- So apologies for the notes.
I don't normally like to read my lines
but if, like me, you've had
about eight meetings today
you'll know that the
word finding difficulty is real.
So hi everyone, I'm Joanne Peter,
the Director of Social Innovation on
Johnson and Johnson's Global
Community Impact Team.
For decades GCI has been working to
support and champion the people at
the front lines who are at
the heart of delivering care.
Because we believe that
every health worker
trained and supported helps us
to build a stronger community and
every strengthened
community brings the world
one step closer to achieving our
global aspirations of health for all.
So before we begin, just a thank you to
our hosts at Skoll and of course to our
mini experts and innovators who
will be joining us onstage in a moment.
We appreciate it.
As all of us in the room know,
good health begins in our
homes and in our communities.
But half the world is lacking access
to essential health services.
And we know that there's about
a nine million deficit in terms of
nurses and midwives and around two million
community health workers in Africa alone.
And those that are in
the health work force
are often lacking the tools
and the training support
that they need.
So how can we effectively deliver care
when the people who are
keeping our communities healthy
don't have the tools that
they need to succeed?
And how can we achieve health for all
when the greatest gaps are the
ones that are closest to home?
So today you're gonna get a chance
to hear from some of our speakers
on how technology is sharing some of
the answers to some of these questions.
Bringing together health
and community-based
primary care, our
panelists are accelerating
the possibility to improve access and
quality of care delivery
from Kathmandu to Nairobi,
Mumbai to Johannesburg.
Thanks.
So we're honored to
kickoff with our keynote
from Dr. Peter Drobac.
Let me get his bio correct.
He's the Director of
Social Entrepreneurship
at the Said Business
School here at Oxford.
Before that, Global Health Physician
and Social Entrepreneur.
He was Co-Founder and
first Executive Director
of the University of Global
Health Equity in Rwanda.
For over a decade he played a key role
in transforming Rwanda's health system,
which has delivered unprecedented gains
in population health and prosperity.
As Executive Director of
Partners in Health in Rwanda,
he established community-based
health system incubators
that developed and scaled health care
delivery innovations, from
infectious diseases to cancer.
So today he'll share why we must treat
the system and not the symptoms
of global health inequities.
So without further ado, welcome.
- Hi everyone.
I haven't quite lost my voice yet.
It's coming, but hopefully
it'll last until tomorrow.
Great to see you all.
There are really comfy
couches in the front,
if anybody wants to join us up here.
This house believes that tech
for good is a false promise.
That's the proposition
that's about to be debated
down the street at the Oxford Union,
the world's most famous debating chamber,
and we happened to organize that
as our Skoll World Forum Debate.
I'm supposed to be there actually.
But the irony when I was asked to
come and talk about the world of
technology and community-based healthcare
was too delicious not
to be a part of this.
So I just had to be here
and be with you all.
I'm sorry to report that the internet
has not ended poverty, that
AI has not cured racism,
and blockchain has not fixed corruption.
We still have a long ways to go.
During our lifetime,
during my time in Rwanda,
we've seen the steepest gains in
population health and human prosperity
probably ever documented but we know
we have a long way to go.
Joanne cited some of those statistics.
15,000 kids are still dying everyday
and they're dying stupid deaths
for stuff we know how to prevent,
we know how to treat, we know how to fix
we're just not doing a good job of it.
So how do we accelerate, how
do we reach more communities
and do so faster?
There are a lot of lessons
we have from Rwanda,
there are a lot of lessons
from the folks in the room.
But today we want to specifically look at
where technology can enable and help us
to turbocharge our aspirations
and strengthen those systems.
But I want to start maybe with
just a few cautionary tales.
We have a tendency, as
a society as a species
to kind of fetishize technology
and its power and its ability to
transform just about everything
and that can oftentimes lead us
down some dark alleys and
down some wrong paths.
And I think there are
cautionary tales from history.
You can go back and look at the
history of international development.
Take malaria eradication in the 1960s
where there was a massive global effort
towards one of the great
silver bullets, DDT,
and indoor residual spraying
to eradicate malaria
that actually came quite far in
many parts of the world until some
of the unintended consequences
and secondary effects halted that effort.
And and fact we've seen in just
recent years, thanks to climate change,
a real resurgence in malaria.
And we're looking at a
generation or two out,
the possibility of a billion more people
being exposed to mosquito-bourne diseases
because of climate change.
More recently, anyone remember Play Pump?
This isn't really technology
it's just a technical,
but a technical innovation and
a great example of how
technical innovations
in international development can fail.
So in the early 2000s the Play Pump was
this really heralded,
great, cool innovation
that was basically a merry-go-round
that functioned as a
pump, a groundwater pump.
The idea was we put
these things in villages,
kids ae gonna play on the merry-go-round
and it's gonna pump water into a tank
and it's not work any more.
And they told a great story and it
was a cute looking thing
and everybody went bananas.
Not everybody but the media went bananas
and in the States they went bananas
and they raised tons, tens
of millions of dollars
to start putting these pumps everywhere.
And it was just a few years before
all of those pumps that had been installed
were abandoned and the organization folded
less than three years after securing
a $10 million grant.
So what went wrong for them?
Well first, the tech wasn't very good.
It wasn't a fun merry-go-round.
You have to keep pushing and
pushing and pushing and pushing.
It's not like you'd get a speed
and then it just keeps spinning
and then you could just
ride around and have fun.
So the kids got really tired
after like five minutes.
And then the moms had to push and
that was more work than
just pushing the hand pump.
So they forgot to ask the kids
if they liked the pump or the
parents or the communities.
They didn't design for and
with their core customers.
They didn't look at the system
and understand what are the needs
of this community and how
are we best gonna solve it.
It was a narrow kind of
vertical intervention
and this is why it failed.
And to their credit, they learned from it
but I think there are a
couple of lessons here
that I've seen repeated again and again.
So I just want to start with some
of those cautionary lessons for
those of us who are thinking about
the role of tech to make sure we can
temper our enthusiasm and start with
a little bit of humility.
First is beware of riding
the silver bullet train.
There is no single solution to
any one of these big and complex problems.
The healthcare issues
that we're looking at
are deeply embedded in extreme poverty
and social and economic
and political systems
that are excluding people and we're
not gonna fix that with
any one intervention.
We're certainly not
gonna fix it with an app.
Second, beware the top down approach
to technical and technological innovation.
We see this again and again and again
and here we are in to
ivory tower of Oxford
talking about solving the problems
of poor people without a lot
of poor people in the room
and so we need to be cautious about that.
And doing that without proximity
and engagement of the folks who
actually have lived
experience with the problem
is very, very dangerous.
So the top down and outside
in approach to innovation
is one that's destined usually to fail.
Third is taking too narrow a view
and actually ignoring the entire system.
And we'll talk more about this.
So these are some of the things
I would say to watch out for.
We're in a room full of people
who care about community-based care.
I'm really excited about
the speakers to come.
So let's think about the possibilities
and how we can possibly approach this
a little bit differently.
Because there are two things that
I would suggest as approaches for
thinking about the how to think
about technology innovation to
help you build stronger
community healthcare systems.
And the first, that was
in the title of the talk,
is treat the system not the symptoms.
The idea here is that technology
can play really important roles
if we look at the entire healthcare system
and we understand where are
there gaps in the system,
where are there gaps in skills,
where is the system breaking down
and then how can we use
technological solutions
to help the system work more efficiently?
If we're thinking about an app
to allow community health workers
to collect better data, great.
But does that app help
community health workers
make better decisions?
Who does that app talk to?
Where do the data go?
Does the app health connect
community health workers
to the health centers and
the doctors and nurses
who are working there?
Does it align with national data systems
or is it gonna be a parallel system
that's gonna be broken down?
How many times, dozens, I've seen dozens
of apps or softwares for
better reporting of data
that ultimately don't
scale and end up failing
because they're too narrow and they try
to do their own thing and they
don't talk to the rest of the system.
And that's just one of
many, many, many examples.
So you start your innovation journey
by mapping the entire healthcare system
and understanding the context as well
and then trying to find levers for change
within that system and
those are the opportunities,
I think, for technological innovation.
Second is lead with equity.
So what does that mean?
Equity when we talk about health
is simply talking about
the right to health.
And that's the idea that
every child, woman, and man
on the planet deserves access
to high quality healthcare.
Sounds simple, I would wager
that everyone in the room
or virtually everyone in
the room agrees with that.
Our approach in public health tends to be
a little bit more utilitarian.
We share that aspiration but in practice
we approach the problem
a little bit differently.
Utilitarianism, effective
altruism would encourage us
to think about doing the
most good for the most people
with the available resources.
The problem with those kinds of approaches
is they often exclude the most vulnerable
because the most vulnerable
are the hardest to reach,
they're the most difficult,
the most complex to reach
and oftentimes it's more
expensive, and more challenging
to reach those folks.
One of the things that
we learned in Rwanda
is that an equity agenda
forces us to think differently.
Rather than saying no, we have to ask how.
And in fact, if we try to solve for
the most vulnerable and hardest to reach
last mile communities that unlocks
new opportunities and new innovations
and actually make our solutions easier
to spread and scale across
context and geographies.
And the history of Rwanda's
health system evolution
over 15 years started with let's go to
the worse off places first and
we're not gonna do it anywhere
unless we can do it everywhere.
And if we can solve the problem there
then we prove we can do it everywhere
because we've already overcome
the most difficult obstacles.
And that was what allowed many
of those innovations, which a lot of them
were no necessarily high tech,
to spread really quickly
across the country.
And doing the basics really well
lead to an 80% reduction in
child mortality in 10 years
and a number of other great statistics.
So treat the system not the
symptoms and lead with equity.
I just want to share a few observations.
