I read an earlier book of Eric Topol’s (The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care) and got a lot out of it, although I don’t know to what extent his ideas will come to pass. The Economist reviewed his more recent book, “Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again”.
The Economist reports:
The fear the author harbours [referring to Topol] is that AI will be used to deepen the assembly-line culture of modern medicine. If it confers a “gift of time” on doctors, he argues that this bonus should be used to prolong consultations, rather than simply speeding through them more efficiently.
But then goes on, in true Economist style:
That is a fine idea, but as health swallows an ever-bigger share of national wealth, greater efficiency is exactly what is needed, at least so far as governments and insurers are concerned…. An extra five minutes spent chatting with a patient is costly as well as valuable. The AI revolution will also empower managerial bean-counters, who will increasingly be able to calibrate and appraise every aspect of treatment. The autonomy of the doctor will inevitably be undermined, especially, perhaps, in public-health systems which are duty-bound to trim inessential costs.
Modern medicine — as implied — is already an assembly line culture. And yes, many of us think it will get worse. Staff retention will get worse, too. If you want to see the future of medicine as a career, look at what has happened to school teachers within public systems (or academics in most universities in the UK). Blame it all on poor Max Weber, if you will. Those in charge have very little feel for what ‘doing medicine’ is all about. But there seems to an elision between ‘greater efficiency is needed’ and talking to patients being ‘costly and valuable’. Interesting to note that only the public systems are obliged to trim ‘inessential costs’: Crony Capitalism feasts on the wants rather than the needs.
“There’s a classic medical aphorism,” he recalls. “‘Listen to the patient, they’re telling you the diagnosis.’ Actually, a lot of patients are just telling you a lot of rubbish, and you have to stop them and ask the pertinent questions.”
Jed Mercurio: ‘Facts used to have power. Now stupidity is a virtue’ | The Guardian
The question is when?
Shortage of GPs will never end, health experts say | Society | The Guardian
OK, maybe the subeditor is to blame, but spare me the cartel of health think tanks and their pamphlets. Enticing people into general practice and keeping them there is not rocket science. When I was a junior doctor getting onto the best GP schemes around Newcastle was harder than getting the ‘professorial house-jobs’. Many people like, and want to be, GPs. If general practice is dying , it is in large part because the NHS is killing real general practice.
A few years back I wrote a personal view in the BMJ, arguing that an alternative model for dermatology in the UK would be to use office dermatologists, as in most of the first world. It is likely cheaper and capable of providing better care as long as you consider skin disease worthy of treatment. The feedback was not good or in some instances, even polite. The more considered views were that my suggestion was simply not possible: how would we train these people? Well jump on a ferry or book Ryanair, and look how the rest of Europe does it.
There are some general discussion points:
Two personal examples:
I received an orthopaedic operation under a GA at a major teaching hospital. I was in the my mid 50’s, and previously fit. At the clerking / pre-op assessment by a nurse, my pulse and BP were recorded, and my urine was tested. I was asked : “Are your heart sounds normal and do you have any heart murmurs?” (There was no physical examination). My quip — that how could you trust a dermatologist on such matters — was met with a total lack of recognition. I recounted the story to the anaesthetist as a line was inserted in my arm. I also mentioned, for effect, that they didn’t ask about my dextrocardia….( I achieved the appropriate response — to this untruth). Subsequent conversations with anaesthetists confirmed that their opinions were in keeping with mine, and this “was management” and ‘new innovative ways of
As a second year medical student, with a strong atopic background (skin, lungs, hay fever etc). I came out in what I now know to be widespread urticaria with angioedema. On going to the university health centre, the receptionist triaged me to the nurse, because it was ‘only skin’. I didn’t receive a diagnosis, just an admonition that this was likely due to not washing enough (which may have been incidentally true or false…). A more senior medical student provided me with the right diagnosis over lunch.
The latter example chimed with me, because DR Laurence in his eclectic student textbook of Clinical Pharmacology lampooned the idea that nurses had ‘innate’ understandings of GI pharmacology, a delusion that remained widespread through my early medical career. Now, sadly, similar prescientific reasoning underpins much UK dermatology. The public are not well served.
A long, long time ago, I published papers on p53 and skin (demonstrating p53 upregulation in a UVR wavelength specific way). But germline mutations are something else. The account below is from a US medical student with Li-Fraumeni syndrome (germline p53 mutations)
The changes to my outlook, my psyche, have been much more profound. It’s impossible to describe the unique panic that comes with imagining that any of your cells could decide to rebel at any moment — to propagate, proliferate, “deranged and ambitious,” as my anatomy professor remarked of cancer. It sounds like a paranoid medical student’s fugue-state nightmare. Any cancer at any time: a recurrence, a new primary, a treatment-related malignancy. Some are more likely than others: brain, colon, leukemia, sarcomas. But the improvisation of my cells and their environment is the only limit. And then there are more practical questions: Should I wear sunscreen every day, or is it better just to stay inside?
