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Good science requires much more than evidence
Empiricists believe that scientific theories are true only if they make correct empirical predictions: if we can't verify these predictions, then there is no reason to expect that they tell us anything about reality. However, Professor of Philosophy at King's College David Kyle Johnson argues that this is mistaken. In response to Bas van Fraassen, who has written on this subject for the IAI, he argues that we have many reasons for believing a theory to be true, such as it being parsimonious and having large scope — qualities which have been used throughout the history of science as criteria for judging theories. In 2024, Princeton philosopher Bas van Fraassen wrote a short article for IAI News entitled “Science Does not Describe Reality: The Limits and Benefits of Explanation.” At the time, I was working on two projects (a science book and a Great Course) that, when completed, would (among other things) defend science’s ability to describe reality. I wanted to write a response to van Fraassen, but the projects demanded too much of my attention. But now that those projects are complete, I am in a position to explain the objections to van Fraassen’s thesis. Summarizing van Fraassen’s argumentIn a nutshell, his argument is this: What scientists do is make predictions based on theories and then invite others to test to see whether those predictions are borne out. “If theory T is right, result R should happen in experimental condition C.” Many think that running an experiment that shows that R happens in condition C is proof that theory T is true (and should be believed). But, van Fraassen argues, that R happened in condition C is only a reason to think that R happens in condition C. That’s the only observable, or empirical, result we can actually see, so that is all that we are really justified in believing. (The underlying theory that made that prediction still may or may not be true.) That is why he calls those who accept his position “empiricists.”Before I explain what is wrong with this position, let me explain what it gets right. What van Fraassen Gets RightFirst, a theory correctly predicting the results of an experiment is not, strictly speaking, “proof” that the theory is correct. The basic line of reasoning is this:If the theory T is true, result R should happen. Result R did happen. Thus, theory T is true.In other words:“If T then R. R. Thus, T.”This is a deductively invalid, fallacious mode of reasoning, called “affirming the consequent.” Those premises do not guarantee that the conclusion follows. “If I am in Pennsylvania, then I am in the USA. I am in the USA. Thus, I am in Pennsylvania.” Clearly that argument doesn’t guarantee its conclusion; neither does the above argument.However, science is not a deductive method of reasoning; it is an inductive one. And inductive arguments merely try to raise the probability of their conclusion, not “prove” them for certain. Thus, the fact that an experimental result doesn’t prove a theory is true is irrelevant; it’s not supposed to. That is not what scientific reasoning is about.___If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational.___Second, it’s also true that a single experimental result doesn’t provide enough justification to believe that a theory is true. Scientists do not come to a consensus about whether a theory is true by looking at a single experiment; they look at all the evidence to determine where the preponderance of evidence points. The mere fact that I am in the USA raises the probability that I am in Pennsylvania, but not nearly enough to conclude that I am in Pennsylvania. However, if I am also regularly encountering people wearing Eagles and Phillies hats and seeing advertisements for Founding Father tours, I probably am. In the same way, a theory successfully predicting the outcome of one experiment is not enough to conclude that it is true; but if a theory makes a wide variety of predictions that are all vindicated by multiple experiments, performed by many different groups and people, all actively trying to prove the theory false (which is what good scientific experiments are designed to do)—that is a good reason to conclude that the theory is true. In other words, if you repeatedly try to prove something false but can’t, that is a very good indication that it isn’t. The problem of underdeterminationIn reply, those whom van Fraassen calls “empiricists” often point to the “problem of underdetermination.” For any given theory that makes successful predictions about what happens in experimental conditions, there are countless other possible theories that make exactly the same predictions—and since they do, the experimental evidence in question is just as much reason to accept any of those theories as it is to accept our original one. Thus, the argument goes, we have no way of knowing whether our original theory is true, or one of the other “predictively equivalent” theories is true. SUGGESTED VIEWING How Occam's Razor changed the world With Johnjoe McFadden As an example of underdetermination, philosophers often offer this example. The evidence of fossils seems to provide reason to conclude that the universe is quite old; ancient fossils are what the “ancient universe” hypothesis predicts. But it’s also possible that God created an ancient-looking universe 200 years ago, complete with a “fake” fossil record for us to find, to make it look old. The existence of fossils is what that theory predicts too. So, the argument goes, the fossil record can’t be used as evidence that the universe is ancient; the fossil record supports the “200-year-old ancient-looking universe” theory just as much. The problem of underdetermination points out that, for any theory with supporting evidence, we could invent another completely different theory that predicts exactly the same evidence, and thus undermine that evidence’s ability to support the original theory.But this “argument from underdetermination” betrays a fundamental misunderstanding of what scientific reasoning is and how it works. To explain, let me use another rather strange (but very real and commonly discussed) philosophical thought experiment called “The Grue Problem.” The “Grue” ProblemSuppose I want to know what color emeralds are, so I observe a few, see that they all appear green, and form the theory that “all emeralds are green.” I thus predict that the next 100 emeralds I find will also appear to be green. And let’s say that happens, and so I thus conclude that my theory that all emeralds are green is true. Now, one might rightly point out that I don’t know for sure that all emeralds are green—I have not seen them all. Maybe some I haven’t found yet are blue. Fair enough. After all, we used to think that all swans were white, until we found some black ones. But let’s say that I go on a quest and collect every emerald in the universe—and, for the sake of the argument, let’s say I can do this, and can even know that I have every one