Today on the CIBC Innovation Banking Podcast:
Russell Glass (00:09):
Understanding where those opportunities are, what is going to be disrupted because of these changes, and where can you either pivot some of your focus or double down in other areas of focus is critical to not only surviving these downturns but the opportunity to come out far ahead of where you would have been without it is there
Here is Michael Hainsworth.
Michael Hainsworth (00:46):
COVID-19 has led to swift changes across all industries as they race to adjust to the new normal. For telehealth success story, Ginger, physical distancing has forced the company to revisit all its assumptions and evolve. For innovation economy entrepreneur, and CEO, Russell Glass, the pandemic has provided him with a unique perspective.
Russell Glass (01:08):
Before the pandemic, there was this huge supply, demand imbalance in the mental health space. Far more people had a need for care than could get access to a provider to provide care. And then, all of a sudden the pandemic hits and we see skyrocketing need in rates of adoption because the friction has just become way too hard, way too high for people to access in person care. We have seen a 200% increase in therapy and psychiatry appointments. We've seen 100% plus increases in our monthly active users. We've seen 25% increases in intensity of conversation.
Michael Hainsworth (01:55):
What do you mean by that?
Russell Glass (01:56):
Yeah. Good question. We measure how intense a conversation is from the provider's point of view. So, we ask a provider, how intense is this conversation from one to five? Because we want to know, from a supply, demand standpoint, how are our providers doing? Do we need more providers available? Because the more intense the conversation, the more of somebody's cognitive load that's going to take up. And so, we've seen that score go from just under three, so two point... high twos pre-pandemic to kind of mid three's, about a 25 point increase during this period.
Michael Hainsworth (02:37):
So, if you're graphing all of this kind of information, you've got all of this raw, granular data, can you use it as a forecasting model? Would you be able to put the graph together that says we can predict that things are actually starting to improve, or we need to raise a red flag about this thing over here?
Russell Glass (02:56):
That's actually very similar to how our system works. The whole goal of Ginger, starting pre-pandemic and really focused on this huge supply, demand imbalance that exists in the mental health space, is to solve for that imbalance. How do we figure out how we can provide far more care per unit of supply or per provider, while maintaining high quality, while maintaining good price points, efficient price points, and maintaining access to as many users want to use the platform?
Russell Glass (03:36):
And there are two approaches to that. On one side, we are approaching it with new technologies, new delivery models, using evidence and using studied practices, but making those able to scale more effectively through technology. On the other side, to your question, we are looking very closely at supply demand factors. How intense are conversations? We're measuring how fast people are getting healthy? Or are they getting worse over time? And that allows us then to predict how many providers we're going to need and make sure those are available as our system continues to scale.
Michael Hainsworth (04:18):
So, I want to expand on the whole idea of AI in healthcare as Ginger sees it. But help fill in some blanks before we get to that point. Being in telehealth pre-COVID, how have perceptions changed since the pandemic?
Russell Glass (04:34):
What's interesting about telehealth in general is it's been available for a while. And yet, adoption rates were relatively low. And I think the reason for that is people were used to going in to see their doctor. They were used to picking up the phone, calling, making an appointment, and showing up at the doctor's office. I think what's happened with the pandemic is we've seen an acceleration of that adoption curve of telehealth because people have been forced to access care in a virtual way versus an in person way. And, if you look at some of the numbers, they're pretty staggering. We heard from Kaiser Permanente, which is a large partner of ours, we do a lot of their telemental health services. They've seen a 10% or so telehealth rate scale to about an 80% or so rate during this period of time. So, we're talking about years of acceleration of adoption that's taken place because people are, A, afraid to go out and get exposed. But B, they are in lockdown situations and the friction of going out is far higher than it used to be.
Michael Hainsworth (05:57):
What do you expect, though, as far as the potential for the rubber band effect? Once we all get the all clear, whether it be a month from now, six months from now, whenever it happens to be, once life returns to normal, do you expect that to shrink back again? Or will it just become part of the fabric of our life?
Russell Glass (06:14):
Historically, we've seen that people who try tele-health tend to stick with it. They tend to realize that it's a far easier, convenient tool compared to the traditional way of getting access to healthcare. And so, you see that, when people try it, 60 plus percent of them stick with it over time. It's a preferred way of doing things once you've figured out how to do it. So, I expect the same thing here. I think, now that people have given it a try and realize just how convenient it is and how effective it is, we're going to see the vast majority continue to get most of their health care through telehealth means.
Michael Hainsworth (07:01):
You say that, once you figure out how to do it, people will take advantage of it, build the better mouse trap sort of scenario. How did you figure out how to do it? What is it that is that secret sauce that has people willing to continue to use you?
Russell Glass (07:17):
It's interesting. Incentivizing somebody is the trick because the convenience of seeing your doctor from the comfort of your home, versus having to get into a car, having to go to an office, having to expose yourself to other potential germs, having to sit in a waiting room and wait for that person to be available. I mean, all of that friction, once you then experience tele-health and you download an app or you connect on zoom and immediately you're connected with someone, you don't have to get dressed up, you don't have to get in the car, it is not the delivery of care that's the problem. It's incentivizing people to try it in the first place.
