The Center for Data Innovation spoke to Lee Omar, Chief Executive Officer of Red Ninja Studios, a Liverpool-based design startup that works on using data to solve complex problems in public services, including health and social care. Omar discussed the importance of data-driven designs that fit unique problems, instead of starting with a technological solution and looking for a problem to force it onto.
This interview has been edited for length.
Nick Wallace: You worked in human rights for 11 years. How did that transition happen, and how much overlap has there been between these two parts of your career?
Lee Omar: I was working with refugees. I loved it, it was one of my favorite jobs. But as I was coming up to about a decade in the field, I started to think that if I wanted to make a real impact, I had to find a way of scaling what I do. So I started thinking about technology and the rise of the app market. I wasn’t a techie, and to begin with I didn’t even have a smartphone, or Internet at home—I wasn’t an early adopter. But I was interested, so I started educating myself. I watched YouTube videos, read up, and I did the Stanford University iPhone developer course just to get an idea of how the technology works.
The more I got into it, the more I saw the potential for tech to improve lives. I decided to create a startup, which was Red Ninja. I started hiring designers who could build apps and who were interested in improving people’s lives here in Liverpool. I saw things like smart cities, I started to learn about things like big data, and I wondered how we can leverage this sort of thinking and put it into a Liverpool context.
We did some studying around what Liverpool’s challenges are. We already had an idea: People die earlier, they’re unhealthier, and unemployment is higher. We knew that, but we wanted proper data, so we looked at what all the current strategies for the city were in relation to health, transport, low carbon, and driving the economy, and tried to get a better understanding of what the challenges are.
We produced a report called “Connected Liverpool – Creating a Smart City.” The first half set out the problems, the second half set out the technologies that might help. Then we started building prototypes, people started talking about them, and we started creating an international profile. We learned as we went along, and we started teaching ourselves about the innovation process. We built custom technology as a consultancy, and then we used the money we made to create our own IP to address the challenges we want to address.
We don’t build a product and find a market; we start with a problem and then look for the solution. In a way, I was doing this fifteen years ago. Now people call this human-centered design, back then, in the voluntary sector, they would’ve called it bottom-up community work, or something like that. I’ve always understood that to make good services you’ve just got to listen to people, and not be too arrogant.
Wallace: Tell us a little about the role data plays in your design process for health and social care projects.
Omar: One project we’re involved in now is called the Life project. We’re trying to reduce the mortality rate of people who have a heart attack or a stroke in the city. We know if you have a heart attack or a stroke, you need an ambulance in five to eight minutes. So we asked the ambulance authority for ambulance data, and the city council for traffic data. We use that to identify the most effective route through the city, and to manipulate the traffic lights for the ambulance using an algorithm. This can cut several minutes off a journey and potential save somebody’s life, or give them a better level of care.
I’m quite underwhelmed by a lot of the applications in smart cities, they seem very tech-focused, rather than people-focused. We spent six months sitting in an ambulance filming what it’s like for an ambulance driver, speaking to the person who dispatches them, and understanding that process and what the journey is. We don’t just want to force technology on someone. We don’t make technology and then try and find a market, we find a market or a problem and then we find a solution. We get help from the experts, as we aren’t experts in health or ambulances.
The data we want isn’t always open, so sometimes we have to scrape it together. It doesn’t sound amazing now, but in 2012, we took live data from the rail network and visualized all the trains on the Merseyrail network on a map. But Merseytravel wouldn’t give us the data, so we used signal box data from Network Rail to get an approximation of where the trains are. We did that to say, “look, if you open up data, you can give citizens a better deal.”
For another project we did in Liverpool, we wanted to democratize the planning application process for citizens, and open up the data for the whole city. The city council said we could have the data, but third party suppliers didn’t always cooperate. So we had to scrape the data off the council website, clean it up, and make it machine-readable.
Once we had the planning data, one of the “Big Six” energy providers came to us and said, “can you start using that data to inform us where we should put our infrastructure, to future-proof us as new buildings get put up?” Because the council gave us permission to reuse the data, we were able to use the data from that project in a totally different sector.