This is what happens when I improvise.
A few observations on some of the areas
where I think technology can be
really well-placed to address
some of the challenges
that we all care about.
First is in training and empowering and
extending the reach of health workers,
those community nurses,
community health workers,
and many, many, many others.
We've seen some great examples
by folks here and this room
and in here at the forum,
like the Community Health Academy that
Last Mile Health is building,
where using the power of
not only online training
but online platforms for
learning collaboratives
can really decentralize and turbocharge
our ability to train more
effectively more health workers,
to empower them to make better decisions,
and to enable them to both
generate more effective data,
and actually make better
decisions as a result of that.
Second is to our patients
and that's not just
with health information but also to
empower patients to dignify
their healthcare experience
and actually to understand their rights
and be able to drive improvements
in the healthcare system.
Third is improving the systems,
both information systems
and supply chains.
Some great examples, one from Rwanda,
is zip line them in you've heard of
which is a program that's
using drone delivery
to deliver essential
medicines and blood products
to remote rural mountainous
healthcare facilities.
That's been brilliant.
Last week at the cancer
center that we started
in Northern Rwanda there
were eight deliveries
of life saving emergency blood
products for kids with cancer
in one week.
But that system, that
company is only working
because it's embedded within the system
through a public/private
partnership with the government
and so it's taking to the
rest of the supply chain.
And then finally there
are lots of examples
where we could go using technology
to bring the fruits of
modern medical science
to the people who need it most.
We have a young woman who I
met when she was a 10-year-old
who lost her leg in a failed attempt
to treat her osteosarcoma,
her bone cancer,
who's since survived
and uses a prosthetic,
whose dream is to use 3D printing
to develop low-cost prosthetics
for other folks with physical disabilities
and amputations across East Africa.
So those are just some of the examples.
We have a terrific,
terrific group of folks here
who know a lot more about
this stuff than I do.
I just want to really encourage you to,
I really believe that this
notion of health for all
is something that we can attain
and we can attain in really our lifetimes
but it's gonna be really hard to do.
Technology has to be
an important part of it
but we have to, as I said the other night
in the opening plenary, we have to
lead with both optimism and urgency
to make sure that our big ambitions
are also tempered with humility
and really grounded in proximity.
So the messages I want to leave you with
are lead with equity, treat
the system not the symptoms,
and that's all I've got to say.
Thank you.
If there are questions or comments
or devastating critiques feel welcome.
All right, thanks.
- Thank you.
- Thank you, thank you so much Peter
for that grounded wisdom before we start.
Now we can move into our
phase of techno optimism.
I'm sure many of our panelists
will hopefully share
with you along the way
some of the ways that they are actually
living into that sage advice
that Peter just shared.
So we're now gonna move
into our first panel.
This one is around bridging the gap.
I mentioned that those
health workforce gaps
so how are some of the ways that
organizations are using technology
to actually embed health
innovation into the everyday lives
of people where there may not be
enough health workers to actually have
those face-to-face encounters.
So as I call your names, you
can come and take a seat.
So first I have our
moderator, Andrew Jack,
who's a global education
editor in the Financial Times.
Thanks so much, you're
gonna get this mic in a sec.
And then we have Aakash Ganju, who is
the Founder of SaatHealth,
working in Mumbai in India,
Debbie Rogers, Managing
Director of Praekelt.org
in Johannesburg in South Africa,
Michael Kapps who is
the CEO and Founder of
TNH Health in Brazil, and then
Sarah Mullane, who's the
Behavior Science Manager
at Johnson and Johnson's
Health and Wellness Solutions.
Thanks so much, Sarah, have a seat.
So a lovely international
and diverse panel.
Thanks so much.
Take it away.
- Great, thanks very much and thanks Peter
for coming to us rather
than the Oxford Union.
I must say I think you're
much more insightful
and very informed
audience and I think that
very important in this discussion.
We'll start with some
discussions amongst ourselves
but really wanted to look over to you
for your reflections and opinions
more generally as well.
And I think your thoughts on the
nuance of tech really as it were
are really valuable.
I'll say different backgrounds
working for a number of years at
the Financial Times it's kind
of an interesting parallel
because the FT has really gone from
an entirely print-based product to
a very largely digital-based product.
And clearly technology has been a
very useful tool for us in many ways
but the fun, technology is an enabler.
The underlying value of the FT,
I would say is the content,
and that's ultimately about human input
not about the technology itself
which helps to facilitate
its delivery as it were.
So we're gonna talk this
afternoon about health,
and of course that's a field where
there's a huge amount of intersection
and innovation around technology
but absolutely important to think about
the nature of the interactions of
humans and patients with physicians
with the wider community.
So maybe let me start
with you Sarah, from J&J
and we were talking earlier and
you actually have a background
in behavior sciences
and it sounds like a number
of others in J&J do as well.
So give us a little bit of perspective
on behavior science and why and how
that's important in healthcare.
- Absolutely, thank you.
Behavior science particularly important
in the 21st century has
always been important
to healthcare but in terms of the
21st century now, I think it's more that
we're more aware of the
value of behavior science.
I think it's important to recognize that
although we understand that
behaviors are important,
there's been a tendency to think of
if we just tell somebody to
do something, they will do it.
And unfortunately some
of the famous slogans,
we are not just doing it.
There may be prevalence of
non-communicable diseases,
there may be preventative healthcare
that we're aware of.
There are also government guidelines
that are telling us what to do.
How to engage in healthy behaviors or
how to avoid engaging in risky behaviors.
And yet majority of us still don't know
necessarily how to put that into practice.
And that's essentially because,
and I think it was
touched upon previously,
thank you Peter, that
this is very complex.
We are complex human beings.
At the individual level
there may be factors
influence whether we
engage or don't engage
in a behavior socially, culturally,
environmentally,
organizationally, policy-driven
factors or determinants that do influence
whether we engage in a behavior or not.
So I think it's important
that in the 21st century
now we understand that
although we know what to do,
behavior science has told
us where there's a problem,
why there's a problem
but now we're seeing that
behavior change theory can
show us how to intervene.
And that moves to the next point
of behavior change theory really that
it provides us with a very
logical, step-by-step approach
by which we're actually always
thinking about these outcomes.
The organizational
outcomes, whether it's at
the hospital setting, whether
it's always a health outcome,
we should always be designing
health interventions
with a health outcome in mind
and not getting too caught up in
the technology innovation
for sake of innovation.
In behavior change theory, when we go to
our evidence-based laurels we can use
behavior change taxonomy and select
some of the behavior change techniques,
which we call the active ingredients
that allow us to target specific
determinants of behavior,
So what might motivate myself,
to engage in a behavior,
to target a health outcome,
to target an organizational outcome.
And just to put that into perspective,
it might help that that's actually
something we do with the Health
and Wellness Solutions Team
within Johnson and Johnson,
we follow a very structured logic model.
So, for example, if we think about
at the top of this ladder,
organizational outcome,
let's say for thoracic surgery we want to
reduce the length of stay in hospital,
we need to think about
what is the next step
that can help us target that.
We need to think about changing
an individual health outcome.
That might be reducing
post-surgery complications.
And then we move to the next step,
so what behaviors do we need to target
in order to reduce some
post-surgical complications?
We look through the
evidence, we do our best to
speak with domain experts,
and you'll see that
there's a lot of evidence
to support quitting smoking,
a very complex behavior,
as I'm sure you all know.
Then we move to to next step.
So if we want to look at these behaviors,
preparing to quit, reducing to quit,
possibly nicotine replacement therapy.
What determinants will dictate
whether I engage in those behaviors?
And then finally we get to the basis
of everything that we do,
the behavior change techniques.
So you can see how we're step-by-step
piecing together a trying of pearls
from a measurement and
evaluation perspective
that keeps us grounded in the science
and make sure we don't
run away with an idea,
get caught up in innovation.
We can step-by-step measure and follow
are we aligned with our health outcome?
Are we aligned with our
organizational outcome?
And that helps us moving
forward as we apply technology.
- Okay, thanks and maybe we'll come back
to some more examples a bit later.
But Debbie, Debbie Rogers, let's talk
a little bit about Mom Connect.
Tell us a little bit
about how that came about,
how it works, how you're
trying to tackle the issue
of thin coverage sometimes of
healthcare workers and so on.
- In South Africa we still have an
enormous problem with
maternal health outcomes
despite some good progress being made.
And back in 2011 I believe
we started a program
to see whether or not sending
information to mothers
could help them change their behavior.
And I'm sure you'll have
a lot of critique for
the way we did it initially in 2011
sending out discreet packets
of information to people
and hoping that they
change their behavior.
And we found that surprisingly
when we sent a SMS from a system,
the mother responded to the SMS.
It sounds obvious now but at the time
we assumed people would know that
a computer was on the other side of it
and not a human being.
But actually they felt that
they had signed up at the clinic
and it was probably the nurse
that they were speaking
to through this system.
We saw that despite giving them
what we thought was a great set of content
around how to look after their child
in a stage-based manner, they
had all kinds of questions
that we hadn't anticipated all the time.
And in South Africa you have very little
opportunity to meet with
your healthcare worker.
You will go to a clinic, you
will probably take all day
just to get about 15 minutes of time
with your healthcare worker.
And if you're trying to save up
all your questions and
get all your questions
answered in that period of time
that's certainly not going to happen.
And there's very little else out there
that is trusted information.
There are a lot of beliefs that
may be passed down through mothers
and various generations
that are extremely harmful.
So how do we start to
help people through that?
And clearly just sending
discreet care packets
of information wasn't quite enough either.
So what we've been looking at a lot is
instead of just thinking of
the systems that we build as a way
to send information to people,
what about thinking about it more
as a conversation between yourself,
the health system, if you represent that,
and the patient, as well
as the healthcare worker.
