Why don’t companies use data to improve and make people’s lives better?
In this episode of Bite The Orange, we feature the one and only, incredible and renowned Dr. Severance MacLaughlin, who shares the journey he is on in building DeLorean AI, his life in the different branches of the healthcare industry, and product development. Severance has traveled the world gathering data and knowledge to improve patients’ lives, and he took all of this to create medical AIs through 5 steps. Sev’s passion lies in helping people live healthier and better lives, even if they have a chronic disease.
Tune in to this wonderful episode about a technology that is making a difference in the world!
FULL EPISODE
BTO_Severence MacLaughlin: Audio automatically transcribed by Sonix
BTO_Severence MacLaughlin: this mp3 audio file was automatically transcribed by Sonix with the best speech-to-text algorithms. This transcript may contain errors.
Emmanuel Fombu:
Welcome to Bite the Orange. Through our conversations, we create a roadmap for the future of health with the most impactful leaders in the space. This is your host, Dr. Manny Fombu. Let's make the future of healthcare a reality together.
Emmanuel Fombu:
Good morning, good afternoon, good evening, ladies and gentlemen. Welcome to another episode of Bite the Orange. And today we have a very special guest. I go way back with this guest and someone that I looked up to and I admire seriously when it comes to the field of data science and his passion for the future of society, the future of healthcare in general, this person is none other than Dr. Severance McLaughlin. Welcome to the show, Sev.
Severence MacLaughlin:
Hey, Manny, thank you so much for having me on, and it's good to catch up again. Excited to speak to you.
Emmanuel Fombu:
It's been a while since we last talked and since then I know you've gone to found your own company at DeLorean AI. And DeLorean is from the car? Are you a big fan of Delorean cars or how did you come up with the name?
Severence MacLaughlin:
So it's actually a funny story. Like, I'm a huge fan of 1980s movies. And so when we founded the company, my partner and I are in the kitchen table, I can remember vividly this was four years ago. And I'm like, what 80s film can we do? And then I'm like, Egon AI from Ghostbusters. And then it came to me, I'm like, we got to go into the future to get information, come back. So I was like, Back to the Future. And then I'm like, okay, what do I do with Back to the Future? And then DeLorean AI came out and I figured we might as well have some fun. If you're going to found your own company and not be stodgy, so DeLorean is here.
Emmanuel Fombu:
Actually, that's quite interesting because right before this interview, I said, oh, let me make sure I looked up what DeLorean means. And I put in DeLorean and I saw the cars and I go, oh, crap. It's literally the car.
Severence MacLaughlin:
Yeah.
Emmanuel Fombu:
And I think that's where the word comes from. But it's fantastic. I'm a big fan of Back to the Future.
Severence MacLaughlin:
Well, same!
Emmanuel Fombu:
I've known you for quite some time and I know your passion and your knowledge base, which I respect quite a bit, but for those that don't know you, I mean outside of what you do? And for those that know you, I'm sure they can learn more about you. So what is Sev? What is the legend behind that name?
Severence MacLaughlin:
That's a thought for the ages, right? Who am I? Have to go to therapy to, you know, continue to look at that. Uh, you know, when you look at your career, Manny, and, like, you're like, how did I get here? I was one of those guys that planned every stage, and there was a Hebrew saying, Man plans, God laughs. And that's a correct characterization of my life. I grew up on a farm in Rhode Island, a turkey and sheep farm, and I thought I wanted to be a veterinarian because that was the smartest guy that came on the farm. And I applied to one college that was Cornell, not because of it's a good school, but because it had a large dairy farm. And I got in and started doing medical research and I got shipped over to Britain to do a project which I didn't know what it was, but it turned out to be Dolly the cloned sheep. And after that I wanted to do my PhD, but back then don't want to show my age, you can probably see my gray, but late 90s, they had mad cow disease and foot and mouth disease. So they shipped me to Australia and I got to do a PhD in Embryonics and physiology and all that data that we had, genomics, proteomics. I had to start coding on a mainframe computer, right? And DOS, and this is back in the early 2000s. And yes, I am old, so I was like, why don't companies in healthcare use data to make people's lives better? And I came back to the United States in 2008 and did a couple consulting jobs where I opened up my own little practice of strategic analytics in their company. And then I started working for the American Red Cross, the Blood division. So it's a pharmaceutical company in a non-profit. And we were able to invent what I call the navigation equation. So it was a supply chain machine learning data science that went from acquiring the donor and the blood all the way to selling to the hospitals. That went well. And then I opened my own little shop to analyze Meditech, the EMR around 2014, and that got acquired by Cognizant Technology Solutions. I became their head of healthcare AI globally and then got recruited by Capgemini to oversee all their AI in the Western Hemisphere. And then I said, you know what, Manny? I'm doing services I want to create. I want to build something, I want to build a product. So this is where it gets crazy. So I say to my partner, I'm going to quit my job, which was a good job, and I'm going to go build a medical AI, and that's four years ago. And I did that and we sold our house and we slept on friends couches and traveled all through the pandemic to friends and family. But we really built an AI that I believe is pretty impressive. And that's where we are today, our flagship product.
