AI-Driven Patient Visibility and Risk Prediction Ft Meghna Misra

Transcribe 

[Marty]

Hello and welcome to the Digital Health Transformers podcast. This series explores innovation in healthcare, one conversation at a time. I’m your host,  Martyand today we are joined by a truly, truly, truly distinguished guest whose work bridges technology, product leadership, and healthcare outcomes.

So, our guest today is [Meghna Misra], Head of Product at ClaritasRx. Meghna is a business-driven product executive with 18-plus years of experience transforming innovative ideas into market-leading SaaS and mobile products. Her career blends a strong engineering foundation with leadership roles at both startups and at industry leaders such as Intuit, Microsoft, Pure Storage, and NetSmart.

She is recognized for her ability to balance risk with a keen sense of product strategy, having launched groundbreaking zero-to-one products and scaled complex healthcare platforms to deliver better visibility and improved patient outcomes. Today, we’re going to discuss how AI is reshaping patient visibility, identifying risks before they happen, and transforming healthcare delivery. Meghna, thank you so much for joining us today.

[Meghna Misra]

Thank you,  Marty for having me.

 [Marty]

You know, your career spans startups and large enterprises, and you have led complex healthcare and technology products, and I’m wondering what inspired you to focus on AI, you know, above other technologies, especially, you know, when it was early and, you know, now everyone’s using AI, but before not everyone was using AI. What inspired you to focus on using AI to improve patient visibility?

[Meghna Misra]

Oh, that’s a great question to start this podcast with. You know, for me, it really comes down to impact. Throughout my career, whether it’s been at startups or large enterprises, I’ve seen how fragmented the healthcare system can be and how difficult it is to get the full picture of the patient journey.

And that lack of visibility, that often translates into delays in care or missed opportunities to support patients. And so, like you said, you know, AI obviously is the hype right now, but I have been focusing on this for a while now, and what inspired me about using AI is its ability to cut through that complexity, to bring together data from different sources, the ability to surface insights faster, and make this super complex process more proactive instead of being reactive. And then at ClaritasRx, that’s the company I’m at right now, I’ve been especially motivated by the chance to apply AI in a way that brings biopharma and specialty pharmacies together, helps them better understand where patients are getting stuck, and how to support them effectively.

So as you know, ClaritasRx, we are the leading providers in the specialty and rare therapy markets, also CAR-T, and so these are patients who have a need to get unblocked and get to therapy faster and stay on therapy faster. So for me, it’s not AI for the sake of technology, I mean, that part is definitely super cool, but it’s about using it to make a very real difference in our patients’ lives.

[Marty]

Oh yeah, you know, I think that just makes me happy when I hear that response, because I see them, you know, I’m scrolling LinkedIn, I’m doom-scrolling LinkedIn, and it’s a lot of, you know, because you said it straight up, it’s not AI for the sake of technology. You know, a lot of stuff out there I feel like is like AI for its own sake now, you know, just so you can slap it on your company title, TeleVC, you know?

[Meghna Misra]

Yeah.

 [Marty]

I think I saw a post earlier, it said, if you haven’t changed your company’s domain extension, like .com.org, to .ai yet, you’re not going to make it in 2025. So, you know, yeah, just hearing that, like, you know, you’re really thinking about how do we apply AI for a problem, I don’t know, that’s really nice. So, yeah, just a little reactionary response there.

You know, another question I had is, you know, how has your experience building these digital products in health care and beyond throughout your career, how has it shaped your approach to designing tools that are going to, you know, proactively identify patient risks at ClearToss?

[Meghna Misra]

You know, I’ve been building products for a long time and I have learned a lot. What I’ve specifically learned from building digital products in health tech is that the strongest products start with truly understanding the problem at their core. So I focus on building products that proactively identify patient risks.

I do that by embedding predictive insights directly into workflows. So care teams can act before risk escalates. You don’t want to take your users out of the workflows.

I do believe in designing products that take a design-centric approach, digging into patient journeys and user workflows, like I talked about earlier, to uncover these friction points and opportunities for timely intervention. That means combining AI-driven models, because they do work, seamlessly integrating data and then applying human-centered design, making sure that every insight that we surface, every analytic that we provide to our users, they drive meaningful action. And so for me, product leadership is about building with intention, aligning technology, empathy and rigor and using those three pillars to empower teams, reducing friction in the product and then ultimately delivering personalized, measurable outcomes.

