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The podcast delves into the realm of health tech, highlighting a common trend: a focus primarily on the US, EU, and UK. However, it advocates for a broader perspective, urging listeners to look beyond this bubble and consider the innovations happening in low- and middle-income countries (LMICs). These regions face significant digital and non-digital healthcare challenges, leading to inventive solutions borne out of necessity. By exploring the work of those in LMICs, the podcast aims to uncover valuable lessons from their successes and obstacles.
Hosted by Shubs Upadhyay, a primary care physician with a wealth of experience spanning clinical practice, innovation, regulation and medical software engineering quality, the podcast offers a unique viewpoint. Through this lens, it reveals a stark disparity between technological advancements and their impact on underserved populations. With a focus on spotlighting individuals and organizations making a real impact in these communities, the podcast invites listeners to join the journey of discovery.
Shubs Upadhyay (00:00)
Welcome to the latest episode of the Global Perspectives on Digital Health podcast. I'm your host Shubs Upadhyay physician working in digital health So far we've had perspectives from Brazil, South Africa, from Eswatini and now we
and travel across the Indian Ocean to get perspective from the context of India. I recently moderated a panel around universal health coverage, comparing and contrasting implementation impact from the NHS and India. And so I'm particularly interested in diving much, much deeper into this. I'm going to be talking to Ruchit Nagar.
He is the founder of Khushi Baby, who've been working for the last 10 years, implementing technology that supports community health workers and their impact on the last mile of health in villages in rural India. There's a lot to learn for anyone building in this space. And we're also going to be getting
some of the challenges that they faced as well that are going to be helpful for us all to to unpack and learn from. So you're building, researching or investing in this context or in a similar context, you'll find this one really valuable.
Shubs Upadhyay (01:19)
Ruchit, welcome to the Global Perspectives on Digital Health podcast. It's an absolute pleasure to have you on the show and the first insights we have from the Indian context. Thanks for taking the time to join me.
Ruchit Nagar (01:29)
Thanks for having me, Shubs. Really appreciate it.
Shubs Upadhyay (01:31)
Okay, so why don't we go into learning a bit about yourself, Ruchit and how Khushi Baby was born.
Ruchit Nagar (01:38)
Yeah, no. So, Khushi Baby this year is turning 10. And it's a big year for us, but we were born a decade ago in a class project. So, I was an undergraduate student at Yale and the class was set up as a design course. The first day of class, they gave us a challenge statement that a million and a half children under the age of five are dying from vaccine preventable disease.
And it was our job to come up with a solution and business plan to take that solution out of the classroom and into the field. And then we went through a whole course of understanding design thinking frameworks, human centered design, and the whole iterative approach towards studying a landscape, identifying opportunity spaces, coming up with rapid prototypes, speaking to users on the ground.
Ultimately, we ended up focusing on data and accountability and working towards building a digital health tool to better track vaccine records in low resource settings, and especially in offline settings. And the initial concept that came out was a mobile application for a community health worker and a portable, wearable, NFC-based digital health record for the person receiving the vaccines.
the family. And that was connected with an NGO that was working in Rajasthan, India, that was already giving services to areas that the government couldn't reach. But it was tracking everything on paper and they were open to experiments. In fact, it's the same NGO, Seva Mandir, that had done the seminal work with Esther Duflo and Abhijit Banerjee that they talk about in their book.
Poor Economics, where they studied whether or not giving lentils as an incentive could help improve immunization rates in that same area. So they had a precedent for doing research. They had a real need to better track the services they were providing. And then we were coming up with solution. It was interesting that our team actually had no developers or computer scientists on our randomly assorted initial team.
We were using open source tools like MIT App Inventor to code up a demo application. We ended up eventually applying for some funding on campus, getting that initial investment, and then setting up as a nonprofit organization. I sent 40 emails, cold emails, to local professors in Rajasthan to see if somebody could help guide us.
One professor replied with their doctoral student at the time who was interested in mobile health. And that person, Shahnawaz has been with us as the co-founder ever since and is now the chief operating officer. So would say it was a very serendipitous start. And it took us to India,
The thing that I take away is that it can really start from anywhere. mean, in this case, it started from a class project, collaboration, students who were interested in public health and design, getting together and trying to, you you have to have a little bit of reckless abandon, you have to be a little bit naive to start to even approach such complex problems. And then the maturity comes over the next 10 years when you figure out how difficult those problems actually are.
So that's kind of how it all really started.
Shubs Upadhyay (05:10)
OK, Can we just go into the problem that you've touched on in terms of the problems with immunization, the problems that community health workers have. Can you just paint a picture of the on the ground problem that was faced, both I guess on the community health worker and the health care delivery side, but also for like villagers and families who were kind of receiving this health care or in some cases not,
Ruchit Nagar (05:32)
Yes. So when it comes to like what it actually looks like for, you know, people in these rural communities to receive access to health care, India has a decentralized health care delivery system. Every village has a locally elected community health worker. Every month, a nurse comes to each village and she's responsible for four or five villages.
And she conducts, with the help of that community health worker known as ASHA a maternal and child health and nutrition camp in which she will screen pregnant mothers for common conditions. She will give infants and toddlers their vaccines and track their growth and development. now whenever any mother, pregnant woman or child is sick,
they are referred from that screening camp to the primary health center where a doctor may be available and then where they may be further referred to the district hospital. in a way, ever since 2005, when this national rural health mission started, India has had a very structured approach to ensuring that services have a way to, there's at least a structure through which services can flow. However, the challenges still remain.
that you need to have the right people. So even in the hardest to reach areas, you may not have nurses that want to deploy, for example. You need to have the right facilities and supplies. You need to have the right training for the personnel. You need to have the right data systems to understand what's going on. And that's all just on the supply side. And on the demand side, you're dealing with low levels of literacy.
Before we even get to health literacy, we have low levels of literacy in general, then health literacy, high levels of multi-dimensional poverty. You have families that have migrant laborers. The families themselves are not living together as a unit. You have multiple kids in the household. Distance to the nearest facility takes a long time. So you have an awareness and sociocultural factors that are also at play.
Both demand side and supply side factors make completing the full recommended health journey difficult, right? Even if the services are all free. So what it takes to deliver a vaccine to a child, a vaccine carrier has to wake up early in the morning, go to the vaccine stock supply, bring the vaccine carrier to a more rural outpost that the nurse can then pick up. Meanwhile, in the village, the community health worker is going door to door and trying to
Shubs Upadhyay (07:53)
Mm-hmm.
