In short
Founder’s Story - Episode 283 Summary
Episode Title He Found $500B Hidden in Healthcare Waste — And Built the AI to Fix It
Host Daniel
Guest Raheel Retiwalla Co-Founder and Chief Product Officer at [Boost Health AI](https://www.boosthealth.ai)
Episode Overview In this episode, Daniel speaks with Raheel Retiwalla, who discusses how Boost Health AI is addressing the $500 billion in administrative waste present in the healthcare system. Raheel explains the need for efficient access to complex medical rules and policies that are often trapped in PDFs and regulations. The conversation explores the transformative potential of generative AI and emphasizes the importance of transparency in healthcare operations.
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Key Discussion Points
- Pivotal Moment:
- Raheel's career shift was influenced by a JAMA–McKinsey study revealing $500 billion in administrative waste in healthcare management, highlighting inefficiencies not related to actual care delivery.
- Generative AI:
- Raheel discusses how generative AI enables the extraction, structuring, and validation of healthcare rules at scale, allowing payers and providers real-time access to essential information.
- Post-COVID Context:
- The financial pressures following COVID-19 heightened the urgency for efficiency in healthcare operations, coinciding with the rise of generative AI technologies.
- Transparency and Trust:
- The importance of explainable AI is stressed. Boost Health AI is committed to transparency, ensuring that payers retain ownership of their intelligence rather than being dependent on vendors.
- Transformative Impact:
- The aim is not merely to speed up existing processes but to rewire healthcare operations for greater efficacy, shifting from reactive to proactive care.
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Key Takeaways
- Unlocking Administrative Waste:
- By addressing the hidden administrative waste, Boost Health AI aims to unlock billions in value while improving patient care delivery.
- Innovative AI Use:
- The most impactful AI solutions will focus on restructuring underlying systems rather than just accelerating current processes.
- Empowerment Through Technology:
- The future of healthcare relies on clear rules and infrastructure that empower human decision-making rather than replacing it.
- Advice for Entrepreneurs:
- Raheel emphasizes the importance of understanding the industry deeply, focusing on inefficiencies, and leveraging technology to enhance operational effectiveness.
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Future Implications
- Proactive Healthcare:
- There is a strong possibility of shifting the focus of healthcare from reactive measures to proactive management, helping prevent health issues before they arise.
- Long-Term Impact:
- If successful at scale, efforts to eliminate inefficiencies could lead to a transformation of the healthcare landscape, potentially saving trillions of dollars and improving health outcomes globally.
- Collaborative Efforts:
- The podcast speculates on a future where healthcare organizations share their technologies and data more collaboratively, enhancing interoperability across systems.
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Closing Thoughts
Raheel’s journey serves as an inspiring reminder that significant opportunities for innovation lie in overlooked problems. By focusing on transparency, collaboration, and the foundational inefficiencies in healthcare, entrepreneurs can drive meaningful change. The episode reinforces the notion that the future of healthcare, shaped by AI and technology, holds immense potential for improving patient care and operational efficiency.
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For Further Engagement
Listeners can reach out to Boost Health AI through their [website](https://www.boosthealth.ai) for more information or to get involved in their mission.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:04so raheel i'm very excited about the future of ai when it comes to health and how technology is impacting the health sphere. I've heard things like AI could solve all of our biggest health problems or health concerns in the future. So how exciting is that? But I'm sure it's intricate and complex going from where we are now to where the future if we never have a health problem and how long that could be away. So what was the moment in your life? Why was this something personal to you. And what was the moment that you realized how not only big this problem was, but a need so big that you are willing to dedicate your life to building Boost Health AI?
0:51Yeah, Daniel. I mean, I would say that I've been in healthcare for over a decade, working with health plans and health systems, trying to figure out how to use digital better, how to improve operations. But it wasn't until in 2020, during COVID, actually, a study was released by an organization called JAMA, along with McKinsey, that mentioned$500 billion of waste, administrative waste, just managing how healthcare runs, not the cost of actually providing healthcare. It's just managing the way healthcare runs is$500 billion. And what that article did is essentially articulated exactly what operational areas are driving that.
