Unique Contributions

The healthcare renaissance is here. How the use of data improves health outcomes

• Josh Schoeller and Shanker Kaul • Season 3 • Episode 3

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Some people are blessed with good health, others are not. But health is not just a factor of physical condition. There are many underlying community-wide social and economic conditions in which people are born, live and work that impact health outcomes. This is what is commonly referred to as social determinants of health. Taking these into account is critical to improving health outcomes. Advances in technology and use of data in healthcare are opening an era of ‘health renaissance’.

In conversation with Josh Schoeller, Chief Executive Officer of the health care business of LexisNexis Risk Solutions and global president of Elsevier's clinical solutions, and with Shanker Kaul, managing director of Elsevier's health solutions in India, YS Chi explores what this means in practice in both the US, and in India where the wonderful ASHA workers, the female front-line workers are making an impact.

This podcast is brought to you by RELX.

YS Chi:

The unique contributions podcast is brought to you by RELX. Find out more about us by visiting relx.com.

Josh Schoeller:

Now I can go out and say you know what I'm doing every day, is I'm helping create healthier communities. I'm helping the US healthcare system and the World Health Care System to drive better operational efficiencies and better health care outcomes.

YS Chi:

Hello, and welcome to series three of Unique Contributions, a RELX podcast, where we bring you closer to some of the most interesting people from around our business. I'm YS Chi and I'll be exploring with my guests some of the biggest issues that matter to society. In this series, I also want to investigate the issue of trust. How can we build trust in data and technology and help create a world that works for everyone? Today, my first guest is Josh Schoeller, who has the dual role of president of Elsevier's global clinical solutions business and CEO of healthcare business at LexisNexis Risk Solutions. He has worked in all segments of the healthcare industry in the US prior to joining RELX family about a decade ago. At the heart of this role is making sense of the ever expanding amount of healthcare related data and effectively applying outcomes driven analytics to help improve healthcare outcomes. So Josh, let's get started. Welcome.

Josh Schoeller:

Thank you. Happy to be here.

YS Chi:

Now, one of the main consequences of the pandemic was increased awareness about the gaps in illness and treatment among different demographics. COVID exposed inequities that already pervaded our society. Can you please start by telling us how you view the current healthcare situation in the US? And where you see the most pressing issues, please?

Josh Schoeller:

Yeah, there's there's a lot there. So first of all, in the US, we spend 4 trillion dollars a year on health care, yet, we're not leading in health outcomes. In fact, we're in the bottom 25% for some of the key metrics like infant mortality, and overall mortality of our population. So we have a lot of work to do to improve the overall health outcomes. And as you mentioned, there are health equity issues, we see a lot of health disparities. And so we need to look at how we can increase access by filling gaps in what we call social determinants of health. The Institute of Healthcare Improvement, defined what they call the triple aim. And I think, we use that in our business. It's around improving patient experience and access. It's around improving health outcomes at a population level. And it's around reducing the cost of health care. And I think if we focus on that triple aim, around all of our solutions, where we're driving with our content, our data, our analytics, that's where we can make the biggest impact. Social determinants of health, you know, if you're not familiar with that, the World Health Organisation as well as CMS here in the US have looked at social determinants of health as elements or factors that impact people's health outcomes outside of their clinical condition. So this could be things like social isolation, and loneliness, or economic instability, housing instability, access to transportation, access to medicine. And so these are all things that we're focused on trying to close those gaps and give healthcare providers more insights into how we can leverage social services and community based organisations to help create more holistic health care here in the US.

YS Chi:

There is a lot packed in all the points you just made here, so let's go one step at a time. Now, I agree that these are critical objectives and challenges. And I think that IHI's is three point aim is really clear. And it's actually surprising that we haven't been doing it already. The pandemic also accelerated a trend where people are changing the way they are dealing with healthcare and accessing the point of care. So it seems to me that this is making the system shift toward a more value-based model of care. Can you explain to our audience what is meant by that?