Wallace: KitchenSense, a system Red Ninja designed for North Wales National Health Service (NHS) Trust, uses sensors to help people with brain injuries and memory loss to cook, by monitoring where they are in the kitchen. How did you go about developing that system? What was the role of data analysis?
Omar: We went about it the same way we approach any problem. We put the experts and the end users at the heart of the design process. The problem we were trying to solve was, “how do we aid the people who are living with an acquired brain injury?” Short term memory is commonly affected, and the occupational health therapists told us that one of the big challenges was cooking.
People can’t remember how to do certain cooking techniques that you and I might take for granted. If I say to you, whisk an egg, you know I mean to take an egg, crack it into a bowl, and stir it fast with a whisk. Somebody with an acquired brain injury might struggle to remember all that. We got people into workshops and they told us, “I can cook one meal and I make the same meal every day for months on end.” It might be beans on toast, day-in-day-out.
So, we just looked at it practically. We built a recipe app with fifteen recipes, simple to understand, big photographs—a journey of how to make a meal. It might be an omelet, so it will say, pick up your spatula, pick up your whisk, stir it like this—there might be a picture of a whisk—the app can be customized to the individual’s needs.
But then there’s a safety element. People start to cook, then wander off into another room, leaving the cooker on and starting small fires. So how do we get somebody back in the room who’s left an unattended chip pan on the stove? We originally experimented with using motion sensors, then smart watches. Eventually we created our own bit of wearable technology, which is a sensor that goes on your wrist and can help with both the recipe and safety.
We’ve used machine learning to train an algorithm to understand what the wearer is doing based on the movement of the sensor. So it can tell if you’re whisking an egg or chopping carrots. We can also tell if they’re in the room or not, because there’s a Bluetooth module to link the sensor to the tablet, so when the sensor goes too far away from the tablet, we know the person’s not cooking anymore. They might have gone in the other room to watch TV. Once that happens, there’s a buzzer to get them back.
Once the person starts using that, the data becomes part of their rehabilitation. We collect the data and visualize it on a dashboard for the occupational health therapist. North Wales NHS only has two therapists dealing with this for the whole region, they don’t have the resources to check in on everyone. The data helps them to understand where people are up to with their rehab process.
Wallace: What do you think it’ll take for IoT-based assisted living systems to become mainstream tools of health and social services?
Omar: The UK is a massive buyer of health and social care. Millions of people work in the sector. But we’re not as innovative as we could we. We don’t have integrated health and social care in the UK. There needs to be more policy to change that. Things like devolution of power to local government—that’s an opportunity to drive the sort of efficiencies that the Internet of Things brings. But the way the health service is now, it doesn’t necessarily benefit an NHS Trust to treat people at home. Their business is treating people in hospital. The NHS is a national treasure, but the system is broken, it’s not fit for purpose.
I think as funding cuts and austerity bite more, we won’t be able to provide the sort of human elements or social support. I think you might see some of that turned into a technology solution as a replacement for a person, because the NHS can’t afford to pay for someone to provide that level of care.
At a more global level, I think this stuff will take off in the next five to ten years, as the baby boomer generation gets older. They’re a generation that’s always driven consumerism, they’ve always got good products and services. I think they’ll demand some of these more modern services for their own care. I think there’ll be a market push, but more of a consumer pull, from a more savvy consumer.
Wallace: What impact do you see big data having on health and social care at the moment, and where do you see it going in the near future?
Omar: I bundle big data in with the Internet of Things. As sensors become more ubiquitous we’ll have more data. As artificial intelligence and this sort of stuff improves, and people become more literate, we’ll get more insight into health and social care through leveraging big data. I think we’ll become more in tune with our health and our bodies and with the way we’re going. People will become the center of a feedback loop generated by their own data. The day when you go to your doctor for a checkup because you’ve just turned 50 might end, because you’ll have all the data already. The quantified self will become more of a regular thing, and more mainstream.