Speaker 1: Hello, and welcome everyone to the next episode of the Analytics India magazine podcast, Simulated Reality. Today, we have with us Suresh Kumar Rajasekhar, he is the VP of Technology at Optum Global Solutions. Welcome, Suresh. How are you today?

Speaker 2: Hey, doing great Kashyap, you know, nice meeting you.

Speaker 1: Yes, likewise. So, I think we are going to speak a very, you know, topic that has been discussed heavily, especially after the COVID-19 pandemic, and that is the use of data, data analytics, data science, AI, and all these emerging technologies in the field of healthcare, right. But I just want to take a step back, right. And before we kind of understand why we use data, most leaders, technology leaders such as yourself say that, first, you have to understand the problems, you do not start with the data and say that, you know, let me take data and solve it with it. What are some of the problems that have, you know, existed, because healthcare as a field, we have collected a lot of data, it may be digitized or not. And the entire digitization process, we can discuss later, but it has always collected a lot of data, what has historically and then maybe closer to, you know, 2022, as we enter 2023. What have been some of the problems in healthcare that data analytics have been identified to be the best solution? And why do you think data is the best solution for them?

Speaker 2: Thanks for asking that, you know, like, instead of directly jumping into where we can apply cookie cutter, right? Thank you. So, let's try to understand, you know, first of all, the healthcare landscape a little bit. Institute of Health Improvement, IHI, almost 15 years back in 2007, they identified patient experience of how they go through the care and overall population health and cost of care as three major challenges in healthcare. And they called it as Triple M, and it is widely popular across the board. And we have made tremendous progress with this aim, a nice guidance that was set in process. However, I would say that even after 15 plus years, some of the challenges in these areas continue to remain same, right? So, let's look at, you know, like, why is it so, right? Let's pick India as an example. If you pick India, in the last 15 years, the challenges have drastically changed. 15 years back, probably, you know, we had more of communicable diseases as a challenge. But right now, lifestyle diseases have, you know, like, taken a front seat, right? And of course, although we have overall positive improvement in most of the areas, one of the offshoot of that is increase in lifetime expectancy. In this 15 years, the lifetime expectancy in India alone, on an average, has actually risen from 64 to 70 years, which is a good development. However, it also poses a totally different challenge in the healthcare area, which is like, how do I handle geriatric care, which is totally different. And it process, it actually kind of, you know, like, poses a different set of challenges as compared to typical challenges that you would have seen before. So, the good news is, as we have progressed in multiple fronts, there is also tremendous progress in the healthcare technology or health tech in the last 15 years as well, which actually gives quite a lot of new opportunities. So, just to summarize, the challenges continue to remain the same, which is around patient experience and affordability, and how do you, you know, like, what is the outcome? How do you create the outcome for the overall population?

Speaker 1: So, what I'm getting from you is you're saying that the nature of diseases or the nature of health, the approaches taken to, for the healthcare might have evolved, but the solutions remain similar.

Speaker 2: The problems kind of remain same, yes.

Speaker 1: The problems kind of remain same, the way the problems are approached remain same. And before we jump to the next question, what were the three, what was the framework, the three things that you mentioned for the cost of?

Speaker 2: It's called tripling. It is basically, how do you enhance a patient's experience, number one. How do you improve overall population health, number two, and number three is, you know, cost of care. So, it is called tripling. And of course, there are some who also say provider's experience is also equally important. I'll touch upon that later.

Speaker 1: Okay. Okay. So, now that, you know, we have a framework, and I think frameworks are very important when it comes to kind of scalability of data solutions or, you know, their implementation. How do you think has data analytics enabled solving problems? And what are some of the state-of-the-art problems that healthcare is solving today? While that's a very broad question, if you can kind of help us understand some of the, you know, some of the aspects of how, what the approach is taken when it comes to solving healthcare problems.

Speaker 2: Sure. For example, let's pick up, you know, improving a patient's experience or, you know, like the care given or outcome of a patient, right? As compared to a couple of decades back, today, we do have availability of multitude of data, not just the data that is typically available once the patient is sick, but also if we are interested in tracking the individual remotely, we can actually have access to the data of typical lifestyle and whether the medication adherence has happened or not. And we can actually also, you know, interject in the patient's life in making sure that some of the positive aspects are continued, for example, better lifestyle and adherence to medication and so on and so forth, and make quite a lot of differences, right? So this level of detailed data that is available can actually help us in providing a customized care, which is also called precision healthcare, right? So it can actually help in providing a customized care to an individual. And of course, there are also some allied developments that has happened in terms of genomic studies. If we can actually have some of the genomic details of the patient, we can actually fine tune the medication that is to be given as well. So these are certain very quick advantages that we have. Number one, availability of data of the individual, which can actually help us to provide a more customized care. Number two, more of a precision health.

