• Fractional use of vials/pills to decrease per-patient cost, because the main driver of high cost of drugs is not manufacturing (i.e. a ten times more efficient manufacturing process would not result in 10 times, or even 2 times lower prices). If you don’t believe me just look at what Sanofi did with alemtuzumab.
• Using real-world data instead of randomized controlled trials, because while retrospective, non-randomized, uncontrolled studies [Note: Now rebranded as “real-world data”. ] are good for generating hypotheses and maybe, maybe, detecting enormous effect sizes [Note: Think: smoking causing cancer, but not: who-knows-what new material causing lymphoma. ] we have learned through much trial and error that RCTs are critical for evaluating whether a medical intervention works or not. Back when personal computers were too big and expensive for mass use, the answer wasn’t to invent a story of why calculators were better — it was to make PCs so cheap and small that not having one in your pocket was a matter of personal choice, not cost. Same for RCTs.
• The Choosing Wisely initiative, which was all the rage back when I was a resident and still seems to have legs. ⊕ [Note: Not to mention that the program unintentionally promoted a dangerous frame of mind in which some doctors thought extensive testing was never indicated, thus missing some rare but life-theratening diagnoses. ] Money spent on producing more content for doctors to read, listen, and watch — thus taking up their time — and encouraging patients to talk to their doctors at length about questionable data behind many of the procedures — thus, again, taking up their time — may have been better spent designing and running pragmatic RCTs that would answer these questions and save both the doctors’ and patients’ time by reducing ambiguity. Oh well.
• Yet another health care delivery reform — this may be just my healthcare policy naiveté, but these all had the whiff of rearranging deck chairs on the Titanic. ⊕ [Note: See also: the Homer Simpson car ] Mandating the desired outcome instead of thinking about the right incentives is bound to increase cost through second-order effects.

Anything else?

Speaking of Quanta Magazine, their own series of year-in-review articles is out. If you have no other plans this weekend (heh), you may learn what was new in 2022 in:

• Biology
• Computer Science
• Physics
• Math(s)
• Comments

Enjoy!

Fascinating how people least deserving of sitting at the table are so often the ones making the most noise.

To all trainees who are smart and lazy: no, you are not getting away with it. Sure, you can creatively avoid responsibilities on your way to graduation, but it will burn many more bridges than you realize. Your teachers aren’t stupid.

Samuel G Rodriques ⊕ [Note: If you were looking for his blog’s RSS feed, you won’t find one listed. Thankfully, NetNewsWire was able to dig up the url. ] is an inventor, entrepreneur, and author of my favorite blog post so far this year:

Serious drug developers have long since learned not to trust animal models when it comes to predicting the efficacy of a treatment for most diseases.

And also:

There is a phenomenon that all biologists will be aware of, where after working on a new idea for 2 years, you one day come across a paper from 2008 and say, “oh my god, if only I had known this two years ago.” If we want biology to move fast, we need to figure out how to eliminate this phenomenon.

And:

In biology, until recently, it seemed like everyone wanted to be a professor or start a company, i.e., that the only high status thing you could do after your PhD was to become a manager.

Not sure I agree with his prescriptions, but the diagnosis is right!

Fad of the day: Longtermism.

Longtermism is an ethical stance which gives priority to improving the long-term future. It is an important concept in effective altruism and serves as a primary motivation for efforts to reduce existential risks to humanity.

This is how you reduce existenal risks to humanity: avoid ruin. The rest is gobbledygook meant to dazzle venture capitalists and other sources of funding.

…is $1.5 million.

A few days ago, The Washington Post wrote about two medical students who are also identical twins being accused of cheating. Their school, the Medical University of South Carolina, apparently doesn’t have anyone on staff who is both versed in statistics and willing to participate in an investigation. Enter paid consultants:

The university sent their test scores to a data forensics company, Caveon, which reported that the chances of two tests that similar being completed independently was “less than a person winning four consecutive Power Ball drawings.”

Invocation of forensics is the first red flag (see: Calculated Risks by Gerd Gigerenzer). Comparing any real-life probability ⊕ [Note: Rule of thumb: if what you are doing professionaly made it into xkcd you should stop doing it. ] to lottery is the second. The uncertanty of real-life probabilities has little to do with known odds of games of “chance”. Confusing the two leads to the ludic fallacy, or “misuse of games to model real-life situations”. [Note: Nassim Taleb, The Black Swan, 2007. ]

The twins, now lawyers, sued and won the said $1.5M. Good for them.

If you would like to hear more about what I’ve been up to professionally for the last year or so — and maybe learn something about cellular therapy for autoimmune diseases — this 30-minute webinar organized by the Myasthenia Gravis Foundation of America may be of interest.

OpenAI’s new chatbot produces paragraphs of text indistinguishable from what you can find in newsletters, blogs, or college essays. It even does (mediocre) poetry and regex.

Halloween came a month late this year.

Alan Jacobs about Amerian health-care, or what passes for it:

I think the first thing to understand about the American health-care system is this: some people lose money from illness, and some people make money from illness. Some people pay, and some people get paid.

…

I don’t think there are many doctors who consciously make medical decisions based on their lust for money. But I do think there are a great many doctors who go along with the incentives established by the system, without thinking about it too much or at all, because on some level they know that thinking about it could well lead to their losing money.

Of course, most people getting paid from the illness of others are not the doctors, the nurses, or the pharmacists. In fact, outside of lucrative procedure-based specialties — and there aren’t as many of those as a Top Docs glossy would make you think — most doctors, certainly most of those who deal with chronic medical conditions, have no idea how much treatments and tests they order actually cost.

This is, in fact, not a feature but a bug of the system, and one of its main ones. Most doctors work not for their patients, but for amorphous “health systems” graced with all the charm and efficiency of a lumbering bueracracy. They, in turn, deal not with the patients directly, but rather with medical insurance companies or, worse yet, “benefits managers” who insert themselves as mediators nominally there to simplify the process but instead further increasing its complexity. And presto, you now have a series of matryoshka dolls each doing its part to create the mother of all principal-agent problems.

Should the patients’ perspective be the primary consideration in improving American health-care? Absolutely! But lets not fool ourselves into thinking that the mess we are in is due to doctors’ priorities overwhelming everyone else’s.