We find ourselves at a critical point in the evolution of artificial intelligence (AI) in healthcare.
While we can take it for granted that the rate of technological innovation will continue to accelerate, what is less clear is how quickly we can adapt healthcare to make use of these advances. This is partly a very human problem.
For example, many of the healthcare professionals (HCPs) I speak with welcome the potential benefits cloud computing can bring such as better data storage, processing power and increasingly sophisticated algorithms that can help diagnose diseases.
However, they also hold genuine concerns that the regulatory environment particularly information governance will continue to lag behind AI development.
There are also other anxieties such as the margin for diagnostic error? Will AI simply add to the information burden? How many HCPs could potentially lose their jobs or see them significantly reshaped? Investment in people and processes must keep pace with innovation if we’re to build confidence in AI and its adoption.
There may be some comfort in the knowledge that human intelligence is also a major growth area in healthcare with continued, sustained growth in healthcare employment expected over the coming years.
What’s more, increased automation will give healthcare professionals what US cardiologist, geneticist, and digital medicine researcher, Dr Eric Topol, calls ‘The Gift of Time’ to build relationships with patients. But making the case for AI is only the starting point.
Realising the potential of this technology requires not just a shift in mindset, but in identity too.
"The emerging generation of AI-literate, ethically aware professionals needs data that is rigorously regulated, freeing them up to spend their ‘gift of time’ on their patients"
The clinicians of the future will be far more than ‘end users’ – they’ll be data literate technicians, involved in the design of AI-enabled technologies.
They will be gatekeepers and analysts, able to evaluate and interpret emerging technology and translate its findings and data into real-world benefits for patients.
The Academy of Medical Royal Colleges in the UK recognised the scale of the task earlier this year in its paper ‘Artificial Intelligence in Healthcare’, which identified training as one of seven key priorities for policymakers and service providers.
Academy chair, Carrie MacEwan, remarked that AI makes the case “for training more doctors in data science as well as medicine”.
Encouragingly, the next generation of clinicians are hungry for this knowledge; a recent survey by the European Medical Students’ Association (EMSA) found that 85 percent of its members wanted to see more eHealth content in the curriculum.
Adapting the medical curriculum to incorporate these new capabilities is no easy task, and will require cross-border, European- level collaboration to ensure we’re learning from our collective successes and failures. This will only happen with considered, forward-thinking data policies.
The emerging generation of AI-literate, ethically aware professionals needs data that is rigorously regulated, freeing them up to spend their ‘gift of time’ on their patients.
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