1:39And it was COVID time. We were, as a company, thinking about healthcare from an AI perspective, even before generative AI at that time. And reading that just kind of stuck. That stuck in us. And we said, you know what? If there's nothing else we could do and contribute to the US healthcare our ecosystem, just increasing the efficiency, increasing productivity, and making sure that we can reduce this administrative burden, that would be huge for us. And we started our journey then. And it wasn't until Generative AI became big that it just snowballed and allowed us to kind of accelerate what we're doing and what we had as a vision at that time.
2:20Some of the most successful entrepreneurs have told us that timing was the absolute critical piece in the story for them. So it sounds like timing for you was massive. Like if Gen AI didn't become what it is, we might be having a different conversation today. So can you dive into detail around what did Gen AI enable you to do within the company? Yeah, I would say, well, specifically to timing, first of all, right? There are timing, at least for us included, in addition to generate AI, it's great that you have a technology, but without a real problem, it becomes just a technology, just another thing.
3:00So for us, another important thing that happened in this period is after COVID, just after COVID, the cost of care became increased significantly. And that even today has healthcare systems and health plans, essentially, they've shaken up. Their financials are not the way they used to be. So what has happened is that the need to actually create efficiencies has multiplied and become more urgent. So that's just keep that in the backdrop because that is one of the timing parts. And then generative AI as a solution, potential solution came about. And what we did is we looked at the power of generative AI and said, where can we apply it?
3:44You know, there's so many different areas and you're seeing and hearing about AI, as you said earlier, lots of different places in health care. but where are those opportunities when we think about the administrative waste as I mentioned to you earlier and what it turns out is that a lot of the decisions that are made in healthcare so whether I should approve someone's authorization for physical therapy how much therapy should they get where should they get it what should it cost all of those things are essentially rules rules that are stuck inside PDFs in guidelines in policies, in regulations, in benefit statements.
4:24So regardless of how much investments healthcare organizations have made to make things more digital and portals, this particular act of validating the rule by some human somewhere to say, should I do this? What should I do here? What policy applies here? It just is what drove that$500 billion administrative base in the US. So our goal was to use and think about application of generative AI in unlocking those rules. What if we just unlock those rules and made them available to every workflow, every person involved in the healthcare continuum, so they have access to the rules in a manner they can use consistently, accurately, and do what they need to do faster.
5:09And that's kind of where Generative AI became the technology platform for us to essentially validate first, test it, and then not make it available for Boost Health. I mean, I can't live without Generative AI. I use it every five minutes of the day. I wasn't feeling good yesterday, and I was asking ChatGBT, what should I do? And so for 48 hours, I basically followed along. I don't know if that's a good thing or not, but everything it told me has been factually correct. So I know you have a bold idea of payers should own their intelligence instead of renting it from vendors. Why is this critical for the future of AI and health care?
5:47And what have you seen when this is capable? Yeah, the biggest reason for us is this idea of a black box. And this goes specifically to the point you made earlier about bias and just the trust in AI. At the same time, there's a ton of innovation happening, right? So there's a new point solution to solve problem X, problem Y, problem A with its own AI something. So if I'm a payer or a provider and I'm starting to just kind of invest in these tools as they're coming along, I have no idea under the hood what is actually happening. And the big thing about healthcare is that it has to be explainable.
6:29Everything that happens in healthcare has to be able to say exactly where it got that from, cite the facts. In our case, from a boost perspective, it means exactly which policy statement, which policy criteria are you referring to? What document did it come from? What specific benefits, specific clause, which regulation is limiting this? So you have to be able to explain that, and you have to cite the criteria, and you have to audit exactly in situations where you're providing a response to somebody, exactly what the situation was and how it responded, how the user actually benefited from that.
7:05Because we want the insights from, it's a partnership. It's an augmentation collaborative between AI assisting, whether it's a person making a decision and authorizing something or a person deciding on the benefits you can apply. All of those are decisions that people make. And AI is just there to help them accelerate it. So they're more confident in the decisions they're making rather than replacing the human in making the decisions. So for us, it's how can then AI become more explainable and auditable and observable? That's the really important thing. If you're buying point solutions, what happens is you can't guarantee you're going to get that level of explainability or observability.
