A senior programme manager in the Primary Care and System Transformation team explains a vision for how digital technology combined a with population health management programme could be a game changer for health inequalities:

Imagine a future where we could turn to technology to give us individualised advice on how to stay fit and healthy.

Some would say technology risks widening the gap between those who can afford and those who cannot – but we in the health and care service want to take both the opportunities tech can offer while mitigating, maybe reducing, inequalities.

We want to make the best of what we’ve got for everyone – regardless of where you live, where you were born or your background.

To do that we need to think differently about our population. Not a single entity, but many different individuals, each with different abilities, influences, attitudes and stories.

One way for local systems to do this is to use a population health management (PHM) approach to reduce health risk in different population groups and think about how technology can benefit our health now and in 20 years’ time if used appropriately.

There’s a vast array of health tech currently in use, from personal home bought fit-bits to skype consultations for clinicians on wards, to prescribed NHS apps, patient record solutions and shared care records. But how do they all link together to provide solutions that work across different parts of a system and in different population groups?

Currently, PHM is a work in progress with various parts of the country testing what can be achieved using the expert knowledge of our data analysts, public health experts, clinicians and local communities.

In these areas Integrated Care Systems (ICS) are supporting community services, public health, social care, voluntary sector, police, fire service, GPs and hospitals to work together better. They are starting to join up data locally from across these sectors, with the aim of thinking about their population holistically – getting a wider perspective on how these people can be better supported and how we can mitigate the risk factors influencing their health.

Take Chorley, where they have pinpointed 140 people who fall within the moderately frail segment with nine or more frailty deficits, eg: mobility issues, long-term conditions, who attend the GP more than others.

Based on the data analysis, the neighbourhood team identified the best way to support these individuals was to link them up with a social prescriber and community support services provided by Chorley Council.

They could then support more personalised and holistic care planning looking at what matters for these patients, not from a strictly medical perspective, but talking through lifestyle goals and supporting them to take greater control of their health.

But how does digital link into a PHM approach? In my mind, it’s two sides of the same coin. In NHS England, we talk about the components of PHM: infrastructure, intelligence and intervention and at every stage technology plays its part.

Through ‘infrastructure’ PHM is reliant on good data via good systems – electronic health records and other systems – that capture data in a standardised and useable way that can be integrated with other data to build a rounded picture of health patterns. Local Health and Care Records are a good example of this.

Through ‘intelligence’ there is much potential for the development of advanced analytics and deeper learning techniques which will hopefully be the next step for PHM.

The predictive element of this analytics will just get more powerful as new data techniques become more widely applicable.

By studying data on people who have problems today we can start to understand early characteristics about how they developed their condition and use this knowledge to pick out younger people today who are at most risk of having the condition in 20 years.

Analytics is at the cusp of being revolutionised across the board and it’s a very exciting moment to be part of how these changes can improve patient care for the future.

And finally there’s interventions, like the MyCOPD app which supports people with Chronic Obstructive Pulmonary Disease to manage their health. The insights a PHM approach gives us, by pinpointing specific patients or residents with additional needs, could show who might benefit from this kind of intervention so their clinicians can recommend the app appropriately.

We can begin to find and help those who may not otherwise be known to services from being left behind.

Crucially though, PHM is about closing the loop and making sure the net impact of these interventions is evaluated at a person specific level and are fed back into the system next time round.

As we get more data about use of digital technology into PHM processes, we will start to get a clear picture of where technology might be risking increased health inequality at a local level. We might even get to understand how we can properly target digital interventions, and corresponding skills and support to reduce health inequalities.

For me, this is the holy grail and why PHM and digital are just two sides of the same coin.