of them. So, I collect them all, look at them all, and verify that they all appear green. Can’t I now rightly conclude that all emeralds are green?Inspired by the problem of underdetermination, a friend might argue that I cannot.Sure, they all appear green now—but there could be another kind of color called “grue.” Something is grue if it is green up to a certain point in time, but then spontaneously turns blue. And there could be an infinite number of “shades” of grue. Something that is one shade of grue will turn blue at noon today, but something that is another shade of grue will turn blue at noon tomorrow, etc. So yes, the emeralds appear green now; and since they haven’t turned blue yet, they are not some “past” shade of grue. But they might be some “future” shade of grue (e.g., they may turn blue at noon tomorrow). And since all future shades of grue are consistent with “being green up to this point in time,” the evidence you have is completely consistent with the notion that all emeralds are some future shade of grue, rather than green. Indeed, that they would appear green until now is what the “some future shade of grue” hypothesis predicts. So, we have just as much reason to conclude that all emeralds are some shade of grue as we do to conclude that they are green.You’re probably thinking “It’s not equally possible that the emeralds are grue; they are obviously green.” You are right! But explaining why your instinctive reaction to my friend’s argument is correct will help inform why van Fraassen’s “empiricist” is wrong and science actually does describe reality.The main mistake my friend makes is in thinking that the “empirical evidence” (of all the emeralds appearing green) is (or even should be) all I am using to draw the conclusion that all emeralds are green. It is not. I am also considering known facts about how colors typically work; things don’t usually change color, and when they do, they don’t do so suddenly, without cause, and all at once. So, even though the simple evidence of the emeralds all appearing green up to this point is consistent with them being some future shade of grue—that is even what the grue hypothesis “predicts”—it is still exceedingly unlikely that they are. The hypothesis that they are green is much more likely. Understanding science refutes the problem of underdetermination The misunderstanding about science that the “empiricist” pointing to “the problem of underdetermination” makes is similar to the one that my friend made. Science is not just about considering experimental evidence; in fact, it’s not even just about considering empirical evidence. As Ernan McMullin and many other philosophers of science have pointed out, the inference that makes science is “inference to the best explanation” (sometimes called “abduction” or “retroduction” by McMullin). While, depending on the circumstances, scientists use many different kinds of reasoning, science as a whole is, simply put, the process of considering multiple competing explanations and comparing them to certain criteria—explanatory criteria (the kinds of things explanations must be and do, by definition, to be a good explanation)—to see which explanation is the best.And these criteria do not deal only with empirical results. Yes, successful predictions raise the probability of a hypothesis, but it’s also the case that the more new assumptions a theory makes, the less likely it is to be true; every new assumption presents an opportunity for the theory to be false. (The fewer assumptions a theory makes, the simpler or “more parsimonious” it is said to be.) Likewise, the more existing evidence a theory contradicts, the less likely it is, because in order for a theory to be true, every piece of evidence it contradicts has to be somehow faulty. (The fewer established theories a new theory contradicts, the more “conservative” it is said to be.) And, obviously, the more something explains, the better explanation it is. (This is called having “scope.”) If a theory raises unanswerable questions, it’s not expanding our understanding, and thus is not wide-scoping. Scientists consider all these things when deciding which theory to accept, because the theory that adheres best to these explanatory criteria is most likely to be true.___the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth.___The reason the grue hypothesis is no good is because it invents an entirely new kind of color—not just a new shade, but an entirely different category of color (a different way colors work)—and thus is not parsimonious. It raises unanswerable questions about how and why emeralds would just spontaneously change from green to blue (and thus does not have wide scope). And it contradicts what is already well established about how color works (and thus is unconservative).The theories that the problem of underdetermination points to do the same thing. Yes, the theory that God created an “ancient-looking universe” (complete with an ancient-looking fossil record) two hundred years ago is also consistent with the empirical evidence (of a fossil record) that presently exists; but that theory is monumentally unparsimonious (it requires many extra assumptions about infinite entities) and not wide-scoping (it raises unanswerable questions about why God would do such a thing). So, I can rationally conclude that it is false.Indeed, the history of science includes many examples of theories that were rejected because they lacked parsimony and/or scope, even before their falsity (and the truth of their competing theory) was confirmed by observation. As I point out in my book, geocentrism was rejected by the scientific community because it lacked parsimony, almost 200 years before the observation of parallax confirmed that the Earth moves around the sun. And the continuum theory of matter was completely rejected by 1860, because it couldn’t explain chemical reactions or organize matter into a periodic table, even though the experiments that eventually confirmed atomic theory weren’t even proposed until the 1870s. Solving the best of a bad lot problemIn response, the “empiricists” are likely to object, this time pointing to the “best of a bad lot” problem. “We have no reason to conclude that an explanation that has been shown to be better than others is true because we have no guarantee that the true theory was among those that we were considering.” If you have a “lot” (a collection) of poor explanations, even the best one is not true.The responses to this problem, however, are numerous. Peter Lipton argues that the set of hypotheses that scientists consider are not just randomly selected and thus unlikely to contain a theory that is true; they use existing knowledge to home in on what is most likely to be true. A doctor trying to explain abdominal pain is not going to bother wondering whether demons are causing it; they are going to stick with things like appendicitis and kidney stones, because they are most likely. Further, despite its name, inference to the best explanation is not just the process of