7:50So for us, what we're trying to do is we're flipping that model. We're in fact giving away our Boost Health IP so that our clients can actually see the code and use it in other ways beyond the initial use case that we may work with them. This allows them to have control over their AI. And as technology, obviously, as we know, enhancing super fast right now, they can actually make inroads and additions and improve that with our help or independently. versus getting stuck and locked into something that they can't understand well. So do you see the future of, let's say, healthcare and AI? Do you think a lot of companies are going to be sharing abilities, having the ability to open their APIs or share?
8:39Like, let's say you're working on some piece and then another AI is working on another piece. Do you think companies will be combining or organizations will be working together more in a collaborative versus competitive nature? Yeah. First of all, just generally speaking, without even AI right now, right? Even if you don't take AI into consideration, the need for interoperability and data sharing is just very important healthcare, just generally speaking, right? Because we all are part of an ecosystem and a machine that works together. So if one hand doesn't know what the left hand is doing, it doesn't work, which is where a lot of the inefficiencies to be, you know, generally are.
9:20So the fact that we need to do that, great. But when I think about the application of AI today, from a maturity standpoint, health plans and health systems have so much inefficiencies just in the way they do things today themselves and then how they run their business. It's like saying how you ran your business, in the sense how you run this podcast. If it was so inefficient, Like what's the point of sharing stuff with other people? You can't even get your own house running correctly and efficiently first. So what I'm saying is that there's an opportunity to clean up stuff, make yourself more efficient while there are regulations already in place demanding the level of interoperability.
10:00So that's going to happen anyway. Let's start cleaning our house so we're able to benefit from that interoperability and data sharing when it becomes a mandate, when people are seriously doing it. And it's happening and it's going to happen soon as well. well, I think we'll be in a better world, right? If interoperability and people are really sharing, and I hope so. I don't know if we've been in a world where we've been so open, right? With, with the ability to share, it's almost the gatekeeping of information, right? Has become why I think some organizations became what they are, but maybe we're going to a world where, where we don't think that way.
10:39It's almost like more of an abundance mindset. What changes in these payers organizations when they start using the foundry and factory? And what do you hope that other organizations who are not using it, what do you hope they know so you can really even scale this more? Yeah, I think the fundamental vision that we share with our health plan clients is very simple. You've got rules that are blocked, drives inconsistencies on how people make decisions, which drives inefficiencies, costs. And that's what we're trying to reduce. So what we work with them on is identifying specifically the document types that are locking up those rules.
11:24Medical policies is a really good example. You unlock a medical, what is in a medical policy? Very simple. When will the plan pay for a procedure? When will it not? What are those rules that somebody has to follow? One of the things that we do when you unlock a medical policy is you open up tons of opportunity for automation. So for example, imagine if we were to be able to tell your doctor when they're submitting a authorization for you to get an MRI with the right information first time versus what happens today is they submit an authorization, somebody on the payer side reviews it for a week.
12:01If it is a complex scenario, then somebody more clinically inclined, a doctor or whatever, has to review that. It can take a cycle. If they don't have all the information, then it goes back to the doctor to submit again. And that cycle can take time from someone who needs care, not getting care at that moment in time. And we want to avoid that. So unlocking the medical policy allows the doctor to be able to validate their submission against the policy real time. So even before they submit, they're getting the information. Like, wait a minute, your document isn't, your submission isn't complete.
12:37Here's why. Provide this level of information. Go do this, go do the why. And it just reduces that cycle. That's just one example of many, many unlock medical policies. And if you think about the other different document types, you kind of unlock value in a wide variety of ways. So for us, it's really about talking to our health plan clients about that approach. Many are obviously working with us and thinking about this and working on early implementations of their workflows. And that's what we want to tell people is that, look, you've spent a lot of money already in point applications, in digital transformation.
13:16Focus on what has always been the problem, which are these rules. So it sounds like if you succeed at full scale, that I think you had said there's$500 billion in inefficiencies or I don't know if I got that. Is that correct? Yes, that's right. That's right. And I would imagine there could be trillions of dollars when you add in a lot of other inefficiencies or things that happen, not just in what you're looking at, but all different aspects of health care. What do you think this impact will have on the healthcare in the U.S. or maybe the world as a whole, just the whole ecosystem in the future if these inefficiencies can be removed, can be solved?