So we've built up some technology
that helps us to have these conversations
but to do so at a really large scale.
So in South Africa Mom Connect
is in 95% of the public clinics.
We've signed up 2.6 million
mothers in the last four years
and that represents about 80% of
the mothers who give
birth in public clinics
over the last four years.
So it's very large scale.
And we're having to operate everything
with quite a small amount of resources.
So just to give you an idea,
at any one time we have about 900,000
active users on the platform and
they generate about 1,500 questions
through to the help desk everyday.
We have four help desk operators
who have to deal with
all of those questions.
So we've been using
natural language processing
not to remove the help desk
operators from the system
but rather to help improve the efficiency
and the quality of the conversations
that they are having with the mothers.
The response from the mothers
has just been astronomical.
And we get amazing
feedback from the mothers.
As an example, we can ask them
was your blood pressure taken
at your antenatal visit?
If so what did the nurse tell
you about your blood pressure?
Did they refer you if they told you
that you have high blood pressure?
And this conversation is
generating a lot of data
that is helping to change
the health system itself.
So we are thinking quite systematically.
If only Peter hadn't left I could have
made sure he understood that we do that.
But all based on this
conversation with the patient
and trying to put the patient at
the center of their own care.
But this two-way conversation is critical
because it's not something that I think
most health systems are trying to solve.
I think they're very much trying to
supply services at a person.
Very much like we tried to
supply information at a person
rather than actually being
involved and engaging
with the person around
their own healthcare.
And I do think while the technology
that we developed
certainly is only solving
a very small part of the problem,
it really can have a lot of impact
when having these two-way conversations
between patients and health
workers and health systems.
- So it'll lead to some as it were
standardized answers
depending on the question
that are coming in.
- Exactly.
- But also when or whether the mother
should come back into
the clinic, for example.
So it's helping to deliver a
much more efficient service.
- Exactly, so they're
not going to the clinic
necessarily if they don't need to.
But they have access to the information
they need in the meantime because
it simply isn't possible
for us in South Africa
with the number of healthcare
workers that we have
to be able to provide that kind of
engagement and care
for every single mother
yet that's obviously what mothers need
and crave if they're asking
us so many questions.
- So let's move from South
Africa to Latin America.
Michael, tell us a little
bit about TNH then and
what you're doing around some of
these issues of personalization.
- It was really funny, I was listening
to Debbie talk and I guess while
you were working on your thing,
the same thing was happening on
the other side of the Atlantic Ocean
because we did the same thing.
We were sending SMS at people
to try to remind them
to take their medication
and they hated it and we begin to see
that actually a
conversation was necessary.
But what we've done in the recent
couple months and the years with our
conversation-based
chatbots, as we call them,
or these virtual assistants,
is a couple of things.
We found in Brazil, which
is a middle income country,
more and more people are
having access to smartphones
and Brazilians are one of the populations
that spends the most amount
of time on a smartphone,
about 2 to 3 hours a day.
A lot of times in traffic
and things like that.
So what we begin to do is really
look at the behaviors that already exist
on social media and things like that.
People are already on
WhatsApp sending messages
and memes and funny videos
and things like that,
and trying to hack that behavior to get
people to engage with healthcare.
It's something that I guess marketers
were doing for a long time to try to
get you to by Coca-Cola
and things like that
but we were trying to
apply that to healthcare.
How can we have a conversation
around something difficult?
And in our case, although we do have
some experience with maternal health,
we focused on mental health.
Brazil I think leads the world in
the prevalence of anxiety disorder.
It's an extremely violent country,
a lot of unemployment, and oftentimes
mental health is sort of a gateway
to other kinds of diseases.
But then how do you get people
to talk to a robot about a
number of different issues?
About how they're stressed
or things like that.
We've seen an excellent example
of Crisis Textline yesterday.
We've sort of been able to do that.
So that's what we do.
We created these chatbots on social media.
We tried to create all these techniques
to try to get people to respond back to us
and to answer about their mood
just so we can identify
potential symptoms or problems.
And then once we do
identify a certain issue,
whether it's something that's
immediate that requires attention
or is kind of a chronic issue,
then we can integrate that back with
the health system and let
the healthcare worker know
or the nurse or the psychologist know
and that gives you this
extreme scalability
that we've seen working
so well in South Africa.
And of course to make it
work you have to have,
I guess two things need to function.
The patient needs to be engaged.
You can't just be providing
whichever information they want.
You have to take the
design thinking approach.
You have to look at the data.
What kinds of questions
are they actually asking?
You have to think to their perspective.
You may say oh here's a
good recipe for you to eat.
They might not have money for it.
Or try to resolve this issue but
you're not living in a slum and
having to deal with violence.
So you have to talk about these issues
and sometimes that's a
little bit difficult.
And the second thing is trying to apply
some more cutting edge technologies like
natural language understanding
and machine learning
to try to personalize things,
otherwise you're just
gonna lose that person.
And if you can do that then you
can get access to those risks,
you can respond to them and you
can have scalability within
the healthcare system overall.
- Obviously we don't
have illustrations here
but some of thee memes and so on,
you got a tangible example
you might describe for us?
- So it's actually pretty funny.
Imagine saying this to a past generation.
We have a lot of people on our team,
we have an entire content team of
clinical people but non-clinical people
and they have to try and explain
to their grandmother that they
basically go on Facebook all day
and creating memes and gifts and
try to explain what that is.
But it could be things from a card media,
sometimes celebrities, sometimes...
You've all seen the internet,
trying to especially
emotional health issues,
stressful day and things like that.
So kind of these animated things
but also trying to be
very careful about it,
not just creating entertainment
for entertainment purposes
but actually having clinical
validation behind that.
That's sort of how we get it to work.
Afterwards I can share some
other funny ones that we use.
And that's what engages people.
That's why people open it up and
they have that channel of communication.
- So Aakash, tell us a
little bit about SaatHealth
and what you're doing.
- We at SaatHealth have
been very interested
in the role of non-traditional
healthcare workers
and not because we wanted to be but
because we realized the gap between
demand and supply is so huge and
continues to expand, almost not possible
to navigate if we continue to
look at the same solutions.
So we started looking very interestingly
at the role of the, in India
they're called , the grocers.
Think of them as the 7-Elevens in the US.
And I'll talk about how and why we got to
the potential role that these
could play in the healthcare supply chain.
But we felt that I needed to talk
a little bit about why
we do and what we do
and how we arrived at this because
it seems crazy to start thinking of the
as a healthcare worker.
Certainly my physician
friends would laugh me
out of the group if I
shared this with them.
So what we do at
SaatHealth, our mission is
to build healthier childhoods.
We focus on low income parents in
the slums of Bombay and Delhi
with children between
zero and six years of age.
Why we focus on them is because
there's tons of data talking about how
the health and nutrition metrics,
the immunization metrics
for many of these children
in urban slums is very underwhelming.
Some of these statistics compare to
some of the worst areas in rural India.
So that's the negative part.
On the positive side, I think there's a
huge opportunity for
really helping the parents
of these children dream the dreams
that they want to dream in order
to make sure that their children
get the right health and nutrition input.
So when we started thinking about
how can we help these parents get
their children the right
health and nutrition
early development inputs between
ages zero to six?
The way we do that is by
building a digital ecosystem.
So on the consumer side we have an app
for the families through which
we push out health nutrition and
community development information
in an entertaining and gamified fashion.
We're very clear that
our competition there
is not the health information that's been
doled out by the ministries.
Our competition that
is YouTube, Bollywood,
entertainment channels where people
are spending their time.
And we have to find a way to
get into the minds of our consumers,
especially when we are talking
about preventive health information.
We're not taking about we want to
prevent them from falling sick.
In order to do that we have to
get into the minds of our
parents before they fall sick.
So we push out entertaining
gamified information
and then we're aggregating the demand
of these consumers in partnership
with neighborhood merchants
and health clinics.
Why are we thinking of the stores?
It's very simple and in hindsight
it seems very intuitive.
We basically mapped the
lives of 250 families
living in the slums of Bombay and Delhi.
We said let's go and identify
the touchpoints that they have
in the course of a month.
Who do they touch points
with in their community?
And it was amazing that the
frequency of touchpoints with the
healthcare worker was once in three months
and they were touching their
store everyday.
They were touching the tea vendors
in their communities everyday.
And when we stepped back and
we realized let's start thinking
about these families from
the lives that they lead.
They don't go to the
healthcare worker everyday.
They don't think about the
healthcare worker everyday.
So if we want to start to get
into their lives and start influencing
how they think about preventive health,
we've got to give them touchpoints through
partners that they have a
relationship on a daily basis.
That's what lead us to the store.
What we do right now is that we
have a partnership in a lot of slum
communities in Bombay with 20 stores.
It's very early but we've seen
extremely encouraging results.
So of these 20 stores,
we've seen that they do two things,
they onboard families in
the community onto an app
but more importantly
they're beginning to have
preventative health conversations
with these families.
So about 67% of the families
who've been on the app for about 12 weeks
told us that they have started
proactively talking to their stores
about children's nutrition.
We did not expect that to happen.
This was just within 12 weeks and
we didn't even give these stores
any tools to talk to.
On the other side, the stores,
77% of them said that they've
started proactively talking to
their families about children's nutrition.
It's very early but we think
these ae very encouraging signs
and we need to start imagining
out-of-the-box scenarios here.
But there are 12 to 14 million
stores in India.
Whatever small proportion of them
could become our partners in serving
the preventive health
needs of our communities.
They have the infrastructure
in the community,
they have the relationships,
they have the trust of these consumers.
Can we find a way to leverage them,
not to replace the healthcare workers
because the healthcare workers are
completely overburdened.
