases like diarrhea, pneumonia, and malaria are mentioned as leading causes of child mortality, particularly in developing regions like West Africa. The speaker contrasts the prevalence of communicable diseases in these regions with the rise of non-communicable diseases in other parts of the world.

💡Burden of Disease

The burden of disease refers to the impact of health problems on a population, often measured in years of life lost or health deteriorated due to illness. The video discusses the shifting burden of disease globally, from communicable diseases to non-communicable ones, and the differences in disease burdens across countries like China, India, and the US.

💡Risk Factors

Risk factors are behaviors or conditions that increase the likelihood of developing a disease or health condition. In the video, the leading risk factors in the US, such as poor diet, smoking, obesity, and high blood pressure, are highlighted as major contributors to health loss. Understanding risk factors helps in targeting interventions to improve public health.

💡Health Visualization

Health visualization refers to the graphical representation of health data to make complex information easier to understand. The video emphasizes the power of visualization tools to explore global health trends, disease burdens, and health outcomes by region and risk factor. These visualizations enable both specialists and the general public to engage with the data.

💡Epidemiological Shift

An epidemiological shift is a change in the patterns of health and disease in a population over time. The video explains how China experienced such a shift, reducing the burden of communicable diseases like tuberculosis and increasing the prevalence of non-communicable diseases like heart disease between 1990 and 2010. This shift is used to illustrate broader global health trends.

💡Health Disparities

Health disparities refer to the differences in health outcomes between different populations, often due to socioeconomic, geographic, or racial factors. The video highlights disparities in life expectancy within the US, showing how counties in some parts of the country have life expectancies similar to developing nations like Libya. Understanding health disparities is key to addressing inequalities in health access and outcomes.

Highlights

Smart cities like Rio de Janeiro are using real-time data to manage complex systems, first responders, and urban challenges.

A global health database has been compiled by 500 people from 50 countries over five years, covering over a thousand clinical outcomes for 187 countries.

The data provides insights into patterns of disease by age, sex, and locality, highlighting areas making progress and those that are lagging behind.

Child mortality worldwide has decreased from 12 million deaths in 1990 to 7 million in 2010, with a shift in deaths to older populations.

Premature mortality is a key focus, showing significant loss of years of life in children due to preventable causes like diarrhea, pneumonia, and neonatal issues.

In young adults, diseases like HIV, tuberculosis, road traffic accidents, and mental health disorders are major causes of premature death.

Global health is not just about mortality but also the burden of disease, with mental disorders, musculoskeletal issues, and sensory impairments like hearing and vision loss contributing significantly.

Health outcomes vary greatly by country, with countries like China showing a shift from communicable to non-communicable diseases over the past two decades.

China has reduced its communicable disease burden by 80% since 1990, while ischemic heart disease has risen by 50%.

The tool developed allows users to visualize health loss from both diseases and risk factors, highlighting dietary risks, smoking, obesity, and high blood pressure as major contributors in the U.S.

Data collection from various sources, including handwritten records, is crucial to understanding global health patterns, despite biases and inconsistencies in medical reporting.

A new generation of data scientists is using advanced techniques to turn raw health data into actionable insights.

Visualization tools make complex health data accessible, helping users engage with information and ask new questions about global health trends.

The tool highlights disparities within countries, such as U.S. counties where life expectancy for women is equivalent to that in Libya.

By learning from both successful and struggling regions, communities can 'leapfrog' in improving health outcomes globally, benefiting from shared knowledge.

