0:15

Pushkin. I'm

0:18

Maybe Higgins and this is Solvable Interviews

0:21

with the world's most innovative thinkers

0:23

working to solve the world's biggest

0:25

problems. My name is Nevine

0:27

Rao. I'm the senior vice president

0:30

for Health and Rockefeller Foundation, and

0:33

I believe the crisis of maternal

0:35

mortality is solvable. This

0:37

episode, we're hearing from doctor Nevine

0:40

Rau. You just heard him there. He's from the Rockefeller

0:42

Foundation and he is a renowned

0:45

expert in safe pregnancies

0:47

and healthy deliveries around the

0:49

world. Now, if

0:51

you had to guess how many babies would

0:53

you say are born every day, I'll

0:55

give you a second. Now I

0:58

cheated. I looked it up and UNISF

1:01

estimates that an average of wait

1:03

for it, three hundred and fifty

1:06

three thousand babies are

1:08

born each day around the world. Is

1:11

not incredible. It's more than four births

1:13

every second, and most

1:15

of those they're safe for both the mother

1:18

and the baby. But many of

1:20

those births are not. In fact,

1:23

nearly eight hundred and thirty women

1:25

die every day due to

1:27

complications during pregnancy and

1:30

childbirth. Now, most

1:32

of these deaths can be prevented

1:34

through skilled care at childbirth

1:37

and just having access to emergency

1:40

obstretric care. But in Sub

1:42

Saharan Africa, where maternal mortality

1:44

ratios are the highest, fewer than

1:46

half of women are attended

1:49

to by a trained midwife or a nurse or

1:51

a doctor during childbirth. So

1:54

you can probably guess that maternal deaths

1:56

mirror the gap between the rich and the

1:59

poor. Less than one percent of

2:01

maternal deaths happen in wealthy

2:03

countries. But I wonder if you knew

2:06

that America has the highest maternal

2:08

mortality rate of all industrial

2:11

countries, in fact, by several

2:13

times over. Maternal and

2:15

tile survival are the hallmarks of

2:17

healthy communities, and doctor

2:20

Rown knows that. But he also

2:22

understands that although major advances

2:25

in digital technology and data science

2:27

are definitely improving health intervention

2:30

effectiveness, the global health

2:32

divide persists. All of these

2:34

wonderful innovations, well, they're

2:36

just not reaching the poorest and most

2:38

vulnerable communities. Doctor

2:41

Rao envisions a world where the

2:43

data gap, and therefore the

2:46

health gap, can be bridged, and

2:48

we'll hear more about how he reached

2:50

this thinking and also his daily

2:53

work towards this much better future.

2:56

Let's listen to him now with an apple bound

2:59

What in your background led you to this problem?

3:02

How did you identify this as a

3:04

concrete problem that can be solved? And

3:07

how must have been about twenty five

3:10

part of my training as a medical student in

3:13

rural India, and I remember this

3:15

sixteen year old girl being

3:18

brought in. She had

3:20

twins, and these were the days when we didn't know

3:22

she had twins. There was no echo cardiogram, and apparently

3:25

she delivered one of the twins at home. It was

3:27

a prolonged labor. And now they

3:29

brought her in to the hospital because

3:32

she had a second baby that was

3:34

also obstructed. And I remember

3:36

there and helping with that, and as

3:38

part of that second delivery,

3:41

she started bleeding and

3:43

then literally bled out, and

3:45

I remember trying to stem the blood

3:47

and it's so horrific when

3:50

you see blood gushing out of a woman's Wigiane's

3:52

just and you could see that she was

3:54

dying, and she knew she was dying. But

3:57

I never forget that, but that stayed

3:59

with me. And that was almost forty

4:02

five years ago. And

4:05

when I got to America and I finished

4:07

my training and was a practicing

4:10

physician, I was horrified

4:12

to hear that this problem still exists

4:14

and in fact is getting worse

4:16

in some countries, and that even

4:18

today woman died

4:21

during pregnancy and childbirth. The

4:24

tragedy is that we know how

4:26

to save them. Most of the drugs

4:28

and most of the procedures have

4:30

been in place since the nineteen forties,

4:33

and in some countries there is no

4:35

materal mortality so to speak of, and

4:39

so it is solvable. It has been

4:41

solved in this day and age. There's some Scandinavian

4:43

countries that have solved it. So

4:45

it is truly solvable, and it has

4:48

been solved. The fact that

4:50

we still have eight hundred women

4:52

dying every day. Literally that's two

4:54

jumber jets crashing every day. I

4:57

realized that we as a human

4:59

race are not going to progress unless

5:02

we say no to these unnecessary debts.

