COVID-19 has accelerated our understanding of how data-led insights can support better healthcare. Dr Shaun O'Hanlon explains citing examples of what can be achieved.
It will soon be two years since the COVID-19 pandemic hit the UK and the pressures on the NHS continue – from new COVID-19 infections and booster vaccinations to long COVID and mental health issues.
And then there are the indirect impacts – the deficits in care for those with long-term conditions and the worrying lag in detecting new illnesses.
Let’s not forget the valuable role that data and analytics will play – right now
Cancer Research UK estimates that more than 45,000 fewer people began cancer treatment between the start of the pandemic and March 2021 due to disruption to cancer screening, diagnosis and treatment.
How should we respond? Alongside the obvious need for extra investment and solving the mammoth workforce challenge, let’s not forget the valuable role that data and analytics will play – right now.
A watershed moment
The pandemic has proved to be a watershed for our understanding of how data-led insights can support better healthcare.
Emergency COPI (control of patient information) notices turbo-boosted the UK’s research capability, enabling us to understand the virus better, develop new treatments and prioritise high-risk individuals for early vaccination.
The OpenSAFELY research project is a shining example of what can be achieved. It has, and will, continue to provide important insights into not only COVID-19 but also wider public health issues – offering powerful, data-driven insight based on real-life GP interactions across a large population.
Trusted research environments
OpenSAFELY has also shown us that it is possible to access confidential patient data for research in a trusted manner.
It has modelled the concept of the Trusted Research Environment (TRE) – its work underpinned by principles such as transparency, a clear purpose, secure infrastructure, privacy safeguards and strong governance.
Research from the National Data Guardian (citizens juries’ exercise) shows that this model has attracted a high level of public trust.
Going forward, the TRE structure will be pivotal in giving researchers quick and secure access to data to help them uncover new insights that will improve patient outcomes and speed up essential research.
We are working with one integrated care system (ICS) that is using just this approach to tackle the thorny issue of how to manage rising primary care demand.
It has uncovered some fascinating data-led observations which should stimulate discussions around service redesign, including:
- a 17 per cent increase in primary care demand across the board, regardless of patients’ individual health needs
- identifying a key demographic (18-35-year-olds who are generally well) who are bypassing primary care and going straight to emergency departments for help.
Finding unmet need
The detection and treatment of long-term conditions is another key area of focus for a post-pandemic NHS.
With appropriate access to patient records and the right technology, we can start to address problems by quickly pinpointing those who are in most need
Research from HEART UK – The Cholesterol Charity – illustrates the challenge: a survey of cardiologists found that 71 per cent felt patients did not present for emergency medical support during the outbreak for fear of contracting COVID-19.
The charity also highlights the 1.2 million missed NHS Health Checks which means patients with poor lifestyle, obesity, high blood pressure and high cholesterol may not have been detected and opportunities for intervention missed.
With appropriate access to patient records and the right technology, we can start to address problems like this by quickly pinpointing those who are in most need. We can use machine learning to review the medical records of patients with, say, asthma to identify gaps in care (e.g. missed reviews).
Those affected could be invited to go directly to their GP or we could use digital tools such as a symptom questionnaire to further screen need before an appointment is offered.
The key is effective risk stratification – understanding the factors that put people at most risk and leveraging the power of technology to find them quickly.
ICSs: a brave new data-driven world?
A future health service powered by continuous data-driven insight, measurement and review will be a powerful one indeed
The newly forming ICSs provide us with an opportunity to give fresh impetus to data-driven solutions for health and care and to fully embed the data gains of the pandemic.
For example, rather than organising care around traditional organisational structures, ICSs can instead focus on health needs and demand based on the individual and their medical, psychological, and socio-economic factors.
Data-driven insights can also help to find the individuals who are most in need of services and enable the ICS to measure the impact of the services they deliver in response.
If there’s a negative result to questions such as: “How successful was that screening programme?”; “Did it reach all those targeted?”; and ultimately: “Has it improved health outcomes further down the line?”, then a different approach is needed.
In this way, data becomes knowledge and knowledge becomes action – creating a virtuous circle that can drive continuous improvement in healthcare services.
A future health service powered by continuous data-driven insight, measurement and review will be a powerful one indeed.
Dr Shaun O’Hanlon is chief medical officer at EMIS Group. Follow Shaun and EMIS Group on Twitter @drshaun @EMISGroup