Use of AI in healthcare can solve the inequality of access

A platform called RadVid-19 that uses AI is helping Brazilian doctors detect and diagnose new Covid-19 cases. — AFP

MY 85-year-old uncle was hospitalised due to ageing issues at a private hospital in Kolkata, India. In the intensive care unit, he contracted Covid-19 from another patient whose infection the hospital was not even aware of. It took the hospital days to figure out that many of its ICU patients, doctors and other professionals were already infected.

The pandemic shows us the inequality of healthcare access. This collective global experience will invariably lead to demands of massive upscaling of healthcare. Economic and political inaction under such demand is not an option.

So far, experts have hesitated to implement the broad introduction of healthcare AI (artificial intelligence). However, if the choice is between AI and no diagnosis at all, choosing the former can give the deprived a fairer chance.

The explosion of digitised medical data demands a fundamental change in mindset of how technology should be used in clinical workflow. Training already available healthcare workers in rural areas how to use a new smartphone app is much easier. We already witnessed such a technology transition when photography moved from physical film to digital. Platforms such as Flickr and programmes like Photoshop have changed the entire landscape of how photos are processed, handled and consumed globally.

While measuring the economic impact of healthcare AI, it is not enough to just think in terms of how much AI saves for a particular diagnosis compared with the currently available method. This approach only measures profit. The alternative here is massive, long-term investment in traditional healthcare during a global economic slowdown. The explosion of digitised medical data cannot be matched by increasing the number of high-quality healthcare professionals.

The cost of diagnostic delay during a pandemic is substantial at sociopolitical and economic levels. A global acceleration towards AI-ready healthcare is of paramount importance.

There are, of course, legitimate concerns about data security, privacy and unprecedented surveillance. Nobody is suggesting this will be easy. But shouldering this responsibility is the price we pay for living in democracies.

When it comes to something as basic a need as access to primary healthcare, it is not an option for the haves to decide detrimentally for the have-nots.



Note: The letter writer leads a research group on medical computing at the Department of Computer Science, Technical University of Darmstadt, Germany.

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