comparing hypotheses and accepting the best one; we also want one that is a good explanation in its own right. If it’s not, we are going to keep looking until we find an explanation that is. And while that process does not guarantee that we will come across the exact truth, it’s very likely that the theory that emerges as the best will be at least approximately true, and thus we will be justified in believing it. And lastly, as I point out in my book, although many theories not based in scientific evidence (like geocentrism and continuum theory) have been completely overturned, science almost always progresses by the refinement of scientifically established theories—not their replacement. (Although our sun is not the center of the universe, heliocentrism was our first step in understanding the Earth’s true place in the universe.) So even if a theory we accept today may not be completely right, accepting it is a step on the journey toward the complete truth. The example of atomic theoryNow, it’s worth pointing out that most empiricists are not skeptical of all scientific theories; they are only skeptical of the ones that hypothesize the existence of “unobservables.” It’s not like they think that round Earth, heliocentrism, and germ theory are just useful (but untrue) “instruments” for making predictions about how to most efficiently navigate the seas, predict planetary motion, and treat diseases. They admit that the Earth actually is round, that the planets revolve around the sun, and that germs exist and cause disease. These facts and entities can be observed; the theories that suggest they exist are true. It’s only when theories start hypothesizing the existence of unobservables—like electrons, or quantum fields—that can’t be observed directly, that we should start doubting the theories’ truth. And to be fair to van Fraassen, in this published work, he doesn’t really say that we should doubt the truth of such theories. Only that scientific reasoning does not rationally force us to accept them as true. Skepticism, or agnosticism, he argues, is warranted. SUGGESTED READING Science is based in metaphor By Andrew Reynolds But the history of atomic theory throws a monkey wrench into that argument. Atoms used to be unobservable; again, scientists first accepted the theory that they exist because it had such grandiose explanatory power. But then atoms were seen with electron microscopes. They thus moved into the category of the observable. But this didn’t substantially change anything about what scientists were justified in believing; it certainly didn’t change any “atomic skeptics’” minds. It just confirmed what everyone already knew! If the hypothesis that something exists clearly provides the best explanation for what we can observe, then the belief that it exists is what is rational. The fact that the thing itself is not technically observable does not make doubting its existence rational.What’s more, the atoms were seen with an electron microscope. But electrons are themselves unobservable. How can an electron microscope reveal an atom if electrons are not real? This leads us to what is famously known as Hilary Putnam’s “miracle argument.” It’s (not) a miraclePhilosopher Hilary Putnam’s miracle argument is somewhat famous. Basically, he argued that a scientific theory being able to repeatedly make successful predictions—even about unobservables—without being at least approximately true would require a “miracle.” In other words, it would be such an improbable occurrence that it could not rationally be believed—the better explanation for why scientific theories about unobservables make the right predictions is because the unobservable entities and structures they hypothesize exist.Van Fraassen has addressed this argument. Indeed, in his original article, where he references Alison Gopnik’s point about orgasms not being “necessary for procreation” even though the desire for orgasm “drives the creation of progeny,” he is pointing to his own argument about how organisms are not naturally selected by evolution to get true beliefs; to the extent that belief-forming processes are selected for, the ones that are selected are the ones that are useful for survival—not the ones that produce true beliefs. In the same way, van Fraassen argues, scientific theories are accepted, not because they are true, but because they aren’t falsified; they make successful predictions; that’s what makes them “stick around.” So, the fact that they make successful predictions (and thus became accepted) is not a reason to think they are true.This argument is similar to C. S. Lewis’s “argument from reason,” which he used to argue against evolution: “The truth of evolution undercuts our ability to know that it is true.” Lewis’ argument famously failed; Elizabeth Anscombe, by Lewis’s own admission, demolished Lewis in a debate on the topic, and I have explained elsewhere why modified versions of the argument fail as well. In short, it’s because it fails to recognize that a belief-forming process can make an organism more likely to survive because it reliably produces true beliefs. It is therefore not the case that beliefs generated by naturally selected belief-forming processes are automatically false or unjustified.In the same way, the reason a theory “sticks around” could be because it’s not falsified, because it “makes correct predictions.” But the reason it makes correct predictions is most likely because it is true. (In pointing this out, I am echoing the arguments of Musgrave, Lipton, Psillos, and Kitcher, who refuted van Fraassen’s argument and analogy long before his 2024 article.) It would be a huge coincidence that it could do so without being true. And that is the point of Putnam’s miracle argument. Thus, contrary to van Fraassen’s suggestion, the mere fact that a theory’s predictive success is why it “sticks around” or “becomes accepted” in the scientific community is not a reason to be skeptical about its truth. ConclusionLet me close by saying something about the fact that empiricists don’t doubt the truth of all scientific theories, just the ones that hypothesize unobservables. In today’s society, this theory is dangerous to espouse publicly. The nuance between being skeptical about all of science, and just the highly technical theories about unobservables, is guaranteed to be lost to the average reader. And there is so much unjustified skepticism and doubt about the findings of science and experts that a headline like “Science Does Not Describe Reality” could easily fuel the anti-science movement, worsen climate change denial and cause the next pandemic.This is why I believe it was important to still respond to van Fraassen’s article, a full two years after he wrote it. Not only, as I have argued, does it represent a philosophically inaccurate view of how scientific reasoning works and what scientific reasoning can do, but it is a dangerous view to boot. It should thus be rejected.
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September Monthly Review: Health MCP Guy?