I recently saw a college friend I hadn’t seen in 10 years and told her about my mutation. Nonmedical people react badly to such news. Medical people probably would, too, but we have rehearsed emotional distance, so our reactions often stay internal, to be unearthed later. “You must be very careful about what you…eat? Drink? What you…put into your body?” she said.
“No,” I said. “There’s no point to that.”
“Oh,” she said, saddened. “This must have changed you. It must really affect the way that you see…the world?”
I nodded, thinking, You have no idea.
I like statistics and spent most of my intercalated degree ‘using’ medical stats (essentially, writing programs on an IBM 360 mainframe to handle a large dataset, that I could then interrogate using the GLIM package from the NAG). Yes, the days of batch processing and punchcards. I found — and still find — statistics remarkably hard.
I am always very wary of people who say they understand statistics. Let me rephrase that. I am very suspicious of non-professional statisticians who claim that they find statistics intuitive. I remember that it was said that even the great Paul Erdos got the Monty Hall problem wrong.
The following is from a recent article in Nature:
What will retiring statistical significance look like? We hope that methods sections and data tabulation will be more detailed and nuanced. Authors will emphasize their estimates and the uncertainty in them — for example, by explicitly discussing the lower and upper limits of their intervals. They will not rely on significance tests. When P values are reported, they will be given with sensible precision (for example, P = 0.021 or P = 0.13) — without adornments such as stars or letters to denote statistical significance and not as binary inequalities (P < 0.05 or P > 0.05). Decisions to interpret or to publish results will not be based on statistical thresholds. People will spend less time with statistical software, and more time thinking.
There is lots of blame to go around here. Bad teaching and bad supervision, are easy targets (too easy). I think there are (at least) three more fundamental problems.
Science has been thought of as a form of ‘reliable knowledge’. This form of words always sounded almost too modest to me, especially when you think how powerful science has been shown to be. But in medicine we are increasingly aware that much modern science is not a basis for honest action at all. Blake’s words were to the effect that ‘every honest man is a prophet’. I once miswrote this in an article I wrote as ‘every honest man is for profit’. Many an error….
A couple of articles from the two different domains of my professional life made me riff on some old memes. The first, was an article in (I think) the Times Higher about the fraud detection software Turnitin. I do not have any firsthand experience with Turnitin (‘turn-it-in’), as most of our exams use either clinical assessments or MCQs. My understanding is that submitted summative work is uploaded to Turnitin and the text compared with the corpus of text already collected. If strong similarities are present, the the work might be fraudulent. A numerical score is provided, but some interpretation is necessary, because in many domains there will be a lot of ‘stock phrases’ that are part of domain expertise, rather than evidence of cheating. How was the ‘corpus’ of text collected? Well, of course, from earlier student texts that had been uploaded.
Universities need to pay for this service, because in the age of massification, lecturers do not recognise the writing style of the students they teach. (BTW, as Graham Gibbs has pointed out, the move from formal supervised exams to course work has been a key driver of grade inflation in UK universities).
I do not know who owns the rights to the texts students submit, nor whether they are able to assert any property rights. There may be other companies out there apart from Turnitin, but you can see easily see that the more data they collect, the more powerful their software becomes. If the substrate is free, then the costs relate to how powerful their algorithms are. It is easy to imagine how this becomes a monopoly. However, if copies of all the submitted texts are kept by universities then collectively it would make it easier for a challenger to enter the field. But network effects will still operate.
The other example comes from medicine rather than education. The FT ran a story about the use of ‘machine learning’ to diagnose retinal scans. Many groups are working on this, but this report was about Moorfields in London. I think I read that as the work was being commercialised, then the hospital would have access to the commercial software free of charge. There are several issues, here.
Although, I have no expert knowledge in this particular domain, I know a little about skin cancer diagnosis using automated methods. First, the clinical material and annotation of clinical material is absolutely rate limiting. Second, once the system is commercialised, the more any subsequent images can be uploaded the better you would imagine the system will become. This of course requires further image annotation, but if we are interesting in improving diagnosis, we should keep enlarging the database if the costs of annotation are acceptable. As in the Turnitin example, the danger is that the monopoly provider becomes ever more powerful. Again, if the image use remains non-exclusive, then it means there are lower barriers to entry.
