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22 November 2018updated 09 Sep 2021 5:06pm

How data science is shaping the modern NHS

New analytic technologies have the potential to transform the future of healthcare. 

By Aziz Sheikh

The fourth industrial revolution (4IR) is a cross-sector phenomenon. Digitisation, specifically through big data, artificial intelligence and machine learning, has the potential to transform any industry, especially healthcare. With the National Health Service perennially under pressure, from budget constraints and an ageing population, it must find a solution that is capable of driving efficiencies without compromising on quality.

Large data sets, if used effectively, could help to inform earlier diagnoses. Earlier diagnoses, then, lead to faster treatment, which stands to reduce people’s time spent in hospital, nipping conditions in the bud, rather than allowing them to drag on. Data should be at the heart of every decision-making process in the healthcare industry, and updated on an ongoing basis. Healthcare as a sector, with all of the longitudinal data it holds on patients across their lifetime, is well positioned to take advantage of what the 4IR has to offer.

That our health service is free at the point of delivery forms a huge part of the reason for its widespread use. That widespread use means that we have a plethora of data that can be recorded. From diagnostics, interpretation of lab tests, scheduling appointments, to personalising care, finding cures to conditions and creating new and innovative solutions to long-standing problems, data is a game-changer for the NHS.

Data can paint a picture for a patient’s pathway. Installing a culture within the health system to not view information in silos, but instead to view data in relation to other data is the key to making the most of the 4IR. If a patient is checked for one condition but also displays symptoms of another, getting into the habit of cross-referencing and collating data is to be encouraged. The aim should be to create a health system that continuously learns and is personalised to individual patients’ needs. Digital medical histories not only save on space previously used for paper files, but being able to check the details of past hospital visits in real time is a valuable asset.

At the policy level, we see common problems with data, including the challenges of its collection, curation and storage. But ensuring that there are appropriate security measures in place, tackling the interoperability of software and making sure that we have trained experts who can work with the growing complexity of data systems, is well worth the investment.

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As vital as collating and correlating data within a healthcare setting is understanding how that data corresponds to other sectors as well. Several smart city initiatives – such as those designed to monitor electricity grid use, air pollution and more – on some level will have an impact on the NHS. The Data-Driven Innovation initiative is part of the Edinburgh and South East Scotland City Region Deal – a government-led investment in the region where nearly a quarter of Scotland’s population lives. As part of this deal, the University of Edinburgh is leading on data science innovation, making use of forecasting trends, risk and probability assessments, genetics analysis, patient behaviour studies, and understanding the true value of digital infrastructure.

Ultimately, in modern healthcare, we should be striving for a system that is predictive and preventive. Data is central to that vision.

Aziz Sheikh is director of the Usher Institute of Population Health Sciences and Informatics at the University of Edinburgh.