For all the time I spend talking about APIs and data exchange, this newsletter has had embarrassingly little interoperability of its own. It’s old-school SaaS, baby - UI or bust. Not all of that is my fault! Substack, for all its popularity, is (as mentioned before) really frustrating as my system of record. The primary user it optimizes towards is the reader, whose attention feeds the app, the Notes feed, and the recommendation network that Substack is actually selling. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe They’re falling into the same trap that Medium once sprinted into, albeit at a much more glacial speed. Younger generations may not remember (or never knew) it, but Medium once lured publications like The Ringer and Signal v. Noise onto its platform, only to lose them as it rebuilt itself around a paywall and an algorithmic feed. Substack’s original pitch circa 2020 was the antidote (you own your list), but every new feed feature chips away at it. I get it: writers are generic supply in the eyes of the Substack product team. Generic supply follows demand, so the consistent pressure on the PMs is to generate demand, which leads to every product cycle going toward discovery (Notes, recommendations, the app, live video). The end result lackluster author tools (laggy and broken analytics are truly crippling) all despite the premium price point. The archive is where it crosses from authorial gripes to actual reader impact, though. Across Substack and LinkedIn, I’ve published 1,218 posts and nearly 900,000 words since 2018. Substack’s native search can see only the 464 posts that live on Substack, and even there it’s woefully inadequate at surfacing relevant content (even for the guy who wrote it)! Readers have the same problem, writ large. Ask the Archive Fixing search (for both my readers and my own use) turned out to be extremely non-trivial, unfortunately: There’s no public API for readers to access content RSS exists for new content notification, but it only carries the 20 most recent posts and cuts paid ones off at the preview The only Substack MCP is an admin tool for analytics The export exists for authors, but it’s painfully awkward and slow. So I built something to work around that: the Health API Guy MCP. It’s a private MCP server holding the full text of everything I’ve written across Substack and LinkedIn. Add it to Claude or ChatGPT as a connector and you can ask things like: It pairs keyword search (for acronyms and case names, of which we have many) with semantic search. Every post is also labeled by topic, form, and court case, so you can pull a lawsuit’s (or multiple cases’) entire docket across Substack and LinkedIn in one query: Hail, Healthapiguyhydra This is also a bit of me eating my own cooking. I’ve spent the year arguing that headless healthcare is arriving and that developers want primitives over abstractions. Last week in Hail, Benihydra, I watched Salesforce plug its platform into Claude and bet that the records underneath outlive whatever interface sits on top: Salesforce must believe that the Hydra’s immortal head is the records, permissions, and business logic (in that they will survive whatever happens to the interface). It felt a bit hypocritical to keep my own archive behind a Substack search bar. The archive is the body. Substack is one head, and now whatever tool you might use is another. Will the EHRs follow my lead? Probably not imminently, but one can hope! Why Founding Members Only The MCP is available to Founding Member subscribers. A few reasons: It costs money and time to run. Hosting, the database, Clerk usage and AI compute for search and labeling are significant operational costs (that increase with usage). Substack gives me no way to automate access. There’s no API to check whether someone is a paid subscriber, so every user is manual operations for now. It’s a beta. We’ll need to improve things and parts will break. I’d rather they break for a small group of dedicated readers who will tell me about it. The Founding tier deserved a real benefit. Until now it was mostly a generous tip. Now it comes with something. If you’re already a Founding Member, reply to this email with the address you’d like provisioned. If you’re not and want in, upgrade here. Larger teams (such as companies) can get access too: group subscriptions at the Founding tier come with the group discount. The admin for the subscription can reply with the list of addresses to provision. Get 20% off a group subscription Pricing Founding membership is now a flat $200 a year, replacing the old suggested $150 that readers could adjust. Existing Founding Members will have access grandfathered in at their previous rate. Month in Review Articles Published Make Networks Dumb Again (Sep 11): AI is making old analog networks cheaper to use and flooding them with machine traffic in the process. A plea for agent-native rails with the intelligence at the endpoints, and for Washington to drag them to ubiquity. Interoperability, Unbuttoned (Sep 29): Interoperability is a series of workflows in a trenchcoat, and this post finally takes the trenchcoat off. A color-coded map shows which provider workflows went digital, which are fragmented, and which still run on fax. Video Content Antitrust’s System of Record Problem (Sep 3): The FTC’s investigation into Epic prompted a ninety-minute webinar, now posted with chapters and a smoothed transcript. We get into why market definition, missing B2B share data, and the SSNIP test leave antitrust poorly suited to systems of record, plus why information blocking may be doing more than any pending lawsuit. The Information Exchange: Cerner Milking Edition (Sep 18): This was so fucking fun. Ryan Tucker, Ryan Brickner, Brad Thorson, and I try an Around the Horn format, complete with points, penalties, and a mute button. We debate whether Oracle Health is dead, who would actually buy Cerner (IBM enters the chat), p(Doom), and why the front desk still hands you a clipboard. Regulatory Ask Not What Your Network Can Do (Sep 23): CDC’s RFI on public health data intermediaries lists use cases already served, unevenly, by eCR, lab reporting, IZ Gateway, and syndromic surveillance. The real opportunity sits in one question about AI: a network that can handle the next emergency without another interface project. Court cases Particle v. Epic: The Naughty Schoolteacher (Sep 4): After a summer-long vigil, the answer on Epic’s early summary judgment bid is two paragraphs and a remedial assignment. Particle advances to the next grade, and market definition gets another year of discovery. The Epic Discovery Files (Sep 8): Texas’s motions to compel arrive with a 251-page appendix of requests, objections, and meet-and-confer letters with Cravath. Inside: Epic using generative AI for document review, denied interoperability requests in scope, and Noerr-Pennington raised against lobbying discovery. Epic v. Health Gorilla: “Working as Designed” (Sep 9): Epic wants nothing to do with the data breach MDL, and explaining why puts fresh discovery on the public docket. The spiciest allegation: Health Gorilla told GuardDog to scrub its law firm business from its website instead of cutting off access. Veeva v. Epic: Legal Bypass Surgery (Sep 15): Veeva asks the Wisconsin Supreme Court to skip the Court of Appeals, while law professors and three policy groups line up as amici. Meanwhile, Epic’s lawyers apologize for another round of citation errors, including a quote that never existed. Texas v. Epic: Behind the Black Bars (Sep 17): The court portal served up Epic’s unredacted filings, revealing a $5 million document review budget and the AI workflow behind it. Also inside: the 200-plus company names Texas wants searched, and one very expensive Zoom invitation. OpenEvidence v. Doximity: Consequences Will Follow (Sep 25): OpenEvidence tells the court it will not comply with a discovery order, and its own lawyers at Quinn Emanuel say they won’t defend the choice. Add years of Slack reported unrecoverable, and Rule 37 sanctions come into view. Health Tech Keeps Choosing Violence (Sep 28): Doximity moves to end OpenEvidence’s case, Epic asks Texas to show its work, and a sleepy Audacious Inquiry patent fight sprouts antitrust and information blocking counterclaims. The main event is a long-sealed Cognizant v. Infosys ruling that hints where system of record antitrust claims can survive. EHRs One Verb for Oracle Health (Sep 14): Oracle’s earnings call quantifies every data center to the decimal point, while Oracle Health gets a single verb: “accelerate.” Panning the few healthcare mentions turns up an agentic care management system, a research-to-care ledger play, and the question of whether healthcare gets Larry’s patience. Epic’s Forretress Under Siege (Sep 30): Judy Faulkner tells a panel Epic paused hundreds of projects to harden its software and calls it a “shame,” while a spokesperson insists the roadmap hasn’t changed. Project Glasswing, a Pokémon-branded QAN sprint, and a trove of Jodel grievances reconcile the two Epics and preview the Jevons paradox coming for all software. Industry Analysis Scanning for a Network (Sep 1): Scan.com raises $220M to build the imaging network labs never got, speedrunning Zocdoc’s consumer-to-B2B pivot. Its wedge to network density may be the most American one available: personal injury litigation. The Front Desk Wants the Damn Whole Building (Sep 16): Hello Patient buys Converse Health, pushing its AI front desk into referrals, chart work, and prior auth. The copilot categories keep blurring, and your distribution partner is still your final boss. Cross-industry Comparisons A Different Patchwork Quilt (Sep 10): Healthcare loves to envy open banking, but the US version has no mandate, a toll booth at Chase, and data quality problems of its own. The grass isn’t greener; it’s another American patchwork quilt, and perhaps a worse one. Hail, Benihydra (Sep 21): Salesforce brings its platform into Claude, Slack, and its own agent, inviting the interfaces that might replace it. Cut off one head and more grow back, so long as the records underneath stay put. Living on A Trade Secret Prayer (Sep 22): Six credit unions are suing Fiserv, the Epic of core banking, by claiming their own member records as trade secrets. Banking has no Cures Act, so its lawyers reach for legal alchemy that healthcare has already tried. Other News None this month External Media Nabla Accelerate NYC: I kicked off fall conference season at Nabla’s Accelerate event in New York, where Delphine Groll opened by asking the room to picture the company it wants to become and the one it doesn’t. I liked her framework of bureaucracy, fear, and ego as the blockers. I also love vendor conferences/events in general - different vibe than industry biggies. Healthcare 101 with Nikhil Krishnan: I briefly guest lectured Out-Of-Pocket’s Healthcare 101 class. Appreciated Nikhil’s takeaways cover whether AI doctors can query HIEs, why healthcare’s data-liberation rules beat most industries’, and the hi-res graphic is in the comments. HCN: Epic Probed by the FTC: I joined the HCN guys to talk through the FTC’s investigation into Epic. Cedric’s new hairdo was an unexpected plot twist. The episode also covers MFN drug pricing, healthcare M&A and Eli Lilly’s acquisition streak. Fall Conferences: At eHealth Exchange’s Annual Meeting in Austin on Oct 27, I’ll moderate a panel on the tensions between AI, HIEs, and timely patient access with Jean Ross (Primary Record), Therasa Bell (Kno2), Byron Crowe (Doctronic), and Michael Marchant (Freenome). Here’s the rest of my schedule if you want to meet up: CommonWell (Redwood Shores, CA): Oct 13-14 Will be participating in a fun Jeopardy event Open@Epic (Madison, WI): Oct 20-23 Will be enjoying Verona, Willy Street, and other local adventures eHealth Exchange and Sequoia Project (Austin, TX): Oct 27-29 Yeehaw HLTH (Vegas): Nov 15-18 Groundhog Day, Venetian Edition RSNA (Chicago): Nov 30-Dec 2 See me at “Governing AI in Breast Imaging: What Health Systems Are Actually Doing” Digital Health Counsel 2026 AI Summit (Seattle): December 2-3 Will likely be speaking to a bunch of lawyers about information blocking Posts I Liked ChatGPT’s Epic integration: game changer or nothing burger?: Joshua Liu, MD offers five thoughts on OpenAI’s Epic launch, starting from the point that it rides the same open APIs available to anyone. He argues read-only access leaves ordering to Art and the ambient startups, and asks why HCA is piloting it alongside Commure. He’s sorta a must-follow at this point - consistently excellent, thought-provoking takes. Epic, Lilly, and the Discovery pass: Seth Chaney reads Epic’s first major Discovery deal (with Eli Lilly), as well as its revised developer terms on commercial displays, as the pipe finally opening between EHRs and pharma. Life sciences and health continue to collide. Scott Rossignol on EHR payer platforms and ePA fees: Scott argues the top ambulatory EHR vendors are turning the prior auth mandate into a per-member-per-year toll on payers, for an API whose operating cost has nothing to do with covered lives. His fix is two lines of regulatory text: put the CRD/DTR/PAS certification criteria in the Base EHR definition, and bring payer-facing ePA connectivity under § 170.404’s cost-based fee rules. It’s a good solution. Health API Guy is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