14:01And potentially it could be trillions of dollars, I'm thinking, reduced. What do you think will happen to healthcare for everyone in 10 years from now? Yeah, it's an amazing question, because, I mean, you know, the lens we have right now at the moment with Boost Health is focused on payer efficiency, right? Even within the payer efficiency, our goal and our goal generally as a whole, as everybody involved in AI and systems, is not to just do what is already being done just faster. It's to rewire things, because it's, in many ways, the processes that were built were done because of how the situations were at those moments in time.
14:42in the past. We're not shackled by those anymore. We have lots of capability, lots of ways to kind of think differently. So our goal is to essentially not say, well, here's exactly how you did it. Now AI is going to make it a little faster. No, what we want to do is we want to completely rethink the process, rewire that operation so that you're gaining 50 % improvement, not 10 % or 15%. that's where you really get into the value of AI. So if I think about, you know, administrative burden, even just on the payer side, and if you start unlocking, just even taking the documents as a way to kind of unlock value, it's in tens of billions of dollars or close to 100 plus billions of dollars aggregate across the pairs.
15:27It's a massive improvement. Now, when you add on the other side, you know, and the bigger thing is one of the places we want to get to is we want people not to get sick, you know, when we could have prevented it, being more proactive about working with people on their health. The problem is we are so reactive today in healthcare. Most of our care managers, people who are working with people that need care, are doing so with the top 10 % of the population that is, you know, that is very, that's highly sick or has multiple diseases. The rest, 80%, have no visibility, right? We want to direct the attention to those folks that are rising riskers that we have no clue about until they become really sick.
16:10So it's those kinds of things that when you start thinking about what impact that could have when people are leading better, more improved healthy lives, and then you add what's happening on the health system side, how AI is changing the way diseases are detected, medicines are being created. The change and shift is, I can't imagine, to be completely honest, it just boggles my mind as much as yours. I'm sure. But I think there's meaningful steps we can take along the way. Reduce your operational burden. Get ready for that change that can come and help that you can really become more proactive versus reactive.
16:46And that's what our Foundry does. It has these components. You can start plugging into these rules and into your workflows and start making those meaningful impact today. You don't want to get into analysis paralysis. There's a lot we can do today. And we try to get our clients get moving versus getting stuck in like, where can I go? Where should I start? Right. We had a guest on a few years ago, they had raised a couple hundred million dollars to build out these preventative centers that were basically no humans. Unfortunately, they went out of business. But I think the idea that they had was great around this huge thing of preventative care and using a lot of wearables and all these devices to detect things in advance and then and then having that data then spread to doctors and stuff.
17:30But I think they're maybe ahead of their time. But the things they told me, though, I was like, wow, you know what? I wonder how much further could we live or how much further can we live healthy versus living to 100, 130, but I'm not healthy because I wouldn't even want to live at that point, right? But I'm excited, like you said, of how many diseases can be eliminated, how many medicines can be created in fast times. But for other entrepreneurs like yourself or other entrepreneurs that want to be like you in the sense that they want to create something that's going to change the world, they want to impact something, they're going into a space that probably is not so up to speed with technology and they have a huge problem to solve.
18:17What advice do you give to them to really get started? Yeah, I mean, I think the biggest advice is get to know a domain really well, like a domain, an area, whether it's an industry and a specific process in the industry. I think there's, you know, as we get started with application of AI, the way we're thinking about it right now, it's about how people do what they do and how they run their businesses, right? If you start, you know, if you start focusing on those inefficiencies, you're going to make businesses run better, which just allows them more capital, more abilities to invest in different ways, different things in enhancing your own products and services or reach to market.
19:01It just changes the game for them to be able to unshackle from just being able to be constricted by the way they're running things. So that's what I would say. I mean, I have kids who are in high school. I tell them even now, I said, look, learn industry, understand processes. Think about why is this happening the way it is? And then think about if I had AI assisting me here, what could it take from my plate? Where could it help me do more of the, you know, mundane things that I can then focus on more value things and what those things could be? So I think that's what I would say. And if you look at every industry that's going through an AI renaissance, you know, many of those use cases are very much in those areas.