Speaker 1: Correct. Correct. So while these are the problems, right, the implementation through the use of data for healthcare needs good professionals who understand data science, right, or data analytics per se. But at the same time, there's a tremendous talent crunch. And we have talked several in the last year, there's a big talk around the entire idea of citizen data science, where it is, it means that professionals or domain experts within the field, use technology or leverage technology, how efficient or where do we stand when it comes to, you know, doctors or healthcare professionals understanding data driven technologies? And how do you think it can be, you know, how do they, how can they leverage it the best?

Speaker 2: According to American Medical Association, which did a survey of doctors and clinicians in US, almost 50% of the people who were surveyed, gave one or two symptoms of burnout. And watching burnout is very critical, because this can actually lead to a much more riskier outcome with respect to patient safety, right. So this led to some of the leaders even calling out physician burnout as a major problem to tackle. And they started talking about provider experience. And people even called out saying that to the triple aim, can we add provider experience as a fourth focus area and call it as quad triple aim, right. So if you look at, you know, why they get into this burnout, if through the interviews, it is understood that one of the top reason why they get burnout is because of the related administrative work that they need to do, very manual, mundane, day to day work of reporting what they did in that overall patient journey that they came across that particular day, right. So these are very simple learning fruits for a technologist, which can be completely automated. This is also motivation why a lot more healthcare professionals are embracing modern AI based tools, because they find that it can actually enable their job much better. And overall, it can improve the outcome as well as reducing that burnout. So, so that is a, that is a huge motivation for healthcare professional to embrace these tools. And again, you need not be a technocrat to use these tools as well.

Speaker 1: Yeah, I think the motivation is a very good point that you make, right? Them embracing technologies, while it is dependent on their work getting easier, there are various other factors that can, you know, enable this a bit better, when it comes to the usability of it, right, or, let's say that they, the technology is shaped in a manner where everybody kind of is, or it's democratized and in a way that all of the healthcare professionals are using it across, what are some of the what are some of the what is some of the advice that you will give these health, health tech companies or healthcare startups for building these tools, right, to kind of catalyze the process of healthcare professionals embracing technology?

Speaker 2: Kashyap, I'll go back to the triple aim again, you know, like, or the quadruple aim and I'll chart out some three areas which definitely technologists and startups can equally focus upon. The first one is continue to have a patient-centric approach. That's the most important thing. You need to remember that, you know, your journey is around the patient. And of course, the way we should work upon is, we should be able to anticipate the patient needs and involve the patient in their complete healthcare journey, so that we are able to provide the best care and at their most convenient location. That's another important thing that has evolved off it. The second area, as we talked about, is the provider experience by itself, right? We would like to envision a future where doctors can actually spend their time, which is their core time on what they like the most, which is basically to interact with the patient and provide care. That is what they like. And of course, with all the digital solutions, it is very easy for us to enable that particular provider experience to be much more enhanced and better. And the last, but most important factors, still the healthcare cost is still expensive and there is potential scope for making it much more affordable. For example, if we are able to steer our members towards more affordable generics, we can actually save a lot of money for them. If you're able to provide clinicians with some of the state-of-the-art decision support system with them, where by pulling some historical data, they are able to make some critical clinical decision at the time where it is needed, we can actually help in improving the clinical outcome. Overall, all of this can actually lead in reducing the overall cost and make it more affordable. So I would say that a patient-centric approach is a must and keep the provider experience to the core and look forward towards making the overall healthcare more affordable.

Speaker 1: Okay. So a patient-centric approach is the message to take out of it, right? Absolutely. At the very beginning of the conversation, we did mention, right, the overall industry is changing in a lot of ways, but at the same time, the problems remain the same. When that is the case, right, do you think that even if we keep the approach patient-centric, the problems will change over a period of time or taking a step back, do you think that COVID-19 impacted the entire approach to be taken when it comes to emerging tech in the field of healthcare? And what are some of your predictions going forward and how will it change?

