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Empowering the digital health ‘data donor’

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Stephen Critchlow is executive chair and founder of Evergreen Life .

The digital health company is empowering people to take control of their own health by giving them access to their own health record.

Health Tech World speaks to Stephen about AI, chronic disease management and the emergence of the patient ‘data donor’.

What is Evergreen Life?

Evergreen Life was founded on the principle that people should own their own health record.

You don’t need interoperability if the person has the record themselves and can choose to share it at the point of care.

It’s free and we’ve managed to connect to every GP in the country. And there is an app that can be used for your wellness.

                           Stephen Critchlow

You can raise your prescriptions from there, you can get an appointment from your GP, you can download your record onto the app.

We’ve got three million users overall, about a million of those can access their GP record on the system.

Digital health has obviously exploded in the past few years. But you’ve been working in this space for decades.

It’s interesting you say that.

The very first programme that I wrote was prescribing for Total Parental Nutrition, which is one of the more clinical things many people are currently doing with AI and digital healthcare.

So yes, in the late 80s and 90s, I was using technology that is not dissimilar to what we’re using today. It’s just that the computing power is far greater.

What is the impact of giving patients access to their own health records?

We believe that if we want to change the way that healthcare is provided, we need to start at prevention.

All of us on average suffer 20 years of ill health.

We get ill at about the age of 62 and we die at the age of about 82, whereas in other countries like Japan and Sweden, they only have 10 years of ill health.

So the starting point is that the app will give you a wellness score, and, using AI, drive content to you based on the answers you give to those questions.

That started to result in our users dropping their BMI, blood pressure and hBA1c, and that’s become demonstrable over time.

So much so that if your GP found that you had hypertension, 60 per cent of those of people who use the app returned back to normal in six months.

We’re finding that people are following prevention advice and that dropping blood pressure more than any drug.

It’s the same thing with blood sugar and weight.

We’re now linking it with GPs, and we’re using it for appointments and GP triage.

We’ve integrated with an app that we acquired called Ask My GP.

By using that, we’ve taken GP practices down from a two-week wait for an appointment to seeing the GP on the same day.

And in dermatology clinics, we’ve dropped the waiting time down from over six months to less than two days.

Presumably, there’s lots of positive spin-offs. Fewer people with long term, untreated chronic conditions means less strain on health service, more time for GPs to spend with patients, and so on.

Absolutely.

When you get onto the impact on the NHS, you start to reduce the number of appointments that are needed in the first place.

We manage nine GP practices with [a total of] 100,000 patients. When we take our software there, we can see the impact it’s having.

Their waiting time dropped from more than two weeks to everybody being seen physically on the same day.

But also their blood pressure dropped by 18 millimetres of mercury, so it starts to become an interventional study.

Not only does that mean that there’s fewer people to manage, we’re also reducing the impact on A&E because if people can get appointments on the same day, why would they call A&E?

Another really interesting element of what you’re doing is allowing people to volunteer their data to be used for medical research.

Is that something that you’re already doing now? And are these studies already underway? 

If someone gets a disease, their loved ones will want to raise money to fix it. So why not give them the opportunity to do that with their data?

It doesn’t cost them anything and it will make a massive difference.

We work with 25 universities, on everything from Alzheimer’s to Parkinson’s, heart disease, cancer and general wellbeing. 

In terms of making the biggest difference to health and wellbeing that we can, we’re doing a few things at the moment.

One of them is improving access to GPs.

We have a system where people can fill in a form on their practice website to ask for an appointment.

We find that most people want to use the form because it saves them from having to call in at 8am and wait on the phone for ages.

Instead, they can fill in the form the night before.

From all of that data, we can work with research organisations to see if we can get closer to a diagnosis and understand their needs based on what they’re saying.

Many of the things that people contact a GP for are what we would call admin.

It might be that their prescription has run out and they need a repeat. Well, that doesn’t have to go to a GP. It can be done by admin staff.

So we’re using large language model technology to look at the data so that we can improve things even further.

In dermatology, we collect pictures of people’s moles and we also know the outcome.

So because everybody’s contributing to that research, we’re able to train the system to diagnose whether or not a mole is cancerous based on an image straight from a mobile phone.

I recently had an exciting meeting with NHS England who were asking about how we can save carbon.

Imagine the carbon savings if, instead of going to a clinic, millions of people just sit at home and take a photograph and let a computer tell them whether they need to worry or not.

We’ve saved the journey to the GP which would then become a journey to the hospital and the dermatologist and so on.

We’ve got to the point where we can diagnose a mole, whether it’s cancerous, more accurately than a clinician can.

Where are you expecting to take things in 2024?

We’re working with NHS England on doing a better health check. It started off with which blood tests you take and so on.

We’ve worked out that we can use AI to predict which questions we should ask you to see if your blood pressure is raised, for example.

By choosing five questions based on your age, weight and gender, we can now predict your blood pressure reading more accurately than a doctor could measure it.

The measurement that a doctor takes is less effective at working out whether you’re hypertensive than the questions we ask.

To get here, we needed millions of patients who have connected themselves to the GP record, enabling us to make health checks more efficient.

It must be rewarding for patients to be part of this process.

Absolutely. Just as you can be a kidney donor, why not be a data donor?

If we’re all prepared to let our data contribute to research, we can [help overcome] some of the problems that we’ve got in healthcare, not just in this country but throughout the world.

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