He Found $500B Hidden in Healthcare Waste — And Built the AI to Fix It | Ep 283 with Raheel Retiwalla Co-Founder and Chief Product Officer at Boost Health AI

Summary

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Founder's Story Ep 283: “He Found $500B Hidden in Healthcare Waste — And Built the AI to Fix It”

Guest: Raheel Retiwalla, Co-Founder & Chief Product Officer of Boost Health AI
Host: Daniel (IBH Media)
Date: November 18, 2025

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Episode Overview

In this episode, Daniel sits down with Raheel Retiwalla, co-founder and CPO of Boost Health AI, to explore how artificial intelligence can transform the $500 billion administrative waste crisis in U.S. healthcare. The conversation delves into Raheel's personal journey, the pivotal moment that spurred his mission, the power and limitations of generative AI, and what the future of an efficient, interoperable healthcare system could look like. Raheel also shares advice for would-be tech founders and reveals the wider paradigm shift toward explainable, collaborative, and proactive healthcare systems.

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Key Discussion Points & Insights

1. The Moment of Realization: $500B in Hidden Waste

[02:07]

• Raheel’s “aha” moment came in 2020, when a JAMA and McKinsey report revealed $500 billion in administrative waste—not in care delivery, but in the “management of how healthcare runs.”
  • Quote: “It wasn’t until in 2020...a study was released...that mentioned $500 billion of waste, administrative waste in just managing how healthcare runs...That stuck in us.” (Raheel, [02:16])
• COVID and its operational disruptions heightened this awareness and urgency.

2. Why AI, Why Now: The Role of Timing and Technology

[03:36]

• Generative AI’s emergence and post-COVID financial strain on health systems converged to create the right timing for Boost Health.
  • Quote: “The need to actually create efficiencies has multiplied and become more urgent...Generative AI as a solution...came about.” (Raheel, [04:02])
• Administrative waste largely stems from human “manual validation of rules” trapped in documents.
  • Quote: “All of those things are essentially rules, rules that are stuck inside PDFs, in guidelines, in policies, in regulations, in benefit statements.” (Raheel, [05:04])
• Boost Health’s vision: Use generative AI to "unlock those rules" and embed them into workflows for consistent, accurate, and rapid decision-making.

3. Explainable, Auditable AI: Moving Beyond the Black Box

[07:07]

• The critical need for AI transparency and explainability in healthcare decision-making.
  • Quote: “Everything that happens in healthcare has to be able to say exactly where it got that from, cite the facts. In our case...which policy statement, what document, what regulation...” (Raheel, [07:34])
• Boost Health’s radical approach: Sharing their IP with clients so they “own their intelligence” rather than relying on opaque, locked-in vendor solutions.

4. Collaboration & Interoperability

[10:10]

• Daniel raises future potential for collaborative, open healthcare data/API ecosystems.
• Raheel offers a pragmatic take:
  • Interoperability is already legally mandated, but most health organizations need to clean up internal efficiencies before true sharing delivers value.
  • Quote: “If one hand doesn’t know what the left hand is doing, it doesn’t work...So there’s an opportunity to clean up stuff, make yourself more efficient while...interoperability...is going to happen anyway.” (Raheel, [10:33])

5. Real-World Impact: Automating & Unlocking Health Policy

[14:16]

• Boost Health’s approach starts with analyzing and extracting rules in “locked” documents like medical policies.
  • Quote: “You unlock a medical policy...imagine if we were able to tell your doctor...when they're submitting an authorization...your submission is incomplete—here’s why—provide this level of information.” (Raheel, [15:20])
• Tangible benefits: Minimized back-and-forth between doctors and payers, faster authorizations, reduced delay in patient care.

6. The Multiplier Effect: Towards Trillion-Dollar Impact

[16:36]

• Daniel summarizes: Addressing $500B is just the beginning—true system transformation could unleash trillions in savings globally.
• Raheel envisions not just incremental efficiency, but “rewiring” processes for 50%+ improvement.
  • Quote: “Our goal...is not to just do what is already being done, just faster. It’s to rewire things...gaining 50% improvement, not 10%.” (Raheel, [17:34])
• Long-term hope: Proactive healthcare, better health outcomes, AI-enabled prevention.

7. Founder's Advice: Become a Deep Domain Expert

[21:37]

• For aspiring founders tackling complex spaces:
  • Quote: “Get to know a domain really well...If you start focusing on those inefficiencies, you’re going to make businesses run better, which just allows them more capital, more ability to invest in different ways.” (Raheel, [21:41])
• Adds practical advice: Leverage AI to handle the mundane—freeing humans for creative, high-value work.