Ruchit Nagar (08:12)
make people aware that today there is a health camp and you need to bring the pregnant women and the young infants to the camp. And then the health worker finally comes, the beneficiaries finally come, and the health worker is carrying we still see this today, 10 different registers for different programs that they're responsible for, flipping through, trying to identify the patient, trying to update the records on paper.
and then trying to make sure that they're giving the right medicine, the right vaccine to that beneficiary who's in front of them. So that process is incredibly taxing and time-taking. And that process still continues today. The thing that has changed over the last five years, I would say, is that in addition to those 10 registries, you now have 10 apps in your phone. So while before it wasn't
really imagined that, ASHA workers would be using smartphones, digital literacy has improved. There has been a, definitely a sea change in that, but the work burden has only increased. And we surveyed ASHAs in Rajasthan, for example, the majority are saying that they spend 45 to 50 hours a month on data reporting related tasks. That's compiling the initial data, tabulating it into summary statistics.
getting the required photocopies, traveling to the primary health center, sitting with the data entry operator, in some cases needing to give a cut of their incentive to the data entry operator or the supervisor. And ultimately that whole convoluted series of steps takes 50 hours of their time that they could be spending with their family or with a high risk.
pregnant women or visiting a newborn child or giving other services within their community. And there's over a million ASHAs across India. So the world's largest decentralized community health workforce is spending I mean, we're estimating here, but could be spending up to 50 million hours or more on all these, I would say low yield reporting based tasks that could easily be automated with the tools that they're already using.
Shubs Upadhyay (10:11)
you
Ruchit Nagar (10:19)
if we're just able to intelligently design that system. And then the other question is like, what are we really incentivizing? Do they feel intrinsically motivated by the data that they're reporting that, hey, I'm going to report this data of these sick people in my community, that something is going to come back to me so that way I can better take care of them, so I can better prevent the same problems from happening again and again. That's the intrinsic value of the data that
Ideally, you would imagine from a reporting type activity, that also doesn't seem to have the same level of real-time connect, real-time feedback that you would expect if you are the ones who are taking so much time to submit all this data. And then the incentives, what are the incentives showing? The incentives are showing that, hey, we need to be TB free by 2025. We need to reduce infant mortality, maternal mortality. The incentives are not towards
How can we best report the ground truth? How do we have the best quality maternal and child death investigations? So that way we can actually understand the areas that need more support. So we can actually get them more services, right? So because the incentives aren't, looking towards improving health outcomes before understanding the ground truth. And because there's lack of supervision and because anyways,
Shubs Upadhyay (11:18)
Mm-hmm.
Ruchit Nagar (11:37)
these health workers are overburdened, all of the data that they're reporting is severely affected in terms of its quality and its usefulness. So these are the kind of deeper cutting problems that we see today and that have kind of grown over time as we've tried to use technology to solve the problem. And when I say we, mean the broader public health community without necessarily
designing the system in a way that can be horizontally integrated. In a way, we're making things more challenging for the health workers.
Shubs Upadhyay (12:11)
Man, you've traversed so many topics there. we will definitely bookmark the incentives piece and the goals. I wanted to just touch on a couple of things that you mentioned at beginning. just for those who are not aware, ASHAs are the name for the community health workers in India. Can you just kind of quickly mention exactly what that stands for?
Ruchit Nagar (12:29)
Yeah, ASHAs are accredited social health activists. They're considered to be the daughter-in-law of their village. So, you know, they have to be 18. They are moved into the village that they've been married into. And they're a representative of their village. So it's a democratic process to get elected. They then are responsible for
health promotion, mobilization, taking pregnant women to the hospital to deliver, checking in on newborn children, and also screening for a lot of that are on the ground for all the different programs. So they initially, I guess the focus may have started with maternal and child health, but it really has expanded to 50 activities across every single health program
Shubs Upadhyay (13:13)
Okay, next next bit that you mentioned. you mentioned 50 hours are spent on data entry, right? On across multiple platforms. And so is that per month? per month. So and then you said there are
Ruchit Nagar (13:24)
Per month.
Shubs Upadhyay (13:27)
How many community health workers? Yeah. And so, you know, I guess you can extrapolate then the potential cost of that, right? That time that could be used better in other other means. Thank you for highlighting that problem. And I think the other thing that you touched on that Echo in Eswatini mentioned was all these different layers that
Ruchit Nagar (13:27)
over a million in India. Yeah.
Shubs Upadhyay (13:48)
are at least on the supply side in terms of like the delivery of healthcare that are important to consider and they're so intertwined with each other. So you mentioned the people aspect, you mentioned the facilities, you mentioned the supply chain, you mentioned then the data systems and the infrastructure and the technology then kind of sits on top of that, right? For those who might not be familiar, can you give us a
quick whirlwind tour of like what is the backbone system of digital health infrastructure in India.
Ruchit Nagar (14:14)
Yeah, so the way that digital health evolved in India, it started in a vertical approach. So you had the reproductive child health bucket, had its own portal that was developed, initially started at the state level, then it was adopted by the Ministry of Health centrally. Later you saw the national communicable disease, the non communicable disease bucket.
also develop out its own portal focusing on things like diabetes, hypertension, oral, breast, and cervical cancer. And then you had a third bucket that was looking at communicable disease. So, know, vector-borne illnesses, for example. And a fourth bucket that's somewhat related but was just exclusively looking at tuberculosis. So these four buckets have had, they've built out their own solutions.
Initially building out web portals that could happen in and then moving into applications for the nurses and then now moving into applications that could be used by the ASHAs. They also have different portals that would work at the facility level like the district hospital or the primary and community health center. So.
Shubs Upadhyay (15:08)
Mm-hmm.
Ruchit Nagar (15:28)
So now you're in this world where you have all these apps that are getting to the most decentralized health worker. But the problem still remains is that, okay, I could have a patient, for example, who both has a non-communicable disease issue like diabetes and is in my maternal health tracking system. And I need to now keep track of them in both places. I have to enter their data twice.
Shubs Upadhyay (15:49)
Mm-hmm.
Ruchit Nagar (15:54)
people don't fall into just one bucket at a time. So there has been a push now to say, hey, and we're just talking about the government public systems right now. We're not even talking about all the private systems that have mostly been, you know, kind of paper-based tracking for a majority of the private providers. The major hospitals have adopted, you know, electronic health registries, but
It is a very fragmented ecosystem. So what did India do? Beginning in 2018, they came out with something called the National Digital Health Blueprint, which has now moved towards creating an ecosystem in which all information systems can speak with a common language, which is the FHIR,
Shubs Upadhyay (16:25)
Mm-hmm.