5:04

Walk me through the nature of the problem.

5:07

So you say, the medical profession has come

5:09

up with solutions, we have ways

5:11

to prevent women from dying in childbirth.

5:14

What is stopping people from getting the healthcare

5:16

that they need. I'll

5:18

break it down. It's very traditionally broken

5:21

down into three segments. They're

5:23

called three delays. And

5:25

this is very well researched and written about

5:28

The first delay is delay in seeking care.

5:31

So this is a delay in the

5:33

woman herself going to

5:35

the hospital getting prenatal checkups,

5:38

understanding that this needs and should

5:41

be a medical care and take care of her body

5:43

and her health, or the family also

5:46

understanding that this should be a delivery

5:48

in the facility and that usually

5:51

the feeling in these villagers is the

5:53

mother in law saying, look, I delivered your

5:56

husband in that back room. You go

5:58

and do it. We're not going to spend money on hospitals

6:00

doctors, and by the way, you still have to

6:03

sweep the barn and make the cows. So

6:06

the first delay is in seeking care even

6:09

is a huge delay. And the

6:11

second delay is getting to care. So

6:13

they have realized, okay, they have done that,

6:15

they've gone and seen and had some prenatal

6:17

checkups, but they have not planned

6:20

for how they're going to get to care. Either

6:23

they have not don't have the money at the last

6:25

minute to pay for the automobile the taxi,

6:28

or they're no ambulances, or even in certain

6:30

parts such as Zambia, if

6:32

the flash floods have come and the road is washed

6:35

out, there's no way to get to care. So the

6:37

second delay is in getting to care.

6:40

And the third delay is receiving

6:42

care. So there sometimes they do that

6:44

and they come and at the hospital there

6:47

is either no alexity, there's no medication,

6:49

there's no train doctor, there's no anesthesia,

6:53

there no facilities, And so the

6:55

third delay isn't receiving care. And

6:58

so it's not just enough for us to say, oh,

7:01

okay, we'll make sure they're ambulances, because

7:03

if they don't get into the ambulance,

7:05

it's meaningless. And or if they say, we

7:08

say, we'll just put dication and we'll train

7:10

doctors, but if you haven't done

7:11

the community

7:14

outreach to make them want to come, it's

7:16

meaningless. So really all three delays

7:18

need to be addressed together. And usually

7:21

most of these women die a combination

7:23

of the delays. Most often it's all

7:26

three. So maybe can you give

7:28

me some idea of what we're talking about

7:30

in terms of numbers

7:33

how many women die annually, but

7:35

also how have those numbers been reduced

7:38

in recent years, and how

7:40

do you foresee them being reduced further in

7:42

the next ten or twenty or thirty years.

7:45

The goal is to reach preventable

7:48

maternal mortality, to reduce it down

7:50

to seventy by twenty thirty.

7:53

I mean, no death is acceptable, but seventy

7:56

is a number that the world has put us taken

7:58

the ground saying, if we can make

8:00

sure every country comes down to seventy,

8:03

that would be achievable. Some countries

8:05

today that number is five and

8:07

in some countries that number five thousand,

8:10

and so we have made huge

8:12

progress in the last ten

8:14

years. We've halfd metal mortality as

8:16

a world, but we're still

8:18

very far away from the seventy number.