I mean, the goal here isn’t just to build products, like I said, or just identify risks or surface insights. It’s really about transforming how we think about care and doing that proactively as opposed to reactively.

 [Marty]

Yeah, yeah, yeah, yeah, because, you know, you think about what AI is good at, right? It’s like prediction, you know, using all this data, you know, putting it through a big old GPU data center, bloop, bloop, bloop. And then you have a…

[Meghna Misra]

Applying all your models to it. I think, you know, everybody is sitting on a lot of data. It’s what you do with that data.

And then how do you build these products? Like how do you apply that craft of product management where you’re building products that truly delight?

 [Marty]

Yeah, yeah, yeah, yeah, no, that’s, yeah, anything with like predictive, you know, I’m a big Brian Johnson fan and he’s really bullish on AI because he uses it, you know, Brian Johnson, right? The, yeah, the man who’s trying to live forever. He, yeah, he’s like, I think AI is going to make us immortal because it’s so good or like live really long, bigger than any other medicine, because he said, you know, it’s like that, you know, it’s so good at predicting things, right?

Taking all the data, predicting things so we can predict, you know, what’s going to make us healthier.

[Meghna Misra]

Yeah. And it can do a lot of predictions and really not just cool predictions, but impactful ones. I mean, we have so many use cases and case studies from those use cases where we’ve applied AI and seen tangible and meaningful impact in our patients’ lives.

Yeah, well, someday I’m going to be happy to share those with you.

 [Marty]

Yeah, no, it’s great. It’s great. It’s great.

You guys, Tempest has been like, have you seen Tempest? Tempest stock? Tempest stock is crazy right now.

[Meghna Misra]

No, I haven’t. I’ll look it up once I get a chance.

 [Marty]

Yeah, no, but like this AI, I think, I think.

[Meghna Misra]

Look how Nvidia is doing this, the stock prices through the roof. There are so many different companies and we do leverage a lot of the models. We do leverage the improvements, not just in building our product, but also how we do our work, analysis of data, making sure that, you know, we have the right tools available for our customer success teams.

So we are we are at the forefront here, not just in building our product with AI baked in the DNA, but also in leveraging tools that are out there.

 [Marty]

Yeah, no, that’s that’s great. That’s that’s I think I’m going to try to invest in Claritas whenever it goes public.

[Meghna Misra]

I will, I will let the team know that they’ll be happy to hear.

 [Marty]

Yeah, like my like a hundred bucks.

[Meghna Misra]

We’re still venture backed, but yeah, private company. But I am quite happy with the way things are going.

 [Marty]

Oh, yeah, it’s I think it’s going to be a big thing with health care, it’s nice. Yeah. So, you know, AI has been transforming health care decision making like we’re like we’re talking about.

And so from your perspective, then what what are the most impactful way? We already kind of touched on this a little bit. What are the most impactful ways that AI can improve the patient visibility and predict the potential risks before they escalate?

But like the more particular ways, like what is AI really good at right now when it comes to prediction? Like, you know, maybe it’s not too good at predicting cancer, but it’s really good at predicting diabetes or something like that.

[Meghna Misra]

Yeah, and I’ll keep my response specific to what we’re doing, because, again, we are talking about leveraging AI for real use cases like use case backed. I do think AI is really becoming a force multiplier in health care, especially in health care. It’s helping us see patients more clearly by connecting the dots across, like I said, you know, a lot of fragmented systems, pharmacies, clinics, access programs, hubs, specialty care.

So what it’s doing is it’s helping us see that patient journey more clearly and giving us real time view of the whole journey. And that kind of visibility means that is quite unprecedented, that we can spot these risks super early on. So, for example, you know, a refill delay or a coverage hurdle, like some financial hurdle or signs that a patient is not as engaged in the therapy as they should be for it to be effective with maximum benefits.

And so because we can see these risks early on, we have the ability to surface those and act before it affects our patients care. And the real shift here is from hindsight to foresight. So AI can predict where barriers might appear, but also why those barriers are happening.

