Healthcare Unbound_Sapna Prasad: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.
Healthcare Unbound Intro/Outro:
Welcome to Healthcare Unbound, a podcast powered by Clarify Health, where healthcare's changemakers discuss ways to advance care outcomes, cost, and affordability.
Saul Marquez:
Hey everybody, and welcome back to the Healthcare Unbound podcast. I'm Saul Marquez, CEO of Outcomes Rocket and co-host of the show. Today we have the privilege of hosting an incredible guest. Her name is Dr. Sapna Prasad. She's a senior director of Clarify Insights. She brings over ten years of experience working with different healthcare organizations and pharmacoeconomics and biomedical research. At Clarify, Sapna leads a team of eight analysts clinical informaticists with the responsibility of delivering data-driven insights to Clarify payer and provider customers. We're really privileged to have her here on the podcast to talk to us about best uses of data, practical applications and really just so excited to have her here. So Sapna, thanks for joining us today.
Sapna Prasad:
Thank you for having me, Saul, really excited for our conversation.
Saul Marquez:
Likewise. Before we kick it off, Sapna, one of the things that I really enjoy is learning more about the people. If you can just share what got you into the healthcare space and what is it that makes it your North Star?
Sapna Prasad:
Yeah, I was fortunate in that I came into healthcare almost from birth, so my parents both work in the healthcare industry. My dad is a physician-scientist, my mom was a bench scientist, so healthcare has really been where I grew up. I have fond memories of working in a lab with my mom when I was very young and really over the course of my life and my education have had a chance to explore, is it the bedside patient care that I would really be interested in? Is it the more system-level interaction that I really think I could make a difference in? And it wasn't until I was in graduate school and thinking very seriously about how do I make a career out of all of this interest I have in health that I really came to understand just how different the US healthcare system is from other systems in a country. And there's some really great pros and cons to that, but it really made me have this interest in system-level thinking, how all of the pieces in healthcare work together, and then most importantly, everybody cares about the numbers. So what does the data say and how can we continue to leverage data in a way that we can make data-driven decisions? So it's really been this journey from the very micro level of like patient care to the very macro level of let's think about how we can change the system that's led me to this very unique company called Clarify, where I get to interact with all of those facets of healthcare.
Saul Marquez:
That's great. Thank you for sharing that. So it really started from when you were born and now you mentioned several things, system-thinking, thinking about the data, and then there's the patient journey. I think a lot of our conversation today, I think would be great if we focus it on and the patient journey. So let's start there, what are patient journeys and why is it important for us to understand them?
Sapna Prasad:
Sure. So patient journeys are not new in healthcare, for those who have been working in healthcare for a long time, there's something that we've talked about, we've built, we've addressed, we've identified over the course of the existence of the healthcare system here, but they really have evolved over time. So when we think about patient journeys, we're thinking about every interaction that a patient has with the healthcare system. And that traditionally started with a very clinically focused, almost episode-based approach where you would think about when did the patient come to the physician, what's the course of the care that they had with that physician or at that hospital system? And what are all of the things that happened? And ultimately, patient journeys are about patterns, right? So we wanted to understand how are patients accessing care, how are they seeking care, what are their outcomes, what's happening to them while they are a patient? And it's really, I think, the building block of a lot of the initiatives we see today, like value-based care, where without understanding how patients are accessing care today, without that benchmark, we really wouldn't have an opportunity to understand inflection points and figure out where can we drive change in the system and make outcomes better for patients.
Saul Marquez:
Yeah, that's really great and it's all the touchpoints, and I think it's, a lot has changed, right? The way that patients, people, we access the healthcare system. Sometimes it starts with Google and it just continues, right?
Sapna Prasad:
WebMD, yeah.
Saul Marquez:
So WebMD or the many platforms now that exist that help diagnose things that are happening on your body or your kids, for your kids. So what was the traditional model of understanding patient journeys?