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Lanesboro Arts is thrilled to celebrate the release of Chris Koza’s latest album, “Millsmoke on the Skyline,” with a concert at the St. Mane Theatre at 7 p.m. on October 24. Chris Koza is a composer and performer based in Denver and Minneapolis. In his writing, Koza both honors and builds on the vast genre of Americana music. For every song that sounds like it could be strummed from a boxcar clacking slowly across a grassy midwestern plain, there’s a tune sailing from a city rooftop, echoing across a valley of streets and traffic, or a melody twisting and shimmering like a dim frequency deep into the starry night.Both as a solo artist and with his band Rogue Valley, Koza has supported and shared the stage with artists such as Brandi Carlile, Gordon Lightfoot, Ingrid Michaelson, The Jayhawks, Neko Case, Kathleen Edwards, Dan Wilson, and many more. His music regularly appears on ABC’s “General Hospital,” “60 Minutes,” and “Good Morning America.” Koza’s song, “Be Wild,” was also featured in a state of Minnesota tourism campaign.#placement_932485_0_i{width:100%;max-width:550px;margin:0 auto;}var rnd = window.rnd || Math.floor(Math.random()*10e6);var pid932485 = window.pid932485 || rnd;var plc932485 = window.plc932485 || 0;var abkw = window.abkw || '';var absrc = 'https://ads.empowerlocal.co/adserve/;ID=181918;size=0x0;setID=932485;type=js;sw='+screen.width+';sh='+screen.height+';spr='+window.devicePixelRatio+';kw='+abkw+';pid='+pid932485+';place='+(plc932485++)+';rnd='+rnd+';click=CLICK_MACRO_PLACEHOLDER';var _absrc = absrc.split("type=js"); absrc = _absrc[0] + 'type=js;referrer=' + encodeURIComponent(document.location.href) + _absrc[1];document.write('');Koza’s latest offering, “Millsmoke on the Skyline,” grants the newfound outsider perspective of the rich life and golden fleeting days throughout the rural Midwest. Weaving melody and lyrics into vignettes and narratives set in places where love is powerful, dreams are vast, and life is beautiful.The St. Mane Theatre box office will open at 6 p.m. on the day of the concert. Tickets will be sold in person at the door or can be purchased online at lanesboroarts.org. Seating at the St. Mane theatre is first come, first served. Tickets are on sale now for $25 for general admission or $22 for Lanesboro Arts members.The 2026 performing arts season at Lanesboro Arts is made possible by our season sponsor, Poet Refinery, as well as our concert level sponsors, High Court Pub, Krage Insurance Agency & Preble Farmers Mutual, Stone Mill Clothing & Gifts, E2 Boutique/Amish Experience, and The Cottage House Inn, and community sponsors, VIS Plumbing, Granny’s Liquor, Kingsley Mercantile, Batstone CPA, Clara’s Eatery, IGA, Niagara Cave, and Huntington Electric. This event is made possible by the voters of Minnesota through a Minnesota State Arts Board grant, thanks to a legislative appropriation from the Arts and Cultural Heritage Fund. #placement_932489_0_i{width:100%;max-width:550px;margin:0 auto;}var rnd = window.rnd || Math.floor(Math.random()*10e6);var pid932489 = window.pid932489 || rnd;var plc932489 = window.plc932489 || 0;var abkw = window.abkw || '';var absrc = 'https://ads.empowerlocal.co/adserve/;ID=181918;size=0x0;setID=932489;type=js;sw='+screen.width+';sh='+screen.height+';spr='+window.devicePixelRatio+';kw='+abkw+';pid='+pid932489+';place='+(plc932489++)+';rnd='+rnd+';click=CLICK_MACRO_PLACEHOLDER';var _absrc = absrc.split("type=js"); absrc = _absrc[0] + 'type=js;referrer=' + encodeURIComponent(document.location.href) + _absrc[1];document.write('');
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“I’m just going to run to the grocery store!” How many times have we said this without thinking about it? For most of us, it's usually an easy walk or a short drive to get the cheese we forgot. In reality, though, 13% of the U.S. population (about 39 million people) live in “food deserts,” which means living more than a mile from a grocery store in urban areas and more than 10 miles in rural areas. This was the case for people in Pittsburgh’s Hill District, where a quick run to buy food wasn’t an option. In the 1930s, federal maps marked the Hill as "hazardous" for lending, a practice known as redlining that steered investment away from Black neighborhoods. Decades of disinvestment followed, and residents went about 30 years without a nearby grocery store. This made it hard to keep healthy eating habits and contributed to chronic disease. When a grocery store finally opened in the area in 2013, researchers saw the opportunity and launched the PHRESH study, which initially compared the health of participants from the Hill district to those in the Homewood district. Over time, the study expanded to other factors such as brain health and Alzheimer's risk. Residents like Roderick Blair overcame initial hesitation to share their health data, trusting it would benefit their neighborhood. Then, in August 2026, the NIH abruptly canceled the study’s grant, citing that it was “subjective” and fell outside their scientific scope—an effect of the administration’s interpretation of diversity, equity and inclusion (DEI). Research like PHRESH can help determine what changes in a neighborhood actually improve health, so cutting it has left that question unanswered. Other canceled studies have examined health issues like maternal health, preterm birth rates, or sickle cell disease. Courts have reversed some of these grant cancellations, but not all of them. If we really want America to be healthier, research into why some communities get sicker than others is absolutely critical. The law that created the federal minority health research institute passed with bipartisan support in 2000. But these days, as evidenced by grant cancellations, the political shift in attitudes toward DEI means we often lose access to the health information we need to help all communities thrive. DEI vs. health equity vs. equality and the overlap (or lack thereof) The letters “DEI” evoke very different reactions depending on who you are in the U.S. DEI programs can address gender, disability, age, and other factors, but the fiercest debate centers on race. For some people, hearing DEI brings to mind policies that may have cost them a job or a college seat because they are white. Others see DEI as a matter of justice: a way to expand representation and opportunity for groups that have been historically marginalized. Both