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Managing Health of a Lifetime, a Conversation with Peter Ohnemus, CEO at Dacadoo
87 Plays1 year ago
The concept of scoring and normalizing health assessments, similar to FICO in FinTech, is being explored to establish a global standard for health. Peter Ohnemus, serial entrepreneur and CEO & Founder of Dacadoo, joins Alantra to discuss how his design for digital health assessments aids dynamic pricing for Life & Health Insurance, and the importance of digital health engagement in a member's lifetime.
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Transcript
Introduction to Crossroads and guest Peter Onimis
00:00:05
Speaker
Welcome to another episode of Crossroads by Elantra. I'm Fred Lawyer and I lead the firm's digital health practice. Today we are honored to have Peter Onimis as our guest speaker for this episode.
What is Decadue and how does it work?
00:00:17
Speaker
Peter is a serial entrepreneur and the current CEO and founder of Decadue. Decadue is a digital health platform that
00:00:22
Speaker
provides a range of tools to help people improve their overall health and wellbeing. The platform is designed to help users track their daily physical activity, nutrition, sleep, stress levels, and other health related data using a variety of wearable devices and mobile apps.
Peter Onimis's career beginnings in banking and tech
00:00:39
Speaker
I believe you started in banking at COS in Switzerland, right, Peter? Yeah. Welcome everybody. And thank you so much for giving me the opportunity here.
00:00:49
Speaker
So originally, I started selling and financing IBM mainframes. This was back in the 80s. And the company was called COS. We took it public on Zurich Stock Exchange and Frankfurt Stock Exchange. And then I founded the SQL group. So with the SQL group, I moved into the database industry and started programming late 80s relational databases, met Mark Hoffman, who was the founder of Sybase.
Taking Sybase public and ventures into tech industries
00:01:19
Speaker
built up the SQL group, merged it or sold it to Sybase. And Mark Hoffman is the vice chairman of Dacadoo today. So Mark and I have been partners for many, many years. So after Sybase and the SQL group, we obviously took Sybase Public on NASDAQ and it became at the time the world's fifth largest software company. I worked with LogicWorks. So LogicWorks had investors which were the same people that had money in Sybase.
00:01:48
Speaker
And LogicWorks was in the database modeling industry. And then the modeling of the data. So this was called Ervin. It's the world's most used data modeling tool. And we took, just like Sybase, we took LogicWorks public on NASDAQ. After that, I moved into broadband communication.
Innovations in IP multicast and sustainability ratings
00:02:08
Speaker
And the reason that I tell this story is it all has a connection line.
00:02:13
Speaker
So we built the world's first IP multicast, a satellite company called the Fantastic Corporation. It was Intel's first venture capital investment in Europe at the time with Les Fidesz and all the guys. So we basically built a point to multi-point broadband network around the world. And my last company, as you mentioned, was Asset 4. So I was doing sustainability rating, built it with Goldman Sachs.
00:02:42
Speaker
and sold it to Thomson Reuters. So I've been part of three IPOs and two trade sales. And after we sold asset floor to Thomson Reuters, I thought if you can do a sustainability rating of a public quoted company, looking at their energy usage, water usage. So sustainability for me is not about your political view. It's about efficiency. How efficient do I run my corporation?
00:03:10
Speaker
So I thought if I can do a sustainability rating of a public-coded company, I can do a sustainability rating of human health.
How does Dacadoo's health score platform work?
00:03:17
Speaker
And that gave the idea through the Dacadoo health score platform. So we started them in 2010. So that really was the impetus right. That was the idea behind Dacadoo. You started in FinTech and thought you could transpose the same concept to healthcare. Is that how you were thinking about it, Peter? That's correct. So we saw an opportunity
00:03:38
Speaker
creating a global standard. And I like that you touch on the FinTech world. So I think everybody in America, they know a FICO credit score. So basically taking a score over to the health industry. Why? Because health is one of the largest industries in the world. We spent around, depending on who you talk to, eight to nine trillion dollars on health globally. And we didn't have a health outcome.