So, you know, it’s one thing to say your patient is at risk. What’s more important is your patient is at risk. We expect this risk to manifest three months from now.

And here’s the reason why. So what we do is that we get all the data, you know, obviously data that we have the rights to. We also bring in social determinants of health data.

We layer all of this. We run it through our models and we are able to come up with like really our accuracy rates are very high and our precision is fairly good, too. So we are able to do all of this so teams can step in early and personalize support.

And like I’ve said before, you know, AI shouldn’t replace empathy. It should amplify it. As a product leader, I’m super excited by a future where AI gives in health care, AI gives every care team the foresight to act early and every patient the support that they need to stay on therapy and, you know, just be on a plan and a path to better health.

So I’m very bullish about the future of AI in health tech.

 [Marty]

OK, yeah. So it’s really good at like detecting whether there’s going to be a cover turtle. I’m getting like a refill delay, these kind of like really annoying administrative problems that or, you know, kind of get in the way a lot of the times.

That’s that’s really important. I think that’s actually I think that’s great. That’s better than what I was thinking, which is like just straight up like on the ground predicting someone’s disease, because, you know, these things are what gets in the way a lot of times.

[Meghna Misra]

But predicting diseases is also happening where, again, we’re not and this is not something that we do, but there are many companies out there. And to my earlier point about it’s not about replacing the doctors, it’s not about replacing these health tech professionals who know what they’re doing. It’s about getting the right tools, amplifying it, amplifying the patient experience.

I get my lab results and yes, I will talk to my doctor, but I’d like to know what’s going on there. And I can help with a lot of that, too.

 [Marty]

Yeah, yeah, no, it’s it’s really it’s really nice what’s going on for the patient, you know, for the patient, for us, you know, we are all patients in the health care system. That’s true. That’s true.

That’s true. That’s true. Yeah, I mean.

It’s it’s going to it’s going to make us healthier. It’s nice. Probably, you know.

Solve a lot of the bureaucracy and or not bureaucracy, what’s the right word?

[Meghna Misra]

Yeah, the administrative complexity, all the complexity that health care has. And it’s not just about patients, right? It’s about all the providers who are working so hard, the caregivers, the payers, the entire health care ecosystem.

 [Marty]

Yeah, yeah, yeah, for sure. Yeah, we do OSP, too, and at OSP, like I see, like I see the numbers they put up, these guys are good. Like I’m like, wow, you know, there’s a real demand for people reducing this this crazy complexity we got in America, at least the health care system.

You guys are doing it, too. And it’s good to see. It’s good to see the markets, you know, doing its thing, working.

It’s all of these problems. So, but yeah, OK, so then how how can the health care providers and payers use these insights to improve outcomes, but then also balancing, you know, their their cost and their operational efficiency and these these kind of things that providers are going to face and payers?

[Meghna Misra]

And that’s a great follow up question,  Martyyou know, because just visibility that I talked about earlier, visibility, just visibility alone isn’t enough. The real value comes when providers and payers can act on those insights. And with AI driven analytics, they can make much more strategic decisions that balance these outcomes that we talked about with cost and with operational efficiency.

So, for example, they can spot when patients are getting stuck, whether that can be, you know, issues to the medication itself, adherence or even coverage, and then focus resources like resources, whether no matter which industry you’re in, resources are always tight. But having that level of transparency and visibility, it allows them to focus resources where they’ll have the biggest impact. So, you know, they can benchmark performance across networks.

They can streamline coordination between different stakeholders. And and you talked about the administrative burden there. And all of this then reduces the administrative friction that slows care down.

And what’s powerful is that AI turns this into a continuous feedback loop. So it measures what’s working, what’s not, and then how these programs can be refined in real time. If you think back to the time, what is now the dark ages without AI, that entire feedback loop took literally months to happen because we just didn’t have access to the data.

And even if we did have access to the data, we weren’t able to compute fast enough. And so ultimately, these insights will help organizations, you know, spot patterns. It’ll help them spend smarter, not just more.

And then that in turn is going to lead to improved patient experiences, reduction in based and then generally accelerating the path to successful treatment for the patients. So all in all, I do believe that this is, you know, the the benefit is across not just the products that are being built in the market, but you can see these far reaching implications on people’s health, but also within the peers, within the providers and also the cognitive burden, you know, the reduction in cognitive burden for folks in the administrative roles. You know, I want to come in the morning and see a list of I wish my email based on all the emails that have come in through the day, I get a list of your make.

