Researchers from the University of East Anglia (UEA) claim they can predict life expectancy by studying data collected by healthcare providers.
Statisticians, computer scientists and medics from UEA have launched a four-year project that will test how factors such as lifestyle, medical conditions and medical interventions affect “mortality and longevity”.
“People around the world are living longer. We want to develop software tools that use big data routinely collected by healthcare providers to forecast longevity,” said lead researcher, Prof Elena Kulinskaya.
“When we talk about Big Data what we mean is data that is vast, complex and difficult to analyse. We want to be able to use it to see statistical life expectancy trends, based on large-scale population-based data collected over the long term.”
The research team imagine that using big data to predict lifespan will benefit both patients and healthcare providers.
Knowing how long you are likely to live benefits patients by helping them plan for retirement, while healthcare providers will enjoy savings from knowing how particular drugs such as statins or beta-blockers affect longevity.
“Pension contributions were recently freed, so now people can take their pension pots out and use them as they wish. But to be able to plan for retirement, and to understand how much you can spend, it is good to have some idea of your life expectancy,” said Prof Kulinskaya.
“As well as being useful for people planning retirement, it is also important for GPs deciding whether and when to prescribe particular drugs or how to advise their patients. It could also benefit local health authorities planning resources, and insurance companies deciding on the size of pension you can buy with your pension pot.”
The research project, called ‘Use of Big Health and Actuarial Data for Understanding Longevity and Morbidity Risks’, is particularly focused on finding out how various chronic diseases and their treatments impact life expectancy.
However, the team from UEA aren’t the only researchers trying to unlock the value of big data to healthcare.