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Notable Quotes

• “It wasn’t until in 2020...a study was released...that mentioned $500 billion of waste, administrative waste in just managing how healthcare runs...That stuck in us.”
  — Raheel ([02:16])

• “It’s great that you have a technology, but without a real problem, it becomes...just another thing.”
  — Raheel ([04:04])

• “Everything that happens in healthcare has to be able to say exactly where it got that from, cite the facts.”
  — Raheel ([07:34])

• “We’re giving away our Boost Health IP so that our clients can actually see the code and use it...This allows them to have control over their AI.”
  — Raheel ([08:37])

• “If one hand doesn’t know what the left hand is doing, it doesn’t work...So there's an opportunity to clean up stuff, make yourself more efficient while...interoperability...is going to happen anyway.”
  — Raheel ([10:33])

• “Our goal is not to just do what is already being done, just faster. It's to rewire things...gaining 50% improvement, not 10% or 15%.”
  — Raheel ([17:34])

• “Get to know a domain really well...If you start focusing on those inefficiencies, you’re going to make businesses run better...”
  — Raheel ([21:41])

---

Important Timestamps

• [02:07] – The $500B healthcare waste revelation and COVID’s influence
• [04:02] – Generative AI meets urgent industry need
• [07:07] – The problem with “black box” AI in healthcare
• [10:10] – Interoperability: hope and current limitations
• [14:16] – How unlocking medical policies with AI transforms care cycles
• [16:36] – Potential for trillions saved and a global healthcare transformation
• [21:37] – Founder's advice: Domain expertise and real problem-solving

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Memorable Moments

• Daniel’s reflection on daily reliance on generative AI for health advice:
  “I can't live without generative AI. I use it every five minutes of the day...I don't know if that's a good thing or not, but everything it told me has been factually correct.” ([06:36])

• Raheel’s transparency pitch:
  “We’re giving away our Boost Health IP...so [clients] can have control over their AI.” ([08:37])

• Daniel’s enthusiasm for democratized innovation:
  “You could have people on an island somewhere...that can do something that might solve a problem globally.” ([23:10])

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Conclusion and How to Connect

[24:14]

• Raheel invites listeners to connect at BoostHealthAI.com, emphasizing the openness of their team and approach.

Host’s Closing Thought:
Daniel expresses optimism about the massive, transformative potential of AI-driven healthcare efficiencies and hopes for a future conversation when Boost Health AI has realized its vision.

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This episode offers a compelling, practical vision for reducing healthcare waste, increasing transparency, and harnessing AI to move from reactive to proactive health—anchored by Raheel’s clear, domain-informed leadership and actionable advice for entrepreneurs.

Transcript

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[Raheel]

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[Daniel (Interviewer)]

So 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?

[Raheel]

Yeah Daniel, I mean I would say that. You know 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 in 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. And, you know, it was Covid time we were as a company thinking about, you know, 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 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.

[Daniel (Interviewer)]

Some 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, if Gen AI didn't become what it is and we might be, you know, having a different conversation today. So can you dive into, detailed around what did Gen AI enable you to do within the company?

[Raheel]

Yeah, I would say, well, specific to timing, first of all. Right, there are timing, at least for us included, in addition to generative AI. It's, it's great that you have a technology, but without a real problem, it becomes, you know, just the technology, just another thing. So for us, another important thing that happened in this period is after Covid, just after Covid, you know, the cost of care became, became increased significantly. And that even today has health care 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 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? There's so many different areas. And you're seeing and hearing about AI, as you said earlier, lots of different places in healthcare, but where are those opportunities? When we think about the administrative ways, as I mentioned to you earlier, 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. So regardless of how much investments healthcare organizations have made to make things more digital and Portals, this, this, 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. And that's kind of where generative AI became the sort of the technology platform for us to essentially validate, first test it and then now make it available through Boost Health.

[Daniel (Interviewer)]

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 ChatGPT what should I do? And so for 48 hours I basically followed along. I, 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 healthcare? And what have you seen when this is capable?

[Raheel]

Yeah, the biggest reason for us is this idea of a black box. And it goes specifically to the point you made earlier about, you know, bias and, you know, 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 that it has to be explainable. Everything that happens in healthcare has to be able to say exactly where it got that from, cite the facts again in our case, from a Boost perspective means exactly which policy statement, which policy criteria are you referring to? What document did it come from, what specific benefits, specific state 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 if 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, what you know, because we want the insights from. It's a partnership. Yeah, it's an augmentation collaborative between, you know, AI assisting, assisting, whether it's a person making a decision on and authorizing something, or a person deciding on the, 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 and making the decisions. So for us it's how can then AI become more explainable and auditable and observable? That's the more 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. So for us, what we are 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, you know, 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.