Emmanuel Fombu:
Quite impressive. I mean, I know how focused you are and how driven you are. So if you say you definitely have an AI, I trust it. I don't have any data to validate it because I've worked with you and I know how passionate you are with this. So with, DeLorean in general, talking about the company, are you focused only on medical or do you cover other areas? Because I know, for example, I know I've seen things on the trading side of things that you do. And so tell me, what is the overall scope of your current practice?
Severence MacLaughlin:
Well, that's a good question. So this goes back to like how do you, a founder and founding the company. So Manny, when I founded the company, I thought, well, you know, what I'll do is I'll build great technology and I'm going to sell it to a larger company. So I developed sales AI first, which was based on CRM and being able to predict deals will win or not. And a friend of ours, Richie Etwaru, he's like, yeah, go with the sales AI, and I was going to try to sell it to Salesforce. And then I found out, Manny, that no one buys just a product, they buy revenue. So I was like, God damn, now I have to grow the side that I don't like. And so then I'm like, I said to Richie, I was like, I'm going to do medical AI like. So that's a long sales cycle. I'm like, well, we have it in process. So we had about 4 or 5 products, but Medical AIs are our flagship product. We're deployed at United Healthcare, but we also have our sales, which is deployed currently at Grupo Bimbo. They're the largest bakery in the world. They're based out of Mexico, but they own like Entenmann's and Thomas Cook English muffins, fantastic company, great family. But yeah, we have a couple products.
Emmanuel Fombu:
And the reason why I ask that question on specifically is to show that even though in certain fields you might need, you know, like medical data to prove that something works, but the logic behind it doesn't change, right? The logic on how you use your technology in the bakery business or it's in sales or it's in medical, the concept is overall the same, right, in prediction, correct? Is that fair to say?
Severence MacLaughlin:
That's exactly it. And our first patent, we submitted in 2020, was that broad mother patent, that same logic flow, right? And then as we've gone forward in different areas, we've patented those more specifically. But you're absolutely right, it's the same machine just tuned a little bit differently to different industries.
Emmanuel Fombu:
So with that being said, for us to hone in because most of our listeners all come from the medical field, if you're listening and you are from a health system or from ACL or from a payer site, whatever site you come from, and you listen to this, I mean, there are different ways you could apply, you know, the AI into your own specific area of focus. But with that being said, I do my research prior to our conversation today, and I was very impressed with your rural type medical care management AI, so I think you did a great job. You have great videos on your website that anyone that is curious could go on to DeLoreanAI.com. We'll have the website in the show notes, but tell us what the overall vision is for this product. What is the gap overall from perspective and what is it that you're able to do with your technology to improve healthcare?