Russell Glass (08:03):
And I think what's happened here, from a Ginger standpoint, is we have done a lot of work historically to help people recognize the power of what we can deliver for them 24/7. In the middle of the night, if you're having a panic attack, Ginger is there for you. And, within 60 seconds, you're going to be able to connect to one of our providers to help you with that situation. Again, very different than the standard of care, but there's always friction in adopting something new.
Russell Glass (08:33):
So, what we had to do, as Ginger, was help people understand all it takes is a download. All it takes is clicking a few links to get started. And yet, it still had relatively low adoption rates pre-pandemic. Now, the pandemic shows up. People can't get access to their traditional therapists or psychiatrists. People are not willing to go to a doctor's office and yet, realize they need support. And frankly, their anxiety levels are up. Their stress levels are up. Their depression levels are up. And they are now incentivized to figure out how to try this for the first time.
Michael Hainsworth (09:10):
We've been speaking so much about how we can use artificial intelligence for things like contact tracing and keeping on top of a pandemic generally. How are you applying artificial intelligence for the future of healthcare? We're unleashing this remarkable power into telemedicine.
Russell Glass (09:29):
Artificial intelligence is an incredibly powerful set of technologies that I believe will both help personalize, scale, and make healthcare more efficient over time. For us, the way we use AI today is primarily on the provider side. We're monitoring conversations. We're extracting information from those conversations like someone's history, medications, other comorbidities, or other illnesses that they might have along with the mental health issues, family histories, their tone of voice, their change in the way they're speaking over time. So, we're taking all of this information and we're looking historically at different conversations at different interventions and predicting what is the most likely next best action? What is the decision that a coach or a therapist should make in order to help get this person healthier faster? Is this person at a certain degree of risk? Like, are they showing suicide risk that might not be picked up by a clinician, but the AI can pick it up? So, all kinds of decisions like that we are applying to the care model to help make it more personalized, more effective, and more scalable.
Michael Hainsworth (10:53):
You mentioned that you're monitoring these conversations. So, we have to have that discussion about privacy and the issue of bias in artificial intelligence. When you have large data sets, sometimes biases get inherently built into those systems. . How do you monitor conversations while retaining privacy?
Russell Glass (11:18):
An important issue. First of all, critical to understand that everything we do, we're a hospital system, we have med PCs or professional corporations set up around the country and follow all the HIPAA regulations and healthcare regulations that are prevalent worldwide. Second of all, when you have this kind of information and you're using it for this, you have to make sure that you have the right privacy restrictions in place.
Russell Glass (11:46):
So, when we extract this information, the first thing that we do is de-identify it from the of view of anybody who is accessing this information is either a care provider for that person, so that they're actually providing care, or, if they're not, they only have access to de-identified information, so information that can't be reconnected to the end user again. And we're actually doing all kinds of things from the standpoint of security and making sure that, if there ever was a breach, information distribution would be limited, making sure that we are following all best practices and even going above and beyond so that information like PHI, or protected health information, can't be exposed at scale.
Michael Hainsworth (12:37):
What are those issues of scale though? Do we require international agreements for data sharing, standardization, and anonymization of this kind of sensitive information?
Russell Glass (12:47):
Today, we follow local regulations. So, any country we're in, we are going to follow regulations there, at least as strict. But, because we're trying to create a scalable system, it's important that we don't have different standards for every different country that we spend time in. And, because of that, we will always follow the strictest regulation of all of the countries that we are in. And I think that's an important principle because, if you really want to scale, you can't have a whole bunch of different rules and regulations. And you can't have to follow different standards. And so, our approach has just been, look, let's understand what the most rigorous set of laws are and follow those across the entire system.
Michael Hainsworth (13:41):
So, how does your team layer on the mechanisms of advancing AI next to the actual clinicians who are using it? I can imagine that the most effective technology is one you don't even know exists.
Russell Glass (13:55):
Decision support is a very valuable use of AI today. It allows you to super charge the provider because you're giving them information that they might not have access to without this technology. So, I'll give you a simple example. Let's say that you're a therapist or a coach and you've been working with somebody for months. It'd be very hard for you to remember all that that person had said during that three month period. You might remember snippets. You might have summaries. But we're human and we can only store so much information. But a system like ours can monitor those conversations and see micro changes in how that person is communicating and, at a certain point, recognize that this person, let's say, is heading in the wrong direction relative to what our expectations would look like, and can recommend an escalation to another level of care, That is a game changer from the standpoint of being able to provide quality care. And I think it's really the very beginning of what we're going to see with technologies like this.
Russell Glass (15:19):
So, another example is we're starting to roll out what we call our smart answers system where we can actually predict what a coach should reply with based on the personal care plan for this person, based on how they're trending over time, based on all of the conversations we've seen in the past. And now, a coach can actually choose to reply directly with what we recommended or edit it and then reply. But again, that leads to better quality control. It leads to that coach having access to the millions of conversations and the intelligence gleaned from that, which they'd never have on their own. It allows them to be highly measurement based, highly data-driven. And ultimately, allows us to scale their ability to handle many more members than they could without technology like this.
