Having access to accurate real time information is transforming how we plan, manage, and sustain services, enabling leaders, clinicians and frontline teams to make more informed and effective decisions.

Over the last century, we have seen significant improvements in healthy life expectancy, but the rate of progress has slowed in recent years, particularly amongst more deprived communities which further exacerbates inequalities. This has been driven by a higher prevalence of modifiable risk factors within certain population groups, particularly Core20Plus5 population cohorts.

Non-Covid excess mortality has risen, primarily driven by cardiovascular disease (CVD), liver disease and diabetes.  The NHS is experiencing a sustained period of high demand for urgent and emergency care, with respiratory disease and CVD (for which diabetes is a major risk factor), amongst the leading drivers of A&E admissions.

We know we can do more to make a difference. There is extensive evidence on high impact preventative interventions, and we have seen the benefits a person centred approach to delivery of these interventions can bring through work on the ground. It can support what matters most to individuals and population groups as well as addressing the risk factors which drive downstream ill health and demand on the service.

Joined up data and population health analytics will be essential in enabling ICSs, place and neighbourhood teams, to understand the needs of their different population groups and to design, tailor and target a range of evidence-based interventions that aim to prevent downstream risk to groups which are currently under-represented in services.

The Fuller stocktake report and the work integrated care systems (ICSs) have done to embed population health management has highlighted the importance of local analytical teams working with neighbourhood teams to understand population need and to translate data into new care models. The challenge for ICSs will be to quickly develop their use of population health analytics, from using data to inform their approach to condition management, to utilising predictive risk factors which helps to increase early detection and prevent ill health.

Transforming long term and sustainable delivery of these person centric care models will require systems to rethink financial, workforce and contractual levers in a way which traverses traditional organisational and care setting boundaries. The move to cost patient level interactions, across the system, coupled with what we know about the bio-psycho-social risk drivers leading to further ill health will enable local teams to predict and pinpoint where targeted interventions can have the greatest impact.

ICS and place-based intelligence teams will play a vital role in creating this actionable insight and working with integrated neighbourhood teams to translate the data into service redesign.

We have published guidance to support ICSs in developing local Intelligence functions which start to bring together this capacity and capability across system partners to transform population based preventative care. Co-developed with local teams, the guidance shares good practice principles, top tips and case studies aimed at improving the adoption of data and analytically driven decision making across all tiers of a system. It also sets out how some of the enabling programmes of work from NHS England (including the federated data platform) will support and help join up the national data architecture as part of the national whole, allowing us to create an effective learning system across the entire health and care landscape.

We are expecting each system to appoint a chief analyst, or an equivalent executive leader, who may be an existing leader in the system. This role will realise the vision for the widespread use of data, analytics and insight. To achieve real change, it is important all leaders across each ICS commit to the routine use of evidence based decision making as a core principle.

Ultimately, our vision is to enable systems to make decisions based on the best possible intelligence, at every level.  We can support them to harness the power of their data to identity at risk population groups, plan services and coordinate care across systems, places, and neighbourhood teams.

Person level linked datasets, including information about the wider determinants of health are crucial to this process as are the analytical teams and data literate leaders that can make use of them. We have recently co-developed an ICS Data Navigator Tool which we’ll be making available to ICSs to help them understand how their current analytics investment and aspirations can be integrated with the Federated Data Platform.  This way we can continue to build towards a data driven learning health system. More information will be available soon.

The opportunities presented by using data and intelligence to save lives and improve wellbeing are close to endless and our journey together in this space has only just begun.