Sapna Prasad:
Yeah, I think the traditional model is, as much of sort of data and healthcare was a little bit more siloed. So again, focusing on kind of the clinical things that we could, we could account for even from a claims perspective. So what are the activities that are billed? What are the activities that are documented in a chart? How do they define this particular episode of care, and particularly limited to maybe a specific specialty like oncology or a specific institution, because that was really the limits of our data at the time. And I think to your point, not, as healthcare and our interaction with healthcare has changed, where you see patients who have moved from, in some cases being a passive user of healthcare to really coming into their doctor's office with printouts of here are all of the things I have. Can you run these tests for me? Advocating for themselves, really having more resources, having direct-to-consumer marketing, all of those things have really changed how we can think about patient journey to where even in our work at Clarify today, it is definitely focused not only on what happens to that patient in that interaction with the physician or in that interaction at the hospital, but how do you even get that patient to the hospital? So what are all of the factors that are going on outside of their existence as a patient that might lead them to access care in an efficient manner? Maybe to let a condition go undiagnosed for quite a period of time. So I think the benefit of where we are today is that, A, there's so much data available and so many different types of data, but also that for us as consumers and patients, our interest and our appetite in consuming that data and having a front seat in how we access care has also really shifted. And both of those bring us to a really interesting dynamic where I think patient journey is maybe more powerful than it ever really has been before.
Saul Marquez:
Yeah, that's really well said, Sapna. And it could be overwhelming too. There's data everywhere.
Sapna Prasad:
Absolutely.
Saul Marquez:
And just curious what your thoughts are for any provider or payer executives out there trying to wrap their brains around how to do this, or maybe they're doing it and they're looking for better ways. How does one segment the data? What recommendations would you give us to to think about this more categorically in an organized way?
Sapna Prasad:
Yeah, it's a really great question. It's something that we struggle with our customers on a daily basis. And I think to your point, anyone, even as a consumer of healthcare price transparency data is available today for us to be able to use. And even as somebody that's worked in healthcare for over a decade, that's hard data to really go into and sort through and make a judgment call from. And so I think the recommendations I would have are, there's really two approaches. Sometimes you want to let the data speak for itself. And that's a situation where we would take the millions of claims that we have, map them to touchpoints, inpatient, outpatient diagnosis, time to diagnosis all of the very tactical touchpoints that we see in claims data that we know have occurred to the patient. And for a provider or a hospital system, you could really focus that on the patients who are coming to your institution, orders and maybe even for specific. So I think that's an opportunity to let the data speak. And I think this alternative approach is to say I have this targeted question about a specific patient population, how quickly they're getting access to a procedure, what their outcomes are, and really drilling down to identify those specific patients who have had that specific procedure and to see what their, to measure their outcomes.
Sapna Prasad:
I think the really necessary component for providers and payer executives is to bring that clinical lens to what we see in the data, right? So data can tell you lots of stories, you can really make a data set, say anything, but you ultimately want the patient journey to be relevant to the physician, executive, to the payer system so they can understand how to use it for change. And I think that's where today on my team, for example, in lots of organizations that have this much data, you do see a lot of clinician-scientists who can take all of that data and help us put it into context for what is appropriate care, what is, what are good outcomes, how do we measure what we're seeing in the data against those very real clinical benchmarks and patient outcomes that we should care about. Because ultimately that's what we want, right? We want our patients to get better care, we want them to get that care faster and most efficiently and the most affordable way. And that really does require, in addition to the data, having that clinical lens for what's important here.
Saul Marquez:
That's really great, Sapna, and folks, just to reflect on what Sapna said, it's very, I love how simple you made, it's let the data speak, it may reveal things that maybe you don't know about and you push it up against the benchmarks. Clarify has so much data, you push it up the benchmarks and see how you're doing, how you're performing. Let the data speak or come in with a problem and try to find solutions to your specific problem and the world's your oyster here with that type of guidance. So I love that, Sapna. Thank you for grounding us in how to think about this better. What is the inclusion of technology mean to how we think about patient journeys?