Michael Hainsworth (16:09):
I like to focus on the entrepreneurial side of running Ginger and come back to COVID-19, and specifically how you responded. For you, what was the biggest adaptation, as an entrepreneurial leader, that you had to overcome yourself?
Russell Glass (16:23):
That's a great question. I've been an entrepreneur for my entire career. I've been a part of four or five startups, whether founded myself or part of the founding team. And this is my first time in healthcare. So, I think the biggest thing, at this point... I have a good sense for how to hire great people, how to build great cultures. Both, I think, are critically important to success. How to build strategies and how to make sure the team is focused on those strategies.
Russell Glass (16:58):
I think the difference in health care and what I had to learn and get up to speed on is just how complex and multilayered the industry is. From understanding the economics, the different payers involved, from employers, to governments, to insurance companies, understanding perverse incentives that exist throughout the ecosystem, to understanding how and where you need to focus on the way things have been done and when you can truly innovate and change how things have been done. All of those are our new ways of thinking that, at one side, has been extremely fulfilling and exciting, but on the other side is a new mind space for me.
Michael Hainsworth (17:46):
And then, let's forward that into how you applied your entire career as an entrepreneur to addressing COVID-19 and the impact it had on your organization and your ability to not only capture the growing momentum in an area where people had a demand for what you offered, but also to build on that momentum and accelerate it.
Russell Glass (18:09):
Another good question. I think any entrepreneur that has done this for a while would say that you're going to have ups and downs in any company. And, if you're lucky, you won't go through a cycle like this. But, eventually, everybody is going to go through downturns and hard times. I've been through... this is, I think, my third major downturn in the global economy that I've had to navigate. In all cases, downturns present challenges, but they also present opportunities. And understanding where those opportunities are, what is going to be disrupted because of these changes, and where can you either pivot some of your focus or double down in other areas of focus is critical to not only surviving these downturns but the opportunity to come out far ahead of where you would have been without it is there, if you can execute quickly against the opportunities.
Russell Glass (19:15):
In Ginger's case, you could hardly define a better business model and value proposition for these times. We are focused on mental health. We are delivering entirely virtually. We're doing it in a highly scalable and convenient way. We are trying to solve for supply, demand imbalances that already existed, but now have a system that can scale when that gets even harder. So, all of these things are huge advantages for us. And I feel fortunate that we're in a position to really provide help to a lot of people during this period of time.
Michael Hainsworth (19:51):
So, what is your advice to a startup entrepreneur who feels blindsided? This is their first global downturn. This is the first time they maybe have been unable to execute on the business model they've spent however long crafting.
Russell Glass (20:07):
A few things. One would be revisit every assumption. So, anything that you thought was true going into this period, you need to very quickly take a step back and decide what's still true and what may not be true. I'd say two, be realistic. Don't be Pollyanna about what's happening here. Assume your uncertainty in your plans, in your assessments has gone up literally exponentially. And then, use that assumption, use that uncertainty to make better decisions about your business with the revised set of assumptions that you looked at in step A. And then, I would say, finally, focus on your team, focus on your culture. Make sure your people are doing okay first. Make sure that they are in a position to execute. And, as you're then changing and shifting your plans based on this, you're going to be in a much better position to execute if you have a strong team that feels secure in what they're doing day to day.
Michael Hainsworth (21:11):
And what did you do to check in with your team?
Russell Glass (21:13):
Well, we're constantly doing it. I think the first thing we recognized and very quickly acted on was that we didn't want people going to the office anymore. And so, we very early decided we were going to have people stay home. It was easy for us because 60% of our staff was already working remote. So, we had a lot of the systems set up. And we just recognized there wasn't going to be any upside to forcing people to come into the office anymore. So, that was one.
Russell Glass (21:42):
We then built a cadence of check points and making sure people had a good understanding of how we were looking at the pandemic, how we were looking at how our operations were going to change. We had a people operations team that continues to this day to provide updates in terms of how we're thinking about the world so that people can make good plans on their side. We're doing more frequent surveys of our employee base to understand how they're feeling. We are building all kinds of content, both for our providers, so our coaches and our care providers, around the issues you're going to face with social isolation, with fear of a pandemic like this, with family life changing so dramatically, children home from school, caretakers, dealing with your parents who are at high risk, et cetera.
Russell Glass (22:38):
We've done the same thing in terms of racial allyship and building racial trauma content to make sure that, during this period of racial unrest, people also have the feeling like they're supported. And we're increasing benefits. We've increased our wellness budgets. We're ensuring people are taking time off. So, it's easy not to take time off at a time like this. So, we had, in May for mental health month, we had a take time campaign to make sure that people were taking at least a day off. We're asking people to take at least a week off this summer to recharge and refresh.
Russell Glass (23:17):
So, we're really trying to make sure that people are treating themselves in a way that's sustainable and they can continue to operate at a high level during this time of uncertainty.
Michael Hainsworth (23:28):
Russell, thank you so much for your time and insight. This has been fascinating.
Russell Glass (23:31):
Of course. Thanks for having me. It's been a pleasure.
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