Who understands our health better, machine or human?
The rise of artificial intelligence, machine learning and our interaction with digital tools and resources, is opening up fresh debate as to whether machines will be able to understand our health better than humans.
How AI is enabling better health outcomes
In 2018, a report released by PWC, Top health industry issues of 2018: a year of resilience amid uncertainty revealed AI is already gaining traction in healthcare’s back offices and supply chains, generating quiet efficiencies and enabling better health outcomes.
One of the ways AI and deep learning is already being used in healthcare is image classification, which enables extracting information from multiple images to help healthcare providers like radiologists mark file and mark low priority X-rays, making the process quicker, easier and more accurate.
Meanwhile in the UK, researchers at Oxford Hospital are using this technology to help improve diagnosis for heart disease and lung cancer. AI can also help primary doctors fund and refer patients to specialists faster, and offer more fast, accurate and actionable insights for doctors and their patients.
In China, a recent study revealed a new artificial intelligence system designed to diagnose childhood diseases, can even recognise symptoms more accurately than many human doctors.
The “deep learning” programme, tested in China, assimilated information from more than 1.4 million electronic health records.
It was then able to draw on its “experience” to diagnose a broad range of childhood diseases, with accuracy rates of more than 90% in some cases. But although the system performed better than junior doctors, it did not perform as well as more senior experienced physicians.
Putting our health in Dr Google’s domain
According to MedicalDirector’s recent report, Dr Google, How Self-Diagnosis Impacts Clinical Care, there’s still an alarming percentage (18%) of people who believe Google is actually better equipped with health information than their doctors, as it has more access to information about medicine, diagnosis and treatment than their doctor.
The research, which recently gained significant media coverage, including being featured on Channel Ten, Channel Seven, Sky News, Sunrise, The Daily Telegraph and A Current Affair, found 21% of Australians claim to have self-diagnosed accurately, and are convinced Doctor Google is ‘always’ right about what illness their symptoms represented.
This is an interesting sub-group: those who think Google – a search engine – has better health information than their health practitioner – a trained medical professional. So does this all mean there’s an emerging trend that humans are starting to trust a machine more than a qualified human being?
Prediction in a fear-based economy
According to Matt Bardsley, CEO of MedicalDirector, disruptive technologies, artificial intelligence (AI) and machine learning can be powerful tools to drive better health outcomes.
But in ‘a fear-based economy’, these predictive tools need to be handled with respect, and be fully understood within the context of each individual person and their circumstances.
In his recent article, ‘Prediction in Fear: AI in Healthcare’, Bardsley explained how universally, we transact in two things – fear or pleasure. Every decision we make always comes back to one of these two things, and within each of those two utilities, there’s a moral compass, he said.
When it comes to health, our behaviours and the way we ‘transact’ in healthcare, are all predominantly dictated by fear, as we are always worried about the worst that could possibly happen.
“The impact prediction has in a fear-based economy is very real and has far more implications for our individual decisions,” he explained. “If the fear doesn’t manifest itself or the fear is greater than what was initially predicted, these are much harder for the human mind to cope and take on board. So it needs to be managed a lot more carefully.”
This means taking the time to clarify any information (or misinformation) the patient has sourced online, and contextualise it in relation to the patient’s individual health conditions and family history.
“For machine learning to really be a powerful tool in healthcare and an enabler of better health outcomes, we need to make sure it is done respectfully, there is a level of empathy in the system, and a layer of emotional artificial intelligence, before it can be unleashed into the healthcare ecosystem,” Bardsley says. “Otherwise, just one health prediction delivered incorrectly can lead to a life or death situation for a patient, and stifle innovation.”
Human-machine interactions and the future of health
So moving forward, how can health practitioners mitigate risk, reduce anxiety and be mindful of how patients are interpreting Doctor Google within a fear-based economy? According to MedicalDirector’s CEO, Matthew Bardsley, the solution lies in health practitioners being accessible, participating in technology themselves, and integrating more knowledge sharing into their practice to put patients at ease.
This means taking the time to clarify any information (or misinformation) the patient has sourced online, and contextualise it in relation to the patient’s individual health conditions and family history.
“For machine learning to really be a powerful tool in healthcare and an enabler of better health outcomes, we need to make sure it is done respectfully, there is a level of empathy in the system, and a layer of emotional artificial intelligence, before it can be unleashed into the healthcare ecosystem,” Bardsley says. “Otherwise, just one health prediction delivered incorrectly can lead to a life or death situation for a patient, and stifle innovation.”
Bardsley also believes there’s a broad acceptance amongst patients that doctors have a vital role to play in translating symptoms and data in a human-focused way that machines can never replicate.
“Diagnosing an illness and treating a patient in a sympathetic manner is never a linear process, making many elements of the doctor and patient relationship necessary within a human-to-human interaction,” he added.
Bardsley stressed innovators in healthcare need to understand and respect this layer of emotional AI required, and really lean into this problem and understand its repercussions, so healthcare can enjoy the same capabilities as other parts of the market.
“The best outcomes will be achieved when doctors work in tandem with technology. This includes having a competent understanding of how patients wish technology to be incorporated into diagnosis or treatment, and being open to using technology for training or communication purposes in the medical profession,” he said.
To access MedicalDirector’s FREE report, Dr Google, How Self-Diagnosis Impacts Clinical Care, click here.