Sapna Prasad:
Yeah, when I started and I think maybe many of our listeners, right, when healthcare started to evolve, it was really patient charts, right? Handwritten notes. I remember collecting data as a researcher, like going into a patient's room, asking them sometimes two hours worth of questions to like, very burdensome data collection, if you will, to get us to a point where we might be able to understand just a piece of what we're able to do today. So I think technology has, first of all, made that data available, right? You don't even have to work for a healthcare organization necessarily. If you're interested in consuming healthcare data, there are so many ways to access it and there are so many types of data, so many millions of records of data that can be accessed, which I think is really amazing. So technology has enabled us to access that data, I think first and foremost. But then second, really link that foundational data set, which at Clarify is our claims data, to other types of data. So maybe we now want to understand what type of testing patient have and what was the outcome of that test. What types of resources do they have access to in their neighborhood? What type of education do they have in their family? Are they living in a home they own or they rent? So the ability to link data sets has really, I think, changed the game in terms of patient journey, because again, you're now widening that perspective not just from when the patient comes to your physician or comes to your institution to say, what are all of the things that are happening to them beyond kind of those walls, if you will.
Sapna Prasad:
And then lastly, I think all of the conversations recently around ChatGPT, AI, ML being able to take those patterns that we see in the data and then predict what could happen in the future if we tweak one part of this patient journey, if we got the patient in to see the physician faster, if they were in for follow up in 15 days instead of 30 days, if they didn't have a readmission, how might that change outcomes for the patient? How might that lower cost? So it really gives us the ability to now move forward and say this would be an optimal journey for this type of patient, for us to meet those criteria which are better outcomes, right? More affordable care, more efficient care. So having the data is great, technology is definitely enabled that. But I think the linking of the data and then being able to use those patterns to predict future outcomes is just game changing.
Saul Marquez:
Yeah, that's really, that's super interesting. And really it's the idea of getting all the data in, making a hypothesis that, hey, if we do this, potentially modeling it out in a way that could help you say this is something we can do, let's do it, or, oh, that doesn't look too good. what if, is that? That's what we're talking about here, right?
Sapna Prasad:
That's absolutely right. Without having to change it for a patient, which is sometimes hard in healthcare, like how do you think about using a patient as a case study, right? Intentionally changing levers without knowing the outcome, I think a lot of us would pause at the thought of that, especially if it was ourselves or a loved one.
Saul Marquez:
Oh, yeah.
Sapna Prasad:
You're going care. But to your point, looking at these types of predictive models would allow us to say with some certainty, we could never predict exactly what will happen, but with some certainty that this might be the outcome, or that we feel 50% confident that shifting this one lever would have this impact on your patient, on your organization, on your physicians. And I think, you know, in addition to the patient being important, it's also a little bit about how do the physicians want to interact with the system, right? The way they have had to interact with care is so differently with the types of incentives that we have. Hospitals are always on a mission to be more efficient. So I think there's a lot of reason for an interest in knowing what you're getting into, if you will, with some informed decision making before you actually go out on a limb and change something in your institution.
Saul Marquez:
Yeah, for sure. It sounds like a great tool set and a great set of data to actually work with. You mentioned this idea of bringing in data from a lot of different sources. It almost blurs the line between what was provider or payer and what is consumer type of work and data research. Do you care to comment on that and what's happening?
Sapna Prasad:
Yeah, it's a very interesting question. I think sometimes when we're working in the data and you are bringing in data that is outside of kind of the clinical claims or the utilization claims, it can make you pause and think, does somebody out there have my data, right? My data about my education, where I live, how I access resources, things like that. So it is definitely, when we think about data today, you can't think about it without that conversation of what does it mean from a sort of privacy perspective, if you will, and just the ability to identify a patient. I think in the ways that we consider it, it is, hopefully, for the better of our population, right? It is definitely about how can we think about this population that's maybe historically underserved, that maybe we didn't even know why they weren't coming in to to seek care or why they weren't able to seek care. And a very simple example of that is we've done a lot of work with some of our customers to identify infusion centers for individuals who maybe need to go receive cancer treatment every 2 to 3 weeks. Big cancer institutions exist, but they're often very far from patients who are in regions where that's tough to access. It requires a caretaker, there's so many factors to consider. And I think just being able to say, my patients are clustered here, within five miles of where they are, is there an infusion center or is there a need for an infusion center that would then make it easier for my patients to be adherent to their therapy, which we would then say could offer them better outcomes?