Now, here are your tasks that you’re the top tasks that you need to focus on. I’d love to get that summary. And, you know, many of our products do do that today.

 [Marty]

Yeah, that’s great. You know, you know, isn’t it doesn’t it kind of freak you out when you have like a doctor who’s like he’s like, I’m a little bit overwhelmed. I’m stressed out.

It’s like, what do you mean you’re giving me drugs and stuff? You got to be on your game. You can’t be so, you know, if they have all their data there, it’s easy for them that, you know, as a patient, it helps with cost management, you know, efficiency, like why our health care costs so high?

[Meghna Misra]

Because a lot of time is spent in administrative tasks.

 [Marty]

Oh, yeah, all the coding, all the this and that, I don’t know. Oh, my goodness. Yeah, no, it’s great.

It’s great to see, you know, it’s great to see organizations like Claritas in the industry fixing it up. You know, really fixing it up. You know, a lot of people talk about, oh, we got to change policies and change this.

And it’s true, you know, but you guys are you guys are you guys are just like, you know what? We’re just going to build, we’re going to build, we’re going to fix this by building. And you guys are doing that, guys are making good money.

And then you guys are solving real problems. It’s pretty awesome. You know, and even just talking to you, like you understand, OK, we’re going to use AI to do this.

We’re going to use AI to fix that. And it’s it’s good as a as an American patient. I’m very happy hearing these things.

You know, you know, and then talking about policy and policymaking, what what role do you see, you know, big health care leaders and policymakers, what role do they have then in ensuring these AI solutions are, you know, effective, make sure they work, they’re not causing some some dystopian problems, make sure they’re transparent, like, you know, people know what’s going on, making sure they’re equitable because, you know, we’ve heard about the problems with biases and whatnot in AI, so effective, transparent, equitable. How do you see health care leaders and policymakers making sure that these solutions stay effective, transparent and equitable?

[Meghna Misra]

Yeah, so, you know, you’ve called it out beautifully. I strongly believe that health care leaders, as well as policymakers, have a huge role to play here. So for health care leaders, that means driving that culture of accountability, making sure AI decisions are explainable, that data that the AI models use, that data is of high quality and it’s diverse, and that the technology actually works for providers, for payers and patients and not just around them.

So I think that’s something that health care leaders really have to pay attention to. And as far as policymakers go, I’d say for them, it is about creating frameworks. I’m not going to use the word regulations, but rather frameworks that encourage innovation, but also encourage safe experimentation while making sure that patient privacy is protected, while making sure that, you know, there are mechanisms and these frameworks are preventing bias from creeping into the algorithms.

So that structure is required. And I think policymakers should be paying attention to that. You know, tying it back to what I said about health care leaders, the quality, it’s garbage in, garbage out.

The quality of data becomes very important. The diversity of data becomes very important. And then the cleanliness of data becomes really, really important.

And so making sure that the data that’s being fed into these models is accurate, it’s diverse, it is, you know, in a lot of ways, free of bias, but also having the structure built into enhancing these models. So together, between the health care leaders and the policymakers, I mean, at the end of the day, they do need to work together because only together can they foster collaboration. They can promote, you know, high ethical standards and ensure that while doing so, AI’s full potential can be harnessed to improve outcomes for not just a few patients, but for every patient.

So it goes back to that point you raised about it being equitable, it being free of bias and working for every single person, not just a select few.

 [Marty]

Yeah, you know, I love, I love, I love that you said, OK, let’s not, let’s not think about it like creating regulations. Let’s, let’s think about creating frameworks. I really love that personally, because like, yeah, I feel like if you set out like, OK, I’m a regulator, I’m going to create regulations.

You’re just going to, you know, you’re going to say you can’t do this, you can’t do that without end, even when it might hurt the patient, you know. And so, yeah, creating a framework so that you’re thinking about how do we, how do we focus on regulating the right things, you know, like not just thinking about, all right, well, what’s regulate, but like what should these regulations look like? What should not be regulated, like a framework, you know, how it’s going to actually I think that’s really smart, you know.