8:21

And the business is usual as

8:23

the rates of reduction as we see

8:25

it now will not get us to

8:28

that number of seventy metal

8:30

mortality. So there has been a

8:32

huge progress, but the rate of reduction

8:34

is not enough to get us where we want to go. Those

8:37

are the numbers. And currently, as I said,

8:39

eight hundred women die every

8:41

day in the world, and by

8:43

the way, seven hundred women die every year

8:46

here in the US. It's

8:49

almost two deaths a day. Wow. So how do

8:51

you overcome this first barrier? How

8:53

do you convince people to come to appointments,

8:55

to come to hospitals. How do

8:58

you get them used to the idea that birth

9:01

is not something that takes place at home. So

9:03

if you take India as an example. They

9:05

have done a huge outreach

9:08

to including conditional cash

9:10

transfers to community

9:12

health workers to bring these pregnant women into

9:14

the facilities, and there

9:17

was a push and there's almost been an eighty

9:19

percent increase in facility

9:21

birth rates in India, so it can

9:23

be done, and behavioral change communications

9:27

they've been they've used local

9:29

storytelling, they've used the

9:31

power of pure experience,

9:34

so all that has worked, and in fact

9:36

there's been a huge increase in facility

9:38

births rather than birthing at home.

9:41

But unfortunately that eighty

9:43

percent increase in facility

9:45

births has not resulted

9:48

in an equalent eighty percent decrease

9:50

in maternal mortality. The facilities

9:53

were not ready for this onslaught and the quality

9:55

of care they were receiving or the protocols

9:58

that they had in place were not suffice and

10:00

so they did initially

10:03

see the eighty percent decrease. But the

10:05

way India went about it is first is raising

10:08

the demand, using the awareness and incentivizing

10:11

women to give birth in facilities, including

10:13

making the whole experience free,

10:16

including the transportation, and

10:18

now are very much focused

10:21

on the quality that the woman will

10:23

receive during that childbirth process. If

10:25

you add to that data analysis and data

10:28

predictability and predictive analytics to see

10:30

which woman is a high risk and

10:33

once they come into the hospital and to

10:35

triage them, and to be able to use

10:37

the latest and the best in data

10:39

and technology is again leads

10:42

us to believe this is solvable and hence

10:44

is something we should be doing. Tell me a little

10:46

bit more about data. You know, we're

10:48

talking about remote communities. What

10:51

kind of difference can data make? How

10:53

does that help doctors in rural

10:55

India. I have been

10:57

in communities and it's amazing how

11:00

the advent of mobile phone technology

11:02

has so penetrated even the rural

11:05

areas in a lighter way. They say,

11:07

they probably more telephones than bathrooms

11:09

in India, and so the people who have access to a phone

11:11

more easier than electricity

11:14

with that kind of penetration, I

11:16

have seen, say in

11:19

that village, in these communities,

11:21

in a house, the husband who's

11:23

usually the farmer, the

11:26

male, the man has

11:28

a phone and today on his phone,

11:30

the farmer has a weather forecasting

11:33

app that tells him went

11:35

to plant and went to harvest. He's

11:37

got an app that tells him the prices

11:39

of his harvest and the produce in

11:42

the market that day, so he knows when to sell.

11:44

He also has on an app transportation

11:47

like the equordent of the ubers,

11:49

to be able to move his produce and his harvest

11:52

to the cities for a better price.

11:55

This exists today, We've seen

11:57

it. And in that same house is

12:00

the wife who's the community health

12:02

worker, and she carries

12:04

around six registers, does

12:07

not have access to the phone, has

12:10

twenty families that she's seeing, has no

12:12

idea how to optimize her day,

12:14

which household is at risk, which child

12:17

in her community of who she's responsible

12:20

is at risk for my nutrition? Why

12:22

couldn't she have similar predictive

12:24

analytic tools like weather forecasting

12:27

that would help her do her job better.

12:29

So it is not just the doctors having

12:31

access to data, It is how can the community

12:34

health workers, the frontline healthcare workers

12:36

have predictive analytics tools that will optimize

12:39

their work process but also in

12:41

real time can give them insights and inputs

12:43

on how to take care of these patients, of what tests

12:46

to do, which ones are the

12:48

triage, which ones are the ones at high

12:50

risk. So this could be something

12:52

as simple as community health

12:54

workers having a kind of app on their

12:56

phone that could help them give advice to pregnant

12:59

women or help them make decisions about

13:01

who needs what kind of care. That would

13:03

be exactly the start. From there,

13:05

you can envision where she could have the story

13:08

of her village to know if there's

13:10

a huge absence of children in

13:12

one school in her community, she

13:14

should now go there to see is there a diary

13:16

outbreak, what's happening? Why are the children are coming

13:19

to school? There are so many ways we

13:21

can then build on it. What about

13:23

doctors in these communities, how can they

13:26

access data and how can that make a difference

13:28

to what they do? So take

13:30

supply chain. Most doctors in

13:32

these villages, if there's

13:35

a primary secondary health center, the

13:37

doctor in charge is the superintendent

13:40

of the hospital, and he or she has

13:42

never been trained on stock

13:44

forecasting, has never been trained

13:46

on human resource distribution

13:49

and how to supply and demand.