Not often I spot typos in the New York Review of Books, but here is one that matters. The article dealt with the price of prescription drugs, and there are of course plenty of villains to go around: crony capitalists; advertising spending being larger than research spending —because it works!; and sloppy thinking with regard to IPR and patents. The article on paper read:
In late October, however, just before the congressional elections, Azar declared to reporters that high prices constituted “the greatest possible barrier to patent access.” Democratic strategists gave prescription drug prices high priority in congressional campaigns. Yet leaders in both parties understood that curbing prices would be no easy task. The pharmaceutical industry, which has long deployed one of the most powerful lobbies in Washington, was increasing its representation in the capital.
Yes, should have read patient not patent, although no doubt pharma might not have agreed.
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“It’s not that easy to make money out of emptying anal glands.”
Interesting article in the Economist on what is happening to vet practice in the UK. The march of the corporates and private equity firms buying up vet practices from vets who want to get out (recognise the cry of the professional?). The plans are “rationalisation”, and then resale at a higher multiple of income in a few years time (well, to be correct, EBITDA which is earnings before interest, taxes, depreciation and amortization — Wikipedia has more on it here). This is essentially capital doing what capital always does in a world driven by financialisation. The caveat is that for this
Ponzi scheme speculation to work, there has to be an end buyer. The Economist, as ever fills in any gaps in logic with the usual magic variables:
As private-equity firms support the consolidation of smaller vet practices, the latter’s productivity should improve. Bigger firms can provide better salaries and more support to vets.
Well, that’s all right then — you just insert the bullshit variable. We are told:
Partly this is because young vets have high student debts; many drop out of the profession because the pay is not good enough. They are also demoralised; suicide rates among vets in America are at least twice the national average, and in Britain, almost four times.
The problem is that the money has to come from somewhere: the animal owners; or the vets (as in salaries); and also accommodate the capitalists’ profit. Downward pressures all round I guess — and wait and see what happens to productivity when you are an employee rather than running your own business. I doubt animal ownership is going to get cheaper.
The Susskinds have written elsewhere on the ‘Future of the Professions” but everywhere I look — dentistry, law, medicine — you see some common themes (no sunlit uplands). Lambs to the slaughter.
The parallels between being a school teacher and being a doctor interest me. It is difficult to think of any job more important and potentially more rewarding than teaching schoolchildren. But in the UK (and many others countries) teachers are — with good reason — deeply unhappy. Much, if not most of the dissatisfaction reflects politics, the New Public Management dogmas, and the resulting deprofessionalisation of teaching and teachers. Teaching in many UK schools is hard in a way few appreciate. If you doubt me check out Lucy Kellaway’s articles in the FT, where she has documented the stories of a group of people who went into teaching late in life, after very successful careers in other domains. The graph below tells a story. I wonder if we might imagine similar trends in medicine.
A slow-motion train-wreck: In England, the rate at which teachers are retained in government-funded schools has declined in each of the last seven years: https://t.co/kDuexCJkFk pic.twitter.com/XqpyYxNFTj
— Dylan Wiliam (@dylanwiliam) February 28, 2019
After needles and morphine were deployed in the American civil war, as many as 100,000 veterans were left addicted. In 1895 scientists at Bayer, a German pharmaceutical firm, began selling a strong morphine compound called diamorphine. To market it, they called it “heroin” from the German word meaning heroic.
Article in the Economist on oxycodone dealing with — well not medicine — but business
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In addition to its vulnerability to spoofing, for example, there is its gross inefficiency. “For a child to learn to recognize a cow,” says Hinton, “it’s not like their mother needs to say ‘cow’ 10,000 times”—a number that’s often required for deep-learning systems. Humans generally learn new concepts from just one or two examples.
There is a nice review on Deep Learning in PNAS. The spoofing referred to, is an ‘adversarial patch’ — a patch comprising an image of something else. In the example here, a mini-image of a toaster confuses the AI such that a very large banana is seen as a toaster (the paper is here on arXiv — an image is worth more than a thousand of my words).
Hinton, one of the giants of this field, is of course referring to Plato’s problem: how can we know so much given so little (input). From the dermatology perspective, the humans may still be smarter than the current machines in the real world, but pace Hinton our training sets need not be so large. But they do need to be a lot larger than n=2. The great achievement of the 19th century clinician masters was to be able to create concepts that gathered together disparate appearances, under one ‘concept’. Remember the mantra: there is no one-to-one correspondence between diagnosis and appearance. The second problem with humans is that they need continued (and structured) practice: the natural state of clinical skills is to get worse in the absence of continued reinforcement. Entropy rules.