[Daniel (Interviewer)]

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. 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?

[Raheel]

Yeah, I, you know, 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. Health care, just generally speaking, right. Because we all are part of an ecosystem and a machine that works together. So if, 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. So 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, so much in, so much inefficiencies, just in the way they do things today themselves within how they run their business. Like it's like saying how you ran your business, in a 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 inefficiently 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. So that's going to happen anyway. Let's start cleaning our house so we are able to benefit from that interoperability and data sharing when it becomes, when it becomes a mandate when, when people are seriously doing it and it's happening and it's going to happen soon as well.

[Daniel (Interviewer)]

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. It's almost like more of an abundance mindset. What, what changes in these payers organizations when they start using the foundry and factory? And what do you what do you hope that other organizations who are not using it, what do you hope they know?

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[Daniel (Interviewer)]

Edu so you can really even scale this more?

[Raheel]

Yeah, I think the fundamental vision that we share with our health plan clients is very simple. You've got rules that are locked, drives inconsistencies and how people make decisions which drives inefficiencies, cost 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 roles. Medical policies is a really good example. You unlock a medical and 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, you know, 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 size reviews it for a week. If it is a complex scenario then somebody more clinically inclined to 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 the submit they're getting the information like wait a minute, your document, your submission is incomplete. Here's why. Provide these this level of information, go do this, do go to the why and it just reduces that cycle. That's just one example of many. When you 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, it's really about talking to our health plan clients about that approach. Many are, you know, obviously working with us and thinking about this and working on, you know, early implementations of, of their workflows. And that's what we want to tell people is that, look, you know, you, you spend a lot of money already in point. Applications in digital transformation focus on what has always been the problem, which are, which are these rules.

[Daniel (Interviewer)]

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?

[Raheel]

Yes, that's right. That's right.

[Daniel (Interviewer)]

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 healthcare. What do you think this impact will have on the healthcare in the US or maybe the world as a whole, just the whole ecosystem in the future? If these inefficiencies can be, can be removed, can be solved and there. You mean we're potentially could be trillions of dollars, I'm thinking reduced. What do you think will happen to health care for everyone in 10 years from now?

[Raheel]

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 in the past. We're not shackled by those anymore. We have lots of capability, lots of ways to kind of think differently. So, so our goal is to essentially not say, well, here's exactly how you did it. Now AI is just 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 administrative burden, even just on the bear side, and if you start unlocking, just even taking the documents as a way to kind of unlock value, it's, it's in tens of billions of dollars or close to 100 plus billions of dollars aggregate across the pairs. It's a massive improvement. Now when you add on the other side, you know, and the bigger, bigger thing is one of the way, 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. So 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, that kind of, we have no clue about until they become really sick. So it's those kinds of things that when you start thinking about what impact that could have when people 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 it, to be completely honest. It's just, 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. And that's what our foundry does. It has these components. You can start plugging into these rules, into your workflows and start making those meaningful impact. Today we 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.

[Daniel (Interviewer)]

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. But I think they're maybe ahead of their time. But, but what they, the things they told me though, I was like, wow, you know what this. I wonder how, how much further could we live or how much further can we live healthy versus, you know, 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, of how many diseases can be eliminated, how many, 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. What advice do you give to them to really get started?

[Raheel]

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, and enhancing your own products and services or reach to market, it 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, you know, learn industry, understand processes, think about, you know, 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, where could it help me do more of the man, 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. Is that call center? Why is call center automation? Call center is so big. It's just a massive cost. It's just a massive cost. Right. So let's improve that.

[Daniel (Interviewer)]

You know, so well, I've been, I've been vibe coding, Rahel. I've been, I've been making apps. I'm not doing anything with them because I, I'm too, 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'm going to solve this problem. Let me make this app. But it's, it's almost scary. So I've had to cut myself off from making apps. But it, it does make me excited that people, it's not like before. I think you had to raise 20 million, 50 million, $100 million. Right. 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. Like, 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?

[Raheel]

Yeah, reach us at Boost Health AI. BoostHealth AI. That's our website as a contact us page. It'll lead you directly to, to me and my team.

[Daniel (Interviewer)]

Well, Raheel, this has been great. I'm, 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. But this is amazing. Boost Health AI. I hope that you solve the AI, the health care crisis that many, many people are in. And I hope that this will help those people. Maybe it'll help affordable healthcare. Like I think it could do a lot of things with the amount of money that will be saved and the efficiencies and, and the time and everything. So I, I foresee the impact is going to be massive. But thank you so much for all that you do in joining us today and founders story.

[Raheel]

Thanks Ding and thanks for having me. It's a good pleasure.

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