The Labour government has proposed a series of positive pledges to revitalise the NHS, including:

• One billion pounds to provide 40,000 more appointments, operations and scans every week. 

• A commitment to move to a ‘neighbourhood’ health service with more care delivered in local communities.

• New ‘young futures’ hubs to provide open access to mental health services for children and young people in every community.

The mission is clear. But in the run up to the Autumn budget, all eyes will be on the level of investment the government is willing to put into technology to safely harness the abundance of NHS data available. And, importantly, use it for positive outcomes in line with its promises that saw Labour come into power.  

But success relies on the public and private sector working together to ensure that any implemented strategy isn’t just focused on the technology needed, but on achieving operational and patient-led outcomes. But what do these technologies look like, and how will they equip the health service with what it needs to deliver against this ambitious plan?

A data-led approach to reducing the elective backlog

Better waitlist management and operational efficiency will rely on better practice for appointment scheduling, operational management and resource utilization – which at the front of NHS Trusts minds.  

This is where Decision Intelligence (DI) comes in to enable any organization to unify data, create context and then augment and automate decision making – at speed - based on data. By applying Entity Resolution (ER) to that data, it’s then possible to integrate data from various sources to provide a complete and unified picture of an individual patient, members of staff and capacity challenges – accurately linked social determinants of health data – helping target vital resources to better support the highest at-risk people with complex health and social care needs. They key to success isn’t about just implementing this change. It’s about increasing the number of appointments, operations and scans conducted weekly without the need for more physical resources – and doing so as efficiently as possible.

A data-led approach to community care

The same can be said when it comes to providing a ‘neighbourhood’ health service. The NHS is battling a serious supply-demand issue. ICBs know all too well how vital it is that we start to understand healthcare needs at a more local level. This means making contextual data more available to providers and patients.

To give an example of this in action, the University of Liverpool’s Civic Health Innovation Labs (CHIL) and partners will use a £4.9 million award from the Office for Life Sciences (OLS) to make better, quicker decisions from Integrated Care System data.  Here, AI-enabled Decision Intelligence technology is being harnessed to help connect multiple data sources into a trusted data foundation that equips researchers, care teams, and patients to access, co-create and benefit from mental health research. And this is just one example of what is possible when there is a trusted data foundation in place.  The same can be applied to analyse the mental health needs amongst children and young people. 

Ultimately, Labours promises won’t be delivered overnight. The solution is complex. But with the right investment in the right technology, it truly is possible to connect the NHS’ wealth of data to drive operational efficiency and better health outcomes for patients.     Vishal Marria, CEO and Founder of Quantexa