Severence MacLaughlin:
You know, Manny, when we were looking at this, there is a gap in our society where the data for healthcare in the US lives, right? And I think the pandemic really showcased that is the data truly lives in the EMR and then also in the payers and not all the doctors have a view of this. And there are chronic diseases such as chronic kidney disease or diabetes or mental health, where we believe AI can enhance a physician's ability to improve health. And so what we did is we developed medical AI. We're currently applied at scale at United Healthcare and chronic kidney disease, end-stage renal, diabetes, as well as cardiovascular. But what the technology does, Manny, is five things. So the first thing it does is you turn it on and it classifies people in a risk category in those disease states. That's not really anything new, we believe we have a better mousetrap but, you know, that's not completely novel. What's novel is step two. So milliseconds later, the machine tells you in the future, will this person get better or worse with a probability? Will they go to the hospital? Is there a hospitalization event in the future? Number three is what is the next best action by the care team, by the patient themselves or the care management team to take to improve that health? So that could be anything from medical adherence, the person needs to increase the prescription number or the refill number, or maybe there's a health equity or mobility issue that they're not picking up their scripts. So we'll mail it directly to them, it might cost an extra 12 bucks to the payer, but it stops a 10,000 or $60,000 emergency room visit. But it could get all the way, Manny, really interesting down to like, we need to change the size of the needle at the dialysis to increase blood flow or flow of the clearance. And then the fourth thing we do is we can predict the transition from like diabetes to chronic kidney disease or CKD 2 or 3 or 6 or whatnot. And then again another next-best action to slow that down. And then finally, we are identifying unknown patients to our payer clients that they were not aware had CKD or diabetes so that they can catch those individuals at an earlier stage, treat them and hopefully keep them in that stage for a longer period of time before that slippery slope into the chronic later stages. So that's the five pillars of what our technology does.
Emmanuel Fombu:
Which is quite impressive. And I liked how you looked at cardiovascular disease and end-stage renal disease because you could see that quick transition from cardiovascular disease, right? And predict, well, I really liked about it, and tell me what you think about this, is the fact that your prediction models now go on retrospective data. So it's not like you're looking at this data sets and you say, all right, this is what we found out in the past, right? You literally go on a personalized level and you are saying this is a particular health system or a particular ACO payer, and you're saying based on this individual. This is the risk going forward and something actionable.
Severence MacLaughlin:
And it's real time mean. I need to get you to do advertising for me, Manny, because you just nailed it. It's real-time risk versus looking backwards, you're looking forwards and it's being able to now change the dynamics from treating an issue to preventing the issue or attempting to prevent the issue.
Emmanuel Fombu:
So which makes the name DeLorean actually quite useful in this particular case, right? Because you are using historical data to learn and then you're using that to go back to the future, right?
Severence MacLaughlin:
You're exactly right.
Emmanuel Fombu:
So the name is actually quite appropriate in this particular case, right, and what you do. So tell me some of the use cases that you've had, because I've seen several, I know you mentioned you've been deployed in several health systems, several databases. But give us some interesting use cases or things that you could share with us.
Severence MacLaughlin:
Yeah, So number one, we're really proud of and this is the scientist in me, right, that we know that we did the right thing is we believe, because I don't want to be arrogant, is that we believe we are the first AI in the world to be biologically validated. What does that mean? That means that our forecasts and our predictions by the model have been proven to be accurate by third parties and using lab tests, lab panels, EMR, hospital follow-up, infection follow-up. And one of these was really interesting, Manny, is that we were working for a provider client and they were working with end-stage renal failure patients. And so the nephrologist knew who their high-risk patients were, like they needed a lot of tender, loving care and they know the low risk was. But because we were processing the entire population, we discovered a sub population that mimicked most of the characteristics of low risk but we're about to crash into the hospital or we're about to crash into the emergency room. And so we were able to predict those and actually decrease the hospitalization rate for that client. So not only are we decreasing the costs associated with it, we could then transition those over to a better care plan with their nephrologists and care teams to prevent that and then get those people stabilized.
Emmanuel Fombu:
I think that is going to model were very useful in especially in the world of the affordable care. If you look at how you're going to save on value based care model in case anyone's sensitive to the Affordable Care Act, right? So in the value based healthcare model, I think this is like a perfect kind of piece because you're predicting risk, you're saving on costs, improving efficiency across the board. So with that being said, what is your ideal customer right now for your products, right? So someone is listening right now, I know, by the way, if you're listening to this right now, I don't think Sev and the team at DeLorean are focused only on renal disease, right? I think just take the concept and apply it to problems that you might have. And I'm sure you can work with the DeLorean team to actually come up with a solution to this. So what's your ideal customer?