Josh Schoeller:

Yeah, absolutely. So value-based care is the healthcare delivery model in which providers are paid based on driving better patient outcomes, versus traditionally in the US, we had a fee for service model, which which was really being paid based on the amount of services provided. And you can imagine that that's a really fundamental shift when your economics are driven by doing more versus doing what is needed to create a better health outcome. So certainly, the pandemic has heightened both the awareness and the adoption of the value-based care model, but this was something that was actually a part of the Affordable Health Care Act. And there are metrics that are legislated to help the US system move more towards a value-based care model. But it's a huge system, it's this giant battleship that we have to slowly turn. And it's taking I think, a lot longer than everybody would like. But the benefits of that value-based care, maybe I'll give a quick example, my son, when he was two years old, fell down and broke his arm. And it was a it was a compound fracture. And when we went in, they took an x ray, and they they set his arm and a cast. And we went back in three or four weeks later to get it looked at, and they did another x ray. And they realised that they didn't set it quite right. And so they had to go in and do surgery, and they had to pin his arm and recast it. And the net net of that was that the hospital system, instead of getting reimbursed about $1,500, for fixing a broken arm, due to the surgery and the anaesthesia and all that it was a $20,000 procedure. And that was not based on creating a better outcome. But it was based on hey, we had to do more things to solve for that. And so what we want to do is be able to go in and say, "We will pay more, we will reimburse higher for a better outcome. But if you don't have better outcomes, than those costs will not be reimbursed". And what that does is it really shifts everybody's perspective on laser focusing on creating optimal health outcomes. And that's really what value-based care model is all about.

YS Chi:

It almost sounds as if we spend a lot of money for those exceptional outcomes rather than outcomes for a lot of people. So vertical versus horizontal. Am I seeing it correctly Josh?

Josh Schoeller:

Yeah I think we do. You know, research has said that in the US about 30% of our total healthcare cost is waste. And that's a, when you're talking about $4 trillion as a base, that is a lot of waste. Some of that is related to what we just spoke about, additional services that maybe aren't required, or don't link directly to driving better health outcomes. Some of it is fraud, waste, and abuse, some of it is layers of different bureaucracies that we have in healthcare. So we really are focused as a broader system on how we can make health care more efficient, so that we can lower that cost and we can drive better health outcomes, but there's a lot of different areas to dig into on that.

YS Chi:

So let me dig even further. Because the number one point you made of IHI's, Triple Aim is patient access. And, and reducing cost. If we have a country in US where the most difficult, the most advanced procedures can be exercised here. That's great. But that doesn't mean that normal health care for the broader population may be available. So I'm a little bit confused as to where is there a guideline in the vertical excellence versus horizontal access?

Josh Schoeller:

Yeah, it's it's a great question. I think access is a big issue. Some of it is due to the fact that we just don't have enough doctors and nurses and facilities in the US to treat our population. Some of it is the fact that we don't fund social services. And this whole focus on we treat illness, but we don't necessarily focus on wellness. And we are seeing a shift right now, you know, if you look at some of the large health insurance companies in the US, they are marketing themselves no longer as health insurance, but as wellness companies. And I think some of that's marketing, but you can also see in some of their actions that they are taking that seriously, I can give you a quick example, one of the top five insurers in the US just invested in a programme, where they have risk assessed their Medicaid population, understanding and done a lot of analytics utilising data assets to understand what are the core, non clinical risks of this population. And then they've educated frontline health care workers. So these are not necessarily doctors and nurses, but more social workers and public health officials to go out, knock on doors, make phone calls, to better work with this population, to help understand the risks, and then fill those gaps, whether that's I need healthy food, I need access to transportation, right. And they're starting to fund those programmes where we've never seen that before. So those are good steps forward. But we have a long way to go.

YS Chi:

You know, that kind of implies clearly that the pandemic has increased people's interest in their own health through these kinds of methods. And we're seeing also a growth in consumer driven health care, right, with people increasingly doing their own research and making decisions about their health care based on cost and quality. Now, as a data analytics firm, you depend on health data and data sets at Elsevier. How do you reconcile this with patient privacy?

Josh Schoeller:

You know, it's probably one of the most important balancing acts we need to do as a business, we are very firmly rooted in rules of the road and ethics bound data for good philosophies here. And when we say data for good, then you have to define what what does good mean. And good means that it benefits the patient who ultimately owns their data. But then it also can benefit society. So on an individual level around individual patient privacy, HIPAA is the rule of the land, there. Covered entities get the right to utilise patient or consumers information for treating that individual. And we've all signed that HIPAA form when we go in to see a healthcare provider. And then downstream of that business associate agreements can be signed with covered entities to help manage that data and do analytics, but it's very highly regulated, for the use of that covered entity for the treatment of that patient. One of the key areas that's evolving, and the pandemic really, you know, put this on hyperdrive, is we needed to have use of more patient data in broader datasets to do clinical research. And that was very difficult to do. So what's evolved, and is a really budding area of focus is real world data and real world evidence, if you're not familiar with that this is the practice of taking large clinical datasets, health datasets, and completely de identifying or tokenizing them. And what that means is that there's no ability to go back and understand who the individual patient is. But then you can start looking at health data on 10s of 1000s, or even millions of individuals, right, and help understanding how do we create better therapies? How do we create better infrastructure to treat certain disease states? And certainly, this was critical during the pandemic, as we tried to get those vaccines to market as quickly as we can.

