Go to openevidence.com and you will see, right under the elegant logo and a free text box prompting you to ask a medical question, an immodest tag line: “America’s Official Medical Knowledge Platform”. The boast sits above an enviable lineup of official partners: The New England Journal of Medicine, Journal of the American Medical Association, National Comprehensive Cancer Network, Cochrane Systematic Reviews. If you were a clinician in need of information these would be the first places to go, [Note: Save, perhaps, for a few journals in the JAMA network, and I write this as someone who has published in and reviewed for JAMA. ] but now there is no need because OpenEvidence will do it for you, for free and — unlike those poor community doctors whose practices can’t afford an NEJM subscription — with full access to all those journals.
Their About page is even more effusive. “Our mission is to help doctors save lives and improve patient care.” Great! It goes on:
This year, more than 100 million Americans will be treated by a clinician using OpenEvidence. As a product, OpenEvidence is an AI copilot for doctors that helps them make high-stakes decisions at the point of care. OpenEvidence is the most widely used medical AI among verified U.S. clinicians. To date, we have supported over 200 million AI-powered clinical consultations from U.S. doctors and other frontline clinicians.
In a remarkably short period of time, OpenEvidence has become the default operating system of medical knowledge in the United States.
Underneath lies the Team, laden with Harvard and MIT affiliations, and long list of medical advisors ranging from Mayo, Hopkins and Mass General staff to prominent YouTubers.
It was a rather obvious idea, to create a specialized LLM chatbot which restricts its data sources to medical literature only, so when I first saw OpenEvidence, the way it presented itself (partnership with NEJM and JAMA, MIT affiliation) and the price (free for everyone with an NPI) I was pleasantly surprised that these institutions came together for the common good, to create our generation’s PubMed.
Hardy har har.
Scroll further down and under another immodest headline — “Supported by the Best” — sit the logos of Sequoia Capital, Kleiner Perkins, Blackstone, Andreessen Horowitz, Nvidia, Google Ventures and the like. Not listed on the website because there is no “Investor relations” page — that may spook the clinicians! — is the financial history. Earlier this year it raised $250 million in a Series D round at $12 billion valuation. Just three months before that it raised $200 million at $6 billion valuation. In total, it has received close to $700 million in funding over its four years of existence.
Yes, OpenEvidence, “the default operating system of medical knowledge in the United States” (their words, emphasis included), is a tech startup zipping through the first phase of enshittification, i.e. attracting users with a high-quality offering. I would argue that even the “high-quality offering” is a bit of a crock, but we’ll come back to that shortly. Let’s, for the purposes of this paragraph, go with the premise that the unique thing that OE provides is the “artificial intelligence” portion. Well, from what I understand the company relies on OpenAI, Anthropic and others for the actual compute and if that is the case they are one-step removed from the absolute carnage whose genesis Ed Zitron and others have been diligently chronicling. The default operating system of American medicine is an earnings miss away from the blue screen of death.
I won’t cry for the billionaires involved. I will, however, mourn the opportunity cost of so many smart physicians and programmers on their medical and technical teams spending their time on point-one-percenter enrichment instead of truly building our generation’s PubMed. It would not even require compute! The true value of OE is the curated collection and unrestricted access to peer-reviewed journals, treatment guidelines, and systematic reviews, supplements and all. Let me google all that — or better yet, look it up on Kagi — and I will not care at all for the LLM-generated veneer glued onto man-made knowledge. But good luck having NEJM, JAMA et al. open their vaults without the VC-backed carrot of (I suspect) God knows how many millions of dollars for access rights combined with the FOMO stick that Anthropic and OpenAI’s PR teams have been so diligently whittling.
Trigger warning for an LLM-sounding phrase: the mounds of AI slop added to OE search results aren’t just wasteful, they are dangerous. Back in the Triassic era when shmucks like yours truly were nursing their middle-finger calluses writing progress notes by hand you knew that every part of that note contained useful knowledge. With the electronic medical record mandate — thanks, Obama — much of it became an unreadable mix of computer-generated charts and copypasta; you had to look at the end of the note to find actual human thought, whether it is in the Assessment and Plan or the Attending Addendum section. Well, I can report from the front lines that much of the time even that one meager paragraph has become a copy/paste job carrying with it that distinct LLM waft.
I am not against using LLMs for progress notes — we have been using human scribes for decades to write up the facts of the doctor-patient encounter. But those are costly and your rural primary care physician certainly won’t have one, so why not delegate that work to AI? The assessment and plan, however, are where you infuse those facts with meaning and then act on them, which is the entire purpose of the physician’s job. Writing is thinking and millions of US medical professionals have decided to delegate the one job they have to AI while keeping all the moral and legal responsibility, reverse-centauring themselves willingly and with eyes wide open.
This may seem like a “the food is horrible and the portions are too small” joke — have I not just wrote that the whole thing will soon be dead? If you are a physician who values their brain and doesn’t copy off a clanker why should you care if either start relying on them and then get a rug-pull? Three reasons:
- Expectation-setting: those who copy will need 15 minutes per encounter, then 10, then 5, continuing to ingest slop and regurgitate it over patient notes even as it gets increasingly bad from more and more expensive compute.
- Asbestos exposure: as in, AI is the asbestos we are shoveling into the walls of our society, only the asbestos here is in the form of regurgitated slop we are putting into patient medical records. That, too, will take our descendants some time to dig out, although human life span being what it is it should be less than a whole generation.
- Thinking of the kids: some of my own highest yield learning moments were reading the attending addendum on my note, or the dictation of a particularly skilled specialist’s consult note; will the incoming generations of medical students and residents have the same opportunity?
So if your mission truly was to help doctors save lives and you weren’t a greedy son of a bitch would you not have made a non-profit to achieve that goal? It may not have been as slick as something coming out of Silicon Valley, but it would also not have the risk of blowing up if the financial winds turn and the funding flywheel stops spinning. After all, there have been many attempts to replace the government-funded Medline/PubMed combo, but none of them were that much (if at all) better to justify the cost.