He Found the $500B Problem No One in Healthcare Wanted to Fix… Until Now | Raheel Retiwalla

What this episode is about

Raheel Retiwalla discusses the significant $500 billion in administrative waste within the U.S. healthcare system, which was largely highlighted during the COVID-19 pandemic. He emphasizes the potential of generative AI to address this issue and improve operational efficiency, driven by his personal commitment to transforming healthcare through technology.

Key takeaways

• A $500 billion waste in healthcare admin could fund universal coverage—let's prioritize efficiency before expansion!
• Generative AI isn't just shiny tech; it solves real problems in healthcare by eliminating outdated rules and bottlenecks.
• Post-COVID, inefficiencies in care skyrocketed—urgency is the new norm for AI solutions we've long delayed.
• In healthcare, timing is everything. Without generative AI, we might still be drowning in outdated paperwork.
• Unlocking the rules of healthcare with AI is like finding the cheat codes in a video game—game changer!

Who speaks in this episode?

• Daniel (Host) · 9 min speaking
• Raheel Retiwalla (Guest) · 14 min speaking

What is discussed, and when

1. 0:00 – 5:00: Boost Health AI, JAMA
2. 20:00 – 22:55: Boost Health AI

Notable quotes from "He Found the $500B Problem No One in Healthcare Wanted to Fix… Until Now | Raheel Retiwalla"

• I'm very excited about the future of AI when it comes to health and how technology is impacting the health sphere.

  about Artificial Intelligence · at 0:00

• 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…

  about Boost Health AI · at 1:29

Who and what is mentioned in this episode?

Companies & orgs

• Boost Health AI — Company · Business focus · 3 mentions · first at 1:45
  Company founded to address healthcare inefficiencies using AI
• JAMA — Company · Referenced expert · 1 mention · first at 2:05
  Organization that released a study on healthcare waste
  I've been in healthcare for over a decade but it wasn't until in 2020 during co IGA study was released that mentioned $500 billion of waste administrative based and reading that just kind of stopped. Some of the most.

Concepts & topics

• Artificial Intelligence — Concept · Core topic · 2 mentions
  Central theme of the episode, discussing the impact and future of AI in healthcare

Full transcript with timestamps

0:00 I I'm very excited about the future of AI when it comes to health and how technology is impacting the health sphere.

0:07 I've been in healthcare for for over a decade but it wasn't until in 2020 uh during co IGA study was released that mentioned $500 billion of waste administrative based and reading that just kind of stopped. Some of the most successful entrepreneurs have told us that timing was the absolute critical piece in the story for them.

0:30 It's it's great that you have a technology but without a real problem it becomes you know just technology just another thing because after co you know the cost of care increased significantly. This particular act of validating a rule by some human somewhere 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 roles. So Rahil, 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, you know, all of our biggest health problems or health concerns in the future. So how exciting is that? But I'm sure you know it's it's intricate and complex going from where we are now you know 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

1:33 personal to you and what was the moment that you realized uh 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. Yeah, Daniel. I mean, uh, I would say that, you know, we've I've been in health care for for over a decade, um, working with, uh, 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 uh during co actually a study was released by an organization called JAMA along with McKenzie that uh mentioned uh $500 billion dollars of waste administrative waste just managing how healthcare runs not the cost of actually providing healthare is just managing the way healthcare runs is 500 billion and what that article did is essentially uh articulated exactly what operational areas are driving uh are driving that and you know it was it was co time we were as a company thinking

2:39 about you know uh 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 uh and contribute to the US healthcare ecosystem uh ju just increasing the efficiency increasing productivity and making sure that you know we can reduce this administrative burden. Uh 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 what we had as a vision at that time. So

3:16 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 it 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?

3:42 Yeah I would say um well specific to timing first of all right there timing uh 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 a technology just another thing. So for us another important thing that happened in this period is after co just after co um 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 uh your financials are not the way they used to be. Uh 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 and said where can we apply it you know there's

4:41 so many different areas and you're seeing and hearing about AI as you said earlier lots of different places in healthcare but where is where is where are those opportunities when we think about the administrative waste as I mentioned to you earlier what it turns out is that a lot of the decisions that are made in healthcare so where 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

5:41 billion administrative waste in the US. So our goal was to use and think about application of generative AI in unlocking those rules. What if we just unlocked 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 and and you know do what they need to do faster. And that's kind of where generative AI became the sort of the the the you know the technology platform for us to to to essentially validate first test it and then now make it available through Boost Health.

6:16 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 chatbt what should I do? What's 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 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 uh when this is capable?

6:48 Yeah. Um the biggest reason for us is this idea of uh of a black box and it goes specifically to you know the point you made earlier about you know uh bias and and uh you know just the trust in in AI. Um 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. Uh 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 like in this in our case as a 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

7:44 regulation is is limiting this. So you have to be able to explain that and you have to site 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. What you know because we want the insights from it's a it's a partnership. Yeah. It's an augmentation collaborative between you know AI assisting uh assisting whether it's a it's a person making a decision on and authorizing something or a person deciding on the the benefits you can apply uh all of those are decisions and 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 those decisions. So for us it's how can then AI become more explainable and auditable and observable. That's the more the really

8:39 important thing. If you're buying point solutions, what happens is you can't guarantee you're going to get that level of explanability or observability. So 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 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 we know enhancing super fast right now they can actually make inroads and you know additions and improve that uh you know with our help or or independently uh versus getting stuck and locked in to something that they can't understand well. So are you do you 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 you know the ability to to open their APIs or or