[Meghna Misra]

And that’s why it’s important for them to work together, because policymakers, they are not technologists, they are not health care, you know, the health care leaders understand the space much better than the regulators and the policymakers do, which is why it’s super important for them to be able to work together and understand the context there.

 [Marty]

Oh, yeah, yeah, yeah, for sure. Oh, like I, yeah, I watch the YouTube videos like of the live, like the Senate, you know, I don’t want chat GPPT to, I don’t want chat GPT, they always say the, they always say the GPT part wrong. It’s so funny.

Okay, 90 boards.

 [Marty]

2025, but in 2023, you know, and they, they, you know, if you, if you, they, they, you know, they don’t want people to know this, but they like in 2023, 2022, they’re like, I don’t want chat GGP to be my doctor. Right. But if you’re in the field, you know, like, okay, well, yeah, but the technology is going to get better.

And that’s what all the technologists said. These guys are like, no, stop it, regulate it, you know, but that’s like, just your point, you know, because at the end of the day, they’re all supposed to be helping the people, the patient. Right.

So, yeah, but no, that’s just, that’s just, I had a light bulb moment when you were talking about that just there. I thought that was very, very smart. So could you, so then, you know, on that, could you share some examples of how, you know, AI driven tools have successfully, well, improved the patient visibility that you guys have seen or prevented any adverse events?

Some examples of that?

[Meghna Misra]

Yeah, absolutely. You know, like I said earlier, AI is giving care teams that real time visibility into patient journeys, spotting delays, adherence issues, or potential drop-offs before they actually happen. And also, like, why is that adverse event or why is that risk happening?

What’s the risk factor behind it? And the results that we’ve seen at Claritas RX are very tangible. You know, we’ve been able to, I would say, quantifiably, yeah, anecdotally, everybody says we have made a difference, but quantifiably, we improve brand performance with our customers.

And I’m going to quote some numbers here where we’ve actually been able to achieve 20% increase in fill rates and greater than 17% boost in refill rates. And that’s huge for our segment where, you know, we are really focused, hyper focused on the rare and specialty disease, oncology, and CAR T. Those are very material numbers and percentages.

And so just by having these models for discontinuation prediction or refill abandonment or, you know, abandonment or cancellations, we are able to give insights to our customers and they in turn do timely interventions. And that care coordination really helps patient not just start therapy, but also stay on therapy longer, which in turn means it’s really helping them. So, and I mentioned this earlier that we’ve got like case studies where our AI models have been able to predict risk and it’s really changed the way the team has worked with the patient and gotten them back on therapy.

So it’s use case that we see these tangible results and hence we are making even more investment in ensuring that our product is driven by many of these machine learning capabilities and models.

 [Marty]

Yeah. Yeah. You know, and yeah, but like, you know, it sounds like numbers, they’re like 20%, 17%, but I remember the last time, you know, I didn’t take medication, I wasn’t…

[Meghna Misra]

Greater than 17% because it varies, you know, from brand to brand.

 [Marty]

Yeah. Yeah. Um, uh, but like, yeah, I, I remember the last time, you know, I, I had to take a medication.

I didn’t take the medication. I was having like, I was having like, like, um, shivers, like, like my hands were like cold, like my feet were like super cold. Like this specific thing, I was like, what is going on?

What in the world is going on? Because I was having withdrawals from the sink and it was like, am I going to die? And so just thinking that, you know, it sounds like, oh, it’s a 20% increase, right?

But, but it’s really, you know, it’s preventing that it’s preventing, you know, real symptoms when, when you, when you help people, um, you know, take their meds. It’s pretty awesome. Um, you know, just think about the actual tangible, what’s going on there.

It’s really making, you know, saving a lot of people from having a bad day. It sounds like. Yeah.

So that, that’s, uh, that’s pretty nice. And then, and then looking ahead then. Okay.

So what, what trends are you seeing then in AI and patient based, uh, visibility? Uh, what trends do you see shaping, uh, healthcare delivery over the next few years? Especially because, you know, we were talking about AI now or AI in 2023, 2024, it was like kind of clunky.

It was kind of, you know, row body. It was like a, like awkward, like it hallucinated all the time. Um, and then now compared to now, and then, okay, what’s, what’s GPT nine going to look like?

