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Why AI adoption in healthcare could be the key to a healthier society

by uma


By Stephane Arnaudo, Head of AI & Data Analytics Sales, EMEA at NetApp

The ancient Roman poet Virgil once said that the greatest ‘wealth is health.’ There’s a truth behind that saying as the impacts of health are deeply felt within every society, by the individuals and the networks that exist around them. Ill health also has a significant cost impact on societies, with individuals sometimes unable to work and greater funding required for healthcare services, in many cases with the additional pressures of an aging population. For example, in the UK, just 4% of the healthcare budget is spent on prevention.

The phrase ‘prevention is better than cure’ has underpinned modern healthcare but far too often, the potential opportunities for technology to prevent disease and improve healthcare outcomes are missed. This piece will look at how artificial intelligence (AI) can transform healthcare and the importance of a data fabric to unlock the full, life-changing potential of AI and data.

The state of AI adoption healthcare industry today

With the global AI adoption rate now at 35%, people are beginning to see the benefits. However, the UK healthcare sector unfortunately has one of the lowest adoption rates at 11.5%, with the IT/telecommunications and legal sectors having the highest adoption rates at 29.5% and 29.2% respectively. In mainland Europe the adoption rate across healthcare is higher, at 47%, for at least one type of AI technology. 

It’s clear that more needs to be done in the UK to encourage AI adoption in the healthcare sector and by making AI/data skills an important part of the National Curriculum and introducing legislation to inspire greater trust in AI technologies, this can be done in small, incremental ways.

The number of applications of AI in healthcare sector has exploded in recent times to hundreds of use cases and will continue to rise in the coming years. AI remains widespread in radiology, but it is increasingly used for other purposes, including as part of preventing health checks, the discovery of new drugs based on a patient’s symptoms and issue patterns, immunotherapy for cancers patients, and determining the most effective treatments for a dialysis patient, for example. So, what are the possibilities for AI in healthcare as we look to the future?

What’s the future for AI in healthcare?

The healthcare sector is still recovering from the biggest crisis it has ever seen, COVID-19. Healthcare professionals are looking at how they can better improve their practices so if something happens like this again, they are better prepared, and AI is one tool that can help drastically. To beat the clock against future COVID-19 mutations, researchers at the University of Southern California developed a machine learning (ML) model that creates vaccine design cycles in just seconds, instead of months or years and delivers them to the front of the line.

Meanwhile, Optum carried out a survey which revealed over half of healthcare professionals (56%) are accelerating or expanding their AI deployment timelines in response to COVID and senior health care executives are increasingly optimistic that their AI investments will soon pay dividends, with 59% anticipating AI delivering tangible costs savings within three years — a 90% increase since 2018. 

As medicine continues to evolve and wearables/internet of things (IoT) devices are gaining market share, patients, clinicians, and researchers are relying more and more on AI to automate administrative tasks, streamline diagnosis, fast-track treatment research, predict risks, and manage public health.

However, it’s crucial to remember that AI can have the same biases that humans can express. The World Health Organisation published a policy brief looking at combating age-related bias in health-related AI tools. They expressed concerns that the future quality of healthcare provision for older people could be affected by AI technologies which are encoded with stereotypes or discriminatory provisions. The ethical challenges around AI must be addressed for it to cater to the needs of an increasingly older population in many countries. The future of AI will only be a success if the technologies underpinning healthcare delivery are equitable and free from bias.

Weaving a data fabric together

But what use is AI in healthcare if it is not supported by the right data foundations? A key challenge identified by over half of UK public sector leaders is that their data is stored on infrastructure that is not fit-for-purpose. To take advantage of not only AI, but also applications that are supported by AI, healthcare organisations need the ability to store, manage, and analyse data across different teams and locations.

The solution to this problem needs to be the creation of powerful data fabrics that allow data to flow seamlessly and securely across multiple clouds, private storage, and Software as a Service (SaaS) applications. This is critical with AI related healthcare applications where data must be shared with specialist experts for analysis to diagnose conditions and contribute to medical research.

AI has a bright future in the healthcare sector and will be key to solving many of the challenges faced by patients and healthcare professionals. For AI to have a true impact, it’s imperative that the right data infrastructure foundations are put in place and ethics is a priority, so that everyone’s health needs can be met.

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