Can we find a way to use them
to augment preventive
healthcare conversations
and helping triage these families
towards the right healthcare worker?
We think it's a very encouraging sign.
It's early days for us but we're
going to spend a lot of time to build
up the capacities of these stores
in addition to building a relationship
and partnerships with
other healthcare services.
- So let's just go back to one of
Peter's introductory remarks around
the issue of equity because one
could imagine with technology,
even though a lot of your interventions
seem to be particularly significantly
targeting lower income communities,
we've got everything from bandwidth
to access to mobile,
let alone smartphones.
But also more widely the issue
sometimes of payment and so on.
Who's got some reflections about whether
it's the digital divide risks
opening up rather than closing that gap
between the hardest to get and the
lowest income versus the wider population?
- I think the wealth of knowledge that
those of us that do have smartphones
and can easily pay for access to
there's just an enormous amount
of information and fantastic apps
and all of those sorts of things.
But I think what we always try to do
is design for the lowest
common denominator first.
All the work that we do
is mediated by technology
so there are people we will not reach.
And that's a sad part
of the work that we do
but market forces we've been reaching
more and more people everyday.
But if you can just design for
the lowest common denominator,
often that makes your
solution much simpler,
which means that you can
scale it more significantly.
So things like SMS might not be
sexy technology but it is something
that can reach pretty much everyone.
Or certainly in countries
like South Africa
where everybody has
access to a mobile phone,
if not a phone themselves.
What I like about the idea of
designing for the lowest
common denominator
is that it puts so many restrictions
on your ability to design.
You can't add all the flashy things.
And yet that means that you have
to have a very simple message
and a very simple thing that you're
trying to achieve and that's gonna
allow you to reach a lot of people.
So I actually find it quite exciting
to design systems with
those kinds of restrictions
because I think often they're just
much simpler to understand and
you have to get to the very core
of what you're trying to do.
So I think as long as you keep in mind
this idea of trying to design for
the lowest common denominator,
hopefully you're going to be able
to reach as many people as possible.
And there are a lot of market forces
that we certainly can't be in control of
that are driving more access to phones,
cheaper data, all of
those sorts of things.
So it's encouraging to see that
that is changing and that we can
continue to reach normal people
as that's changing.
I think one of the biggest problems
that you touched on is cost.
We always ensure that it is
zero cost to the end user because
we've just in our experience seen
even a very small cost means we reach
about 5% of the people we could reach.
But that means someone has to pay.
It might not be an end
user but somebody does
and that definitely prevents scale.
We have a very successful
program in South Africa.
When I show other countries what
they have to pay in SMS costs everyday,
they don't take on the program because
it is extremely expensive to run.
It's about a million Rand which,
I don't know what that is in dollars,
every single month.
- [Man] 150,000.
- $150,000 dollars, thank you.
Every single month just
to pay for the SMS costs.
So I think if you are reaching the
lowest common denominator, if
you are designing for that,
it does come with a massive price tag.
And there's still a lot of work
that has to be done
there to decrease that--
- It's certainly not free.
- Certainly not.
- Exactly that's the case.
But if you can align
the incentives properly,
if you can show that we're investing
in this application but it's actually
generating cost savings.
We're preventing unnecessary visits to the
emergency rooms or to specialists.
We are improving health outcomes,
which in the short or medium term
will prevent other issues.
Even if it's a political thing,
if you can align the political interests.
Like look, look at what you're doing.
You're giving transparency.
If you can align that, then you can
actually find the money.
I think that's where the
power of technology comes in.
There's obviously the digital divide.
You have to have the device and
there's little you can do about that.
But I think that's becoming less and less
of a problem over time.
It's just how do you
align those incentives?
How do you monetize and
create a sustainable model
out of these kind of services?
- I do want to add I agree with Michael.
I think when you're designing for
the lowest common denominator you
have to design for not where the
lowest common denominator is today
but where they're going to
be a few years from now.
We are designing for the future
and this is a massively
shifting landscape.
Suddenly in India we've
seen a massive shift
in the last two years, probably and other
geographies also.
So I think we are talking about designing
systems for the future and I'm not
saying 30 years in the future but
let's keep in mind that there are
huge macro forces that
is changing the landscape
and let's design with that in mind.
- Sarah, go ahead.
- Just to touch on that, I think you raise
a really valid point and that's the
beauty in one sense of the opportunity
of technology where we
have behavioral science
meets data science meets technology.
We can start with the best guess,
sort of our theories that may be outdated.
We're all finding our way
right now a little bit
but we're collecting
data and the main point
is that we have a strong
measurement and evaluation
plan in place so that we can talk to the
health outcomes, the
organizational outcomes
that we can achieve.
And it's interesting that you mention
keeping it very simple.
We kind of go with the same principle,
the minimally viable intervention.
What are the basic behavioral
science requirements
that we can embed into
our health interventions
to achieve that?
Then we want to test and learn.
And I think that's the beauty of
behavior science meets data
science and technology,
there's this capability to test and learn
and not just think that
this first go round
is the right one because 99.9%
they're the opposite of that.
And I think we have
this opportunity in that
collecting that data we can then
optimize the next minimally
viable intervention.
- May I just make a note on that, sorry?
I complete agree with that.
One of my biggest challenges in
the work that we do is that very
few of the people who I know who
are funding this kind of work
understand the fact that it is not
a perfect product that I am launching
immediately and will work.
It is a process and you have to
keep up with the massive
changes and trends.
Something I designed this week is
gonna be different next week and in
two year's time it's gonna be different.
So you can't just buy an app,
launch it into a market
and everything works.
That's not how technology works.
And unfortunately there
are a lot of people
who don't quite understand that and
want to be able to launch a solution
and that solution must be the thing,
then you never have to touch it again .
- [Andrew] With clear metrics upfront.
- With clear metrics upfront.
You know exactly what you're doing.
The number of times I've had to
imagine what the activities are gonna be
that I'm going to be doing in two years
to try and make sure that
I can get the funding.
And I think we really need to talk more
about the fact that this is a process.
We are continually learning,
we are continually changing
and having a good monitoring
and evaluating process
in place too that not only is looking at
outcomes but also trying
to learn as we go along.
And as tech implementers,
we have to learn better
how to show people that this is
an important part of the process
and to make metrics available that
allow them to see progress so that
we're not just saying oh
but we need to do the thing
and people are saying, how many more times
do you have to re-factor the system?
Surely it's done now.
We've got to get better at showing that.
But we also need people
to better understand
that it is not just a thing that
you launch into the market and it's fine.
It's very much a process.
- As far as I think briefly
on equity, it just strikes me
about the question of
literacy in multiple languages
and how far that's also an issue
in all of your examples that's a problem
with text-based
communication, for example.
- Mom Connect is in the
11 official languages
of South Africa.
But one of the major
challenges that we have
is that most of the natural language
processing work that has been done
up to today is primarily English and
primarily American English.
So we're having to in a way kind of
re-invent the wheel because we're
working with very resource poor languages.
So the AI that people think wow,
it's amazing, I can speak to Alexa
and Alexa's gonna listen to me,
that's not something we
can actually implement
for Tswana, for example, in South Africa.
So there's a big gap there and
it's gonna take some time I
think for that to be filled.
- But then also there's
a proportion of the
population that in whichever language
might struggle to communicate to read,
- Absolutely.
let alone to write a response.
- So at least in India in our segment
we have something in
India called Bollywood
that really flattens the playing field.
Everybody gets video,
everybody gets entertainment.
So all of our content is video.
And I'm not the person who said this
but it has been said
that the future in India
is voice, video, vernacular
so we are going with that.
Our content is vernacular video.
We are generating user-based content
in the vernacular video form and
it democratizes information access.
Everybody knows how to consume video.
- We'll come back maybe to the list
but let Peter open it up as
well if there is some questions.
Yeah, please, over there.
Do introduce yourself as well please.
- My name is Avila Salvador,
I work for AmeriCares.
Question for you Debbie, you're using SMS
because you want to reach the
lowest common denominator.
Do you have an idea if you were using
an application instead
of SMS, how that would
effect your operating costs?
Because you're not paying per transaction.
- The biggest problem would be that
we'd hardly reach any people.
Sorry, I am very much
against applications .
I personally have found that the hoops
that people have to jump through to
download an application, to
keep that application updated,
and then their engagement
based on that is very low
and our approach is to use behaviors
and systems that are already being built.
Luckily we're using SMS
and we're using WhatsApp
and we're using other
things that are already
on people's phones to reach them.
I think that that is really the key
to being able to have
engagement and scale.
And applications sound like they're cheap.
In my experience applications
are very expensive.
And the reason for that is that
you have to be able to build applications
that work, if you're
talking to the majority
of the population, you're
not giving them a phone,
and you don't know what phone they have,
you have to keep it running
for so many different operating systems,
so many different versions
of those operating systems,
that the cost to do that
is actually very high.
So I'm sure that it's less linear.
So the one challenge with the SMS cost,
it's very linear.
As you have more people it costs more,
whereas you do have a bit of curve
when you're looking at
something like an application
where it does become more
cost effective over time
because it's not a linear relationship
between the cost of the application
and the cost of reaching each user.
But you do have to reach a very large
number of people for that
to become cost effective.
So I think that certainly the approach
that we're taking is try and use
more cost effective
systems, like WhatsApp,
for example, rather than
SMS to reduce those costs
rather than trying to build an application
that people have to download.
- Okay, who else?
Please.
- Thank you.
I'm Chandu Bodac.
I'm Co-Founder of Kerinext Innovations.
Just to brief and give the context,
we work with 300 plus health workers
who are using the app in India
and exactly we're working on the
same problem statement of improving
the dialogue between
community health workers
and the pregnant women.