9:35 share like 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

9:50 yeah Um I you know first of all just generally speaking without even AI right now right even if you don't take AI into consideration uh the need for interoperability and data sharing is just very important in healthcare just generally speaking right because we all are part of an ecosystem and a machine that works together so if a if one hand doesn't know what the left hand's 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 ine so much inefficiency is 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 the sense how you run this podcast if it was so inefficient like what's the point of sharing stuff with other people you

10:43 can't even get your own house running correctly inefficiently first So that 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 able to benefit from that interoperability in data sharing when it becomes 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 uh where we don't

11:34 think that way. It's almost like more of an abundance mindset. um what what changes in these payers organizations when they start using the foundry and factory and and what do you what do you hope that other organizations who are not using it what do you hope they know um so you can really even scale this more

11:56 yeah I think the fundamental uh vision that we share with our health plan clients is very simple you've got rules that are blocked drives inconsistencies and how people make decisions which drives inefficiencies, cost and that's what we're trying to to reduce. So what we work with them on is identifying specifically the document types that are you know 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 you know uh pay for for a procedure? When will it not? One of those rules that will that somebody has to follow. Um, one of the things that we do when we 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

12:50 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 a doctor or whatever has to uh 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.

13:27 So even before they submit they're they're getting the information like wait a minute your document isn't isn't your sub your your submission isn't complete here's why provide these this level of information go do this do go do the wise 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 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 are in you know obviously working with us and and thinking about this and and working on you know early uh implementations of uh uh of their workflows. And that's what we want to tell people is that look you know uh 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

14:15 these roads. 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?

14:27 Yes, that's right. That's right. And I I would imagine there could be trillions of dollars when you add in a lot of other inefficiencies or things that happen um not just in what you're looking at but all different aspects of health care. What do you think this impact will have on on the health care in the US or maybe the world as a whole just the whole ecosystem in the future if if these inefficiencies can be uh can be removed can be solved and there you I mean we're potentially could be trillions of dollars I'm thinking um reduced what do you think will happen to health care for everyone in 10 years from now

15:09 yeah it's it's an amazing question you know 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 uh 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 is 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 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 just going to make it, you know, little faster. No, what we want to do is we want to completely rethink the the process, rewire that operation so that you're gaining 50%, you know, improvement, not 10% or 15%. That's

16:05 where you really get into the value of AI. So if I think about you know administrative burden and I 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 it's in 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 uh you know when we could have prevented it. Uh 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 is highly sick or has multiple diseases. The rest 80% have no

16:58 visibility, right? We want to direct the attention to those folks that are rising riskers 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 health healthy lives and then you add what's happening on the health system side how AI is changing the way disease are detected medicines are being created the change and shift is I can't imagine it to be completely honest it's just uh it just boggles my mind as much as yours I'm sure uh but I think there's you know meaningful steps we can take along the way reduce you know your operational burden get ready for that change that can come and help you know 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 and into your workflows and

17:48 start making those meaningful impact today. Um it it's it's 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?

18:02 We had a guest on a few years ago. They had raised u 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 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 were 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

18:57 yourself um or other entrepreneurs that want to be like you in the sense they 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? Yeah, I mean I think the the biggest advice is get to know a domain really well like a domain an area uh whether it's an industry and a specific process uh 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 uh it's about how people do what they do and how do they run their businesses right uh 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

19:53 things in in enhancing their 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 they're running things. So that's what I would say. I mean you know I have kids who are in high school. I I 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 uh industry that's going through an AI renaissance You know, many of those use cases are very much in those areas. It's like call center, why is call center automation?

20:44 Call center is so big. It's just a massive cost. It's just a massive cost, right? So, let's improve that, you know? So,

20:51 well, I've been I've been vibe coding, right? I've been I've been making apps. I'm not doing anything with that because I I'm too I'm too much of an idea guy. So, I'm like, I'm gonna 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. It 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, hundred million dollars, 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,

21:31 which is I think incred. 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 I'm very excited for that. But uh 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 they need to get involved because this is going to help their organization, how can they do so?

21:54 Yeah, reach us at Boost Health AI. Boostalth.ai. Uh that's our website. There's a contact us page. It'll lead you directly to to me and my team.

22:02 Well, Rahil, 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, uh, this is amazing. Boost Health AI. I hope that you solve the AI, the healthc care crisis that many, many people are in and I hope that this will help those people. Maybe it'll help affordable healthcare. Who? 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 I foresee the impact is going to be massive. But thank you so much for all that you do in joining us today and founder story.

22:47 Thanks Daniel. Thanks for having me. It's been a pleasure.

Questions about this episode

Who speaks in "He Found the $500B Problem No One in Healthcare Wanted to Fix… Until Now | Raheel Retiwalla"?

Daniel (Host), Raheel Retiwalla (Guest).

What is "He Found the $500B Problem No One in Healthcare Wanted to Fix… Until Now | Raheel Retiwalla" about?

Raheel Retiwalla discusses the significant $500 billion in administrative waste within the U.S. healthcare system, which was largely highlighted during the COVID-19 pandemic. He emphasizes the potential of generative AI to address this issue and improve operational efficiency, driven by his personal commitment to transforming healthcare through technology.

What is mentioned in this Founder's Story episode?

3 people, works and ideas are mentioned, including Artificial Intelligence, Boost Health AI, JAMA. Each one on this page links to its own page with every episode that mentions it.

How long is "He Found the $500B Problem No One in Healthcare Wanted to Fix… Until Now | Raheel Retiwalla"?

The episode runs 23 min; the transcript is about 4,221 words in 35 timestamped sections.

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