Transcripts

so I want to start by getting you to

think about a question if you want to

get to a destination what's going to

help you to get there now some of you

are going to be thinking about a means

of transport clarity of where you want

to go maybe a road map and you want to

know about obstacles along the way

traffic jams weather road closures road

construction now imagine for a moment

that you're in charge of first

responders in a large crowded city and

those that information is even more

important because it really matters

getting the response the people in need

and so we're seeing the evolution of

smart cities this is Rio de Janeiro

where they've real-time gather

information so that they're able to

manage a complex system manage

first-response manage problems that

emerge in a number of systems in that

city what if we had that information for

even more complex things like the

world's health systems now the good news

which we already heard a little bit

about is that that information is

actually now being put together so 500

people from 50 countries over five years

have put together all the world's data

on an enormous number of conditions more

than a thousand different clinical

outcomes by age by sex for 187 countries

over the last two decades giving us

insights into where the pattern of

disease is by age by sex by locality

who's making progress who's not and as

we heard that information is not just in

a commanding control center like we saw

for Rio de Janeiro but that information

is online you can go get it now and

hopefully you'll go get it after this

presentation so there's a billion

results in this accumulation of the

world's

health data and I'm going to give you a

sort of world quick tour of some of the

insights you can get from these tools so

let's start with something very simple

and that is death death by age so this

is one of our live tools it shows in

this case death for the world in 1990

and there are four age groups on the far

left for children and there are all the

other age groups up to eighty plus and

you can see 21 groups of causes yellow

sticks out that's diarrhea pneumonia a

big killer of children the dark blue is

heart disease the lighter blue is cancer

and from 1990 to 2010 we had a lot of

progress in the world so let's see that

again go back to 1990 go forward to 2010

and what you see is that we've reduced

child mortality in the world from about

12 million deaths to about 7 million

deaths and we've had a big shift to

death over age 80 progress but deaths

don't tell the whole story in fact if

you die at age five you've lost most of

your lifespan if you die at age 95

you've lost much less and so we have to

help get the big picture a construct

called premature mortality and now I'm

showing you the number of years lost in

the world by caused by age and you can

see the agenda of tackling premature

death and children is still really large

the big bars in the far left neonatal

causes diarrhea pneumonia and malaria

still important but you can also see in

young adults the dark yellow

that's HIV and tuberculosis you can see

the dark purple those are road transport

accidents and things like homicide and

suicide show up is that salmon color

there's a big agenda around young adult

mortality as well but health is a lot

more than simply avoiding death that's

why we're so interested in wellness

that's why in this study we look at over

a thousand different outcomes and we put

it all together and count up the number

of years lost due to different diseases

taking into account how severe they are

and what's important here is the

dollars on this diagram are different

than the one I just showed you the ones

that leap out are the light green which

are mental disorders and substance abuse

the light purple which are the

musculoskeletal disorders and the darker

purple are things like vision loss that

we just heard about in hearing loss and

congenital anomalies what ails you

globally isn't actually what kills you

and so when you put those two together

you get a global view of all the

complexity about health premature

mortality and children from infectious

diseases cancer and heart disease road

traffic accidents HIV mental disorders

but of course the world is not one

homogeneous whole and part of the power

of this tool is that you can now explore

country by country what are the big

causes and how they're changing so this

view on the top is a square pie chart

just like a pie chart the size of each

box is proportionate to the problem and

the non communicable diseases heart

disease cancer musculoskeletal disorders

mental disorders are in blue the

communicable causes in red and injuries

are in green and on the map on the

bottom is the fraction of health loss in

each country due to the communicable

causes in West Africa in the country of

leisure eighty percent of the burden of

disease is from those communicable

causes diarrhea pneumonia and malaria

are particularly important in India a

country in real transition about 45% is

now non communicable disease forty five

percent is the communicable diseases and

the rest is injuries in China in 2010 it

looks much more like the US where 80

percent of the burden of disease is now

from heart disease cancer mental

disorders other non communicable causes

but China has lessons to tell the rest

of the developing world because if you

go back to 1990 25 percent of the burden

of disease in China was from

communicable diseases they've been

incredibly effective at tackling these

causes particularly in children over the

last two decades now if we go back to

2010 in China and see that

epidemiological shift

in that country we can also drill down

and show you the specific causes because

of course health policy interventions

clinical action requires specific

disease information and so each of those

boxes can be broken down into the 291