YS Chi:

Right. So you're talking about this Gravitas? Is that right?

Josh Schoeller:

Yeah, that's our solution that we launched this year, and what Gravitas does, which which I think is really going to fundamentally change, what we're doing and research is it leverages the LexisNexis ability to have a higher precision linking of data. So we've linked datasets together across industries for decades. And we've learned a lot during that time. And what traditional de-identification or tokenization did is it created really a crypto hash based on the personal identifiable information that was presented. But you can imagine that across siloed data, the PII isn't always in sync. And so we can utilise referential information in a de-identified fashion to create very highly precise linkages. And then as you do that, and you create a fuller picture of a longitudinal health record, it allows us to go much deeper, in utilising that data for research, and to create better patient outcomes.

YS Chi:

Sounds really the right way to go. But explaining that to patients and having them comfortable to give access to data over time, seems to be a challenge.

Josh Schoeller:

It is. I mentioned the other piece of legislation that was passed two years ago, the 21st Century Cures Act also gives us a lot more regulation around an individual's information. And this was based on health companies who had tonnes of data, but were not providing access to that data. And so what the 21st Century Cures Act is it reinforces the fact that the consumer, the patient owns their information. And they are the only ones that can give consent of that data to be used in an identified way out there in the system. So they adopted the FHIR standard, which is really standards around what a clinical record looks like. But then also legislated that if you're found that you're not releasing data on a consumer or patients consent, then you're guilty of data blocking, and there's significant fines associated with that. So when you take that legislation and the new standards, what it has really done is opened up the ability to actually solve interoperability and start actualizing data health exchange for the benefit of patient safety and driving better patient outcomes, something we've struggled with for a long time.

YS Chi:

Right, going to the point about, you know, being able to link the siloed data, how do different entities that sit on this data agree to share? What does it take for them to share that data together under this Gravitas system of de-identification?

Josh Schoeller:

Yeah, it's a great question. And there are different models out there on the market, but I will speak to Gravitas. What we wanted to do is ensure that the consumers as well as the institutions that held consumer data had complete control of that data and how it's used, as well as we didn't want to introduce any ability for a data breach or any data security or privacy concerns to come in place. So the way gravitas works is is our de-identification and tokenization engine is installed behind the firewall at the institutions that have have data. What that means is that no identifiable information ever leaves those systems. And we never get that information. So that's the first level of, I guess, overall security and in ensuring that patient privacy is at the forefront of what we're doing. The next thing that we that we created is a trusted third party exchange that allows these tokens from all these different institutions to go up and be a giant crosswalk to be set there. And if you can think about this, from a researchers perspective, say I'm going to do a research on tumour progression in breast cancer. And I know that I need clinical information from the EHR electronic health record, I want claims information from the payers, I need mammography images. And then I also need different genetic information. All four of those datasets are held in different places. And I know that in order for my study, I need at least 10,000 instances where I have that information. Now, this de-identified tokenized crosswalk, we can run a query to say how many people meet all the criteria of these things, show that number, get a release from each of the institutions that has that information to contract directly with the research firm, and facilitate that dataset creation across those siloed datasets to create a new, powerful research data set that we've never been able to do historically.

YS Chi:

And, Josh, as an expert in this field, how long do you think it would take for this to become a common practice in healthcare in the US.

Josh Schoeller:

It's evolving faster since the pandemic than ever before. And someone once told me that sometimes we go decades without significant progress. And then we make decades of progress in weeks. And I do feel like we have this this heightened healthcare Renaissance that's going on right now. It's not going to happen overnight. But I do see, I think we're gonna progress this greatly in the next one to two years. And it's going to start to be very evident to consumers, as we see and measure better health care outcomes in the next three to five years.

YS Chi:

I am hoping that I can be as optimistic as you because it's really a game changer, isn't it? Let me just go back to that one last point, from the IHI's Triple Aim social determinants of health. Give us another instance of how social determinants of health can prevent very expensive care that comes too late.