Saul Marquez:
That's really interesting.
Sapna Prasad:
Focusing on what's the good that can come from us thinking about the patient as, very holistically, right? Which in public health, that's the mantra, which is it's not just about the physical, but it's about the mental, it's about the social, it's about the psychological and being able to see some indication of that in those data sources that we wouldn't traditionally use, I think is very powerful and still untapped. There's a lot we have to learn about how we use that data, but it is helping us widen our lens and helping us to think about things differently than we have in the past.
Saul Marquez:
That's really great and it just brings my mind to the topic of access and equity and really how data can also help us. And I know there's a lot of health systems and payers focused on on driving access and equity. How does data help with that?
Sapna Prasad:
Yeah, we've seen conversations we've had with patient advocates, with organizations that have patient assistance programs to help with things like picking up patients, to get them to an appointment, to making sure that they have a home health aide who comes into their organization. And I think data can really help you understand even at the very sort of singular patient level, what are the types of interventions that many health systems are already offering? There's case managers, there's social workers. These are not necessarily things that we have to invent, but directing them to the right patient at the right time. So being able to say even the data we're seeing that historically this individual or this type of patient hasn't been able to make their appointments because of this barrier that they have. And it may have been previously that a phone call would be made and maybe nobody answers the phone because they don't have a landline, who does anymore? But they have a cell phone and they visit this organization every Tuesday. So just being able to understand how to direct those resources that people really want to get to the patients who need them, to the right patient in the way that's going to be helpful to them. So is it that they need to come in to see you? Can you deliver the medication at home? Can it be something that's done over telemedicine? I think data allows you to take those resources and make sure that they're being optimized in the best way that they can be.
Saul Marquez:
That's great. Thank you, Sapna. Look, you've certainly given us a lot of insights around how we could better understand patient journeys, use data to help not only improve outcomes, but make care more costly, increase access. There's so many things we could do with this. And then you also touched the tip of the iceberg of physicians, right? And how we could help our physicians with the care that they deliver and helping them make better decisions overall, so I can't thank you enough for today. If we wanted to make this actionable for the folks listening, what call to action would you leave them with?
Sapna Prasad:
Yeah, that's a tough question to pick one thing, but I think what I would say is really use the data, right? We have so much data at our fingertips. It can help the patient, it can help the physician, it can help the hospital system. Ultimately, all of those things, I think, can transform the way that our healthcare system works today. But I think it all starts with being open to asking the questions of the data. And to the earlier point we spoke about, letting the data show you things that maybe we didn't expect to see. And that's one of the things that I personally find so exciting about healthcare is it's every day that we're in the data and there's some new insight that has popped up and that really allows us to be on the forefront of innovation and to continue to work towards the things that are important, which is better outcomes, more affordable and more efficient care.
Saul Marquez:
That's fantastic. Sapna, I can't thank you enough for today's time on the podcast. Really looking forward to staying in touch with you and if anybody has questions for you or wants to connect, what's the best way for them to do it?
Sapna Prasad:
Absolutely. I'm on LinkedIn, also available at Sapna@ClarifyHealth.com. I love having these conversations and talking more about data, so we'd love to chat with people more and thank you so much for the opportunity, Saul, it was great to have this conversation with you today.
Saul Marquez:
It was a pleasure, Sapna. Thanks for being with us.
Healthcare Unbound Intro/Outro:
Thank you for listening to Healthcare Unbound. We hope today's episode was insightful. If you want more information on how Clarify Health can help you, please visit ClarifyHealth.com.
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