Ruchit Nagar (16:42)
Using FHIR as a standard to actually communicate between different systems, whether they're public or private, to have a new universal health ID and to have universal registries for both the facilities and for the providers. This way, at least the information exchange can be done in a more systematic
And that way you don't need all these custom APIs or custom channels to share data between system one and system two. There's a common way that you can share that data to the universe and then whichever system that needs it can pull. And they want it to be patient consent driven, which is great. They want it to be federated and decentralized. So there's a lot of great properties around how it's designed.
The interesting piece is that it still was envisioned to be designed for those people living in the tier one, tier two cities who are accessing, you these are the upper and middle upper parts of that population wealth pyramid who have access to smartphones, who are digitally literate, who are health literate, who are already using things like the unified payments interface to send money from person to person.
Shubs Upadhyay (17:52)
Hm.
Ruchit Nagar (17:55)
those tech savvy people would also have a digital record of their health information. So that's kind of how it was initially conceived. It wasn't initially conceived to figure out, how are we going to work with people that may not have smartphones, may not be digitally literate, who are availing free services from the government? What are we going to do for them? What does consent look like for them? It wasn't really designed for the bottom
So now they're trying to work, I mean, they're working top down thinking that it's going to get to the bottom eventually, but now they're starting to realize that, hey, we need to kind of rethink what it looks like to work bottom up. We need to rethink what it looks like instead of having all these 40 different applications and portals, let's work on making a connector application that can link to their different apps. Or can we have an integrated application that replaces all the redundancy?
That's ultimately what we're trying to do with our solution, which is called CHIP, Community Health Integrated Platform. It takes the 800 public health indicators that these health workers are responsible for, the ASHAs and A &Ms, and it simplifies. It gets rid of about 150 redundant indicators. And then it streamlines it in a process that it's a one-stop solution for that health worker, and it covers all of her work-related requirements. She has something called the Integrated Work Plan.
Shubs Upadhyay (18:53)
Mm-hmm.
Ruchit Nagar (19:17)
that she can click on and she can see, which house is doing to visit today? And it tells her the breakdown by the different program, which houses are going to see in the week and in the month. And for every patient that she goes to, there's all these kinds of custom decision support that's based off the national guidelines, based off that program so that she can then figure out how to refer and the next person in the referral chain can also see the relevant information. So this is what we think would actually be helpful.
for somebody on the ground who is responsible for covering so much of primary healthcare.
Shubs Upadhyay (19:51)
And just to draw parallel, most of healthcare is clearly delivered by ASHAs, right, in India, and other types of community health workers elsewhere. there's a real parallel with
clinicians working in Europe or the US or the UK of like, you know, this overburdening of the electronic health record. And it's really important that, you know, in the so called Western context, we're really focusing on, the value proposition that we're trying to offer, or that we should make make sure we think about is clinician well being. And I just reflect back that, you know, most of clinical care is being delivered by
community health workers, it's important not to, I guess, like forget because we just think about, you know, doctors or nurses in terms of clinician health well-being and make sure that actually the people who are out there really at the last mile of healthcare are really benefiting and feeling fulfilled in their roles, like just as any other healthcare delivery person would. So I think you've called out an important thing there and whilst there are parallels, it's kind of unique to this context, right?
Ruchit Nagar (20:48)
Yeah, I feel like the Western example and being like a resident doctor here, you we spend two thirds of our time in front of the computer and not at the bedside. And I think it's a cautionary tale, but I'm not sure if that caution is being heeded because the same over documentation and almost overuse of these digital health technologies is being now applied to community health workers where
Shubs Upadhyay (21:00)
Yep.
Mm-hmm.
Ruchit Nagar (21:16)
really you want them to be the least burdened so that they can, their work, their counseling, their mobilization is really the thing that's reducing infant mortality and other key health metrics. So it needs to be simple, user-friendly. the main, if I were to pick two indicators that are important is how much time are we actually saving for them? Number one, and would they recommend this system to their peer? If not, then we are not actually adding value.
Shubs Upadhyay (21:39)
Yep.
Ruchit Nagar (21:44)
And even if the system is great, if the system is the 14th app that they're going to give, even if it accomplishes everything that it needs to alone, unless you get rid of those other 13 or figure out a way to restructure that so that those legacy portals can still get the data that they need and still function in a reasonable way, again, you're not going to be solving the root of the
Shubs Upadhyay (22:07)
And what you're really trying to do, if you go to the meta level you're trying to find the real drivers of the outcome, like what are the levers that you need to pull, right? And here clearly you've identified that a big lever is actually ensuring that our community health workers can just get out and like, get out of their way and like, just let them go and do the work, right?
Ruchit Nagar (22:27)
Yeah.
Yeah, and I mean, it's interesting because it runs counter to what people know all the buzz is about where a lot of the global health investment now, where is it going towards? It's going towards digital health, AI, AI for health. And we have to be careful that, are we actually, and then there's also quite, funders will put in hundreds of millions of dollars towards these initiatives.
Shubs Upadhyay (22:39)
Yeah. Yeah.
Ruchit Nagar (22:51)
and then have these expectations that capacity gets built and that governments will adopt these solutions and build that capacity to move them forward. But at the same time, if you look at how the funding is being distributed, it's not pushing us away from the siloed systems that we live in. there is funding. Yeah, the funding is going towards a vertical solution for immunization or a vertical solution for non-communicable diseases, et cetera, et cetera.
Shubs Upadhyay (23:09)
Mm-hmm.
Ruchit Nagar (23:21)
And that is just making the problem, because then those large agencies then become, have a vested interest in continuing that vertical pipeline of control in a way to ensure that they can report what they need to report and show that their solution is successful. So I think really it needs, we need a radical rethinking and an honest conversation about what does collaboration look like.
Not everyone needs to be a digital health expert. Again, a lot of the important work will require other public health technical expertise to better implement programs on the ground. The opportunity that I see for digital health is, first of all, if we do it correctly, if we align the right, if we make the system ink free so they don't have to use paper, that's the first promise of digital, two,
integrated or interoperable so that way we don't need a million different applications that are falling on one person. And three, properly incentivized so that way health workers, know, incentives can be social incentives, financial incentives, or even just productivity incentives that, I did something and it felt useful to me. These three I's of ink-free interoperability and incentivization.
Shubs Upadhyay (24:17)
Mm-hmm.