Josh Schoeller:

Yeah, I'll give you a real world example of something we're working with several large hospital systems in the US. Under Medicare, if you are having an inpatient procedure, call it a surgery. And you spend your two days in the hospital and then you are discharged. If you are readmitted. In other words, you need to be readmitted to the hospital because of any complications of that surgery, the hospital is not reimbursed for that readmission. It's a huge area of cost for both the hospital system as well as the overall healthcare system. And so many times the readmission is not because of anything that's clinically going on, it's because social determinants of health factors, non clinical factors are at play. And so an example of this is you're released and you got really good care, when you were in the hospital, you got three good meals a day, you had really nice nurses that came up and talked with you. And then you went home and you live by yourself, you're socially isolated, you're lonely, you don't have family members. And so, you know, psychologically, you start to think I need to go back to the hospital to get good care. And what we've what we can do is we can actually upon discharge from the hospital, we can utilise our analytics to tell that health care provider that this person is socially isolated. And what the hospital system can then do is say, Hey, we're going to have a social worker come out to your house and check on you on Tuesday and follow up on Thursday, and ensure that you're okay. And that greatly reduces the cost of a readmission. It also helps that individual with their with their overall health outcomes. So that's that's one real world example.

YS Chi:

And would they be reimbursed for that cost of social worker coming out to prevent any more serious readmission potential?

Josh Schoeller:

In some cases? Absolutely. Yes. In some cases, it's not as clear. But what is clear is that the $300 that it would cost to have a social worker go out and do a visit is vastly different than the $6,000 a day it would cost to be readmitted in the hospital.

YS Chi:

Absolutely. Josh, you didn't study medicine. Here you are playing a key role. How did it happen?

Josh Schoeller:

You know, I, I really got into data and analytics at a at a young age. So I started programming when I was in high school and got deep into what we could do with computer science and different data and analytics to change industries. And that was over 30 years ago, and about 10 years into my analytics and data science career. I was very fortunate to start working with healthcare companies. And what I realised is that I am very driven I'm very mission driven. And previously, when I would try doing these data analytics, I was in the financial services industry. And a lot of what I did helped ensure that you get the right credit card offer in your mailbox. And at the end of the day, when people asked me, what do you do for work, you know, it wasn't as fulfilling now I can go out and say, you know, what I'm doing every day, is I'm helping create healthier communities. I'm helping the US healthcare system and the World Health Care System, drive better operational efficiencies, and better health care outcomes. And that's purposeful work, and that that's what drives me. And over the last 20 years now in healthcare, I sit on different I sit on the executives for Health Innovation Board of Directors, it's about half MDs on that. So I've surrounded myself by very high levels of clinical expertise. And I lean on the experts for that. And they lean on me for my expertise in data and analytics and technology. And it's really been a great partnership, to try to help solve some areas where we could be doing a lot better around health.

YS Chi:

Well, this conversation makes it very clear to me how much of a mission driven organisation Elsevier is, and LexisNexis Risk Solutions is, and with people around the world committed to using data and analytics to help improve health care. We've talked a lot about the US, but there are exciting projects elsewhere, and one in particular in India, which I'm excited to talk about with my next guest. Josh, thank you so much for spending time with us, explaining about this exciting path we're on.

Josh Schoeller:

My pleasure. Thank you for having me.

YS Chi:

My next guest is Shanker Kaul, who is based in India and oversees Elsevier's health initiatives. Shanker's work is hugely exciting as it has the potential to make very real difference to health outcomes and health equity for many, many people across the country. Welcome, Shanker.

Shanker Kaul:

Morning, YS. And thank you for this opportunity.

YS Chi:

Now, when I speak with your colleagues, they enthusiastically highlight the work you and the Health Solutions team are doing to improve India's health care system. But before we get into that, can you please outline the challenges India's health care system faces and what your team felt Elsevier could do to address some of these issues?

Shanker Kaul:

Well, YS as you know, the public health system in India faces many challenges. And they are very significant challenges. Our key customers, starting with patients, frontline health workers and physicians in various care settings require support to improve access to health care, to increase diagnosis and help to accurately treat and improve outcomes for an enormous patient base. And just to give you more colour, more than 60% of rural India, which is almost 65% of the total Indian population is grossly underserved from an access standpoint, due to significant capacity constraints, lack of adequate primary health infrastructure, scarce stretched and overburdened resources. These problems have resulted in a lack of timely screening diagnosis. And this result in unacceptably high infant mortality rates, for example. Just to give you some stark facts, 8 million infants and 50,000 pregnant mothers die every year because of lack of timely screenings. In fact, 29% of day one newborns that die happen in India. 57% of women in the age group of 15 to 49 are anaemic, and these rates have risen by 4%, since the last national health family survey was carried out. And just to cap it all, 60% of deaths happen due to non communicable diseases, because they were either not detected, or they were detected too late. So that's the magnitude of the problem.