So my question is open to everyone.
How do we basically generate the data
of this dialogue between these two people?
How do we quantify that?
And what are the techniques?
Maybe coming from behavioral science
you see how we can improve this dialogue.
I know this is not like,
it can be off session,
but some key points and we can follow up.
Thank you.
- Sure, there's the great
behavior science debate,
in some ways.
What works for whom
under what circumstances,
when, and toward what outcomes and why?
So in some cases it may be that
the face-to-face, the
actually communication.
One of the projects that come to mind
is healthcare in conversations where
we're really thinking about the
shared decision making piece,
facilitating a conversation between
the HCP and the patient.
So providing some facilitation
methods to the HCP
because they only have a
certain amount of time,
you can't change that.
That could be one avenue
that you could go down
but if you can optimize the time that
they have with the patient by providing...
And it doesn't have to be an app,
it doesn't have to be a portal.
It could be leave materials that have a
step-by-step way to
interact, ask questions,
ensure they're ticking the right boxes,
covering all the bases.
On the other side, you can also have
health interventions
that target the patient.
And that might be an app
but it might be a diary
then symptom monitoring
because it's sometimes
difficult to remember
how you felt last week.
But if you're tracking it as you go,
whether that's in a log book or an app,
you can go into your consultation and
have that conversation with
something in front of you,
and that's a lot easier.
That optimizes that conversation.
So there are many different
ways to go about it
but I think it's important we're thinking
both HCP and patient, how
to empower the patient,
as Peter was saying,
but also not overlooking
the HCP burden and potential burnout,
which is a huge problem.
So I'd love to talk to you in more detail.
- No, I don't have anything to add.
- Okay, that's easy, that's clear.
- I thought Debbie might actually.
- I mean we do start simple
and get more complex.
So starting simple maybe means
you structure a conversation.
So inexorably how it's
done with Mom Connect
but you do depending
on the gestational age
you have specific set questions,
then you create versions of that
for different types of
mothers or things like that,
and then you start putting in all this
fancy stuff like natural
language understanding,
and then you move into digital platforms.
So you kind of go like that but you
always have that skeleton there and
you can be testing it at every stage.
- One of the ways we're thinking about
how conversations can help relieve
the burden from healthcare workers
is they have a visit and then
they have another visit and there's
a lot of stuff that happens in between.
So if you can help to have an
engagement with the patient in between
the healthcare visits and lift the
burden from it being the health worker
who necessarily has to respond to that.
So perhaps decentralizing to
something like a help desk.
Then it means that when
the healthcare worker
comes the next time they don't have
a hundred questions to ask,
they have the very specific one where
they need to sit and discuss something.
Or perhaps we've given
them some information
around like you said, no this person said
now said they're hypertensive.
You can give them information in between.
So it's definitely not about replacing
the role of the healthcare worker,
I think that it's critical,
the healthcare worker
is absolutely critical, but
removing some of that burden.
And I think it's working with
the community health workers
and with the patients to understand
where technology can do that.
I have some ideas about it, of course,
but as you work with people and
you roll out your systems you'll learn
that there will be other ways that
both the community health
worker and the patient
will identify they could have a burden
lifted off them if they had
those kind of interventions.
- It sounds like you could carry on--
- Forever .
- Yeah, go ahead.
- Hi, John Lusby from
MySearch International.
We work in sexual reproductive health.
We're in the middle of trying to
automate some of our interventions.
And in the quest to save money have
looked at using healthcare providers
and digital phones to help
identify the patients.
And it's really raised
some questions for us
about data protection and privacy.
So I was just interested
from the panel to hear
in all three, four of your settings,
how are you thinking about that in
countries where maybe the regulations
aren't as strong but where you might
want to grow it into where it is stronger?
- I can start.
Brazil is next year passing a bunch
of legislation about regulation
and there's a lot of issues.
For instance, SMS in the United States
is not considered secure.
It can be hacked and things like that.
Obviously social networks
you have this adherence
but obviously I don't
know what Mark Zuckerberg
does with your health data.
In fact, it's an issue.
- It's terrifying.
- And then the issue you can have
a secure app but then you have
the whole issue of how are people
gonna actually download it and use it.
What we found is the easiest way
to do it is through consents.
So what you can do is
you can text with people
but they are just very, very clear
about what data are you gonna collect,
the risks involved.
And more often than not,
people will accept the risks
and will provide that data to you.
And then you do everything in terms of
best practices on your side to prevent
hacking and code
injections and DDOS attacks
and other things that could
potentially infiltrate your system.
- Yep, we found the same ting.
I think you need to be honest enough
for the consumers about what data
you're collecting and what you're
going to use with them.
We found our consumers,
and I'm talking about
low income slums people
living on $2 a day,
extremely sophisticated
at understanding of
you guys are gonna use my data
and monetize my data.
So we prefer to be upfront.
This is what the data we are collecting,
this is how it's going to be used.
Because their understanding
and sophistication
is moving very rapidly, very, very rapidly
so we have to keep pace with that.
- Yeah, I think I echo
what these guys said
and just make people very aware.
What we generally try to do is,
even if we're working in a country
that doesn't necessarily
have very sophisticated laws,
we basically look at the gold standard.
What's the highest level and try to
make sure that whatever country we're in
we're working around those
kinds of restrictions.
Because they're all catching up,
it's going to happen that you're going
to have something as strict as GDPR
in all of the countries
that you're working in
so you might as well aim for that.
I think it does bring
some technical challenges.
So for example things
like because we can't
pass data in South Africa between
South Africa and the US,
we can't do cloud hosting in AWS
so it has to be locally hosted and
that adds costs and it adds a
whole bunch of technical issues but
it's what has to be done.
And also we're gonna see changes
that are gonna mean that it isn't as hard.
That there are gonna
be more locally hosted
cloud services as the
demand for that increases,
then we can shift over to these
more sophisticated systems.
But in the meantime you have to take
some of those technical
steps to protect the data
and you also have to take the
user design approach of making sure
that your users absolutely understand
what you are going to be doing.
And in a way that is not, the one thing
that drives me nuts in South Africa is
we have this Protection of
Personal Information Act,
which is also a very sophisticated one.
They say that you have to make
the information available to people
to say what you're gonna use your data for
and they have to be able
to delete their data
and see what data you have,
all of these wonderful things.
But people make it only
available on a website
which is of absolutely no use to somebody
who has no access to that.
So I think you also have to think about
how do you do this in a way that's
very accessible to people and that's
not always easy.
Like on SMS and USSD to explain
all the data you have for people
is a little bit challenging but you
just have to do it if
you're operating ethically.
It will catch up with you if you're not .
- Take one last question.
- Sure, okay, one last one right there.
- Hi, really interesting discussion.
I wanted to ask, moving away from just
the healthcare relationship
between an individual
and their health or their
particular healthcare worker,
obviously it says in the
title community-based care.
I thought it was interesting
you mentioned earlier
the idea of touchpoints to
other points in the community.
I was wondering to what
point you might have
thought about the role of
other community structures
or organizations in terms
of sharing the burden
or spreading the burden of healthcare.
So whether that's communicating with local
community centers or community groups or
religious groups, whatever it is,
whether or not there's an expanded way
to connect to people's wider healthcare?
- So we are certainly trying to do that.
But also we are working
with healthcare clinics,
the stores,
the pharmacies, the individuals
in the families themselves,
the child centers over there.
The problem is everybody
moves at a different pace.
Everybody's in a different
stage of evolution.
Everybody has different things to do.
We hope to get to a point where
we show the value of this ecosystem
to all the different players and
eventually they'll come along.
So the reason we started first with the
stores is because
they had the lowest barrier
and the lowest resistance
so it's easier to move along with them.
But now having proven the value
of this approach to
them, it's easier for us
to have conversations with the
other players in the ecosystem.
We'll get to a point where there is a role
for everybody working together.
- Yes?
- I think it's very dependent,
for me certainly in the different
countries we've worked in,
and it's a lot about just tapping into
what already exists.
So in Nigeria there are very clear
community structures with village elders
and groups of people who
look after the community.
In Uganda there is what are called
village health teams who are an individual
who might just look after five households.
There's all kinds of different ones
and I think the important thing is not
to try and create something but
use the ones that happen
to be in the community,
which I think is what
Aakash has done so well
is identifying those and
then just leveraging them.
But I haven't certainly
seen a silver bullet
that it works in every
country or every setting.
It's about approaching
the design of your system
by first looking at what is available,
what are the touchpoints,
how can we involve them,
and adapting to each of
these different situations.
- I'd like to jump on that because
I think I'm gonna confirm a
slightly different perspective,
complementary, very complementary.
But community in the sense of not what we
might typically piece together.
A school organization
community, a youth center,
but more a behavioral phenotype.
So we may have a very
similar behavioral path
to quit smoking.
We might not know that but the way
we interact with a health intervention,
some of the data insights
we can draw from that may suggest
that actually we're quite similar.
So we can think of rather than
individualized health interventions
as subgroup interventions in a similar way
to community-based behavioral phenotypes.
So things that we can't necessarily see
right now or may pinpoint
to an environment
or a cultural setting but come through
from the data that we're collecting
from those insights.
- Good one.
- Quickly.
- There's still another panel.
So thank you so much.
That was a great far-ranging panel
talking about really using technology
to bridge the gap where there are
not enough health workers.
From AI chatbots through to bringing in
non-traditional health workers like
owners.
Our next panel starts to talk about
where there is a health workforce,
how do we use technology to make
that workforce more effective?
So this time we have our moderator,
Ari Johnson, who's coming from Muso.
Thank you so much, Ari.
We have Josh Nesbit from
Medic Mobile who's joining us.