perspectives are rooted in lived experience, and both center on the same question: whether hiring and admissions practices are fair. Hiring and admission practices, though related, are not the same as health equity. Health equity is “the attainment of the highest level of health for all people.” It’s the recognition that some groups of people consistently experience worse health outcomes than others. For instance, black mothers die from pregnancy-related complications at three times the rate of white mothers, and rural Americans are more likely to die from issues such as heart disease and cancer. Equity is also often conflated with “equality,” which leads to misunderstanding of how to actually best support communities. Equality ignores the fact that we aren’t all starting life with the same resources or circumstances, whereas equity is about helping people get what they specifically need based on their situation so they have the chance to achieve the same outcome as anyone else. For example, if every household in Pittsburgh got a $30 grocery gift card, that would be equal. But during the decades the Hill District went without a grocery store, that card wouldn’t have helped much. Equity means making sure everyone can actually access a store in the first place. DEI policies can overlap with health equity in many ways. For example, they may help expand access to quality education and stable, well-paying jobs, which in turn can provide health insurance, safer housing, and improved finances—all of which can reduce health disparities. But to make that happen, we first need data to identify disparities in communities and to develop solutions that effectively address them. What we lose when the research stops Community data is important to health equity because: You can’t fix what you don’t see: Data show which communities are most affected by health factors such as infection, heart disease, and cancer. If we don’t know what is happening and where, then we can’t develop interventions to help. Poor health costs everyone: Chronic disease is expensive—both to the individual person and to the overall economy. Understanding what groups of people are most at risk allows us to develop interventions that can save everyone money. Disparities exist for many communities: Health equity includes disparities that exist due to a whole host of factors, such as family background, race and ethnicity, rural vs. suburban residence, gender and sexual orientation, veteran status, disability, and lower income. This means many Americans can benefit from research into differences in health outcomes and how to improve them. Trust is easy to lose: Some participants in the PHRESH study were initially vocal about their concerns about participating. But that trust was earned because the researchers kept their promises and centered their work on the community. When projects are canceled mid-cycle, researchers have no choice but to leave behind communities they had promised to help. This hurts trust in the long run. It’s also a very inefficient use of resources, and it will take significant time and effort to redo the work when the government realizes this work is important again. How should we talk about health equity? This is hard because the words “equity” and “DEI” are currently very politically charged. So whether you’re a public health professional, teacher, or friend, how we talk about this topic matters. The right framing can help people who might otherwise be skeptical see why health equity research is important and deserves funding. Here are some suggestions to help your conversations: Choose your words strategically: Who are you trying to reach with your message? Are they likely to be resistant to terms like “diversity” and “equity”? If so, find alternative words to use to still get the message across. It is frustrating to be in that position, but the goal of improving health is too important not to try to make inroads. Sometimes simply reframing can help the message reach those who need to hear it. Focus on the problem: The terms “health equity” and “DEI” are abstract. Make it more specific. For example, discuss differences in maternal death or ways to improve health outcomes in rural communities. These still have equity at their core but will likely be better understood by those you’re talking with. Focus on systems: Disparities exist, but if they are communicated poorly, people can mistakenly think the issue is the individual’s fault. Disparities are largely driven by failures of the system—such as lack of access to health care and a long legacy of racism. When discussing the disparities, frame them around these systemic issues to ensure blame isn’t placed on the individuals impacted. Tell stories: Personalize these policies by using stories from those impacted that connect to the data you’re trying to convey. This helps make the policies and outcomes more concrete and meaningful. Bottom line Some communities end up sicker than others. That’s just the facts. We can argue about the best way to do that research, but canceling it simply because it may be linked to DEI doesn’t make anyone healthier. It just leaves communities like the Hill district behind. And in the end, it causes us all to move backward in our efforts to improve health in this country. Love, EM Big thanks to MacKenzie Isaac & Legairre Radden, who reviewed this piece and generously shared their expertise and lived experience to help improve it. Dr. Liz Marnik, PhD, is Executive Director of The Evidence Collective and a science communicator and immunologist working at the intersection of public trust, science, and public health. To discuss communication training on topics like health equity and storytelling, email Liz at liz@yle.health or learn more on our website. Your Local Epidemiologist (YLE) comprises a team of experts, ranging from physicians to immunologists to epidemiologists to nutritionists, working together with one goal: to “translate” ever-evolving public health science so that people are well-equipped to make evidence-based decisions. The YLE suite of newsletters reaches over 475,000 people across more than 132 countries. This newsletter is free to everyone, thanks to the generous support of fellow YLE community members. To support the effort, subscribe or upgrade below: Your Local Epidemiologist is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe
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The health secretary, Vice President JD Vance and other top officials addressed a conference sponsored by corporations, including A.I. companies and others with business before the government.