19:45It's like call center. Why is call center automation, call center is so big? It's just a massive cost. is just a massive cost, right? So let's improve that, you know? Well, I've been vibe coding, Rahel. I've been making apps. I'm not doing anything with them because I'm too much of an idea guy. So I'm like, oh, I'm going to solve this problem. Let me make this app. And then the next day I'm like, I want to solve this problem. Let me make this app. It's almost scary. So I've had to cut myself off from making apps, but it does make me excited that people, It's not like before I think you had to raise 20 million, 50 million, 100 million dollars.
20:23Right. You could literally start something tomorrow, create like an idea, get it like workable. And then you could start pitching it, start gaining some traction, which is, I think, incredible. You could have people that are on an island somewhere that have Internet access that can do something that might be able to solve a problem globally. So I'm very excited for that. But thank you so much for joining us today. If people want to get in touch with you, they want to find out more information, they need to get involved because this is going to help their organization. How can they do so? Yeah, reach us at BoostHealth.ai.
21:01That's our website. There's a contact us page. It'll lead you directly to me and my team. Or Ahil, this has been great. I'm very excited. if I'm still doing this show in five years from now, and you're a billionaire in five years from now, come back on and let's talk about how the next five years is going to be from that point. This is amazing. Boost Health AI. I hope that you solve the AI, the healthcare crisis that many, many people are in. And I hope that this will help those people. Maybe it'll help affordable healthcare. I think it could do a lot of things with the amount of money that will be saved and the efficiencies and the time and everything.
21:42So I foresee the impact is going to be massive. But thank you so much for all that you do in joining us today on Founder's Story. Thanks, Daniel. Thanks for having me. It's been a pleasure.
From the publisher
In this episode, Daniel sits down with Raheel Retiwalla, Co-Founder & Chief Product Officer of Boost Health AI, the company unlocking the $500B in administrative waste trapped inside healthcare’s rules, guidelines, and policies. Raheel explains how Boost Health AI structures the complex medical rules buried in PDFs so payers and providers can finally access them consistently, accurately, and in real time. He shares the pivotal moment that convinced him this was the problem worth dedicating his life to—why timing with post-COVID financial strain and generative AI made this mission possible—and how Boost Health AI is rewiring healthcare operations rather than simply speeding them up.
Key Discussion Points
Raheel opens with the moment that shifted his career: a JAMA–McKinsey study revealing $500B in pure administrative waste—not from delivering care but from managing care. He breaks down how the root cause is shockingly simple: healthcare rules trapped inside PDFs, guidelines, and regulations, forcing humans to manually interpret them every time a decision is made.
He explains how generative AI allowed Boost Health AI to extract, structure, and validate these rules at scale, giving payers and providers instant, consistent access to the policies that govern every decision. Raheel walks through why timing mattered: post-COVID financial pressure pushed the industry to seek efficiency, and gen AI arrived at exactly the right moment.
Daniel dives into the deeper challenge: healthcare cannot use black-box AI. Raheel explains why Boost Health AI is built around transparency, citations, auditability, and an open model where payers own their intelligence instead of renting it from vendors. They discuss how unlocking medical policies speeds up authorizations, reduces friction, and creates room for automation across care delivery.
The conversation expands into future impact—rewiring broken processes instead of just accelerating them, shifting from reactive to proactive care, and preparing the system for AI-powered disease detection, drug discovery, and long-term population health.
Takeaways
Listeners learn that the most transformative AI in healthcare won’t diagnose disease—it will fix the invisible machinery beneath it. Raheel shows how Boost Health AI turns chaotic rule interpretation into structured intelligence, unlocking billions in value and reducing the delays that harm patients. This episode reinforces the importance of explainable AI, operational domain mastery, and building technology that rewires industries rather than automating old problems.
Closing Thoughts
Raheel’s story shows that the biggest opportunities in innovation often come from problems no one sees. Boost Health AI is proving that healthcare’s future depends on clear rules, transparent infrastructure, and AI systems that empower—not replace—human decision-makers. His journey reminds founders to look beyond the obvious, solve inefficiencies at their root, and build with transparency, courage, and long-term vision.
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