YS Chi:

These are some stark numbers. So how is this being addressed at all? I mean, it sounds like a very large problem to tackle all at once.

Shanker Kaul:

That's correct. And I guess, the public health experts, the policymakers, and the political leadership have been grappling with this, for the last 65 years. They have, to their credit, come up with a multitude of national health programmes to try and tackle these in bite sized chunks. But the needle really hasn't moved when we come to look at some of the metrics around the SDG 3 goals that India has signed up For. So that, in itself has become a wake up call. And the policymakers and other stakeholders are urgently looking at a variety of models, and increasingly looking at digital health to be able to solve some of these vexing problems.

YS Chi:

Ryan, I mean, digital is far more scalable, isn't it?

Shanker Kaul:

Yes, it is. And it is also our conviction that adopting a digital health approach, particularly in such diverse, underserved markets, would probably be the best bet to be able to leapfrog some of the core infrastructure issues. Because to be able to produce hundreds and hundreds of 1000s of doctors to build primary health and community health centres at the scale that is required to reach 65% of the population will take the next generation.

YS Chi:

Yeah, in a country as large literally physically and diverse as India, I can only assume that these problems would be very hard to tackle all at once. Now, has this issue become even worse because of the pandemic? Or is this something that is underlying constantly.

Shanker Kaul:

The pandemic did kind of accentuate it but it is, it's a problem that we have seen at large over the last 70 years. So the pandemic only brought the faultlines to the fore.

YS Chi:

So, given this background, you and your team have decided to tackle one very important aspect of it, and try to use digital or even fancier word AI systems and capabilities. Please share with us the results that came out of an initial pilot programme and just how successful that was.

Shanker Kaul:

Okay, YS, before I get back into the programme, I wanted to kind of give credit to the team. Back in 2017, after due reflection of what should our approach be to some of these big problems, the team decided to double down on three key areas. One was improving access via more screening. Second was around improving diagnosis. And the third was around improving standards of care to drive better patient outcomes at a population health level. To do all of this, the team decided to bet on our advanced clinical decision support solution, and really harnessing the power of AI to solve some of these big problems. And the solution that was used during that initial pilot was the forerunner to what is now called the clinipath primary care solution. And the goal for us was to be able to bring Indian standard treatment guidelines to the doorstep of patients in the rural setting to screen and diagnose and in the palms of the frontline ASHA workers. ASHAs which which is accredited social health activists, are women that are trained to act as health educators and health promoters in the rural community. So they really come from these communities. And they basically, their tasks are to motivate women to give birth in hospitals, bring children to immunisation clinics, treating basic illnesses and injuries with first aid, keeping demographic records. She is the communication mechanism between the healthcare system and rural population. And it was only during COVID that their role was recognised because they were pivotal in the entire COVID management and the vaccination and the great success that India had in vaccinating 1.3 billion citizens, chiefly, the credit goes to ASHAs. So that was the hypothesis. But the challenge was to prove the effectiveness in the Indian setting of technology based solutions on on, I would say two dimensions as a easy to use job aid at the frontline and second to be able to enable task shifting from the overburdened medical offices. So in 2019, we were we were presented with an incredible opportunity to showcase this through a partnership project jointly supported by the UK DIT and the Government of India. So this resulted in allowing us to conduct a pilot in Bahraich district in the state of Uttar Pradesh, which is an aspiration district. So the project study goals were defined as usability, usefulness and adherence to guidelines. And this pilot got executed the height of the first and the second COVID wave. And it resulted in some, some some great successes.

YS Chi:

So one of the most important piece of that was the under skilled and overworked frontline health care workers. Right? And that's a systematic issue today. And that critical goal of your programme is to improve the technology literacy among these staff. But doesn't having to learn to work in a completely new way only add to the workload, how do you ensure this is not the case?

Shanker Kaul:

Yep, those are those are very logical questions YS, about the adoption of technology in a milieu of frontline workers who are under skilled and almost in many cases semi literate, but just to give you a flavour of the success metrics of this particular pilot, and then I'll come down to the the, in summary, the findings. So the success metrics about this pilot project was that we were able to successfully onboard 50 of these frontline workers. And the outcomes were amazing, they were able to screen 4300 beneficiaries in six months, they were able to detect 471 out of 1057 screened pregnant mothers with high risk pregnancies. When it came down to neonates 164 of the 3201 neonatal visits resulted in urgent referral being recommended. So that was the scale of the success. And this was happening from a technology that they had never used before. And they had just undergone the basic training on not only the tool, but how to basically use the tool. Right.

