Over recent years, attention has focused on how population health management can help improve the lives of citizens. With that in mind, Tracey Cotterill, managing director for population health intelligence at Civica, explores how machine learning can provide the data intelligence we need to deliver better healthcare for everyone.
Prevention, as we know, is better than cure. Intervening early and stopping health issues from escalating leads to improved outcomes all round – for individuals, communities and a range of healthcare providers.
With our UK healthcare system under huge pressure, there’s a pressing need to shift to this more proactive approach. But to make it a reality we need to know what’s behind health outcomes. Why, for example, do people in a particular area have fewer healthy life years than those in another part of the country?
Population health intelligence is about finding the answers to questions like this, so we can make the right interventions at the best time. As integrated care systems (ICSs) work to tackle some of the NHS’s most pressing problems – such as health and care inequalities and financial sustainability – it’s a discipline that can help make the connections between health outcomes and the factors that influence them.
Because ICSs will bring together NHS, local authority and third sector bodies, they’ll have access to all the data needed to gain a deeper understanding of population health – everything from NHS records to data on education, housing and crime. The challenge, of course, is how to extract the relevant insights that can point to new and better ways of doing things.