Ruchit Nagar (24:38)
are the three pillars that we think are required to have a successful digital health solution rolled out and taken up. And then after that, the hope is that it can serve as a way for us to get better data of what's happening on the ground, better identify health inequities, better allocate resources, better allocate capacity building for the people on the ground. So that way we can overall kind of move the...
the health system in the right direction. But the way that I think about it is like you're literally having to renovate a house and redo all the plumbing, which is very, very messy and difficult once the plumbing has already been placed.
Shubs Upadhyay (25:19)
Yeah, definitely. And if you're just thinking only about certain verticals, like just the plumbing for the toilet, or just the plumbing for or just the heating of the pipes for this radiator, you lose sight of like, how this house is not very heating efficient for some reason why, right? So I guess that's a nice that's a nice parallel. So you so we've got Ruchit's three I's
Ruchit Nagar (25:26)
Yeah.
Ink free, integrated and incentivized
Shubs Upadhyay (25:43)
Perfect. Okay. That's really nice. I want to backtrack a bit. We talked about how you identified the problem. And as part of that, what was your approach, especially like, because we've already touched on...
how you found what the levers were to driving towards like real outcomes. You clearly had to speak to the right people. How did you go about kind of delving into and really understanding what was going on in the ground there?
Ruchit Nagar (26:10)
Yeah, so that I think that's an, you know, we talked about like, we did this human centered design course and that was the initial seed, but the human centered design didn't really, really didn't start until we actually went to the field and actually, you know, walked alongside our community health work partners, right? Those insights were tremendous for us. And actually we built it into our team structure from the very beginning.
to have a field monitoring team, to have a community engagement team that functions through a call center. And on a daily basis, we are in touch with anywhere between 100 and 500 community health workers on the ground. And that's been for the last seven, eight years. So you can imagine that that is a wealth of wisdom that we're able to then understand from. And we're able to better design the solutions to actually help address
the needs of the people that will be using those solutions, which I think is so critical. Most of the vast majority of software that is being developed for community health workers, those engineers are not meeting the end users, I can tell you that. And it is so critical to understand what actually works, what is actually helpful. You have to see both the trees and then you also have to see the forest, right? Because
you're also building for a multi-stakeholder environment where the community health worker is the end user or is the person who's using the app. But then you also have these public health officials that need to receive certain data, receive certain insights and reports. So they're a different type of user. And we can argue about how much of that data is actually useful. until the national health policies and guidelines change, we have to also satisfy certain of those requirements. So we also have to work.
in the health department. also have to have our team of policy and program focused people that are also available. So it's really a mix of both, being able to see the forest and the trees. And Khushi Baby's interdisciplinary team composition is really what I think is our secret strength or our special sauce. Because you have the field team, the policy team.
sitting side by side with the design engineering team as well. We have a team for monitoring and evaluation and data science that can help understand whether or not what we're doing is actually making an impact or not, and can be critical of our own approach. So you need to have all those different components to actually kind of have the end-to-end perspective of what it takes to roll out not just a digital solution, but a digital health solution that makes an
Shubs Upadhyay (28:51)
Yep. And you mentioned that kind of when you initially started, you've got, you had this digital health record that was like via NFC for the community. You had the community health workers who had the digital health record. Is there more that you've built around that?
What have you got implemented right now?
Ruchit Nagar (29:07)
So this whole project started off with tablets for nurses. These, I'm actually wearing it right now, this digital health necklace. So tying the tradition with the technology. The black thread was thought to ward off the evil eye. And these voice calls in the local dialect for the families. And it was focused on immunization. And we working with one NGO. That was how it started.
Shubs Upadhyay (29:14)
nice.
Yep.
Mm-hmm.
Ruchit Nagar (29:33)
Then the next step was for us to move from NGO to government. then we expanded from immunization to all of maternal and child health. Because we understood that the nurse is not just giving vaccines to the kids, she's also checking on women at the camp. We did a two-year randomized control trial to get evidence to see if that modified system would improve immunization outcomes. We were able to show that, we were able to improve immunization by 12 percentage points.
Shubs Upadhyay (29:36)
Yep.
Ruchit Nagar (30:01)
in our treatment group. We took that out. Yeah, I'm happy to hear that.
Shubs Upadhyay (30:02)
Have you got a link to that so we can share that out in the notes as well? Yeah, perfect.
Ruchit Nagar (30:09)
And so we took that evidence and we went to the State Department of Health and we said, hey, we want to scale this up. And they said, well, you know, we've got five other projects for you to work on first to gain our trust and also help us figure out this whole mess of 40 different portals that don't talk to each other. So we're like, okay, we'll start to work on this. And that's when COVID came. And then they said, hey, we need help with somebody to kind of help us screen the population for COVID at large. So we ended up making a decision to then
move away from tablets, move away from these necklaces, move towards just the most scalable Android application that can work on any smartphone, because we didn't have time to procure all these different things. That wasn't as scalable. that became a kind of we had to rethink our approach that, hey, this might be a USP of our system that the digital health record adds to some level of accountability, because you have to physically scan it to update it.
Shubs Upadhyay (30:49)
Mm-hmm. Mm-hmm.
Ruchit Nagar (31:03)
means that the health worker met the patient. So we were really looking at the accountability lens, but you were losing off on the scalability lens. And in the time of COVID where you have to do a mass screening, you really need to have a solution that's more scalable. So we said, okay, let's pivot. Also we have to pivot our focus, like the maternal child health focus, we had to the decision to say, hey, we want to go beyond this because that's the need of the hour. Let's apply what we've learned. So then we went through COVID, we helped do the screening.
Shubs Upadhyay (31:20)
Mm-hmm.
Yeah.
Ruchit Nagar (31:32)
Because of the situation of the pandemic, a lot of the red tape was removed to allow us to get into the Department of IT, the state data center, to scale this thing up. And what ended up happening was not only did we screen for COVID, but we also screened for all those comorbidities that make COVID more risky. And a lot of those comorbidities link very well with many other different programs, like non-communicable diseases, TB, et cetera.
Shubs Upadhyay (31:54)
Mm-hmm.
Ruchit Nagar (31:56)
So now you have a database of 14 million people. You have 60,000 community health workers that have used the platform all of a sudden. And we're able to go to different vertical health programs like TB, like non-cancer clinical disease, like vector-borne disease, and say, hey, we have this base. Let's build on top of it. And one by one, we're starting to add the puzzle pieces and starting to now use the data to support their programs, to use the data to study what is working within their existing interventions.