Will things change? Yes, but radiology will fall first, then ‘lesions’ (tumours), and then rashes — the latter I suspect after entropy has had its way with me.
General practice has been undergoing a quiet revolution in recent years that has had little fanfare: it is now an overwhelmingly part-time profession.
Official figures suggest almost 70% of the workforce work less than full time in general practice – the highest proportion ever.
This is from an interview with Geoffrey Hinton who — to paraphrase Peter Medawar’s comments about Jim Watson — has something to be clever about. The article is worth reading in full, but here are a few snippets.
Now if you send in a paper that has a radically new idea, there’s no chance in hell it will get accepted, because it’s going to get some junior reviewer who doesn’t understand it. Or it’s going to get a senior reviewer who’s trying to review too many papers and doesn’t understand it first time round and assumes it must be nonsense. Anything that makes the brain hurt is not going to get accepted. And I think that’s really bad…
What we should be going for, particularly in the basic science conferences, is radically new ideas. Because we know a radically new idea in the long run is going to be much more influential than a tiny improvement. That’s I think the main downside of the fact that we’ve got this inversion now, where you’ve got a few senior guys and a gazillion young guys.
I would make a few comments:
All has been said before, I know, but no apology will be forthcoming.
This is from an article by Stephen Senn in Nature. He keeps making this point — for the very good reason that people want to pretend there is no problem. But there is.
Personalized medicine aims to match individuals with the therapy that is best suited to them and their condition. Advocates proclaim the potential of this approach to improve treatment outcomes by pointing to statistics about how most drugs — for conditions ranging from arthritis to heartburn — do not work for most people. That might or might not be true, but the statistics are being misinterpreted. There is no reason to think that a drug that shows itself to be marginally effective in a general population is simply in want of an appropriate subpopulation in which it will perform spectacularly.
When you treat patients with chronic diseases such as psoriasis, it quickly becomes clear that there is considerable within person variation is response to treatments. We do not understand what this variation is due to. What we do know however, is that assuming variation in response between people at single time points may be misleading in that we have no measure of within person variance. This is only one of the problems. But hey, precision, personalised.. whatever: it shifts units (as Frank Zappa once said of Michael Jackson).
This is from a book review in the FT of American Overdose. by Chris McGreal — prescription for carnage.
McGreal has written an interview-based book, with especially vivid reporting from West Virginia, the state hit hardest by the epidemic. In the little town of Williamson, or Pilliamson as people came to call it, pharmacies were dispensing opioids at a staggering rate both to locals and to out-of-state visitors, who clogged its streets with their cars but boosted some local businesses as well as city tax revenues.
When the federal authorities belatedly raided one Williamson clinic in late 2009, they found that an individual doctor had written 355,132 opioid prescriptions over the previous seven years — about 1,000 for every inhabitant of the town. Another wrote 118,443 scrips over the same period. Most were handed out for cash fees without the doctors bothering to see their patients. The investigators estimated that the clinic took in $4.6m cash during 2009 and they found banknotes stuffed into safes and cupboards in the doctors’ homes and offices.
At my old university, we were encouraged to explore our subjects and to love what we were studying. Now, at medical school, the emphasis seems to be don’t burnout, focus on not making mistakes, and understand that life is going to be hard, so develop the resilience to cope.
The above is from a letter to this month’s Academic Medicine [83(12) 1745-1884, 2018] written by a graduate student at Warwick medical school (TC Shortland). The title is what caught my eye: “Enjoying, and Not Just Surviving, Medical School”
He goes on:
At Warwick Medical School, staff and students are trying to build a more positive environment. Staff and students have organized art classes, interstaff/ student sports events, and several baking competitions; the last winner featured cupcakes that could be injected with either a salted caramel or raspberry filling. As positive health care workplaces and positive cultures are associated with better patient outcomes,why shouldn’t medical schools try and create such environments for future medical professionals?
I am not against the various suggestions (…well, I am actually), but what I and others are in despair about is how much (?most) medical education has become so dull, tedious, and brutal, rather than humane. When I have spoken to others, some hold similar views: the students put up with it, because they want to be doctors, but they no not enjoy most of it. If they are obliged to attend, they do; but out of choice, many would skip much of what we offer.
Now this is not a new thought or phenomenon. I didn’t enjoy — in fact I actively hated — the preclinical years (aka: the prescientific years) — but I did get a big kick out of the clinical years, and loved my intercalated degree. What made the clinical years work, was that the opportunity for some kind of personal bond with some teaching staff made up for all the despots and dull souls who should have been destined to be gravediggers. And unless somebody has recently discovered something I have missed, scale and intimacy rarely go together.
