Machine learning has the power to fundamentally reinvent healthcare. In a world where industries have been radically transformed by technology – healthcare delivery continues to follow the traditional approach to rely heavily on doctors’ ability to not only absorb humongous amounts of varied data but also correctly apply that to your complex personal context. As Vinod Khosla puts it, it’s time to move beyond the stethoscope – which remains the iconic diagnostic tool for most healthcare professionals worldwide, 200 years after its invention.
If you deep-dive into the problem, it really begins at the very onset of healthcare education. As data and research explode, it’s challenging for the average doctor to catch up without technology. To the extent that studies show that “Students who graduate in 2020 will experience four doublings in knowledge. What was learned in the first 3 years of medical school will be just 6% of what is known at the end of the decade to 2020.” This potentially explains why a 2013 study estimated that greater than 400,000 deaths a year were attributable to medical errors in the US. Misdiagnosis and conflicting diagnoses are common challenges plaguing the current medical system – and while solvable, they tend to occur due to reasons so intrinsically human. A challenge, that technology can play a huge role in helping us overcome. On this note though, I find it important to highlight that the target for applying this megatrend to healthcare is not to eliminate doctors, but instead to leverage technology to overcome human deficiencies and amplify doctor’s strengths through relevant insights.
And as you read this, a U.K based startup Babylon Health, strives to make this ambitious vision a reality since the past two years. Ambitious indeed, given the skyhigh expense of engineers who’re experts at building AI models – while the net return on this heavy investment could be simply a hit or miss. The startup’s founder, Ali Parsa, calls it a major step towards his ambitious goal of putting accessible healthcare in the hands of everyone on the planet. “Five billion people globally have no access to surgery. And without adequate primary care, a $10 problem becomes a $100 solution.” But catch it early through intensive data analytics of Babylon’s product, and the founder believes the company can stop an illness from becoming an expensive problem for a state provider like the National Health Service. Moreover, this technology driven assistant can enable doctors can spend their time way more efficiently. With the result that over time, providers such as NHS won’t need to hire so many of them.
Bablyon directly interact with the customer, providing them access to its network of 250 doctors on video-call. To assist doctors in their diagnosis, the company also sells an AI software that helps investigate an ailment. It is this latter feature that Babylon has spent the last two years heavily investing in, so that his human doctors are freed up from note-taking and diagnosing common illnesses, and instead can focus their effort in analysing complex insights and looking after more complicated problems. “You don’t need to see a doctor for every diagnosis, what you want is a treatment.” And Bablyon’s core is working on what goes behind the scenes in assisting the doctors to deliver this treatment with increased reliability and efficiency.
And if this technology sounds far too ambitious or into the future – wait till you read this. In June this year, they challenged their product to the MRCGP exam, which trainee general practitioners take to test their ability to diagnose. And against the average passmark of 72% over the past five years, Babylon scored 82% – an uplifting milestone for the entire company. In terms of diagnosis, Babylon’s digital doctor had proved itself at par with the average human doctor, if not more.
And while the company aspires for the grand long-term future, what does near future look like? Definitely not without its fair share of challenges. The AI doctor’s journey has barely begun – and will only slowly evolve in sophistication – no different than any other great doctor who invests many years in training under best practitioners, even beyond the decade invested in learning at medical school. Our AI doctor would be no different. Similar to what we saw in the IBM Watson case, expect many laughing-stock attempts as this technology begins to grow from infancy. Early in their lifecycle they will be the butt of jokes from many – but let not that cloud your perception of the eventual power the technology holds.
And now the company seeks to expand this product to assist doctors in the U.S. Would love to hear more about the key challenges you think this product could help solve in the US Market.
The AI doctor, will see you now.
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