Summary: The prevailing model of healthcare is more reactive than proactive, treating health problems rather than preventing them. We believe digital healthcare tools can flip this model by offering a more holistic insight into a patient’s health over time. Our Global Clinical Director Dr. Arrash Yassaee explains how Huma is building digital healthcare tools to predict and prevent rather than detect and treat disease.‍

The prevailing model of Western healthcare is generally more reactive than it is preventative. Patients go to their healthcare provider when they have noticed that something isn’t right – when they’ve developed a new symptom or set of symptoms over time.

Although this system works for many short-term, acute illnesses, it often fails when it comes to chronic conditions like cardiovascular disease and diabetes, which may progress slowly over time. By the time there are enough symptoms to trigger a trip to the doctor, irreversible changes may have already occurred.

Considering how our healthcare system serves people with long-term health conditions is important, as more than 70% of deaths globally are the result of chronic diseases, according to the World Health Organisation. The risk of chronic disease increases with age¹, which means as the population ages, more of us are likely to face a long-term illness. In the EU in 2019, more than half of people aged 65 and over had at least one chronic disease².

It doesn’t have to be this way. Moving towards more proactive healthcare - detecting and managing health conditions at an earlier stage - could be transformative for patients and wider society, ultimately improving overall health and wellbeing.

From the perspective of the healthcare system too, preventing disease is more cost-effective than treating it. A review of more than 50 public health interventions found that for every £1 invested in public health, £14 will be returned to the economy³.

‍Digital health: the gateway to preventative healthcare?

At Huma, we believe that digital tools have a critical role to play in shifting away from the reactive model of healthcare towards a more proactive, preventative one. By collecting data directly from individuals over time in a real-world setting, digital tools can provide a more complete picture of health and provide valuable insights to steer healthcare decisions.

Right now, remote monitoring tools - like our award-winning hospital at home technology - allow a patient’s health to be monitored continuously, away from the clinic and from the comfort of their own home. During the height of the COVID-19 pandemic, being able to monitor patients remotely became a critical way of triaging patients while maintaining infection control.

We supported hospitals in England and Germany to monitor COVID patients remotely using our hospital at home platform. A recent evaluation of the German trial showed a 3-4 times lower mortality rate for patients using the technology, and an average hospital stay four days shorter than the German national average for COVID-19 patients⁴.

The same technology can be used to prioritise patients with other conditions, too. In collaboration with Royal Brompton hospital in London, our Hospital at Home technology was used to remotely monitor patients waiting for cardiac surgery.

For six months, patients recorded their symptoms each week, which clinicians could access to quickly assess their clinical severity. Of the 525 patients who used the app, 51 were identified as potentially deteriorating. Almost 90% of these potentially deteriorating patients had their surgery date brought forward thanks to information provided by the app⁵.

In addition to helping to triage patients with acute conditions or those waiting for surgery, remote patient monitoring also has huge potential for chronic conditions, which make up the bulk of primary care.

We recently demonstrated this in a pilot study in Wales, where cardiac patients could input their vital signs and symptoms remotely, with clinicians able to monitor these signs and symptoms over time.

In just 12 weeks, we reduced the time needed to optimise medications by more than 76%. We also helped to keep patients safe, with 82% of cases escalated for further clinical input being identified thanks to data collected in the app. As a result, 10% of patients were able to avoid admission to hospital, and a further 5% could leave hospital early.

‍From proactive to predictive care

The ultimate vision of preventative healthcare is not only to look after patients once they are diagnosed with a condition, but to identify patients at risk of becoming ill, intervening early to prevent or delay the onset of disease.

At Huma, we are validating models that we developed to predict risk of cardiovascular disease⁶, as well as mental health conditions such as anxiety and depression⁷, using easily collectable lifestyle data. As well as predicting risk, we can also use the data we have collected to help patients to reduce their risk through lifestyle changes.

