The medical field has slowly evolved over the centuries from somewhere beginning with barbers, shamans and soothsayers, then slowly expanding from medical mythology and assumptions into a world of anatomically based science. American doctors go through a process that begins with a four-year undergraduate degree, adds another intense four years of graduate education to an M.D. or equivalent degree, adds a couple of years of “residency” and perhaps more than a few more in a specialized “fellowship” at an appropriate hospital. Board certification in specialized practices might be next. Followed by years of experience, lots of available parallel medical research, vast pools of data and accelerating medical technology, treatment, prevention and diagnostics.
We’ve just seen the miracle of a rapidly developed and deployed series of vaccines that are now countering the COVID virus, an entirely new branch of medicine where man-manufactured RNA proteins, mirroring the external “shape” of a contagion, are used to teach the human body’s main line of defenses (T-cells) to identify toxic intruders. We’ve watched as artificially intelligent analytics are applied to radiological interpretation, reading x-rays with astounding accuracy based on growing reams of data (and self-learning). Diagnostic results that exceed the ability of even the most experienced radiologists. There are even robotic surgical machines capable of performing “no human hands” surgery, currently intensely supervised by a surgeon monitoring the procedure.
Still, most of us are less than fully comfortable putting our diagnostic trust in a machine. But the accuracy is objectively compelling. A publication released on July 7th of last year at the Consumer Electronics Show provides this excellent summary of AI’s potential in medical diagnostics: “Companies have used AI to detect patterns in large volumes of data, identifying differences and similarities in different cells, genes and more to find indicators of what can cause a disease and what changes can cure it.
“For example, biotechnology company Berg performed tests on more than 1000 cancerous and healthy human cell samples to identify new cancer mechanisms. By varying the levels of sugar and oxygen to which the cells were exposed to model diseased cells, the researchers were able to track the differences between diseased and healthy cells using real-world patient data.
“London-based Benevolent pulls analysis from source data such as research papers, patents, clinical trials, patient records and more to curate and standardize the knowledge into the company’s knowledge graph. The graph contextualizes the information, predicts potential disease targets that can be overlooked, evaluates molecular structures and more. The company has been using its knowledge graph to help identify a potential treatment for COVID-19.”
The solution is obvious. Bring artificial intelligence into a doctor’s daily practice, specialist or generalist, private office practice or hospital expertise. Make it affordable. Add the potential of telemedicine – which proved to be particularly useful during the pandemic for people afraid to enter a doctor’s office – and the potential grows. The pandemic caused too many people to avoid necessary screenings and treatments, sometimes with fatal results, during this pandemic. See my March 19th Ready for My Annual Screening, Dr. DeMille blog for a more detailed discussion.
But all that is changing. Big tech players, from Amazon to Microsoft, from Wal-Mart to national pharmaceutical chains, are embracing bringing medicine and medical technology into every doctor’s office, reaching consumers with online connections and local simple screenings and diagnostics. One recent corporate acquisition by Microsoft suggests that this new medical direction will become the new normal much faster than we can imagine, perhaps facilitating the deployment of universal healthcare with a realistic cost sensitive approach that does not sacrifice accuracy. In the meantime, adding AI to a traditional doctor’s practice seems an obvious interim step.
On April 13th, “Microsoft announced it had acquired Nuance Communications for $16 billion. Nuance is a pioneer in the field of advanced medical transcription, but the technology is still young. The battle to reduce the administrative burden for doctors using artificial intelligence is intensifying, and the acquisition could position Microsoft well to compete against other tech giants as they jostle for dominance within healthcare.
“Nuance has a long history as a medical transcription service and has invested heavily in voice recognition technology. The hope is that its technology could potentially reduce the number of hours that doctors spend inputting medical information into patients’ electronic health records (EHR). Physicians spend 16 minutes per patient inputting information into their EHR, according to a much-cited study last year. How much of that is time well spent is another question entirely. That’s why Nuance is trying to reduce the hours doctors spend toiling inside of the EHR.
“The 28-year old company is a well-established player in the health industry. Some 77% of U.S. hospitals and roughly half of all doctors in the country use Nuance’s technology. Still, it’s very early days for AI medical assistant software generally.
“‘Most of the vendors I’ve seen . . . are still using humans in the loops for quality checking and to reduce the amount of editing that needs to be done by the provider at the time of sign-off,’ says Dr. Steven Lin, associate professor of medicine at Stanford University who researches medical artificial intelligence. ‘If I have to choose between a well-trained human scribe and one of these AI-powered solutions, I would probably still pick and favor a well-trained human scribe who knows my style and who has the ability to organize complicated patient histories.’” Ruth Reader in the April 14th FastCompany.com. Yes, we are indeed heading into a future where patients will develop a greater comfort level dealing directly with robotic solutions, supervised at least in the early years by doctors. It is as inevitable as self-driving cars. One step at a time.
I’m Peter Dekom, and the introduction of highly accurate but cost-efficient medical technology solutions is a necessary part of implementing high quality universal healthcare.
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