13:52

If these apps can actually in

13:54

real time keep track of stockouts

13:57

demands, is there any

13:59

way that the data can give

14:01

a better insight to these doctors to be able

14:04

to do a better supply management,

14:06

better access to where

14:09

the crisis and they can they have

14:11

an access that tells them based on social

14:13

media and other data inputs.

14:15

Where are the migrants coming from, what's happening

14:18

across borders, where is the water on area,

14:20

what's happening, is there another ebola

14:22

brewing? Data can help identify

14:25

hot spots and cold spots. Cold spots

14:27

could be a whole region where children

14:29

have not being immunized and nobody's kept

14:31

tracked and we don't know because they are

14:33

in the blind spots. Hot spots

14:35

could be where this flash pandemics

14:38

or something brewing that we could get earlier

14:40

warning. But what about specifically

14:43

to deal with the issue of maternal mortality.

14:46

Is there you know, are there particular kinds

14:48

of programs or apps, or is there a

14:50

kind of data that doctors can find particularly useful.

14:53

So if the frontline healthcare worker can

14:55

find out if there is a region where

14:58

women are not coming to anti

15:00

natal care for visits and

15:03

could be very easily tracked based

15:05

on whether the woman has made an

15:07

anti natal visit and if she asn't,

15:10

they could even make home visits or

15:12

they could encourage the woman to come in and

15:14

we know, for example, simple antenatal

15:17

visit to check for protein in the urine,

15:19

blood pressure, sugar levels

15:22

make a huge difference. I've also

15:24

seen an app it's in formulation

15:27

stage. It's actually the camera

15:29

can take a video. So

15:32

I've seen where in India, the

15:34

healthcare worker waves this

15:36

camera her cell phone over the

15:38

belly of the pregnant woman. An

15:40

inside, there is an algorithm that

15:43

based on that image and that picture

15:45

that's taken, the woman's

15:48

size of the pelvis is measured,

15:51

and the baby's head is measured, and

15:54

an algorithm predicts whether this will

15:56

be an obstructed labor, whether the child's

15:58

head is too big for the woman's pelvis. Wow,

16:00

And that can be put in a cell phone. Yes,

16:02

I've seen it. It already exists. Inside obviously

16:05

has to be finalized and commercialized,

16:07

but people are thinking that way. So if you think

16:09

about how data

16:11

and applications are changing in our lives

16:14

today, there's so many people with the Apple

16:16

Watch that has the health monitor on it.

16:19

What can we do if we take that kind

16:21

of mindset and those kind of assets

16:24

to the developing world to improve public

16:26

health, community health And to me, I'm

16:28

using maternal mortality as

16:30

a sentinel indicator the Canadian

16:33

the coal mine, so to speak, where it

16:35

tells me the status and the

16:37

health of the community, because

16:40

the first ones to die, the most vulnerable,

16:42

are the pregnant woman, and if

16:44

we can save them, it means very

16:47

likely we have a system in place that

16:49

is saving many people. And so

16:52

these data, these tools are needed,

16:54

are needed today. They exist. Is just that

16:56

somebody has to put it together, and that's where we are.

16:59

Do you get any opposition to

17:01

the use of technology and data? Do you find

17:03

that people distrusted? Do you

17:05

have people rejecting it? In

17:08

the countries that I am working

17:11

on right now, I can presume it will happen.

17:13

India is putting in place draconian

17:16

and much needed and many aspects

17:19

health data, privacy and security laws.

