Service deliveryDigital Customer ServiceGetting the NHS AI-ready: Four things that need to happen

Getting the NHS AI-ready: Four things that need to happen

Francois Cadillon, Vice President UK & Ireland at MicroStrategy discusses four key steps that need to be taken if the NHS is to get AI-ready

The opportunities for Artificial Intelligence (AI) in the NHS are extensive, a fact the organisation recognises with the various trials it is running around the country in an attempt to become AI-ready. Prime Minister Theresa May also backs AI as a “new weapon” in medical research. To be effective, I believe a solid framework needs to be put in place to ensure patient data is secure and used effectively to further support the nation’s overall health.

1. Create a patient-centric framework

As I highlighted in a recent article for HuffPost, the opportunity for big data in the NHS is huge, but in a climate where the General Data Protection Regulation (GPDR) has just come into force and the Cambridge Analytica scandal is still fresh in our memories, the public is particularly aware of how their data could be used.

Yet access to data is key to future patient care, especially where AI is concerned, as AI machines will need accurate and up-to-date data sets to pull from and create future trend analyses and learn future actions.

Patients need to understand that by giving permission to the NHS and other health bodies to use their data, they are helping other patients. It should be perceived rather like blood donorship; by making their data available, patients will be aiding a bigger cause. Patients also need reassurance on how their data will be used, how they and others will benefit, and how they can rescind permission at any time.

Trust will be key to the success of AI within the health sector, and patients will demand to know if their data is being shared with insurance companies or pharmaceutical firms, for example, and may wish to opt out.

2. Collaborate with health sector partners

There are so many interesting projects going on within the NHS that other bodies could learn from. It is really key that hospitals and departments work together to share knowledge so that all opportunities are maximised and there is no energy wasted on doubling up.

Just think of the possibilities of using AI and big data in the health sector. Future patient care could include a single platform where patient records are collated from various sources—even from wearable tech and Internet-of-Things (IoT) devices to enable clinicians to access a patient’s full medical history quickly and efficiently in an emergency.

This could include patients’ DNA code and family medical history, blood type, finger prints, face and eye recognition, allergies, current ailments, and more valuable information to empower health professionals to give patients the best possible care.

An analytics-based ID system could also help doctors identify hospital staff in real time, giving them valuable access to key people and resources, and improving the all-round patient experience.

3. Communicate developments effectively to the public

A report from pollsters Ipsos Mori in 2017 found that the UK public is broadly optimistic about AI and are largely supportive of positive deployments of machine learning. Health sector bodies need to be clear about how AI is being used in improving patient diagnosis, treatment, and recovery, so there can be no room for speculation around how data is used.

4. Use AI in the context of a wider data picture

The development of AI in the health sector has support from the very top of government, so we can look forward to some exciting developments in this space. AI and machine learning are just part of a bigger picture of how data should be helping to save lives and drive efficiencies in the health sector.

To fully make the most of their potential, the medical sector must adopt a data-led culture and enable it to flourish, especially when complying with the data requirements of GDPR. One thing’s for certain: it’s going to be an exciting journey.

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