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Population Health Management – a mystical topic or tomorrow’s solution?
I get a lot of people asking me what population health management is – a slightly mystical topic currently gathering momentum in the health and care sphere.
The answer is simple; it’s how we use data insights to improve health and wellbeing today and in 20 years’ time.
This could be by stopping people getting sick or, where this isn’t possible, improving the way the system supports them.
To use Rudyard Kipling‘s words on his six honest serving men, it’s about truly understanding who, what, why, when, where and how.
We’re currently testing what can be achieved in Lancashire and South Cumbria, Leeds, Dorset, and Berkshire West using the expert knowledge of our data analysts, public health experts, clinicians and local communities and we’re very excited about what’s possible.
Let’s imagine it’s 2039 – people who are now 40 will be 60 years old.
Over the next 20 years many will develop a series of conditions – respiratory, diabetes, heart disease, frailty, dementia – some will live into old age, some will live with multi-morbidity (two plus conditions), and some will die.
But what if we knew today what those conditions would be in 2039, the reasons why some people would develop them, and how we could prevent them or reduce their impact?
We know the common advice to avoid poor health – stop smoking, exercise more, limit alcohol, eat better, sleep well and stay warm in winter, and more recently the impact of loneliness.
But the reason some people do or don’t follow this advice is complex. It’s easy to blame people for the choices they make but it’s not that simple – we need to get beyond the obvious assumptions before we can try to make a difference.
People in certain geographical areas may be more likely to be unhealthy – but it may be due to a range of factors such as poor housing.
For example, people who live in cold, damp housing may be more likely to develop respiratory problems over the next 20 years because their lungs are affected by their home. If we improved their housing now – they may not have such problems in 20 years’ time.
The fact is we don’t know the answers to hypotheses such as this unless we can use data from a wide range of sources to move from the ‘what’s the problem’ to the ‘so what do we do about it’.
Another question I hear is ‘why is this new now’? Firstly, the NHS Long Term Plan places heavy emphasis on predictive prevention and early diagnosis and secondly, today we have Integrated Care Systems (ICS) where community services, public health, social care, voluntary sector, police, fire service, GPs and hospitals are all working better together.
This is making it far easier to join up data insights locally and take action collectively on things that will make a difference at a local level.
It enables us to build up a rich picture of how health and care systems do or don’t meet the health and care needs of our population.
Segmenting these populations and further analysing the factors driving these needs enables more sophisticated planning and will help us work practically together to reduce health inequalities.
For example, it could identify as a priority people with respiratory problems who attend A&E more often, smoke, have several admissions a year and who also live in poor housing.
The NHS does not hold data on the quality of housing and the council does not hold data on how many times someone goes to A&E but placed together we start to get a picture of where and how we could make a difference.
This can be refined further to look at reasons for A&E attendances, attendances at the GP, social care packages, the education given about respiratory problems and the equipment they have in their home.
This can show a pattern across a group of people with similar characteristics compared to another group who say, may not attend A&E as regularly.
It could be clear that some people need more home equipment to keep them well and out of hospital.
The above example fixes a problem for today but how do we pinpoint people now who may have respiratory problems tomorrow?
By studying data on people who have problems today we can understand early characteristics about how they developed their condition and use this knowledge to pick out younger people today who are most risk of having the condition in 20 years’ time.
For instance, it could illustrate that changes to traffic control would improve outcomes for groups of people at risk of respiratory conditions living in postcodes with poor air quality.
Working together in ICS’ we have a better chance of using all our public resources to innovate solutions together instead of in isolation.
Population Health Management at its heart is about enabling people to live healthy lives in healthy places.
To register as part of our on line Population Health Management network and stay up to date with the latest information please email: firstname.lastname@example.org.
We live in exciting times- this approach should be transformative in how services are commissioned.
Do we understand how much awareness there is of this opportunity across agencies such as social care, boroughs, mental health services, ambulance services, education?
Interagency support for activity data sharing will be easier if there is a good understanding of the opportunities and goals both in terms of an individual qualitative experience and predicted system savings for a population.
The current daily pressure of meeting each of our own short term financial targets and siloed performance indicators distracts from this and hinders innovative collaboration.
The wider communication of the opportunities of this paradigm shift is key to avoid it being solely owned and steered by “ Health”.
We must allow the development of interagency performance indicators that we can hold as shared measures of success for our patients/ residents/ citizens who we serve.
Please can I register for the on-line Population Health Management Network to stay up to date with the latest information?
A great overvue of the impact of collective data; this is vital across the development of Health and Care services in the next 5years and coupled with digital, AI Assistive Technology can support to reduce long term associated risk.
A great summary to a complex theory. Thanks for this!
The greatest barrier to success is the governance around sharing data between organisations at patient identifiable level. For example being able to identify those admitted to secondary care using NHS data and linking it to a Housing database held by County Council to identify if patient is in social housing.
If we can crack this one….and it’ll require a mandate from senior government to fix and breakdown the hurdles…..then we can properly move forward on this to the benefit all.
thanks, Jackie, good work. Our mental health system is actually doing more harm than good to our population by over-prescribing antidepressants against NICE guidelines to 7 million (1 in 7) of which 4 million are addicted, condemning them to keep coming back to primary care in a revolving door, creating the crisis. The good news is Primary Care Networks (launched 1.7.19) which could empower GPs to prescribe social interventions and talking therapies as described on paper 9.143 of http://www.reginaldkapp.org.