Tali, I've got to get
your last name, Ayyangar,
from Datakind.
And also Matt Berg from Ona.
Come and join us.
- Here we go, all right.
Hey everybody, can you hear me?
All right, at the end of the day,
big week but we've got an incredible panel
of folks here with a lot of experience
to share with us and from
three extraordinary organizations.
We're talking today about how
we can work together and how we
can harness the power of technology
to enhance the work, the
incredibly important work
of community health workers.
So I want to start with
Matt in this conversation.
I'm going to ask a question
to each of the panelists
and we're going to
start a conversation and
then we're really going to open it up.
I want to hear from the rich experience
that's in this room.
So Matt, Ona does really important work.
Rather than displacing or replacing
community health workers,
really to enhance and support
their important work.
So tell me how does that work?
How do you do it?
- Sure.
To be honest, we're actually really new
working with CHWs but we have been
working in the digital health space
for a long time, more focused on
facility-based service delivery.
And I'll talk bout a
project related to that too.
We're really focused on this idea of
how do we ensure equitable
access to services.
So when we're talking about service,
it really breaks down
to three key components.
One is are services
accessible where people live?
Can we get those services to people and
CHW is one of the ways
that happens, obviously.
Can we improve quality of care?
Ensure that if you have access to service
it actually helps you,
because that's not a given.
And third, which is I
think one of the ones
that we don't really talk about enough
is that service affordable?
Once that person, or
can this health system
afford delivering that service.
So the affordability issue.
So those are the three areas that
we've been thinking about the problem.
We've been working actually not
with CHWs but in the area
of malaria elimination
with the IRS, so indoor residual spraying,
for the last five years
with a group called
Akcros in Zambia.
IRS basically said that you have to go
household to household and spray
insecticide on walls and the idea is
if you can spray enough homes in an area
you can reduce the
vector in that community
and then hopefully move
towards elimination.
So you don't do this in Ivory Coast
or in Mali where there's really,
really high malaria rates.
You do it more in areas
where you can potentially
move towards elimination.
So Southern Africa's a big area.
So this is in Zambia where we're working.
What we've done is in the last five years
we've had access now to high resolution
satellite imagery.
So we can start to using humans right now
identifying structures where people live.
So basically start to create a map
of where we know people are.
One of the big issues in
healthcare service delivery
is that we count what we do, what we see.
We don't actually measure
what is actually out there.
I call it a Main Street problem.
You walk down Main Street, you count
the homes you visit, you don't count
the people that live
behind the garbage patch.
Even in every community
there's a lot of disparity.
So having this kind of map where we see
where people live, we can then start
to target services for that.
So with the IRS work we've actually
developed an approach where we can
give the health worker, in this case,
it's an IRS spray team,
the ability to see a
map of where they're at
and all the different
structures on that map
and then click on the
house where they're at
and then they mark it as sprayed or not.
Or they can mark it as a non-residential.
So it's like this is a kitchen
or it's a commercial shop
or we can mark it as refused.
So as we're going along we're basically
painting for that community,
filling in coverage for that
day for service delivery.
In IRS that's really critical because
if you don't get to 85%
coverage in that area
you basically leave enough vector
for resistance to come back.
And one of the thing that Bill Gates
and PMIers really worried about is
resistance in these areas
to these insecticides
because they're not IRS programs that are
not being done effectively.
Anyway, I'm rambling a bit but we're
able to basically go
from 50% to 60% coverage,
which PMI is getting,
Presidential Million Initiative,
to like over 85% consistently and
also getting post-event coverage surveys
within 1% accuracy.
So it really is really effective.
So we know now that using technology
we can guide a health
worker to a specific place.
And now we have a grant through Gates
to develop this out in
a platform called Reveal
to broaden it for other
types of campaigns.
So for the campaigns I think this
is an obvious application
whether it's immunization, polio, IRS,
bandaid distribution and things like that,
that's drug administration.
So we also work in,
we want to think how do we actually
bring this to more not campaigns but
routine healthcare service delivery?
In looking at that one of
the big areas is analytics.
So Medic and Muso have
done some really great work
around how do we use data to
monitor health worker performance.
So I think really the biggest
challenge we're facing
is we're all slugging it
out over CHWs right now,
which is kind of dumb because really
it's like I tell people
we're just building
the picks and shovels right now.
Managing the data is gonna
be the hugest task we have
because these health workers
are not data scientists,
their managers are certainly
not data scientists.
So how do we identify
risks in populations?
How do we prioritize visits?
How do we manage health workforces?
These are all big data
issues that we have to face.
But the problem in all this is
we also need a mechanism for action.
That is what we call the task.
In building this IRS
approach we actually realized
if we can send a person to a place,
that's a tasking data model.
So you have a health event,
you have the analysis, and then
you have the task to tell them
to do the next health event.
So forms are really nice kind of...
Amazon is called the spin
wheel or fly wheel, sorry,
you kind of get that momentum going.
So that's the idea of the tasking.
So we've been working now with
support from J&J to look at how
can we take what we've done at IRS
and apply it to routine
to CHW health workers?
So we're looking at a couple of things.
First of all is can we just guide,
can we improve prioritization?
We have a research partner
in Bangladesh that has
10 years of historical data
on all of their clients.
Can we just better identify
the high risk cases
and make sure that at
the beginning of the day
that map has a couple of green spots
that they have to visit?
After that, let them do what they want.
Let's make sure that those visits happen.
So that's kind of one.
Using that similar approach,
can we ensure coverage.
Can we make sure that
in some kind of schedule
all the different areas are visited?
Can we paint that map in a similar way?
That's the second piece
that I think effective.
Second is can with optimize?
CHW programs are, I think we bring in
a lot of paper and archetypes in how
we think about that.
So basically I'm on this side of the road,
you're on that side of the road.
If your CHW gets sick or gets married
or goes on vacation, the people on
that side of the road may be
dropped for a period of time.
UPS doesn't work like that so
if we can start to task we can
start routing health workers to
cover each other's territory
and work in an optimal way
just like any kind of
logistics company does.
So can we bring logistics
or Uber or TaskRabbit
or whatever analogy you want to use
to whatever the donor is to do that?
That's an, I think, exciting
idea that we want to test.
The third idea, which actually is I think
the one which I'm most excited about is
the idea of task shifting.
So it doesn't have to be about
sending a person to a physical location.
It can also be about shifting the work
off the health worker that
already has a lot to do.
And I think of my mom.
My mom's a retired teacher.
If she was living in a village in Africa
and she had a smartphone,
which is probably gonna be the case,
why can't she do the follow up visit
on the sick child just
to do that check up?
If we had the ability of
tasking the orchestration,
we could say hey CHW,
you don't need to do it.
We're gonna assign this
auntie who lives nearby
to do that visit.
Or most likely we'll just have the family
themselves just tell us how
the kid's doing and respond.
I'm sorry, I'm taking
too much time really.
So that's the last bit in
terms of task shifting,
I think it's a big idea.
Relatedly, we're also
looking at how this can
be used for a big problem in any kind of
service delivery coverage estimates.
We rely on these mix and DHS surveys,
which are terrible.
You can ask any nurse in a facility
what the coverage rate is, 90%, awesome.
Of course they're not gonna get out and go
because they think they're doing great.
So this will give us can we use
spatial sampling modeling and
start to tell CHWs to fill in the gaps
to fill models to build
real-time estimates of coverage
and make sure we're also not
missing people on that map.
So thanks, sorry.
- Fantastic, thanks Matt.
So Matt just brought up that we need to
be making more data-driven decisions
and that's what our patients deserve
is a health system that
holds itself accountable
to doing data-driven work.
So given that, there's a challenge.
A lot of folks engaging in this
and making decisions,
whether they're technology
developers or whether
they're policymakers,
they're looking at data in aggregate
at maybe a national
level or a regional level
and they're not seeing the realities
of the patient and they're not seeing
the realities of the
community health worker.
Now turning to Josh, Medic
Mobile is working to change that.
And I'd love for you to share with us
the kind of design work that Medic Mobile
has been working on.
How are you working to
design for the patient
and design for and with the
community health worker?
- Yeah, thanks.
First of all, Matt, I don't think
you went too long at all and we could
totally work together
on five of those ideas.
- We're being funded also to orchestrate
so the tasking goes across platforms.
Just think of it as an
orchestration brain.
- Awesome, right on.
Right on, no, that's awesome.
- She made me do it.
- Thanks, sorry.
Where I have to start is that we are
standing on the shoulders and next to
people who are
accomplishing amazing things
in global health right now.
I'm looking at the room and I know
the role that a lot of you are playing
and I'm sitting next to
Ari and Matt and others.
There's a handful of organizations
and health systems that are achieving
outlier results for the
poorest people on the planet
and we all are, and I
think many of us are,
we should be paying attention.
The cheat sheet for
how they are doing that
is at CHWImpact.org.
You can also see it
reflected in the latest
WHO guidelines on
community health systems.
So that's all really, it's all happened
relatively recently and I think it's
on us to pay attention.
And there are principles in how
those systems are designed.
The thing I want to say
as a follow on to that
is that I know a lot
of those organizations,
we know a lot of those health systems,
there's also a relatively shared process
and it boils down to patient-centered
or human-centered design
and a focus on equity.
It is the big idea that everyone
deserves great healthcare
and deserves to live
the life they want to.
And that is a pretty radical idea and
I think technologists should take it up.
We have IDO, we have all
these very fancy tools
and frameworks but it signals to this
core idea so I guess what I would say
is that the process for us has started
standing alongside patients and their
family members and the experience
of having your health protected, secured,
and living the life you want to.
My mom's a physical therapist so
I really want to include all the
very practical things
like walking to church
that you want to be
able to do as a person.