It’s going to be like Einstein all the time. Uh, and so we, we really want to know then. Yeah.

What, what trends, uh, in AI, uh, do you see shaping healthcare delivery over the next few years? Given that context.

[Meghna Misra]

It’s interesting you asked this question. We were actually having a discussion just earlier this week, um, about this and, um, the way I, um, think about these trends, like, um, there are three big trends in how AI is changing healthcare and especially in the rare and specialty disease and oncology space. So, um, the first one I would say is just predictive visibility.

Um, we, we know predictive analytics exists, um, AI is giving us the ability to see issues before they happen. So instead of looking back, like I mentioned earlier on, you know, why a patient dropped off therapy, we can now predict things like, oh, prior authorization is going to be denied or abandonment risk early on to actually intervene. So that’s the first one.

The second is turning insights into action. It’s not just about knowing who’s at risk. It’s about knowing what to do next.

And that’s where, um, next best action models are helping field and patient services team take the right steps at the right time. And then the third thing I would say is, um, just trust and transparency. So in these high stake areas, I mean, these are very high stakes.

No one wants a black box. The AI that truly makes an impact will be the kind that explains why it made a prediction and how to act on it. So overall, I think, um, the, the, what we are seeing is that we are moving from, you know, having like tons of dashboards and reports and predictive analytics to artificial intelligence as a true decision partner.

So a partner, not, not replacing, um, uh, skill sets, but as a true decision partner, one that helps, um, in our case, these would be our customers are manufacturers of these drugs. So manufacturers hubs that patients, um, get enrolled in and then the care team that provides the care coordination. So one that helps all these segments work together to improve access and continuity of care.

That to me, I feel like a combination of the three things I mentioned is really where we are headed towards.

 [Marty]

Yeah, no, that, you know, that’s great. And that, that, what I, what I think of like tangibly, especially that, that, the thing you said, that turning insight into action, you don’t want to just know the data you want to know what to do next. I got this aura ring and I love it.

I love my aura ring. This thing is awesome. I don’t know if you know about the aura ring.

I have heard of it, but I don’t use it. It’s like, okay. They swear by it.

It’s awesome. Cause it has all this, this, this health data. It shows, you know, how much you slept, how much you had deep sleep, light sleep, REFs, all this stuff.

I didn’t even know existed to be honest until I got the, the thing, but it’s very overwhelming at first, at least, you know, um, all this data, all this, all this stuff. And it’s like, okay, I’m happy that I, I, you know, I’m seeing all this data, but it’s like over what, what, what does this even mean? What, what should I do?

Like, what do you do?

[Meghna Misra]

Should I sleep more?

 [Marty]

Should I sleep less? Yeah, exactly.

[Meghna Misra]

Yeah.

 [Marty]

So yeah.

[Meghna Misra]

In our case, not just telling you what to do from an action standpoint, but also doing that for you. And that’s where agentic AI comes in. Okay.

Now I know I need to take this action. I need to reach out to, and I’m just using this as an example. You know, I know a patient is at risk prior off.

I need to reach out to the provider. I would normally either pick up the phone and do it. How about you make that phone call for me?

How about you send that email for me? So that further, I mean, that’s the transition that’s going to happen. And it’s happening really fast.

 [Marty]

Oh yeah.

[Meghna Misra]

Yeah. Exciting times.

 [Marty]

Yeah, it’s great. No, I hate when I get it. I get a sad.

I get a SAS or something, you know, it’s supposed to give me data. It’s supposed to help me. Um, and then it’s just all this numbers, everywhere’s numbers, numbers here, numbers, their number numbers everywhere.

And it’s like, oh my gosh, just tell me what to do. Dude, I bought your SAS. Okay.

I I’m seeing all this, this data of, of my, you know, marketing analytics or something like that. Is it just tell me what to do? You know, cause I ended up screenshotting it and putting in chat to BT anyway.

But, but you guys are on that. Um, you know, like making sure, okay. We’re not just going to know the problems.

We’re also going to tell you what to do next. So that just stood out to me. I was like, oh, that’s, that’s, that’s great that you guys are thinking about that.