17:21

So it is coming. But right now,

17:24

when we show up and we talk about how

17:26

we are helping women survive childbirth,

17:29

there is open arms and even in even

17:31

in communities. Here in

17:33

the US, it's the only

17:36

developed country in the world where

17:38

metal mortality is rising. And that is

17:40

really an absolute shame, considering that we

17:42

spend more than any other country on

17:44

healthcare. And is that is that for similar

17:47

reasons you have these same kinds of obstacles

17:49

in the US that you have here. Yes, they are the same three

17:51

delays, but they have a different connotation. So the

17:53

second delay is not that there's

17:55

a flash fard and they can't get to The second delays

17:58

she's in a housing project and taxis

18:00

won't come there. She doesn't have money for

18:02

a taxi, and she can see the hospital, but she

18:04

can't cross it because there's a huge highway in between.

18:07

So, yes, you can envision

18:09

the delays. The concepts are the same, the details

18:12

are different. Also here in

18:14

this country we have slightly different

18:17

causes. In the developing world. That three

18:19

big causes are woman bleeding,

18:21

which is postpartum hemorrhage, pre acclamps

18:23

here, which is when the blood pressure shoots up and

18:26

you get seizures and brain damage. The

18:28

third is sepsis, which is infection.

18:31

Here in the US it is coiegulation disorders,

18:34

it is how do you askular disease, It's

18:36

comordabilities, it's older

18:39

woman, it's obesity. It's

18:41

also general lack of health

18:43

and women not engaging with the healthcare

18:45

system. So there are similarities,

18:48

there are some nuance differences, but the

18:50

bottom line is the same. Women are

18:52

dying from preventable causes,

18:55

and to think that the rate is going up in this country

18:58

is just unacceptable. I

19:00

agree, it's very shocking. It's all very

19:02

well talking about technology

19:04

and apps and cell phones, but

19:07

how can you use this technology parts

19:09

of the world where power is unreliable

19:11

and internet connections are unreliable? Do

19:14

you have solutions for that as well? So

19:18

any and all attempts at

19:20

improving health will also have

19:23

to buy nature address

19:26

the data inequity gap. Yes,

19:28

electricity, internet connectivity,

19:31

all these are current

19:33

barriers, but these have been bridged.

19:36

There are solutions for this. They

19:39

are off grade solutions.

19:41

They are offline solutions.

19:43

And in fact, most of the apps that exist

19:45

in most of the ones that are working right now

19:48

in parts of Africa by large

19:50

part work offline and

19:52

then when the internet connection is there, they

19:55

do the upgrading. So these

19:57

are solvable by technology. But

20:00

it's that feeling that we

20:02

can and should do it that is

20:04

the piece that we need to cross. And once we've crossed

20:06

that, I have a feeling we can get to all these

20:09

current barriers. Even if

20:11

you would have asked me twenty years

20:13

ago if I was in charge

20:16

of all health for a coastal

20:18

village that was that was

20:20

routinely hit by hurricanes, and they

20:22

asked me, what would I have to do to

20:25

make to save people when the hurricane

20:27

comes. Based on what I knew

20:29

then, I would have said, Oh, we need to build more shelters,

20:32

we need to have more hospitals, we need to have more

20:34

collar of vaccines, we need to have more clean

20:36

water. How do I save the lives?

20:38

Based on what I know? But today

20:41

probably the thing that saves more lives

20:43

is the weather predicting app forecast

20:45

that tells me the storm is coming and

20:47

I can evacuate people. And

20:50

I would have never thought of that as saving more

20:52

lives. Twenty five years ago, I'd have built more hospitals,

20:54

more shelters, But today

20:57

that single app is saving more

20:59

lives than all the things we could

21:01

have done. Similarly, today, if we were talking

21:03

about how can we save these mothers from

21:05

dying, we're talking about internet

21:07

connect community. We're talking about more hospitals,

21:10

better training, on and on and on.

21:12

Perhaps there's technology out there that

21:15

will take us to a completely different place. I just

21:17

want to make sure that the current barriers

21:19

don't hold us back, and that we do understand

21:21

there's a data in equity and that that is

21:23

exacerbating health in equities, and what

21:26

are the obstacles to you, what's

21:28

still standing in your way, what's keeping you from

21:31

bringing down the this mortality

21:33

rate more quickly? So I will I will

21:35

start that by quoting

21:38

doctor Mohammad Mahmata

21:40

was an obstitation is an obstacian who

21:43

considered the father of this whole concept.