Severence MacLaughlin:
Yeah. So, again, outside of kidney disease, we do cardiovascular disease and diabetes, but United has asked us to deploy mental health for depression, depression AI and COPD and high risk pregnancy. So those will be available in the second half of the year. And so we're looking for Blue Cross and Blue Shields and insurance companies. But also think about maybe like accountable care organizations where they actually not only own the patient but own the physician in at risk MSOs that are working with the CMS patients. And then we'd love to get into the Veterans Affairs. We've been trying to, but you know how complicated government is. But we feel that we could do a lot of good for those men and women who have served our country so.
Emmanuel Fombu:
The thing behind this is I always wanted to point out the fact that this is not something that is only beneficial in terms of cost savings, right? This is about diagnosing patients earlier, predicting the outcomes much earlier, which actually is a better quality of life improvement. So this is something that anyone listening, if you work within the VA or you're part of an ACO or you have this kind of partnership network, please reach out to them and push them to reach out to DeLorean, right, to have these conversations because it benefits people. And the longer it takes to adopt these solutions, the longer people get sick and people die from this, right? I mean, it is a critical emergency.
Severence MacLaughlin:
Yeah. And veterans, unfortunately, have a higher rate of these chronic diseases. But the other thing, Manny, which we find interesting is because we're providing the next best actions, may that be for the physician or for the care management teams or the patient themselves through the patient portal, is that the contact rate between those groups of patient and, let's say clinical care management increases. So satisfaction of both the physician and satisfaction of the patient increases, and indirectly we're seeing increases in star ratings for our clients just because the patient's like, oh, they care about me, right? They're calling me, they're emailing me. So there's a greater opportunity there as well for CMS.
Emmanuel Fombu:
So with that being said, with any dilemma, do you also offer consulting services or thought leadership kind of services? Because I think there's a lot in your headset, but I know that you have a lot of experiences in this thing. And so what other services can you help people think through things? I know you're great at this. What other services do you offer?
Severence MacLaughlin:
We are a product company, so we build products to deploy. But we're not a vendor. We're a partner with our clients. So whatever it takes to get their patients better may be a payer or an insurance company or a provider, we're all there. I feel lucky, Manny, like you, we're in a field where we make differences in people's lives, and I think that we help physicians enhance their capabilities. And to me, it's all about hugs, if we can catch a gentleman that may be in stage two of CKD and extend his life for 20 years because we prevent that slippery slope, that's more hugs with his kids, more hugs with his grandkids. And that's the way I view the outcome for DeLorean and our medical AI product.
Emmanuel Fombu:
That's interesting. So if someone wants to work with you and I agree with you on that piece, you come in and you shop for the product or can someone come to you and then you could develop a product. Like if I have for example, I already mentioned the case of one of your business partners developing something for mental health and high risk pregnancy. If I was an ACL or a payer right now or health system, and I think that based on my scores or my rating scores and I stuck in certain categories and I think that I could partner with DeLorean, you know, to help improve that particular category, you could develop product for clients like that.
Severence MacLaughlin:
So we're basically a product company, so we deploy those because we can deploy quickly. But some of those things after the base model, Manny, we have clients that want to bring in different disease states or they bring in different data. We have a client that's pretty forward thinking in the California area where they bring in unstructured data of weather patterns to alert their patients with COPD and cardiovascular disease of wildfires and close their windows. And we have another client that does home visits. So the home nurse professionals or technician professionals, their notes are then transcribed into the model as well. So there is that adaptation of different, after the base model is implemented, they can bring on some really cool things to enhance that. Another one is I think this is really cool, which I didn't know about, is elderly patients respond to avatars better than humans or more honestly. So another company is using something like an Alexa. I don't know if it is Alexa to ask their patients, how are you feeling today? And then transcribing that response back into the model and getting that. So I guess I would say we're a product, but we after the base model, we can branch out into different ways to achieve better results for your patients.
