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Predictive Prevention: Harnessing the power of data and tech to improve health

Posted by: , Posted on: - Categories: Prevention

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The Government’s Green Paper, Advancing our health: prevention in the 2020s, marks the official launch of PHE’s Predictive Prevention Programme, delivered in partnership with NHSX.

In this blog Professor John Newton, PHE’s Director of Health Improvement, explains the programme.

What is Predictive Prevention?

Tackling the big health challenges our nation faces means making the best possible use of digital technology, combined with data and scientific evidence.

Such technology underpins every aspect of how we live our lives, it is used by all ages and social groups, and it’s no surprise that businesses and services are innovating to engage people more strongly by providing them with the information they need, at the times they are likely to want it and use it.

In the health sector we also have a huge opportunity to consider how these techniques can help us improve the health of the public.

Predictive Prevention is a programme that poses and looks to answer some important questions:

Can taking a more intelligent, personal approach to the way we use data help us go beyond the delivery of messages alone, instead driving deeper engagement and improving people’s health and wellbeing?

What is the potential to improve health by harnessing the data collected by the technology we carry in our pockets or wear?

Do we have an even bigger opportunity through bringing together the data collected through our smartphones and wearables with the health information we share with health professionals, on a visit to our GP for instance?

As it stands, many decisions about our health are driven by the information we pass on during these short, occasional interactions with a healthcare professional, but these interactions can only provide a limited snapshot of our health at a fixed moment in time.

Our ongoing day-to-day lives – what we eat and drink, how often we exercise or whether we’re sleeping well - also greatly influence our health and our wellbeing.

So PHE will be testing the hypothesis that combining person-generated data with existing health data can help us predict poor health in the future and create an opportunity to prevent it with more personalised advice and services.

How will the programme work?

This is not about developing a single product or service. Predictive Prevention is an approach that we believe could lead to a new range of public health interventions, bringing benefits to people’s wellbeing and the whole health system.

For instance, we could aim to empower the public through personalised health advice or bespoke services like text messages or smart phone apps; or make it easy to share information about diet, exercise or sleep with your GP before an appointment to enhance the quality of the conversation.

We could help front line health and care professionals tap into a wealth of holistic information about their patients to help them provide more tailored recommendations or referrals.

And we can inform public health decision makers, giving commissioners better data about large groups of people to inform strategic decisions, design services and allocate resources.

An exciting aspect of the programme is the opportunity for experts in health and care to come together with behavioural scientists, digital engineers and public health professionals to test the approach.

Their work will include the development of exemplar projects to test key concepts and establish the evidence base.

How will Predictive Prevention affect existing public health services?

We see Predictive Prevention as an approach that complements and enhances current services at population or community level.

The key, as always, is understanding what works. Currently there are a wide range of established and evidence-based services that PHE recommends as they are proven to improve people’s health. We’ll assess Predictive Prevention in a similar way, looking at how it builds on existing techniques to add another dimension to our capabilities.

What are the next steps for Predictive Prevention?

To understand and maximise the potential for this programme we will begin with some important fundamentals:

Establishing a clear use-case and developing dynamic, informed models of consent for use of data: We are committed to an ethical and transparent approach to data use, and the first phase of the programme will focus on understanding the public’s appetite for more personalised services, the types of data they are happy to share and the best way to support the public to be able to choose if, how and when they want to share their personal data for this purpose. We will work closely with the Information Commissioner’s Office, the National Data Guardian, the new Centre for Data Ethics and Innovation as well as academics and clinical advisors to ensure we comply with all data protection regulations as well as being respectful, ethical and accountable in how we use data

Building the evidence base: Using behavioural science and digital approaches to support people to live healthier lives isn’t a new concept and PHE’s behavioural scientists and marketing team has already used these methods to effectively target health advice to audiences who could benefit the most. Where our approaches are new – such as combining a range of data-sets - we will rigorously evaluate the impact. We’re already linking-up with experts from across the health system, and engaging academia and industry to test the efficacy of this approach before the programme evolves further.

Tackling health inequalities: Often when people think about health apps and wearable-tech, it’s assumed that the “worried well” - people who are already fit - will adopt the tech first. With Predictive Prevention we will ensure that communities with the greatest need are our focus.

We are both ambitious and pragmatic about this programme and look forward to building an evidence base which helps us fully understand the potential for Predictive Prevention, whether to support established public health interventions or herald the introduction of brand-new products and services.

Look out for future blogs where we’ll update you on our progress.

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  1. Comment by Yoga Bowers posted on

    I trust that equal attention will be given to considering Predictive Prevention in the field of Mental Health, especially for School Children, where the economic and societal benefits are well documented.

    For example I see that back in 2017 IBM Research discussed "With AI, our words will be a window into our mental health" as an innovation that will help change our lives within five years!

  2. Comment by Dr Jez McCole posted on

    This makes lots of sense. We have plenty of data on our desktops in primary care that, when properly used, cross referenced with other information points in the records and high quality research can prevent lots of harm. Examples include our live ACB calculator, thrombocytosis’ prognostic value in cancer and properly coded symptoms raising the suspicion of pancreatic pathology. Data can be cool but it needs context and clinical oversight to design cool systems.

  3. Comment by Julie Hodgins posted on

    This is intersting and could offer another way to support preventing illness or at least reducing the risk of some diseases. Love to keep up to date with this stuff. In breastscreening 30 % of the well women dont engage...want to help get info to them.