So for example, with the TB department, twice a year, they screen for TB across the whole state. And they'll have ASHAs go and ask people for symptoms that related to TB. And we're able to see the efficiency of the screening in vulnerable groups versus non-vulnerable groups. And because we've already done this effectively a digital health census, we're able to pre-identify who is vulnerable and help prioritize them because they're six to 10 times more likely
to turn it up to be a positive case. And we can show that evidence to help affect the policy and move the policy towards something that's more evidence-based. Of course, that requires advocacy. It's an ongoing process. But the data is now available for us to start to make those types of data-driven arguments or positions to help inform policies. So that's the bucket that we're in right now, which is really trying to use data for health system strength.
Shubs Upadhyay (33:02)
Mm-hmm.
So that's really interesting. you had to kind of, there was the need of the hour with COVID. You then kind of, the work that you did kind of helped also reach and make people who were maybe initially not visible in the data, i.e. the vulnerable populations, visible in a relatively usefully granular way. And therefore you were able to then kind of help decision-making.
targeting of resources and also start to make more visible the discrepancies in terms of health inequalities etc I mean that's not the summary of like what you did but I just wanted to kind of touch on that little nugget of what you said because I think that was really important.
Ruchit Nagar (33:59)
No, and that's huge. We really considered the community health worker to be the local researcher of their village, the local reporter or journalist of their village, right? And there's an old Sanskrit saying that I don't know the exact original vocabulary, but, and Nehru repeated this in one of his speeches. It says that the taste of the water changes every few miles. And we can literally now map that because we have
tens of thousands of ASHA workers who are sharing data, the data that they share on social determinants of health we think is very high quality and very rich. And you can literally see the tapestry of different degrees of poverty change from as you go from a few miles out to the next few miles out, kind of reinforcing that concept that India is not a homogenous place, right?
Shubs Upadhyay (34:52)
Mm-hmm.
Ruchit Nagar (34:53)
and village to village, you're going to see differences. And to have a strategy that can now boil down to the village and get closer to the people is ultimately what we're striving for. That social determinants of health data also has positive externalities. It can be used by other departments as well to help with their planning. I know that the poverty index is high here. I'm going to use it for my education, for my public distribution, my other departments as well. So this is the new power of big public health data that's
that has the potential to be unlocked if we're able to properly kind of enable community health workers on
Shubs Upadhyay (35:30)
Really, really nice takeaway there. So that was a technology layer I want to go to the people layer and incentives. And maybe we can envelope that into kind of the next part of the conversation I wanted to get into, which is what challenges have you faced? So you kind of we've touched on like the problems you're trying to solve, some of your approach and really understanding the reality of like how care is delivered. And we've talked a little bit about the impact that you've had, etc. and how you've scaled.
Where have you seen difficulties, challenges, and what you've learned from them?
Ruchit Nagar (35:57)
I think, I won't start with the challenge start with the solution. The solution is that you have to be persistent and consistent because it takes a long time to rework the plumbing, to rewire the system. think, of course, politics is at play. There are vested interests, there are legacy platforms, there is funding that is supporting, preserving a lot of the status quo.
And, you know, once the central government says that, we want to roll out this vertical solution nationally, irrespective of you trying to have a more integrated solution on the ground, by default, you're going to have at least two solutions, right? You're going to have to break the workflow to use this vertical solution for Objective X. We're seeing that in the case of immunizations right now, that, you know, the success of India's effort with the COVID platform
Shubs Upadhyay (36:43)
Mm-hmm.
Ruchit Nagar (36:50)
which was used to generate over 2 billion COVID vaccine certificates digitally and track COVID vaccination very successfully and even share that as a digital public good to other countries as a form of even global health diplomacy. A huge success story in a way. Now being expanded to cover routine immunizations across the country, a very noble and important goal, but again, still working within a silo.
So how does that silo ultimately boil down to the person who has to now juggle 10 balls at the same time? So the question is, hey, can you get the data that you want? But can we think about doing something different at the ground level? Can you share us the APIs? Or can we use a common language to talk so that way a different system on the ground can still give you the data that you need to make your analysis and decisions?
The frustrating part is that it should be easier to integrate between and across systems. The challenge is that there is some resistance, and there may be also gaps in capacity to facilitate those connections from a technical capacity standpoint. And if people are looking to invest, I would look to invest specifically in supporting connections across
across platforms as opposed to investing in developing new ones. That's the major takeaway that I would recommend for those who are out there who are looking to continue to support these initiatives. I think the other challenge really that we are seeing is change is slow. We came into the government, we were very disruptive.
Shubs Upadhyay (38:16)
Mm-hmm.
Ruchit Nagar (38:32)
their internal department of IT and other development agencies that have been there for 10 plus years. They were all skeptical of us. We've had to prove ourselves in a way, but we are impatient as well. We want things to change faster. But in order for things to actually change and durably change, you have to get your system, you have to get your gear within that whole machinery. Once it's in it, it's very hard to then remove.
But the conditions like we talked about need to also be in place for that gear to even turn. So getting the right mandates at the policy level, the right incentives, and then the right kind of collective buy-in to work towards a common solution, that is kind of an ongoing problem. And the approach that we're now taking, so we've worked in Rajasthan, India's largest state, but we're expanding to two new states as well, Maharashtra and Karnataka.
Collectively, 250 million people live across these three states. The other two states are approaching kind of criteria for even entering. Is there a demand coming from the public health department, from the government itself? I think that is the single most important factor that's gonna determine your success and timeline. Even more so than capacity or technical capacity. What is the demand of
Shubs Upadhyay (39:26)
Mm-hmm.
Ruchit Nagar (39:47)
those senior bureaucrats, that public health department to actually move towards this direction. Now, those bureaucrats may change, know, there is a cyclicing, you know,
Shubs Upadhyay (39:57)
So what does the signal look like for you to then say, okay, it's worth going for this or we should we should focus our efforts here.
Ruchit Nagar (40:04)
It, you know, I think, again, you have to reach out to those senior health secretaries, women and child development secretaries, chief secretaries, and mission directors and pitch and see if there is some buy-in or if in some cases they have their own call for proposals that, we want this type of system. And they, you know, in the case of Karnataka, for example, they said, we're going to have a competition between four different
Shubs Upadhyay (40:23)
Mm-hmm.
Ruchit Nagar (40:30)
players to make an integrated solution. We're going to select after six months, and then we're not going to pay you. We're going to expect you to help us for the following two years, and then we're going to ask you to leave. So that way we have the internal capacity to move it forward. And I think that's a very progressive approach towards taking ownership and accountability over the digital public health infrastructure that they're trying to adopt. So we can be a facilitator of that.
that we'd love to be contributing in that kind of environment where it's evidence-based and demand is coming from the government itself.