00:04:05
Speaker
I always said, if you can understand something, you can improve it. So creating a baseline of health became the health score and that became a universal standard. So we set score and we normalized it so a man and a woman can compare themselves, have the same health score. So age independent and gender independent, but having a global health score standard. So yes, we got the idea of course, from the FinTech or from the financial industry,
00:04:35
Speaker
where you know scoring, where you know rating, and taking that into the global healthcare industry. And we're seeing an opportunity to create a standard there, a baseline of
Challenges in digital healthcare transformation
00:04:47
Speaker
health. What is different about working healthcare in your opinion when you compare it to other verticals such as FinTech? I'm sure that as a serial entrepreneur, you have learned many lessons over the years. What have you been able to transfer to Decadue, Peter? Yeah, that's a good question.
00:05:02
Speaker
I think what really differentiates healthcare from anything else is there is, at least in the digitalization process, there has been less competition. And your listener will answer themself, why does he say that? Because when we look at the digital transformation of health, I think it's 10 to 15 years behind banking, behind retail, behind travel. So basically what we are seeing is an industry
00:05:32
Speaker
which by nature is conservative because you have the FDA and strong regulation. But on the other hand side, pretty predefined revenues. So most people, if they have a family doctor and they do not change town, they tend to stay very long with the same family physician or specialist. What I'm getting at is if somebody has high blood pressure and they got used to a high blood pressure pill,
00:06:00
Speaker
They like to stay with that medicine that they know. So, medicine by all terms or health or digital health is not a sprint. It's a marathon. What about stickiness?
Exploring pharma revenue and insurance dynamics
00:06:14
Speaker
In this case, I guess, as you mentioned, your end users are patient, but pharma employers, payers are footing the bill at the end of the day. Do you think it's stickier than what you've experienced in other verticals? Yeah. When you look at big pharma companies,
00:06:28
Speaker
They traditionally have patents behind their blockbuster products. So let's say that they can protect the market at least for 10, 15 years if you take some of the development and go to market time that they lose on a 25-year typical period for big blockbuster products. So yes, they have a predictable revenue stream. Number two, they do very deep research. So they understand the pricing mechanism, the approval mechanism,
00:06:58
Speaker
and the overall, I will call it market adoption rate. If you go over to the payer side, that's a little bit different. So I think when we look at health insurance in America, people flip their health insurance quite often. So we see typical churn ratio of 18 to 24 months. And why does that take place? Because maybe they change job. So if they are with a self-insured employer, when they change a job,
00:07:28
Speaker
they take the prime carrier of that new employer, they have become more open to exchange. Once they get a bit older, we see a higher stickiness. So once, of course, they are on Medicare, Mediate, they stay there. But also, I would say from 50 and upwards, we see a more flattening curve in the stickiness. And what I mean by flattening curve is, of course, positive that they stay longer
00:07:58
Speaker
with their health insurance carrier.
Understanding the health score system and Wheel of Life
00:08:01
Speaker
You just mentioned a topic I really want to talk to you about. Let's put a pin on that, which is pricing. We'll come back to it later during the podcast. First one, the health score index we have already discussed. It really essentially quantifies patient health.
00:08:17
Speaker
Let's talk about the Wheel of Life for a minute. It connects the score and engages users in a way that helps them achieve their personalized health and wellness goals. Could you please elaborate on the real world impact of your two solutions? Yeah. So overall, it's very difficult to obtain sustainable long-term engagement in digital health. Around 45% of all Americans are not adherent to their medical treatment.
00:08:47
Speaker
What we do is we give you a health score, which is the proxy of your health or the baseline of your health. We then use gamification and behavioral economics for you to integrate with your health. The overall engagement levels that we are seeing are typical 20 to 30 to 40% of the consumer. It's very different from age group, where they live, gender, et cetera.
00:09:18
Speaker
When you look at traditional health insurance companies, they have 2% to 4% engagement. And this is based over a 30-year period. So basically, it's when you have to pay your monthly bill. It's when you have to book something. And we are trying to provide, as you said before, a holistic view of your health. So with the Wheel of Life, and why do we call it Wheel of Life? Because you drive through life, and you want to navigate and stay
00:09:47
Speaker
healthy with the wheel of life. You focus on an end market we don't often deal with, which is life insurance. I believe you also sell into health plans and self-funded employers. I'm curious to hear your perspective on the differences between those three end markets. What do they look for when they look at the wheel of life? For instance, how would they use the tools differently?
Differences between life and health insurance goals
00:10:11
Speaker
Yeah. So let's look at the two industries. So the life insurance.
00:10:17
Speaker
They have a key motivation in me living as long as possible. Doesn't sound pretty, but if I don't pass away, I will pay premium every month and there is no payout. So the economic motivation of a life insurance is to keep me alive as long as possible. The health insurance, they want to keep me healthy as long as possible because they want to make sure that the cost do not run out of control.
