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by Ryan Irwin
Published on 23 July 2020

Improving population health requires multiple interventions over time, tailored to meet the needs of individuals at each stage of their life, whilst simultaneously reducing the inequalities that exist in health outcomes across a population.1 The need for a sharpened focus on population health has increased following the global onset of COVID-19. As well as recognising the human impact of loss, the pandemic has surfaced existing social inequalities, specifically how health outcomes can vary from one population to another.

Integrated care systems (ICS) have a key role in improving population health, with joined-up data, along with shared intelligence, infrastructure and interventions, being essential enablers to health improvements and the integrated care vision outlined in the NHS Long Term Plan.

The three Is approach to support population health:

  • Infrastructure: Developing integrated health and social care models such as primary care networks that enable greater provision of proactive, personalised and coordinated care.
  • Intelligence: The use of shared data via a normalised population health record to understand variation and support quality improvement across defined population groups, making the best use of collective resources available.
  • Interventions: Supporting more personalised care to help people measure and manage their own health and wellbeing.2

However, the sheer volume of data and information available, as well as knowing what do to with it, can create a challenge for large, complex health and care systems with multiple and sometimes competing priorities.

A key feature of population health management programmes is the ability to identify groups within their population with similar characteristics or needs that would benefit from action to support improvement in health outcomes, commonly supported through risk stratification applied at a population level or for sub-segments of the population. For example, using combined health and care data to identify those at risk of frailty in near-real time and at the point of care, so checks can be made to see whether the person’s care has been assessed, their goals discussed and interventions such as home, nutrition, personalised prescribing and lifestyle support put in place.

Using data in this way also supports emerging and future approaches to care, such as precision medicine that considers individual variability in genes, environment and lifestyle for each individual.

By combining all available data in a standardised, normalised and scalable way, health and care stakeholders, together with the individuals and communities they serve, can make the best use of their collective resources and assets to improve health outcomes.

Cerner’s HealtheIntent® platform securely connects data in near-real time from a range of settings to form a joined-up, actionable profile of a person’s health and care recommendations from an individual to wider health system level.

Contact your Cerner relationship owner or let us know if you'd like to hear more about our population health management offering. 


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1  Kindig, D., & Stoddart, G. (2003). What is population health? American Journal of Public Health, 93(3), 380–383.

2 (Accessed online 30 June 2020)