That's really what we're designing for.
And if we start from that and
let's say you're in a well-designed system
you're gonna look over the shoulder
of that patient and you're gonna see
an accredited Community Health Worker.
That person is related to that family
probably and one form or another in
degree of separation,
they care about them.
And they have their own problems,
they have their own things
that they need to solve for,
and if we can successfully accompany them
and solve problems that
they're really facing,
we're on our way to a functioning system.
If you look over their shoulder,
you see a supervisor who again,
if you're in a great system, is showing up
in that village to do rounds with the CHW.
They have their own problems and
their own challenges.
We can bring technology
to help solve for it.
And I guess overall what we have learned
is that technology only can expand
to the space given to it by system design.
Having a sense of what's
possible with the tech
can help stretch the vision for the system
and what might be accomplished
with and for that family.
But it is not the intervention,
it is not the solution.
I guess maybe that's one
of our biggest learnings.
- And as Medic Mobile is working
in collaboration with many
other partners in the space
really toward this bigger mission.
This mission of having
this kind of software
and these kinds of tools
available for everyone.
And that's what the
three organizations here
are working to and many
organizations in the room,
working together on this.
And the Community Health
Toolkit is a big new initiative
getting driven forward, just launched,
to try to help make this happen.
So how is the Community
Health Toolkit working
toward making this kind of
software accessible to everyone?
What are the challenges along
the way that you're facing?
What's it going to take
and what's also the role
of transparency in making it happen?
- Yeah, thanks for that prompt.
I'm reflecting on who's up here and
all the panels we've been on and
the questions that we often get
and I'd say maybe one out of
every two meetings that we have
someone raises their hand and says
when is Google gonna solve this problem?
When is Facebook gonna solve--
- They literally do I think.
- They do.
Every single meeting, and they're not.
They're not going to.
They're massive market failures
in healthcare, it turns out.
That relates directly to what companies
do and don't build and
who gets these tools,
where the locus of power is.
So I think it's sort
of on us to do things,
in a weird way, and to do
things a bit differently.
And for Medic, we looked at this
and we said, we made the decision
to take all of our assets,
basically everything we had
built for over a decade,
and move it out from under
our organizational umbrella
and into the public domain.
And just try to start
creating and contributing
to public goods and not private goods.
That then has sort of knock on effects
where it's then on us
to distribute expertise
rather than consolidate
it or centralize it.
Again, not what a tech company does.
It's a terrible idea to do that.
But I think if we can do that,
and I'm sort of looking at all of us,
if we can do that, then
it brings people closer.
First and foremost, I hope it brings
the people up here closer
and then I think has ripple out effects.
So public good not private
good is where we're headed.
- And I wanted to come back to this idea
of collaboration in a minute.
It's so powerful and
important at this time.
And particularly as we think of
the community health
workers we're all here
to support and stand behind.
They are sitting and they are working
and fighting and struggling at the heart
of the communities that we
serve on the front lines.
Tali, I want to hear from you.
I'm so curious to learn more about how
Datakind is partnering with
community health workers
to remove barriers using big data
to remove barriers to access
to care in the community.
Tell us more about that?
- Thank you, Ari for that question.
And also thank you, by the way, J&J
for the opportunity for
me on behalf of Datakind
to be here on this panel
because I'm a little bit
surrounded by my heroes at the moment .
Ari, I think before I
answer your question,
just looking around the room as well
and so many of the people here actually
your organizations are the ones
that are actually on the front lines
supporting the community health workers
to reach patients and change lives
and directly impact lives.
Save lives, to be honest.
So before I answer I just want to say
where Datakind fits into this
sort of larger ecosystem.
Datakind is a global non-profit
and it's raison d'etre, if you want,
is to actually support the impact of
high impact organizations like the ones
you all are leading.
So in that sort of framework,
the way Datakind works to
support community health workers
really is to guide, at
the core of our work
is to guide data science,
machine learning,
and AI expertise to organizations.
These are organizations, for instance,
if you imagine you're at the cusp of
taking a solution that has been tried,
that has been tested, and
you know it to be true
and maybe you want to scale this.
That's just one example
of where that sort of
expertise might be relevant.
Sorry, just to clarify, the expertise
is actually pro bono.
The way that actually works is
we have a huge network of
over 20,000 volunteers,
experts really, right from academia,
from your MITs, your Princetons, and IITs
around the world to
industry, your Spotify,
Netflix, Amazon, and Microsoft.
But also a bunch of
self-taught geniuses really
who are all willing to offer their time
in order to work with organizations
in the hopes that they
can use their superpowers
to make an impact.
So you have a really
motivated group of people
from around the world who are in
those traditional tech
industries in the private sector
who are looking to also see what
are the possibilities out there.
So when Datakind partners
with an organization,
there's an opportunity to match
the right sort of expertise
to that organization's needs.
But those organization's needs,
identifying those needs
is I think something
that's very core to our process.
And absolutely what you were saying, Josh,
that really fundamentally we,
the data scientists, the
machine learning experts,
we humbly accept we're not
the experts in the field.
We're not the boots on the ground,
we're not the eyes, we're not the ears,
and we're certainly not the voices.
So in order to have that partnership
really work to identify some key problems,
what's really holding an organization back
from scaling that solution
that's known to work?
Maybe even what's the
problem behind the problem?
Can we have an honest conversation.
So we try to design the space when
we partner with an organization that
we really identify the core issues,
the core motivations as well.
What's driving you?
So that ultimately when we articulate
a problem statement we are in a position
to actually co-create the solution.
Datakind's been around
for about eight years now
and 250 plus projects later I think
the key lesson we've learned is that
when those solutions get co-created,
then they actually get
embedded in the organization's
processes or in their operations.
And that has basically become
a metric of success for us.
So whether you're working with CHWs,
whether you're sending SMS texts,
ultimately how can the expertise around
just help you?
Is there help?
That's our approach,
can we help you please?
We'd love to help.
But looking ahead little bit,
Datakind's also been doing this model
where we work with one
organization on a project
and we deliver an outcome and a solution
and then that's there.
But I think keeping in with the theme
of the forum here, I think
we're looking at a stage now
where when you said, Josh,
we should all be working together as well.
Indeed, what are the opportunities
to accelerate the possibilities
for the sector at large?
And this is where now I think our
core focus is going to be on that.
Yes, it's going to take big data.
Yes, it's going to take some analytics.
But maybe not.
It depends on how we
define the problem together
and it depends on what solution
is really going to make the most impact.
So I think, yeah.
- Thank you, Tali.
So all three of you
have called out the need
and vital importance for more
collaboration and the space.
I love that.
And we know, we know, we all know
that the tech space is
incredibly fragmented right now,
devastatingly fragmented.
It is a graveyard of fragmentation.
So what is it going to take?
What are the barriers in the way?
Why is it still this way?
What are the barriers to actually getting
real collaboration happening between
organizations working to develop
new tools and technologies?
And also most importantly with
our government partners who are sovereign
in leading the charge for their nations
to make this big change happen.
So how do we, what are the barriers
to getting collaboration right?
And how do we overcome them
with government and with each other?
I'm gonna start with you, Matt.
- As a technologist and thinking at it
from a systems perspective
I'm actually super optimistic
because we're still working on that
20% of the original problem,
which is the client piece.
And honestly I think the
closer you are to the client,
I think there's a lot more room for
customization, localization,
there's gonna be...
Maybe I have more support
but I don't want to
disrupt the local Cote d'Ivoire company
that's built something and it's great.
If they'd like to use
it, let 'em use that.
But if you go up the chain,
especially around data
and standardization,
that's where things get a lot harder
and I think that's where
specialization comes in.
And there's a huge opportunity
for us to coordinate there.
So just one quick example, I'm part of
some working groups at
WHO that are creating
how do we standardize clinical guidelines
in a way that can be
deployed across applications?
And is consistent.
So how do I replicate?
How can WHO publish an ANC protocol
in a way that they can
guarantee different apps
build it?
Because if you look right now,
everybody's re-building ANSI.
There's 80 million flavors,
it's like Baskin Robbins or whatever.
Which is fine but if you want to
create a common analytics
platform for that,
if Datakind wants to be able to
compare across countries
what that data actually means
you have to have standardization.
So there's this thing called,
without getting too technical,
a thing called Fire, which
is basically based off HL7.
It's a way of representing,
it's a data exchange
to exchanging health data but it's also
a way of representing
a data model in health.
And one of the outcomes we're thinking is
can we, as a community,
just like we have this
form authoring around X
forms, unite around profiles,
which is basically
agreeing on a use of Fire
to represent common
primary healthcare things?
So basically in English, can I represent
an ANC visit in a standardized
way in a data model?
Or an immunization visit
or a postnatal care visit.
If my system could output that
data in that common format
and Fire makes this all really possible
then I don't really care
if you're using Medic
or OpenSRP or ComCare, whatever,
because it's all going into
the same shared health record
and interoperability...
I know it sounds magical but it actually
does make that kind of possible.
But more importantly allows the Datakind
or another group to specialize
on just that issue of the data analysis
and be agnostic to the client.
Because right now we're so coupled to
all the way own to the end use.
So that's just one example that
if governments can endorse,
use whatever you want
but your app has to follow
this WHO-endorsed profile
and we all sign off to use that profile
then we start solving problems for people
that we create in a way.
- Right on and I couldn't agree more.
I think in a way I feel
like I failed to get,
I'm just looking around,
people in this room and not in this room
excited enough about that.
You might say Fired up.
- Fire is gonna be a big word.
- But I think either
organizations like ours
get supported to work towards that vision
or it gets way worse.
So it feels like we're at that moment.
- Fantastic, Tali.