Shubs Upadhyay (41:07)
Great. OK. At the beginning, you touched on this incentive thing. So let's visit it now, because it feels like a challenge, You mentioned kind of, and it's kind of related to political aspects as well. Often, you have certain big goals. And how do you make sure that the incentives of those big goals align with the realities on the ground of delivering care?
Because if they don't align, ultimately you get a very skewed or not very real picture. Can you elaborate on that?
Do you have any insights there?
Ruchit Nagar (41:35)
Yeah. This is the hardest question. Everyone asks, how are you going to make impact? What's your sustainability model? And we need to almost rethink about what is the context that we are working in, right? The goal for us is not to become the next tech giant or unicorn, right? That's not our approach to sustainability. Our end game is to really have
a system that can strengthen the public health department that they can own and feel accountable over. And they can ultimately start using data more effectively to help with their decision making in a way that they find valuable and in way that we can actually measure that says that, we were able to improve the ground truth reporting stage one. Maybe the indicators got worse during that first stage. Then stage two, we had a mechanism to actually see
which interventions were working. And we actually used that data collection platform to test, okay, does giving a new mid-level provider at the primary health center improve healthcare utilization and decrease out-of-pocket expenditures? We actually did that study based off our data with the support of J-PAL. We were able to turn our platform into a measurement tool. So that's phase two, starting to see what actually works.
based off the interventions that you're putting out there. And then phase three is then replicating those interventions on the ground that have shown efficacy and then seeing the overall indicators, which initially went up because you had more transparency, start to now go down. So those are the three kind of phases in the evolution of the impact journey. And we're still very much in the first phase where we need to just better report the ground truth.
Shubs Upadhyay (43:20)
Yeah. Yeah.
Ruchit Nagar (43:23)
That's not going to look good to the government. That's not going to look good to the donor. Yeah.
Shubs Upadhyay (43:26)
This is the thing it takes time, right? So it's like, well, if you're trying to show show ROI within a year, like you missing the bigger picture, right? So yeah.
Ruchit Nagar (43:34)
Exactly. And the other thing is, know, certain donors talk to us and say, hey, you to build capacity within a few years and then hand it over. But the reality is that we really need longer timeframes. mean, even if you think about the West's adoption of electronic health registers, it didn't happen overnight, right? It was a at least 10-year journey, maybe 15-year journey for that to kind of fully transition to the
level of adoption that it has now. So you can imagine, and there's still many, it's still like, it's so convoluted. So you can imagine that it's going to be an ongoing, you know, the bet, one of the interesting examples of this is now you have this whole new momentum towards AI for health, right? What capacity does the government already have in AI for health or climate and health, right? How many climate and health, climate AI and health or AI and health experts already exist?
Shubs Upadhyay (44:03)
with still many problems.
Ruchit Nagar (44:28)
It's an emerging field, generative AI. How many of those experts exist? These are all new fields, new technologies that are emerging. And we expect the government, we expect the ethical review boards to just magically have capacity on how to evaluate and adjudicate and regulate those things. So they themselves are trying to figure out what's going on. There's a lot of gray area. Some people are taking advantage of the gray area.
Shubs Upadhyay (44:30)
Mm-hmm.
Ruchit Nagar (44:52)
I think it really, we need to be very responsible in terms of how we state or overstate the impacts of these new technologies. We again need to go back to first principles and see that, hey, okay, I'm making an AI for health tool to help with diagnosis of disease X that can fit into the health of your smartphone. Is that gonna change? How is that gonna change her day-to-day activities? What if there are more false positives that get screened because of this tool?
And is that going to actually meaningfully improve the referral rate or she's still going to tell everyone to go get referred, but the real challenge is the fact that they don't have transportation to get to the facility. So, you know, that fancy AI tool may not be, it may be okay, but it may not be really solving the problem in of itself. So we need to understand the full value chain and go back to first principles to really ground ourselves in a lot of these new developments that are coming through. And I say that
being, speaking from a team that is working on those same technologies. So we worked on the digital health solution piece, that's the first bucket. The health system strengthening is the second bucket and our third bucket is research and innovation. So we are very excited and we think that there's a lot of potential that can come out of these technologies, but we have to also be very careful and responsible about how we study. mean, it needs to be researched, you need to do trials, you need to do qualitative research as well.
It needs to be kind of done in a limited and carefully scaled way. Because otherwise we're just going to overstate the value and then we'll look back and say that, know, I initially, know, the patient came in with a rash, you know, I went through this whole AI, you know, chat bot thing, and it told me that I need to refer the patient to the dermatologist, which I already knew, you know? So like, what is the new value addition that I'm getting?
from whatever that new fancy tool is. Is that actually gonna change my decision making? Is it actually gonna get the patient the care that they need or not? We need to be very thoughtful about those things.
Shubs Upadhyay (46:53)
And some people might be listening to this and say one, you kind of mentioned first principles. One of the approaches to making sure you have all these first principles baked into your thinking is regulation. And that kind of brings me to just very quickly before you wrap up, maybe just quickly talk about the regulatory aspects because regulation kind of in some ways helps makes you think about, okay, well, what is the intended use here? Who is it for? Where does it fit into a clinical workflow?
How is it being used? What are the risks? How do we mitigate them? How do you develop a quality management system to then implement this? And then how do we measure success? How are we setting ourselves up to generate the evidence for this? And then we can talk about the risk benefit ratio, et cetera.
Do you have any experience or views or perspectives on kind of like the regulatory picture for you or like within India?
Ruchit Nagar (47:44)
Yeah, so I think one of the biggest challenges is knowing what is the truth, especially if you're in a post-truth era with social media. But we're also in a pre-truth or post-truth era when it comes to public health and public health information. So if you look at the nationally representative health surveys, they happen every 40 years.
Shubs Upadhyay (47:51)
He
Ruchit Nagar (48:10)
the level of granularity goes down to the district. And those estimates of key health parameters vary significantly from what the official portal is showing for the same indicator, right? For the, you know, it's the maternal child health or TB, et cetera. So first of all, we don't know what the truth is, right? Now, if you're doing a proper sample survey, like that should be closer to the truth if it's a representative sample, but
There's even questions if that's truly a representative sample or not. Okay, so we need to first start off by understanding what is the ground reality? But then on top of that, the issue is, okay, and I'll give you an example, TB free by 2025 was one of the declarations. You need to make these declarations to motivate people in a certain direction. And I totally agree with needing to have SDG goals, health specific goals.