Speaker 2: So there are two parts to this question. One, I'll answer if the problem remains the same, then what is it that has changed, right? And second one is, you know, like how COVID has impacted. So I'll address the first one. The problem remains the same, but what has changed is definitely a plethora of technology and tools have enabled us to actually identify risks much earlier as compared to what it was before. Earlier, it was more of a reactive approach. Now we have an opportunity to be more proactive by being able to identify an individual, what risk an individual may actually go through, number one. And let us say that, you know, like there is an onset of a disease, then right now with the kind of tools that we have, it is much more easier for us to assist with the disease progression management. And also, as I spoke earlier, we can also come out with tailor-made decisions to, you know, like help the individuals in the need. So these are some of the major changes that has happened, although the problem remains the same, the approach has changed much drastically. Now coming back to, you know, coming to the, what are the key areas that has changed post-COVID? Even before COVID started, one of the trends that was happening was care was actually moving out of large hospital towards home. That was, you know, something which was actually happening. But post-COVID, what has happened is people have started to accept telehealth, which is, you know, like today, 38 times much more in prevalence as compared to pre-pandemic. And definitely this convenience has continued to stay as one of the surveys that was done with all who leverage telehealth, almost 83% of the patients said they would like to continue to use telemedicine, even post-pandemic results as well, right? So this is a major shift that has happened post-COVID, where people are accepting telehealth and telemedicine, and they are, in fact, expecting that care should be at their convenience and their convenient location. So this is a major shift that has happened post-COVID.

Speaker 1: Yeah, I think you mentioned that people, so people are accepting technology more. And I think one of the reasons for that is that technology, healthcare professionals as well as technologists when working to build the solutions are taking a more proactive approach than a reactive approach. And I think one of the major steps for this proactive approach is, especially for a data analytics or a data science solution, is enabling good collection of good data, right? So traditionally, legacy hospitals in India, or especially government hospitals in India, they have relied heavily on just paperwork. And there's like huge stacks of paper within the hospitals, which we get to see. As a professional, as a technologist who's working in the healthcare sector, have you seen this changing, especially in India? And going forward, if India has to play a role, an active role, and it can in so many ways, point number one being the amount of data that it can generate. What are some of the steps that we need to take so that India becomes, you know, the torchbearer of healthcare and analytics, healthcare data science solutions?

Speaker 2: Yeah, I'm very optimistic what India can do. Actually, the way we leapfrogged on the telecommunication revolution, the same can actually happen in the healthcare digital space as well. Right now, most of the infrastructure that is needed is right now available. It has been set up very actively by both the central and many of the state governments as well. So I'm very optimistic about that. Now talking about documents to digitization, today, the progress in NLP has come to an extent where you have a decent level of accuracy in converting any paper to a digital, to a digital data, right? So that's not an issue at all. There are hundreds of solutions out there. The difference is only between, you know, like marginal 0.001 or that is the level of efficiency we are talking about in terms of digitization. Now set this aside for a moment. Look at the talent base that we have in this country. We have roughly around, you know, like 1.6 million plus tech pool, and it is only constantly growing. So that actually gives an opportunity for us to transform any sector that we pick up. And healthcare is one such sector, which actually is really in need of advanced analytics and a lot of digital technologies. So I'm very optimistic with the amount of talent pool that is available and the kind of focus that we have around healthcare. I think India can actually set as an example on how the futuristic digital healthcare should be provided.

Speaker 1: Okay. So if we have to put it on a scale of 1 to 10, where, you know, 1 is where we use still papers and 10 is where we are at the highest technology enabled hospital, where, you know, decisions, where healthcare professionals and technology collaborate to give the best healthcare advice. Where do you think we stand on 1 to 10?

Speaker 2: I think I would not like to rate ourselves on that. But if you ask me whether people or the institutions have done the right level of digitization, looking at all their current limitations, I think they have done their best, right? Today, as compared to not saving any records to, saving the records and scanning every paper that actually every patient gets printed out, all these efforts are actually, you know, like big time movement towards making healthcare more digitized. So I would say that, you know, right now the level of digitization is up to where people are seeing some of the major challenges. And as we discover more new challenges or as we uncover or as we, you know, close some of those low-hanging fruits, I would say, we may actually, you know, like up our digital game totally differently. So it is going to be a continuous journey. So it will be unfair for us to rate on a scale of 1 to 10 where we are today.

Speaker 1: Nevertheless, that's very promising, you know. And I think with that note, and hopefully a technology-enabled, healthier lifestyle in India, I would like to come to the end of this podcast. Thank you, Suresh, for your time and your insights. Hey, thank you. Thanks, Kashyap. Okay. Thank you. Great to meet you too.