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About a year ago, I dug into FDA’s newly-released list of its AI medical device approvals. In that post, I noted some surprising findings: AI approvals were (1) becoming more concentrated, with a small group of companies winning a large percentage of the approvals, and (2) most approvals were going to established medical device titans, like Siemens and GE, rather than to startups. Both findings showing that AI in medicine was providing sustaining innovation for established companies more than disrupting the established ecosystem. With this release, I wanted to see if my earlier findings still held, how fast innovation was accelerating, how quickly were more companies getting involved — and what other surprises lay within the data.
Like many, I’ve been reading about, and trying out, the latest AI tool. ChatGPT, created by OpenAI, is the most advanced chatbot you’ve ever seen. In its back and forth conversational interface you can ask questions about just about anything and get pretty impressive answers. So I wondered what it could tell us about the future of healthcare.
Four decades of increasingly consumer-focused IT developments have given consumers more and more ability to care for their own health, pulling activities out of the healthcare system. Healthcare, for the most part, is unaware of the process, or dismissive of “Dr. Google”. But this “selfcare” revolution will continue to empower consumers — and to disrupt healthcare.
In this second of a three-part series, we focus on specific examples of disruption — IT-based and non-IT-based — in healthcare.
Tech disruption is already happening in healthcare, but most healthcare practitioners are unaware of this critical concept. Learn what disruption means, and how it’s changing healthcare.
Assuming that doctors will always be at the center of healthcare is like imagining in 1982 that the US Postal Service will be in charge of email in 2022.
We didn’t need widespread COVID-19 testing to realize that we needed a lockdown: we could see that based on our hospital system capacity. And we don’t need widespread testing to start relaxing that lockdown, because we can guide our first steps based on those same hospital measure.
African-Americans get COVID-19 at twice the rate per population as whites and they die at five times the rate as whites.
And Asian-Americans who get COVID-19 in the District are five times more likely than whites to die.
Everyone recognizes that to fight the coronavirus outbreak we need data on cases and testing. Well, we’re going to need the same level of data on PPE, ventilators and other essential supplies, too — but right now we’ve just got anecdotes. Lots and lots of anecdotes.
“If it bleeds it leads” is in full force for coronavirus reporting: what the media leaves in their stories, and what they leave out.
I wanted a data visualization that gave me a 30,000 foot view of the pace and scale of this outbreak OUTSIDE China. Couldn’t find one, so I made it. Now I’ve got a collection of dataviz that I can’t find elsewhere.
I looked into coronavirus maps from Harvard, Hopkins, WHO, the NY Times and others — and found that every one of them is mapping the wrong information — in a way that makes the epidemic look worse than it is.
Maps are just about the worst way to visualize the progression of an outbreak. So why are they they only one we’re using?
99% of our health data is consumer based, not in any EHR, and that disproportion is getting more pronounced every year. What does this mean for health innovation?
We could save $20 billion annually in healthcare costs if insurance companies would buy us all a Peloton.
Stanford’s 2020 Health Trends Report says physicians are expecting and preparing for innovation — but their own data shows the opposite.
Healthcare IT is a tiny, tiny part of overall tech spending. What are the implications for health data in a world where Apple makes more money on AirPods than the top EHR vendors combined?
Quick look at highlighted startups, including Zocdoc, Oscar, and SolvHealth, from Mary Meeker’s latest report — all of which are changing some aspect of healthcare, whether it’s how we pay for it (Oscar) or how we get an appointment (Nurx).
Mary Meeker’s Internet Trends slide deck is out for 2019. What does it say about health and healthcare? Consumerization is where it’s at.
Apple Health now makes it easy to get our health data. It’s a good start, but we have a long way to go to catch up with the data tools now commonly available for personal finance. Luckily, those tools give us clear examples of how to provide “effortless insight” in our personal data, whether for money or for health.
Jim Cramer of CNBC thinks Apple should buy leading electronic health record provider Epic Systems in order to boost investment enthusiasm, and to allow Apple to integrate all of our health records across institutions. But buying a teeny-tiny EHR company won’t build excitement, and Apple’s already making moves to get us to health record nirvana. Here’s why Jim’s wrong.
So we’re supposed to be disappointed because a computer sitting on a desk provided a treatment recommendation for a particular patient, and it was the same as the one picked by the medical specialist who had trained for more than a decade to do the same thing?
Nearly sixty-thousand medical practitioner jobs have already been eliminated in the United States, not by the coming specter of artificial intelligence or robot doctors, or even by minute clinics, but by the over-the-counter medication and a re-definition of which diseases are “self-treatable.”.
In May of last year, a team of surgical researchers from Children’s National Medical Center in Washington, DC described something never before seen in the operating room: a “Smart Tissue Autonomous Robot” (STAR) system capable of performing truly autonomous soft tissue surgery—and performing it better than human surgeons.
The top area of active healthcare executive interest reported was in using digital innovation to better utilize patient-generated data — but a large majority of respondents were not seeking any solution in that area.
In poor countries, the impact of mobile AI could be far greater: it could bring medical expertise to literally billions of people with smartphones who have never before had access to any kind of such expertise.
Sizable majorities of doctors don’t believe that the move to EHRs has improved practice or outcomes.
FDA recently added almost 200 new AI medical devices to its approved list. What does a closer look at the list tell us about advances in AI, and who is making them?