So, um, and then, um, I guess, I guess before we, we sadly have to wrap up. I want to ask one more question about what advice would you give an organization that is beginning to integrate, um, AI into patient care and risk management being, um, someone who has successfully done it, you know, being from Claritas, which has done it in an awesome way. What, what advice would you give organizations that are just starting to, or thinking about integrating, uh, AI into their patient care and risk management?

[Meghna Misra]

Well, um,  Marty that is an awesome question. Um, and when I think that a lot of organizations are wrestling with right now, they’re grappling with like, you know, everyone’s talking about AI, um, in order to be viable in the market, I need to do something with AI. I literally have heard people say these words.

I need to do something with AI. My boss is asking me. So, um, I’d say, um, and like you said, at Claritas RX, we have been, um, very, uh, mindful about this.

Um, so my biggest piece of advice would be start with the problem and not the technology or the algorithm. Um, you know, it gets really easy to get caught up in the excitement of AI, but the most successful outcomes I’ve seen in patient care and risk management are the ones that begin with a specific question. Um, like why are patients discontinuing or where are these prior auth denials happening most often?

So once you have that clarity, AI becomes a tool to solve it and not just a science experiment or something that you need to do because you need to do that and put it on your website. And then the second thing I’d say is make explainability non-negotiable. So in healthcare, people want to, I mean, this is very high stakes.

It, you’re literally talking about people’s lives. So, um, predictions that aren’t understood will not be trusted. So if you are, you know, if a team cannot see why that patient was flagged as a high risk and what they can do about it, the insights won’t drive action.

And, um, yeah. And finally, I’d say, um, and this is really important is keep humans in the loop. The best AI, I strongly believe this doesn’t replace expertise.

It just amplifies it. It gets the right signal to the right person at the right time so they, they can step in and make a difference. So I think, you know, um, if you get these three things, right.

So clarity on the problem, like really fall in love with the problem, not the solution, like clarity on the problem, transparency in the model, and then the people empowered to act, AI can become a force multiplier for patient access and care. Like, um, sky’s the limit here. And, um, you know, we can do really great things together with AI.

 [Marty]

Yeah, yeah, yeah. Yeah. Yeah.

basically saying with his facial expression it’s so funny if you see it he’s like just like are you an idiot he said no we always put our customers first he said internet schmitter net and so i’d like it sounds like you like have the same mindset as uh you know jeff bezos it’s like it’s the problem it’s it’s the customer not just the the buzzword of today you know

[Meghna Misra]

that’s that’s really critical um especially when you’re building products, it’s important to, like I said, not fall in love with the solution, but really go deep on the problem that you’re trying to solve and why are you trying to solve it and who are you trying to solve it for? That matters. The why matters.

 [Marty]

Yeah. Yeah. You know, look, look where Amazon is today and that’s where, that’s where Claritas is going.

[Meghna Misra]

Oh, well, fingers crossed. You’re basically Jeff Bezos. That might be a little far-fetched, but no, I am, I am excited about what we are doing at ClaritasRx and the value, you know, the impact of the work that we do.

That matters too.

 [Marty]

Yeah. No, it’s awesome. I was just drawing that similarity from that clip.

Yeah, that’s fun.

[Meghna Misra]

Send me, send me that clip after we’re done.

 [Marty]

Right. Yeah. Right away.

Yeah, for sure. It’s a good one. Just the way he looks at this interviewer, like, it’s so funny.

It’s so, so, so funny.

[Meghna Misra]

I will definitely take a look.

 [Marty]

Okay. Yeah. So then, yeah, I guess, thank you so much for coming on, sharing your expertise and insights.

You’re really, really, really well-spoken. It’s like, yeah. And your experience in building these AI-driven healthcare products across companies, you know, NetSmart, Ideon, and now ClaritasRx, which seems awesome.

It’s doing really awesome stuff. You know, it provides a really valuable perspective. To me, I was very happy about this.

And then to our listeners on how we can enhance the patient visibility, you know, it’s a key word of probably this podcast episode, patient visibility, patient visibility, patient visibility, and then the patient outcomes. So we really, really, really appreciate your time and insights. So, you know, listeners, stay tuned for more discussions on healthcare innovation.

Until next time, stay well.

[Meghna Misra]

Thank you. Thank you for having me.