The Streamers Tried To Conquer Labor Day…and Whiffed
(Welcome to my weekly streaming ratings report, the single best guide to what’s popular in streaming TV and what isn’t. I’m the Entertainment Strategy Guy, a former streaming executive who now analyzes business strategy in the entertainment industry. If you were forwarded this email, please subscribe to get these insights each week.) What? Another Streaming Ratings Report already? You betcha. Nielsen has moved up the release of their Streaming Ratings data by two weeks, which means I’ve got two extra issues to get out. But I love this change because it will make this report more timely and easier to publish regularly. This week—with the viewership data for the week of 31-Aug—we’ve got some huge, huge topics to discuss. On the film side, two theatrical films (The Mandalorian and Grogu on Disney+ and Scary Movie on Paramount+) contend with two non-Netflix straight-to-streaming films (Mayday on Apple TV and The Runner on Prime Video). The streamers went all in to win Labor Day weekend in America. And we have a bunch of TV shows to analyze, both new shows (Netflix’s The Gentleman, Hulu’s Chad Powers, and an Alix Earle reality show) and weekly shows like Reacher, Ted Lasso, House of the Dragon and Lioness. All that, plus nepotism in Hollywood, some eye-popping fantasy football stats, all the flops, bombs and misses, and a whole lot more. Let’s dive right in! (Reminder: The streaming ratings report focuses on the U.S. market and compiles data from Nielsen’s weekly top ten viewership ranks, Luminate’s Top Ten Data, JustWatch and Reelgood interest data, Samba TV household viewership, company datecdotes, Netflix hours viewed data, Google Trends, and IMDb to determine the most popular content. While most data points are current, Nielsen’s data covers the weeks of August 31st to September 6th, 2026. You can find a link to my terminology here.) Subscribe Film - A Slew of Labor Day Disappointments? A lot of streamers released big new films this week, why? My theory is that the streamers know that four-day weekends can propel streaming films to glory. But if you’ve been reading more over the last two years, you know that big holiday weekends aren’t driving big viewership numbers the way they did post-Covid. And interestingly enough, Netflix didn’t put out a big new film this week. But four other streamers did, trying to take advantage of the holiday with some (not cheap) swings, including… The Mandalorian and Grogu on Disney+ (a Star Wars film that cost $165 million and made $177 million at the US domestic box office) Mayday on Apple TV (rumored $100 million budget, no theatrical release) The Runner on Prime Video (at least a $40 million budget, but likely $50 to $80 million, no theatrical release). Scary Movie on Paramount+ ($30 million budget, made $108 million domestically). (Paramount+ also released a made-for-streaming film based on the Thundermans IP, and I’ll discuss that later.) So…how’d they do? The Mandalorian and Grogu Leads The Way (But That Isn’t Enough) Let’s start with The Mandalorian and Grogu (which I’ll abbreviate to Mando for most of this article). We’re just getting started with this issue, but the rest is for paid subscribers of the Entertainment Strategy Guy, so if you’d like to find out… How Mando, Mayday, The Runner and Scary Movie performed on streaming... How the powerhouse weekly released shows (Reacher, Ted Lasso and Lioness) have accumulate a LOT of viewership… How House of the Dragon finished its run… The latest Netflix show to have a sophomore slump… Whether top creators can drive viewers to their shows… Nepotism in Hollywood and the music business... All the flops, bombs and misses for the week… And more… ...please subscribe! We can only keep doing this great work with your support. Coming Soon! Since Nielsen has accelerated their streaming data release schedule, I’ve got a lot of Streaming Ratings Reports coming your way! Next issue, I’ll be looking at the second season of Peacock’s The Paper, the latest season of Hulu’s The Secret Lives of Mormon Wives, and a very, very expensive Daily Wire fantasy series that’s now on Prime Video. Plus Crew Girl and Dang! on Netflix, a new Tyler Perry film, and one of the biggest bombs of the summer, Supergirl. In the next two issues, I’ll take a look at the return of the NFL to streaming, Toy Story 5 on Disney+, Backrooms on HBO Max, and The Breadwinner on Netflix. On the TV side, we’ve got Netflix’s Monster: The Lizzie Borden Story, Dancing with the Stars on Disney+, Apple TV’s Slow Horses, a Reacher spinoff on Prime Video, and Paramount+’s MobLand, a Woody Harrelson and Matthew McConaughey comedy on Apple TV, a sequel to a Cosby Show spinoff on Netflix, The Great British Baking Show, and the Unabomber film. And while doing all that, I want to take a look at adult animated shows, Ride or Die’s cancellation, and Netflix’s summer films. So much great stuff! Long term, two bits of comic book news. The X-Men cast has been announced, and go ahead and color me bull-ish, if not very, very bull-ish on this bit of comic book IP. In weirder news, HBO Max ordered a “true crime” show by Jimmy Olsen about Gorilla Grodd being falsely convicted of murder. I mean, what? I don’t know, let’s see what happens.
Harlem Globetrotters announce 5 tour stops in Wisconsin
The lineup includes the team's traditional New Year's Eve show in Milwaukee, dating back to the 1960s.
RB Leipzig Receives €353,000 From UEFA for International Duty
The German side secured €353,000 for releasing sixteen stars, topping 611 European teams in a multi-million euro distribution recognizing the rising cost of international player availability.
Universal health care a 'moral imperative,' Vatican's top diplomat tells UN
The meeting's theme focused on developing a