The Digital Health Update by Paul Sonnier ⋅ Jan 29, 2017 ⋅ #258

I made this announcement to 53,515 members of the Digital Health group on LinkedIn. If you’re on LinkedIn, please do join the group, which allows you to opt in to receiving these announcements in addition to connecting with thousands of other global stakeholders in digital health. Note that I will continue to update this announcement up until sending out the final version via LinkedIn.

The Digital Health Update by Paul Sonnier ⋅ Jan 29, 2017 ⋅ #258

Dear Group,

The most active VC investor in digital health, Vinod Khosla, has famously written that “Technology will reinvent healthcare as we know it. It is inevitable that, in the future, the majority of physicians’ diagnostic, prescription and monitoring–which over time may approach 80% of total doctors’/internists’ time spent on medicine–will be replaced by smart hardware, software, and testing. This is not to say 80% of physicians will be replaced, but rather 80% of what they currently do might be replaced so the roles doctors/internists play will likely be different and focused on the human aspects of medical practice such as empathy and ethical choices.”

These types of productivity gains in healthcare delivery (created by digital health) could help offset the estimated $80–$100 billion in extra healthcare costs attributed to protectionist U.S. trade policies for doctors. What does that mean, you ask? Consider that a foreign-trained doctor must repeat their entire, multi-year residency program to practice medicine in the United States. According to Dean Baker, economist and co-founder of the Center for Economic and Policy Research, as a result of this protectionism we pay our doctors twice as much as the average for other wealthy countries. He also writes that “these forms of protectionism have the same effect on economic growth as the tariffs that supposedly bother the Davos set so much, except their impact is far larger. This is most notable in the case of prescription drugs. The United States spends $430B a year on drugs that would likely cost around $60B in a free market. While patent and copyrights provide an incentive for research and creative work, there are almost certainly more efficient mechanisms for accomplishing this task.”

In one example of a more efficient route, Baker points to a recent Forbes piece by Peter B. Bach, MD (Memorial Sloan Kettering Cancer Center, and strategic director at MIT’s Center for Biomedical Innovation) and Mark Trusheim (Founder of Co-Bio Consulting and Visiting Scientist at the MIT Sloan School of Management) arguing that greater (market and health outcomes) efficiency would be obtained if the government simply bought Gilead Sciences so that it could make its Hepatitis C drug Sovaldi (list price $84,000) and make it available for free to patients. Doing this could cure most of the 2.7 million Americans the CDC estimates are suffering from hepatitis C infections. 

While these types of protectionist policies may not change anytime soon, two recent studies point to the opportunity for digital health to–as I state in my definition of digital health–reduce inefficiencies in healthcare delivery, improve access, reduce costs, increase quality, and make medicine more personalized and precise.

In a provocatively-titled article “Why AI is about to make some of the highest-paid doctors obsolete“, Matt Asay points to a recent article in the New England Journal of Medicine by Ziad Obermeyer, MD (Harvard Medical School and Brigham and Women’s Hospital) and Ezekiel Emanuel, PhD (University of Pennsylvania), stating that algorithms of machine learning—which can sift through vast numbers of variables looking for combinations that reliably predict outcomes—will improve prognosis, displace much of the work of radiologists and anatomical pathologists, and improve diagnostic accuracy.

In separate research conducted at Stanford University and published in Nature, it was found that an AI system was as good as experts at recognizing skin cancers. The researchers used a deep learning algorithm built by Google that was capable of correctly classifying 96% of malignant melanoma lesions, and correspondingly 90% of benign lesions. In comparison, the average dermatologist classified around 95% of these lesions and 76% of benign lesions/moles correctly. According to electrical engineering PhD student Andre Esteva, “The aim is absolutely not to replace doctors nor to replace diagnosis. What we are replicating (is) sort of the first two initial screenings that a dermatologist might perform.”  This system could one day be used on smartphones, increasing access to screening and aiding early detection of cancers.

In other AI news, Mark Zuckerberg and Priscilla Chan’s $45B Chan Zuckerberg Initiative is acquiring Meta, an AI-powered research search engine startup, The philanthropic organization plans to make it easier for scientists to search, read, and tie together more than 26 million science research papers. This will help scientists not only find papers related to their own projects, but because it also recognizes authors and citations between papers, it would also highlight the most important research.

And when it comes to AI Technology vs. the Middle Class (WSJ article), a McKinsey study released this month “Harnessing automation for a future that works” concluded that 49% of the time workers spend on their jobs could be supplanted by automation technology that already exists today. The report states that the “activities most susceptible to automation are physical ones in highly structured and predictable environments, as well as data collection and processing.” and “In the United States, these activities make up 51% of activities in the economy, accounting for almost $2.7 trillion in wages. They are most prevalent in manufacturing, accommodation and food service, and retail trade. And it’s not just low-skill, low-wage work that could be automated; middle-skill and high-paying, high-skill occupations, too, have a degree of automation potential. As processes are transformed by the automation of individual activities, people will perform activities that complement the work that machines do, and vice versa.”

In other news…

The U.S. Federal Trade Commission (FTC) has orders Shark Tank startup Breathometer to offer full refunds to customers for its inaccurate smartphone breathalyzer. Jessica Rich, director of the FTC’s Bureau of Consumer Protection, stated that “People relied on the defendant’s products to decide whether it was safe to get behind the wheel. Overstating the accuracy of the devices was deceptive—and dangerous.”

‪50% of stroke diagnoses are inaccurate, but a new neuroactive chemical biosensor developed by Sarissa Biomedical could be the elusive stroke detector. While some strokes are obvious to see via a brain scan, others are not. And since each 15-minute decrease in treatment delay can provide an average equivalent of 1 month of additional disability-free life, doctors face a predicament and will often provide stroke unnecessary treatment to “mimics”, like migraines.

According to a new Apple patent, future versions of the band on the Apple Watch may link with added health-tracking sensors. Moreover, Apple also wants you to talk to your Apple Watch. In the latest version of its software, Apple will open up Siri to third-party Apple Watch apps related to fitness, payments, rides and messages, which can integrate Siri.

The National Highway Traffic Safety Administration (NHTSA) just released a report on the 2016 fatal accident involving a Tesla Model S and found that driver inattention was the culprit. Moreover, it stated that Tesla’s crash rate dropped 40% after Autopilot was installed in its cars in 2015.

Follow me on Twitter @Paul_Sonnier for all the news I share each day.

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Paul Sonnier
Keynote Speaker ⋅ Management Consultant ⋅ Social Entrepreneur
Founder, Digital Health group on LinkedIn ⋅ 50,000+ members
Creator, Story of Digital Health
Facebook: StoryOfDigitalHealth
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Twitter: @Paul_Sonnier
San Diego, CA, USA

 

 

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