Emmanuel Fombu:
Oh, that's fantastic. So as we wrap up, what has been some of the challenges that you faced so far? Because I don't want it to sound like it's been like this easy frozen piece, right? So what have been the challenges up to this point and where do you see yourself in the next year, the next three years?
Severence MacLaughlin:
So it hasn't been easy. Manny, right? You know, science is tough. You know, you've done a PhD or a master's, as a person you know the scientific process and the hypothesis. And I think what people think of AI or business that they think, oh, we'll just throw a couple data scientists at that data set and they'll come up with something. Well, that's not AI is true science, and we went through that. It's taken us four years to do this, and not many companies would actually invest the people and dollars to sit in a room for four years to be a cost center to get this innovation out. So that was very challenging. And the long sales cycles as well as, you know, we have to be interoperable with all Microsoft and Google and AWS and Teradata. So we had to check all those boxes, right? So it was challenging. But mean anything worth doing is worth doing well. In terms of where do we see ourselves in a year or so? You know, we'd like to be at 20% of the market in terms of the healthcare companies, our sales AI increasing across consumer packaged goods. But in the future, where do I see DeLorean? I would love to be the Intel of AI. Like X Powered by DeLorean AI. So that's the dream. And we've got a great team, Manny, you know, some of them and advisors and Ritchie and you know, I think the growth trajectory for we're at the right time and we got the right work. I think good science always comes to the top, as you know. And so we're excited about the future.
Emmanuel Fombu:
I'm excited about the future as well as you have great advisors on, Ritchie, yourself, and people I respect and great friends as well and I'm very happy to see you on this particular journey, Sev. Thanks to be on the show. I would love to have you again to see how things going. In the meantime, I'll make sure that through our network we'll make the right connections to make sure you get more payers on as customers get more investors on your site to make sure that you grow and succeed. Thank you. It was an honor to have you on the show, my friend.
Severence MacLaughlin:
Manny, Thank you so much. Great to catch up, man.
Emmanuel Fombu:
Thank you for listening to Bite the Orange. If you want to change healthcare with us, please contact us at info@EmmanuelFombu.com or you can visit us at EmmanuelFombu.com or BiteTheOrange.com. If you liked this episode and want more information about us, you can also visit us at EmmanuelFombu.com.
Sonix is the world’s most advanced automated transcription, translation, and subtitling platform. Fast, accurate, and affordable.
Automatically convert your mp3 files to text (txt file), Microsoft Word (docx file), and SubRip Subtitle (srt file) in minutes.
Sonix has many features that you'd love including enterprise-grade admin tools, transcribe multiple languages, collaboration tools, automatic transcription software, and easily transcribe your Zoom meetings. Try Sonix for free today.
Severence MacLaughlin:
Dr. MacLaughlin is the Founder & CEO of DeLorean Artificial Intelligence (DAI), which produces sentient and semi-sentient systems of intelligence for Sales, CPG, Financial Services, Healthcare, Life Sciences and Natural Resources markets. DAI has successfully submitted and holds Patent Pending rights on a number of Predictive and Interventive AI capabilities.
Dr. MacLaughlin is one of the top-ranked Life Sciences/Healthcare Data Scientists globally (Ranked among the top 20 Life Sciences Data Scientists; Ranked #2 Healthcare Data Scientist; Ranked #1 Consulting Data Scientist in the Life Sciences and Healthcare knowledge base; Recognized as American Healthcare Leader for Q1 2018).
Dr. MacLaughlin has delivered over 40 new disruptive technologies and/or implemented Systems of Intelligence resulting in over $1.8 billion in net present value to customers and an estimated $8 billion ROI over the next five years.
Severence earned a BS (Magna Cum Laude, Honors & Distinction in Research) at Cornell University, a Doctorate Degree (Honors, Top 1%) from the University of Adelaide, and a post-doctoral fellowship at the University of South Australia. Severence has authored over 20 international scientific papers and given invited lectures and conference papers at academic institutions as well as international scientific events.
Things You’ll Learn:
Many healthcare executives get tired of the administrative work and end up creating their own companies.
Data in healthcare has the potential to improve patients and caregivers’ lives.
No company is interested in buying only a product, they are looking for revenue too.
AI technology and product development may come from the same mother patent.