21:46

He very famously once said, and I'm quoting

21:48

him, women are dying not

21:51

because we don't know how to save them. They're

21:54

dying because we have yet to decide

21:56

their worth saving and to live.

21:58

That it is very clear that

22:00

for any of what solutions

22:03

we come up with to stick, sustain

22:05

and scale in country, first

22:08

we need the country. We need

22:10

a political sustainability. We

22:12

need political will. We need the policymakers,

22:15

the decision makers to decide that

22:17

the woman are worth saving. Second,

22:20

we need social sustainability.

22:23

We need the culture to be where the

22:25

woman is valued and where healthcare

22:27

is considered important for these women

22:30

to get and to deliver

22:32

in a facility. And then we

22:34

also need the commercials

22:37

sustainability that whatever systems

22:40

are put in place have to benefit

22:42

society and that we do understand

22:45

that these are not just

22:48

programs that we can go in and set

22:50

up as philanthropy and

22:52

turn around and walk away, because we

22:54

need to teach them out of fish, and then we need to make

22:57

it commercially viable for them to

22:59

fish rather than just give them the fish. So we need

23:01

to set up systems where this is then sustained

23:04

locally within the community. So that is the barrier

23:06

is how do we sustain scale

23:10

the solutions that we put in place. But

23:12

it also sounds like, you know, there are

23:14

these incredible pieces of technology available,

23:17

but there's also a fundamental emotional

23:20

or psychological obstacle, which is that

23:23

not everywhere do people think that

23:25

women's lives are important. Obviously

23:27

that is true here in the US too. They

23:29

are countries that have come together that have realized

23:32

that saving the woman is not just that I think

23:34

to do, but it's the smart thing to do. And there

23:37

is equality and there is no mental

23:39

immortality so to speak of. So it

23:42

is just this that they are still communities

23:44

and their countries that wage political

23:46

wars on women's bodies, and even

23:49

here in this country is no different.

23:51

So we need to be able to break those barriers.

23:54

But just breaking those barriers and not enough. We need

23:56

to come up with the medication technology training

23:58

to then actually really save them, because no

24:01

amount of cultural

24:04

training will help the woman who

24:06

needs associated section. A lot

24:08

of people listening to this might be

24:10

inspired by some of the things you've said and

24:12

might like to want to try and help solve

24:14

this problem. Are there things that listeners

24:17

can do? Do you have any advice for people listening?

24:19

So the first thing, there are many organizations

24:22

that are linked. I would say, be

24:25

aware, get to know it, and if

24:27

you depending on the sliding scale, whether

24:29

you suggest your pocket, whether you can give

24:31

some money, whether you can give time, whether

24:33

you can give some volunteer hours

24:35

work, it's a sliding scale.

24:37

I think it all depends on where your heart is.

24:39

But I think the journey should start from

24:42

educating oneself, finding out who

24:44

are in this space, and then reaching

24:46

out. And obviously, the Rockefeller

24:48

Foundation has our website, and on

24:50

that website there's a health section, and

24:53

then you can see how we are working towards

24:55

trying to solve this. Really powerful

24:58

words from doctor Navine Rao from

25:00

the Rockefeller Foundation there about

25:03

maternal mortality and also

25:05

talking about what it's really dealing

25:08

with, which is women and children's

25:10

lives, and how things can

25:12

change when society decides that

25:15

they are worth saving. Solvable

25:19

is a collaboration between Pushkin Industries

25:22

and the Rockefella Foundation, with production

25:24

by Laura Hyde, Hester Kant,

25:26

Laura Sheeter, and Ruth Barnes from Chalk

25:28

and Blade. Pushkin's executive producer

25:31

is Neia LaBelle, Research by Sheer,

25:33

Vincent, engineering by Jason

25:36

Gambrel and the great folks at GSI

25:38

Studios. Original music

25:40

composed by Pascal Wise and special

25:42

thanks to Maggie Taylor, Heather Fine,

25:45

Julia Barton, Carly Mgliori,

25:47

Jacob Weisberg, and Malcolm Gladwell. You

25:50

can learn more about solving today's biggest

25:52

problems at Rockefella Foundation

25:55

dot org, slash Solvable.

25:57

I'm Mave Higgins now got solvus

26:10

then