We have also been working on a more general risk score – called the C-Score – which determines risk for mortality from all causes. The easy-to-understand, points-based score is based on lifestyle factors data collected by smartphone⁸. The C-Score can predict risk for all-cause mortality within 10 years, with a recent validation showing that the score was able to predict 87% of mortality in a US sample⁹.
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‍Building digital tools, the right way

Digital tools are central to the vision of a more proactive, predictive and preventative model of healthcare. However, as we move towards this vision, it is vital that digital tools are built the right way. At Huma, we keep four key considerations in mind when building all of our technology.

Firstly, we believe that digital tools must allow patients to collect and input their clinical measurements in a way that is both simple and robust. We are continuously developing new methods of monitoring vital signs that meet these goals, such as measuring breathing rate using just a smartphone¹⁰.

We believe digital tools should be able to manage multiple conditions. In the US, 40% of adults have two or more chronic illnesses¹¹. This means digital tools need to be able to monitor a range of vital signs, rather than signs or symptoms that are specific to just one condition.

We also believe that digital tools should empower the patient to improve their health and wellbeing. For all our models in development, we make sure that the data collected is used not only for clinician review but also for the patient’s own consideration, along with tailored advice that could help their health.

And, of course, it’s essential that all of our digital tools are attractive and easy to use. We believe using an app to manage your health should be just as simple as using an app to order a takeaway. We want people to want to use our technology, helping everyone to better understand their health and the steps they can take to live longer, fuller lives.

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Sources

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2. OECD/European Observatory on Health Systems and Policies (2019), United Kingdom: Country Health Profile 2019, State of Health in the EU, OECD Publishing.
3. Masters, R., Anwar, E., Collins, B., Cookson, R. and Capewell, S. (2017). Return on investment of public health interventions: a systematic review. Journal of Epidemiology and Community Health, 71(8), pp.827–834. doi:10.1136/jech-2016-208141.
4. Lim, A. et al. (2022) An Outpatient Management Strategy Using a Coronataxi Digital Early Warning System Reduces Coronavirus Disease 2019 Mortality Open forum infectious diseases 9(4), ofac063. DOI: 10.1093/ofid/ofac063.
5. Obika, B.D., Dolezova, N., Ponzo, S., Valentine, S., Shah, S., Gledhill, J., Plans, D., Nicholson, C., Walters, C., Stephen, L., Ng, S., Ayres, J., Petrou, M., Bhudia, S., Denny, C., Schrauwers, H. and Markides, V. (2021). Implementation of a mHealth solution to remotely monitor patients on a cardiac surgical waiting list: service evaluation. JAMIA Open, 4(3). doi:10.1093/jamiaopen/ooab053.
6. Dolezalova, N., Reed, A.B., Despotovic, A., Obika, B.D., Morelli, D., Aral, M. and Plans, D. (2021). Development of an accessible 10-year Digital CArdioVAscular (DiCAVA) risk assessment: a UK Biobank study. European Heart Journal - Digital Health, 2(3), pp.528–538. doi:10.1093/ehjdh/ztab057.
7. Morelli, D., Dolezalova, N., Ponzo, S., Colombo, M. and Plans, D. (2021). Development of Digitally Obtainable 10-Year Risk Scores for Depression and Anxiety in the General Population. Frontiers in Psychiatry, 12. doi:10.3389/fpsyt.2021.689026.
8. Clift, A.K., Lannou, E.L., Tighe, C.P., Shah, S.S., Beatty, M., Hyvärinen, A., Lane, S.J., Strauss, T., Dunn, D.D., Lu, J., Aral, M., Vahdat, D., Ponzo, S. and Plans, D. (2021). Development and Validation of Risk Scores for All-Cause Mortality for a Smartphone-Based ‘General Health Score’ App: Prospective Cohort Study Using the UK Biobank. JMIR mHealth and uHealth, 9(2), p.e25655. doi:10.2196/25655.
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