But you have to couple that with the right monitoring and supervision mechanisms. And it has to be like, we talk about smart goals, right? It has to be specific, measurable, achievable, realistic, time-bound. So is it a realistic goal or not? Well, maybe not. Maybe we need to be more patient with kind of achieving these goals. Not to say that we should delay it, but really because it does take more time.
So what's the fastest way to become TB free? The fastest way to become TB free is to report that there's no TB. That's it, right? It's simple, it's solved. You report that from my village there was no TB. And they have this campaign TB free India, TB free Rajasthan for example. And they're giving incentives for every screening that was done across, in Rajasthan, over 7,000 villages that they identified as target regions.
So every screening you get, you get 10 rupees. Okay. There's, let's say there's a thousand people in your village, you get 10,000 rupees. Great. ASHAs should be paid more. I would argue that they're underpaid, but they can easily just say that everyone was asymptomatic. They didn't collect any sputum samples of the cough and they'd never have any TB in the village and the village gets stamped TB free. And then they get to promote that, we have these many TB free villages across the state.
That's not right. mean, if you're not actually going and screening people and then you're declaring yourself as TB-free, TB is not going to magically go away.
Shubs Upadhyay (50:32)
Is that what's happening on the ground?
Ruchit Nagar (50:34)
Yeah, see, the unfortunate truth is that the health workers also have some fear of reporting the truth that their higher ups. So that's the nurse or doctor or somebody is going to end up, you know, they're going to receive some kind of punitive, you know, feedback for finding it, for highlighting that this child died or that this patient has TB or that, you know, their village is a problem area. Right. So it creates, mean,
Shubs Upadhyay (50:49)
thing for finding it.
Ruchit Nagar (50:58)
For some health workers, not everyone is a good apple. It creates more work and they don't want to do that. But for others, they have a genuine fear that there are going to be repercussions that come back to them for being honest and reporting the truth. now they've coined this term, supportive supervision. So report whatever you want to report. We will support you and we'll supervise you in a supportive way, not in a gotcha type.
Shubs Upadhyay (51:23)
Mm-hmm.
Ruchit Nagar (51:23)
And think at least TB is moving somewhat in the right direction because they also pay more for identifying cases. know, several hundred rupees for each case, positive case that's identified. And that's good because if you don't identify the cases, you will never stop the chain of transmission. The only question now is how do you actually align the incentives and the supervision and the monitoring in a way that makes sense, that avoids
cheating or misrepresentation of the data. Like why should we even give 10 rupees for every screening if we're not meeting certain quality metrics in terms of the number of symptomatic cases that should be expected to be reported, the number of positive cases that should be expected to be reported based off quality standards.
Shubs Upadhyay (52:00)
Mm-hmm.
So part of your three I's that you mentioned was incentive. So I think that's a really great example of how it can unintentionally kind of mess things up, Yeah.
Ruchit Nagar (52:13)
Yeah.
Yeah, and I just want to clarify one other thing. I ASHAs have told me, one of the most powerful things that ASHA workers told me is that I get paid less than a daily wage laborer. So it was such a profound statement to think that, you know, ASHA workers that are responsible for this huge drop in neonatal mortality, for example.
are getting paid $2 a day, and they have a component fixed salary, they have a component incentive-based salary, they should be getting paid more. Why are they paying for their own data plans to report all this data? Why are they having to spend money to travel to the health center and sit with the data entry operator? They should certainly get, India and other countries should increase the percentage of health spending as a fraction of their overall GDP.
Shubs Upadhyay (52:47)
Yeah. Yeah.
Mm-hmm.
Ruchit Nagar (53:05)
you know, and support the people on the ground. I'm totally for that. But at the same time, I also believe that we need to have better metrics to evaluate which health workers are really contributing to the impact of their communities, which health workers need more support and appropriately allocate resources to help them. You know, whether that is on the basis of increased poverty index, which we can now measure, increased climate vulnerability, which we are now able to measure as well using
a new climate health vulnerability index that we've developed, we need to find ways to actually get resources to people that need them and then the right capacity and skills to build them up.
Shubs Upadhyay (53:46)
One of my questions was going to be in terms of challenges, how do you measure what bit of effectiveness quality and performance tracks towards what's really valuable? How do you elevate the things that are harder to measure,
Ruchit Nagar (53:56)
So we have international regulations for health data privacy, HIPAA, GDPR, et cetera. Now India has a patient data protection bill, which is a good step in the right direction, or personal data protection policy, rather. But when it comes to regulation, there's still so much gray area, not just around sharing of information, but even if you look at regulation of
these new technologies, right? So the AI for health medical devices, know, yes, to a certain extent, you know, they do have standards for devices that again are catering to the, you know, public and private hospitals, but the regulation as you go more towards the community gets more diluted. And then the other question or concern that kind of underpins this is to what extent are patients that are
Shubs Upadhyay (54:22)
Yeah, medical device regulation,
You
Ruchit Nagar (54:47)
or participants that are being enrolled in the studies to prove these things out, to what extent are they giving informed consent? What does informed consent look like for somebody who doesn't have that level of health literacy or even literacy, right? So do they understand the risks and benefits? Do we understand the tax that this could potentially put on the system by adding another technology?
And I think that India is a unique place because of the chaos and gray area. you can innovate faster. But at the same time, when it comes to somebody's health, you have to be much more thoughtful. So it cuts both ways and you want to stay away from areas where they're
that output of your system could really make a big decision one way or the other. We can use things like AI to help prioritize who we need to call back or who we need to visit at their home. In terms of giving some kind of extra services or services that a human alone wouldn't be able to do,
So more on the automation side, think, you know, the technology has a huge benefit to play. when we start to get into prediction and now generation of new content, we need to be a little careful.
Shubs Upadhyay (56:04)
And who's overseeing this? What's the body that oversees this kind medical device regulation in India?
Ruchit Nagar (56:09)
So it's, an evolving landscape. You have the Indian Council for Medical Research, ICMR. You have CDSCO for medical devices. Now there are new AI centers for excellence that just got announced. A lot of the All India Institute of Medical Science group is going to be looking after that. So it's emerging. And we need that. We need to build up that capacity and infrastructure to test the future of what public health
technology and innovation will look.
Shubs Upadhyay (56:40)
great insights on the challenges What's next for you guys at Khushi Baby? What are you kind of working on? What are you excited about?