00:10:47
Speaker
So let's just go back to the life insurance. The life insurance, as we know it today, is based on life tables. Life tables are published by a country. They are so-called pictures of your life. So life tables were invented in 1824 by Gometz, who was a mathematician. And he said, I will try to calculate the distance to death.
00:11:12
Speaker
So basically he created a risk model. So how many die of smoking in America every year? How many die in a car accident? How many die of cancer? So this is a statistical value and this is how you price life insurance today. When we invented Dacadoo in 2010, we said it has to be predict and prevent. I'm predicting where you are and I prevent you
00:11:38
Speaker
to get ill. I prevent you to die. Instead of creating this frozen picture, which is a static value in the life table, which is great, it's what actors use. Now we are changing the world and adding what I will call the movie component because your life moves on and health is not something static. Your health goes up and down. It's a long-term perspective, but from a mathematical perspective,
00:12:07
Speaker
I create a lot more. What is very interesting is the health insurance, they are having lower margins. Normally I know right now that health insurance is profitable, but if you look over a long-term period, life insurance have higher margins, more cash on the book. So they are long-term thinking and health insurance, they recalculate their book every year because people can jump away from the health insurance every year.
00:12:37
Speaker
Most people buy a life insurance with duration 10, 20, 30 years. So the way of thinking is a lot more long term, but you don't have touch points. Most or many life insurances are built once per year. That's the only time the life insurance has contact to you. So what we are trying to do is to give the life insurance touch points to the consumer's life.
00:13:05
Speaker
enhance their overall product offering, enable them to upsell and create a more dynamic relationship with the consumer.
00:13:15
Speaker
Fascinating. It almost sounds like life insurance is starting to encroach into health insurance. The end goal is to keep patients healthy and to lower costs after all.
The future: Dynamic pricing and AI in insurance
00:13:25
Speaker
Now, going back to the dynamic pricing topic, let's talk about it. How does it work? What are the data inputs required to do it? What does it enable? Does it mean lower risk, higher profits? Can you please elaborate? Yeah. So as I mentioned before,
00:13:41
Speaker
A live table is static and most pricing models are static, but your life is not static. So what we are seeing coming is called pay as you live. So basically that there is an index based component. So let me give you a concrete example. We've just created a cancer policy with an insurance operator, a very large one in Japan. So we have actually gone to the FSA in Japan
00:14:09
Speaker
and said, this is how our model, this is how our AI risk engine scores, cancer risk, this is the mortality risk, et cetera, et cetera. So what I'm getting at is you have something called straight through processing in insurance. So if a normal ACK2R has to calculate or price most of the insurances, then they have preferred, non-preferred, so they create small buckets and they put you in there.
00:14:37
Speaker
So this is a lot of extra administration. If you look at, and I cannot prove it, McKinsey says, if you do straight through processing, you can take out 25 to 35% of the cost of running the pricing and the selling of the insurance. So I think the future is straight through processing. So it gets calculated and optimized via AI models. Of course, some of them will get reviewed by human beings.
00:15:05
Speaker
It's the same as if you look at chat GTP, chat GTP is only as good as the person who has trained it. And the same goes for accelerated or dynamic underwriting. So as we go forward, we will see a more dynamic pricing, a more dynamic underwriting and the straight through processing. This will create lower cost per issue policy. It will create
00:15:30
Speaker
a more variable so you can add, you can slice and dice the policy because you know more in real time and it enables you to go back and revisit your book.
Global insights on insurance and concluding thoughts
00:15:43
Speaker
Hey, Peter, thank you so much for joining us today. We often come across vendors that sell into payers, but I think you're the first one that actually sell into life insurance as well. Most of the vendors or the payer tech vendors that we cover do also only sell in the domestic market, giving how complex the US insurance market is. So airing a perspective from a global player is captivating and very, very intriguing.
00:16:08
Speaker
For me, the highlight of this episode is the discussion on dynamic pricing and how that changes premium coverage and patient overall well-being. Again, a real pleasure talking to you and having you as our guest today. And I do hope we get to meet one day. Thank you so much to you and the whole Atlanta team. I really appreciate that you gave us the opportunity and thank you to all the listeners to listen to my little story. Take care, Peter, and enjoy the rest of your day.
00:16:44
Speaker
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