- I'll take a slightly different approach
to that answer just because I can't speak
with much authority about
interoperability of data or Fire.
But I think one of things that when
you were asking that question
that sort of got to me is,
I've learned some of these nuggets,
by the way over the past few days
at this Skoll World Forum.
I was at a workshop with Molago,
that Molago was running and
they were actually saying
that there's a role that
technology has to play
in actually creating fidelity around
your solutions when you're scaling them up
and working with partners,
if you're not the one scaling
up your own solutions,
and you're actually going
to work with other partners,
maybe with governments.
So there is that role that the
technology can play in building that.
And I think that there is a sense then
that you also, in order to
have a good collaboration,
you also can ease the path and
ease the way towards that collaboration
using technology.
Joshua, you seem to be nodding.
I think maybe you can articulate better
what I'm trying to say.
- Right on.
- So there's that part.
An then the second thing is also
Datakind's model is
essentially working with
organizations and other impact partners.
So collaboration at that level as well
fundamentally relies on
a foundation of trust.
And I think there is a,
and I know this might
sound really obvious,
and you mentioned Ideas did another
talk earlier and they were just like
well the foundation for
that is actually listening.
That sounds really simple but it seems
to be a critical step most of us miss.
So building that space to understand
the needs and the solutions and
are they actually matching up together
is something that we take to heart
at Datakind and in our own engagement
with our partners in
order to create that stage
to co-create solutions.
- Yes, fantastic.
- 10 seconds?
- Yes.
- Just to add very, I totally agree
but someone said two words that
I think will stick with me,
that there is this invisible mesh
that exists across organizations.
People are trying to learn stuff together
and that exist in
community health right now
and we need to support it
and it's all sweat equity
and it's all extra hours.
And there's not a learning officer who's
talking to other learning
officers anywhere
and that feels insane to me.
I feel like there's enough organizational
and country level buy-in but
just not enough support for that mesh.
- So collaboration takes sweat equity
and it takes real equity to make it real.
So before I kick it out
to our community here
for more questions, I've one more question
for our panelists here.
I wanted us to finish talking about power.
Because in the health
systems where we serve,
the folks who have the most responsibility
to make change, the ones on the front line
who we have to stand behind,
our community health workers
and midwives and nurses,
are often the ones vested
with the least power
to make change in the system.
So what role can technology play in
transferring and shifting
the balance of power?
And this is for any of our panelists.
How do we make that happen?
- Well who has the most
power in your opinion?
- Mmm.
- So I have one.
Affordability I think,
we have to unlock new ways
of financing healthcare
and I think a big part of that
is verification that services happen.
I think for the most part,
I brought up fraud earlier.
I think for the most part health workers
and nurses get far less credit
for all the work they do
and health systems are not accountable
to the work that they do.
So one of the really
thing that's happening
on the technology side
is within the next year,
biometrics, whether it's they're using
your face, your palm, or your finger
using just a camera phone
is gonna be come ubiquitous.
It's already available
and you're gonna start
seeing it introduced in health
apps over the next year.
If we mirror that with a health platform,
it becomes not just a health delivery tool
but a health service verification tool.
We can prove that the
woman was present for care.
So we can create a
digital signature saying
yes, proof happened.
What that'll do is that will then
create a system where
performance-based financing,
where insurance and all that can
enable better accountability and then
funding of health services, I hope.
But I think that gives power though
to the women that are doing and the men
that do a lot of work they
don't get credit for it.
And basically a voice saying,
actually we're doing this.
Here's the proof.
Let's hold the government
accountable now to our work.
And I think donors can
then hold the government
accountable for getting them paid
and all of those things I think.
But we lack that
accountability at the bottom
that I think makes it easy
to scapegoat health workers.
- So verification is accountability,
accountability is power?
- Yeah.
- Yeah?
All right, I like it, I like it.
Any other thoughts on this
before we kick it out?
- Yeah, I think one of the things about
power or empowerment is
about recognizing agency.
So I think the work that so many
of your organizations are doing,
the effort is indeed to realize and
actualize the agency of the
community health worker.
It's about also, an agency to want
agencies to make informed decisions,
not only about the care of their patients
but very much about themselves as well.
So I think tech can play a role certainly
but I think just intentionality
is a part of it as well.
Intentionality in design,
intentionality in creating
the solutions that
actually augment the agency
of that community health worker,
recognize that health worker has not only
the data that you're offering but
in that environment has
a very good understanding
of the other dynamics that are
going on in that community.
Whether it is to do with
dynamics within a household.
Yes, you want to get
that mum to the clinic
but is mum the best person to go
and talk to at the
moment given the dynamics
going on within the household?
Maybe we need to talk to mum in law
or maybe we need to talk to the husband.
So that kind of very fine,
and I think this is related
to the first panel as well,
there's some information
that's just very intangible,
very hard to get.
But I think community health
workers deeply understand
what is going to create
a change in behavior
or what might instigate
a certain behavior.
And I think that there's a marriage there
that's super valuable to augmenting.
- So we need to design
with that goal in mind.
- Absolutely.
- Fantastic.
Josh, you get the last word on this.
- What I'd say in a sentence is that
the community health workers that I know
are doing everything in their power
to care for their neighbors.
So maybe we should give them more of it
is what I would say.
- Absolutely.
Great, thank you, Josh.
All right, let's bring it out to
questions from the audience.
- [Woman] Thank you all.
Would love to hear what
is the little thing
that's lurking at the edge of your mind
and your consciousness in
the next 18 to 24 months
that this is something that is lurking
that could just dramatically
change the landscape
from a technology
perspective, in particular?
What is that thing that
is at the very edge
of your consciousness that
you're kind of thinking
this could become an issue?
- Sorry, I didn't get your name.
- [Woman] Oh, hi, I'm Kiah.
I'm the Co-Founder of Serum.
I work in healthcare in the United States.
Other thought is how do you rrevent,
this as a question specific to Matt,
I'll give you the second one.
How do you ensure interoperability of data
and prevent systems like we have in the US
where there is a lack of
interoperability of data
and thus transitioning between
different health platforms
is basically impossible?
- I think the first question you asked
was really cool because
lots of possibilities.
I'm thinking more when you say what's
at the fringes, I'm
actually thinking about
the possibilities in
the most positive sense
because one of the things
that from Datakind's
perspective, like I mentioned earlier,
we were doing these individual projects
to really supercharge the impact of
individual organizations but we've seen
so much momentum in this space,
in the community health workspace,
where organizations are
really partnering up.
They're really sitting there and
figuring out things like
interoperability of data.
But more than that it's also
I think for Datakind we're looking for
in the next 12 to 18 months is
some key engagements with partners
who will help us articulate those barriers
where data plays a role.
Where we can really use data science
and machine learning to
supercharge a solution
because the likelihood is that many other
organizations in the sector
are facing similar problems.
So the optimist view, I'll
say realistic optimistic view,
is that through those key engagements,
once we sort of nugget those
key problems and barriers
and maybe even create some
prototypes and solutions,
then other organizations who may not be in
the immediate learning group or cohort
may benefit from that.
Because you create a
prototype, especially one
that's been guided by folks.
If I imagine working
with Ona and Medic Mobile
and Muso, the kind of insight
that we're going to get
is just going to definitely
benefit the sector
as a whole, whether you
take it as a solution itself
that can be directly replicated or
maybe prototyped to inspire you.
Because if you don't know
what you're looking for,
prototypes kind of inspire
the imagination as well.
Or just learnings as well.
A fabulous opportunity
I think at the moment
with all the groups around in this room.
- Fantastic and that relates
to the question for Matt
about interoperability.
With the opportunity
lurking on the sidelines
much more sharing and collaboration
and the more rapid spread of good changes.
What's it going to take to
build that underbelly of it?
- I want to answer the
first question first.
I think on of the biggest things that's
really gonna happen in
the next 18 to 24 months
is buy-in.
I'm actually looking at Ari and with Muso
they painstakingly built up in Mali,
I used to live in Mali
so it means a lot to me,
evidence that this actually works.
And to a point were the government
is committed now to adopting CHW systems,
not as an NGO thing but
as a government thing.
And if you don't get government support...
So I think that's a change.
And I hope, I think
that if Mali can do it,
other countries will do it.
So I think that's a big
thing that we need to,
so first of all, Ari,
that's really amazing.
And second, I think that's really gonna
set the model for other countries.
So I think that that's a really big thing.
We're lucky in terms
of the interoperability
that it's pretty green acre.
What's it called green field, whatever?
In that there's not a
lot of systems in place
so there's a lot less to deal with.
But I'm also really, really
big into working standards.
So not going to some ISO
committee and voting on it
at some WHO meeting.
It's about hey Josh, come on dude,
let's get our stuff talking.
Let's agree on what
immunization register looks like
and let's just commit
to doing it together.
And we've seen this in the
mobile data collection community
around ODK and there's an
underlying X form technology.
And everybody now in the space uses it.
SLS forms, all these basic things.
That creates so much value.
We have to do the same thing now,
it's just working standards,
it's not ISO standards or whatever.
- Right on, I so agree.
And Kiah, thanks for the question.
I'll just add
- Please.
- briefly I mean there's
the looming question
of China's involvement and
deals with African governments
I'd say.
There's also for me all these
community health strategies
being written or re-written
and an open question
of whether or not those health systems
will be designed to deliver
or designed to fail.
I'm putting it in stark terms but
the design will constrain
what tools you can use.
So I think it's the biggest
thing that will affect
all of the technologists.
- Fantastic.
Other questions?
All right.
Well, thank you to our amazing panelists.
We're gonna work to shift the power.
We're gonna work to
collaborate and partner hard
and we're gonna bring the field forward.
Thank you so much.
Thanks to everyone for coming.