Ruchit Nagar (56:48)
Yeah, we just finished 10 years. I would say the first 10 years were all about getting our foot in the door and scaling up a digital platform in a complex environment and understanding the landscape. The next 10 years are hopefully making a big impact. So I would say the impact that we've made right now is more on the digital enablement front and on helping conduct a big health census and identifying inequities in...
diseases, but now the next frontier is, okay, we've identified these many hundreds of thousands or millions of people at risk or with certain health conditions. How many of them got successfully referred, successfully treated, did not relapse from the condition? And that part of the kind of care delivery chain is the harder part to solve. It requires a more deeper collaboration with the government and with the other partners on the
So that is really our goal from a health system strengthening standpoint. We're excited that we're moving into two new states. Ultimately, our goal is for the technology platform to be adopted as a digital public good by the Ministry of Health of India. All of the solutions we are giving to the Department of Health free of cost, we want them to adopt a solution that works for the community health worker and for them at scale.
Shubs Upadhyay (57:48)
Mm-hmm.
How do you make sure that you guys are able to be sustainable as an entity through that if you're doing it free
Ruchit Nagar (58:18)
Yeah, the public health department is unique in that as a software provider, you're not going to be very satisfied if you function as a vendor. You're going to be a lot more fulfilled if you are able to make an impact if you work as a partner. So we've taken that approach as a development partner. Funding for us, there's still hundreds of millions of dollars that are being invested in the digital health space.
and in related health system strengthening space, probably billions of dollars, in fact. I'd have to look and see how much India is getting out of that pie. But there is plenty of philanthropic support that is available. And if the government wants to engage in public-private partnerships through its own budgets, of course we would be open for that. But I don't think that the philanthropic capital is close to expiring. And I think that
Shubs Upadhyay (59:14)
Is it hard to get access to like is that one of it would that be one of your challenges as well? Where is it on the spectrum for you to kind of make sure you get that funding?
Ruchit Nagar (59:21)
I mean, there are organizations that are working in sub-Saharan Africa who have annual budgets of $25 million a year for doing digital health solution work at, you know, we're talking about one third of the scale that we're working at right now. So there's certainly funding out there. I don't want us to be necessarily that resource intensive. you know, I would argue that we are about 20 times more cost efficient than those, some of those other competitors.
Shubs Upadhyay (59:35)
Mm-hmm.
Mm-hmm.
Ruchit Nagar (59:49)
or parallel colleagues in different places. Peers yeah. But at the same time, there is funding available. think what will happen with us is more of a shift from working on the core digital health solution to working more on the data analytics, health system strengthening, and the research and innovation piece. We want to switch from 70 % working on the solution to 70 % working on program delivery analytics.
Shubs Upadhyay (59:51)
Yes.
Ruchit Nagar (1:00:17)
and new ideas. So that's where we think we can make impact over the course of the next 10 years.
Shubs Upadhyay (1:00:23)
Great, great to hear that. And great to hear that the things that you're focusing on, I guess, really attached to the realities. Because often you hear pictures, or like, what's next? Yeah, so we're going to do this thing with generative AI, or this thing. it sounds very.
grounded in what really needs to happen.
Ruchit Nagar (1:00:43)
Yeah, I mean, think generative AI, it's got a lot of potential. It's the new sexy thing. Everyone's making a chatbot. We're making a chatbot as well for ASHA workers. But again, the deeper question is, how do you ensure in a systematic way that it's safe? And I think that's something that people are working on, how we can better solve that. We were super excited about we have one of the
probably the world's largest study to do machine learning on images of the inner eyelid to predict maternal anemia in the clinically relevant range to help with getting pregnant women iron transfusions, blood transfusions that will eventually protect them at the time of delivery from life-threatening bleeding and help protect their child from malnutrition.
So we're working on it. So you take the phone, you don't have to poke anybody, you don't have to draw any blood, you just take a photo. We estimate your hemoglobin level. We're working on that. But that's still going to take some time. It's going to need regulation. It's going to need community-based trials and settings. then ultimately, again, we still need to ask the question, is that screening tool going to meaningfully change how many people got the treatment that they needed? Even if it's much more cost effective than a handheld device that you have to poke somebody's
Shubs Upadhyay (1:01:44)
Mm-hmm. Mm-hmm.
Yeah. Yeah, what's what's the kind of bigger clinical outcome that you're gunning for? Is it moving the needle on that? Absolutely. Okay, let's wrap up. Do you have any other kind of key top takeaway for you know, someone who might be building kind of early
Ruchit Nagar (1:02:04)
Exit.
Shubs Upadhyay (1:02:16)
in their journey creating impact for underserved communities or kind of working in India or working to support communities, health workers What's your top takeaway for them?
Ruchit Nagar (1:02:26)
You have to visit the field. That is the most important thing. It's been part of our DNA from the beginning. You cannot build from the comfort of your home. You have to go out and work and see what actually is going on before you introduce a new technology. The name of the initial class was called Culturally Appropriate Technology for the Developing World. Culturally Appropriate or...
you know, having cultural humility is now kind of a different way of phrasing that is really, really important to understand this larger concept that we're talking about. Like, is this going to be something that actually moves the needle is something that we can actually co-create value, not to think of ourselves as the problem solvers, but really to think of this as a collaborative effort to think about how we can move things forward.
Shubs Upadhyay (1:03:18)
I think that's definitely a good takeaway, especially for anyone who might be building from the context of Europe or the US or the UK, and perhaps going out to implement a technology in another part of the world,
and kind of part of the why of this podcast as well, like making sure that we we're learning from all contexts, learning happens both ways, right? And so yeah, I think that's a great thing to share.
Ruchit Nagar (1:03:43)
I think this platform, being able to have these honest and open conversations, exchange of ideas, that's such a key piece to moving the discussion forward and moving the agenda forward. this is a small community working in the global digital health arena, and there's a lot of change that we can make, but we need to do it together.
Shubs Upadhyay (1:04:08)
Definitely. Ruchit, I'm really, really grateful that you have shared your experiences, your insights, the impact that you've had, the challenges that you've tried to overcome. Thank you for your time, Ruchit. Thank you.
Ruchit Nagar (1:04:19)
Thank you so much.
Shubs Upadhyay (1:04:19)
Before you go, a quick word. I started this podcast, to expand all of our perspectives. I think it's really, really important that we do that and learn from people who are really solving complex issues with implementing, particularly for underserved populations. We can learn a lot about...
solving challenges around health equity, ethics, implementation science, generating the right evidence, et cetera. But from the perspectives of these places where it's even more challenging often. so people who are kind of, know, elbow deep in these problems have so much unique insight to share. So if you found this useful or know someone who will.
Please hit follow on your podcast channel Check out the website gpodh.org We're also on YouTube so you can subscribe and also we have a LinkedIn page global perspectives on digital health and share that with those who might find this interesting as well if you have insights to share or know someone who
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