diseases and the thousand plus outcomes

but there's another way to see this

information I'll keep on the theme of

China and this is a ranked list

people love ranked lists you know

they're always in newspapers and so

we've made a ranked list on the left is

the ranked order of whatever outcome you

care about in this case overall health

loss in 1990 and on the right is the

ranked list for 2010 and the causes are

connected Reds or communicable causes

blues or NCDs greens or injuries key

story here is the big drops tuberculosis

diarrhea pneumonia going down 80 percent

in two decades in China and at the same

time ischemic heart disease going up by

almost 50% China has lessons to teach

the developing world China has lessons

to learn about how to manage ischemic

heart disease from places like the US

where we've brought ischemic heart

disease down over time

now disease and injury is not the whole

story because health is a got some

underlying determinants we think of them

as risk factors things that you can

modify in your own life but we can also

think about modifying at the community

level so the way to see that I'm going

to show you the view in this tool for

the u.s. is what are the leading risk

factors and in this case the number one

risk factor in the u.s. more than 14

almost 14 percent of all health loss all

years lost is diet

followed by smoking followed by obesity

and overweight followed by high blood

pressure high blood sugar physical

inactivity and alcohol the big dominant

risks in the u.s. now there's a billion

results and we could spend the rest of

today and tomorrow and the rest of the

week playing with these tools and I hope

you do but what I want to do is tell you

where this come from and what's the sort

of central motivation behind it and so

the story behind this tool starts

actually 40 years ago it starts with my

parents

deciding to drag our family from

suburban Minnesota by to Land Rover's in

the UK drive across the Sahara and start

and run a family as a hospital and so we

all had jobs my father was a physician

and I was the scrawny little kid here

and my job was to set up the hospital

pharmacy and run it and in that

experience the ten-year-old and in

subsequent places working for my parents

in Africa I ended up with two questions

that I'm still working on why are people

so sick in some communities and what

makes them so sick and how can we go

beyond giving care to individuals to

transforming the health of whole

populations now when I finish college

I got to start to address these

questions head-on and there were two

sources back in the late 80s early 90s

one source was the media where you were

simply inundated with a cacophony of the

number one problem is this that or

something else no way to get the big

picture the other source was to go at

the time to public health authorities

and I did I went and added up all the

claims about what people died from and

it turned out that everybody in the

world died three times over and I knew

one thing was true that you can only die

once now what that spawned is almost two

and a half decades of an effort to get

the four things together for us to

really understand patterns of health

around the world one is data data comes

in lots of forms we think about

digitized data these days but there's

lots of data that looks like this

that's handwritten down but the thing

about figuring this out for patterns of

health getting sort of real-time

information on health over time is it's

not like stock market prices where you

just grab the price and deliver it to a

laptop through some clever bit of

technology there's actually an

incredible bit of science behind

figuring out all the biases that are in

the data all the different case

definitions different countries use the

variation across places

in how doctors assigned causes of death

or make diagnoses so there's science

there's data and there's also the

evolution of a new cohort of data

scientists here's some of ours with

seeming superpowers at the Institute in

Seattle but it's the idea that we have a

new generation of people who have the

skills to take raw data about health and

turn it into information and the final

transformation in developing this type

of tool for everybody to use has been

the recognition of the power of

visualization here's a storyboarding

that we did for one of the first

visualizations namely how do you take

such rich information and make it

available to everyone why is this so

important why am I so passionate about

figuring out the answers to my two

questions I think one way to see that is

to look here in the US so on the top is

life expectancy by county this for women

it ranges from the counties in red to

the counties in green by 12 years huge

variation within the US and in fact in

this little tool on our website you can

ask the question what counties have a

life expectancy like which country in

the world so I'm going to highlight

Libya and those are counties in the US

where women's life expectancy is the

same as in Libya today now the reason

this is so important is that if we can

understand what are the diseases and

injuries and the risk factors that

explain patterns of health in each place

and we can learn from different

community communities there's a huge

potential to leapfrog and actually

transform health of different

populations so I want to leave you just

with three thoughts first this tool

allows us to ask questions that we

didn't even know to ask before some of

the Geographic patterns leap out at you

new hypotheses second we can learn from

success and failure all over the world

there's lessons China can teach lessons

China can learn lessons

and third the one that we're most

excited about is the power to engage

everyone in seeking understanding about

how to improve people's health because

this is no longer the purview of the

specialists this is in your hands thank

you very much