YS Chi:

So very briefly, how does that technology actually work?

Shanker Kaul:

The beauty of the technology is its simplicity at the front end, I will just put that as the kind of the overarching headline. What it does is that in the palm of an ASHA worker is a smartphone. And what is happening at the backend is that the clinical reasoning engine is firing a lot of questions to the ASHA through her palmtop, based on the basic demographic information that the ASHA puts in, so age of the woman date of pregnancy, and then it starts the rules start firing in and these rules are fired by Indian treatment guidelines that have been converted to computer interpretable guidelines. And it's a very smart and a very complex engine at the back end, which also is sceptical about some of the answers and continues to check and probe in a manner that an expert obstetric gynaecologist would have normally asked the questions, so that that's the beauty. But in the hand of the ASHA, the questions are coming off on a screen in a language that she's familiar with. So we were able to translate all of these guidelines into Hindi. So the questions that were being fired were were in Hindi. So that became very intuitive and easy. Plus, also the screen. The touch screen was something that the ASHA was able to pick up and learn in two days of training, the questions come up on the screen.

YS Chi:

And so this is all driven by menu you pick pick pick.

Shanker Kaul:

Exactly, exactly. And then the pages get refreshed with questions that become pertinent because the clinical reasoning engine has started the journey around the possible disease profiles, this particular patient would probably have and then it basically starts that investigation.

YS Chi:

And the beauty of this also is that it creates no paperwork, which is another big problem of scaling right.

Shanker Kaul:

In the ideal state, this will make all paperwork redundant

YS Chi:

And yet the records are there, which is amazing. So, tell us please, what is the ambition of this programme as the pilot has been so critical to prove its scalability? What is the ambition now going forward?

Shanker Kaul:

Well, the ambition really gets captured by a major and a very ambitious pilot that is being, that is that has been conceptualised in India. And this has been done at the behest of a national piloting agency called Ease of doing business. And Elsevier has been selected as a partner. And the ambition is to digitally upskill 250,000 of these ASHA workers in the first phase in potentially nine states. So this YS, will translate into 150 million screenings of Maternal and Child disease conditions.

YS Chi:

Wow. That's quite a scale. And all because of the use of AI, and even current technology, using mobile phones.

Shanker Kaul:

Absolutely. But I would say that the pilot that we did with NITI turned out to be the to be the real eye opener for significant stakeholders in the Ministry of Health in the Ministry of Finance, as well as NITI Aayog. And they said that if we could do this, and that this was defined as a paradigm shift, then we should start to pilot it in more states in India, that kind of led to this agency, building up this hugely ambitious pilot,

YS Chi:

Shanker when we started this back in 2017, as a concept, and then put it into pilot in 19. And here you are sitting and seeing this exciting rollout. What would you say is the greatest positive surprise, from your perspective?

Shanker Kaul:

A, it's the, it starts without conviction. I think the conviction that was that received a very strong endorsement within Elsevier, whether it started in India, but it was quickly recognised as something with which we could basically deliver so much impact driving science for the benefit of humanity, which is our credo. The second was that through conducting this pilot in India, basically harnessing the efforts and the collaboration of significant Indian stakeholders, whether it was policymakers, whether it was the subject matter experts, whether it was the state government officials, there was so much of an openness to basically try out a disruptive way of tackling problems. So there was there was conviction, there was belief. And then there was an openness. And that is what was very pleasantly surprising and very fulfilling actually for us.

YS Chi:

Indeed, this is an amazingly fulfilling project that is an amazingly scalable, and intuitively easy application of technology and our domain expertise. And I would say this is a prime example of what we call Unique Contribution. Thank you so much for joining us, Shanker and to sharing this great story that is still to unfold, as you said, 250,000 of these ASHAs will be equipped and be able to make the difference. Thank you so much.

Shanker Kaul:

Thank you YS.

YS Chi:

So it's about improving access. It's about improving diagnosis, and it's about improving the standard care. And I think that these advanced clinical solutions are not nearly as difficult to the patients and to the care workers, if we put in the innovative mind and collaboration together, just as Shanker said. So I want to thank our listeners for tuning in. And please don't forget to hit subscribe on your podcast app to get new episodes as soon as they're released. Thank you for listening.