Of course, what makes matters worse, is that the ennui and anomie will get worse: for many junior doctors, after the initial high of being qualified, their working jobs are miserable. If they get to higher training, things may improve, but not for all.
George Steiner’s comments in a slightly different context are apposite:
“Bad teaching is, almost literally, murderous and, metaphorically, a sin. It diminishes the student, it reduces to gray inanity the subject being presented. It drips into the child’s or the adult’s sensibility that most corrosive of acids, boredom, the marsh gas of ennui.”
The NHS (for this is the fault of the NHS rather thant the universities) is accumulating a massive moral debt, borrowing on the very market it has rigged (because it can!), forgetting that this is like PFI on steroids. It assumes it is too big to fail: I think otherwise.
How did you go bankrupt: slowly and then suddenly.
This is from an editorial in the NEJM, discussing the results of a trial of a synthetic peanut antigen to facilitate tolerance. Prevously the ‘raw’ stuff had been shown to be useful. The synethic version will of course cost a lot, and might be considered IPR created through regulatory arbitrage.
AR101 and other, similar products such as CA002, which is being developed by the Cambridge group, would therefore appear to have a role in initial dose escalation. The potential market for these products is believed to be billions of dollars. It is perhaps salutary to consider that in the study conducted by the Cambridge group, children underwent desensitization with a bag of peanut flour costing peanuts.
Costing penauts: I wish I had said that
Over 40 years ago, I remember lectures on basic demography, and what changes to the population mix of the UK were likely. The late John Grimley Evans was one lecturer, but others went over cognate themes including Klaus Bergmann who pointed out the relevance of increased mobility when considering family and / or social support. ‘Were we prepared to adopt each other people’s grannies?’, stuck in my mind. If you look at the family structures in some working class areas (think parts of Newcastle), and how they have changed, it was obvious what might happen. The sociologist Peter Townsend published studies based in London, highlighting the depth of community support that once existed.
Which is why I get so cross when you come across this as a new problem, as though all these baby boomers (like me) were born yesterday. As though we didn’t know; as though nothing could have been done to prepare for such a change. Remember too, when to study dementia or stroke, or seek funds for such topics was……well futile.
The following is from an article in the FT (How Britain can heal its ailing social care system | Financial Times). Once again the dismal leadership of the UK compares unfavourably with that of some other European countries
The pressure on staff is becoming unbearable. Good social care is about creating relationships. Staff who work for domiciliary care operations like those run by Allied Healthcare must walk into the home of a stranger, reassure them, figure out what is needed, and build trust. That takes maturity, emotional resilience and time. Yet, all too often, the reality is rushed visits from a plethora of different faces.
A few years ago, I met an 89-year-old man who had made a note of every carer who had crossed his threshold in the past year — Meals on Wheels, district nurse, domiciliary care staff. He showed me the list. There were 102 names on it. Some had only come once, then vanished — probably into better paying jobs at a supermarket. That is the stark reality of how little we value our elderly.
I do not have a coherent overview of many of the traditional professions, but I wonder if people will soon say similar things about doctors.[Link]
“The big issue that concerns me at the moment in the English education system is the supply of high-quality teachers. We’ve seen quality issues in recruitment to teaching and our schools are getting increasingly desperate to find decent teachers. The whole workload issue has come to a big head again in England with teachers having very big workloads and their conditions of service is deteriorating a lot recently. We’re seeing a big exodus in teaching and so of course, we need a bigger inflow to maintain the balance.”
Yet despite these innovations and those to come, quantitative risk prediction in medicine has been available for several decades, based on more classical statistical learning from more structured data sources. Despite reports that risk models outperform physicians in prognostic accuracy, application in actual clinical practice remains limited.
It seems unlikely that incremental improvements in discriminative performance of the kind typically demonstrated in machine learning research will ultimately drive a major shift in clinical care. In this Viewpoint, we describe 4 major barriers to useful risk prediction that may not be easily overcome by new methods in machine learning and, in some instances, may be more difficult to overcome in the era of big data.
The hype cycle marches on.
When working in Africa in the 1980s with my good friend Victor Pretorius, I heard a legend about an important tribe in Central Africa, the Masai. The legend claimed that a genius member of the tribe in the nineteenth century or earlier had the idea that cow’s urine was the safest fluid for washing cooking utensils. Compared with the previous practice of using far from clean river water, it avoided the dangers of dysentery and probably saved many lives. This simple and effective public heath practice was cast out by medical missionaries who had quite different ideas, more religious than medical, about what was clean and what was dirty. Neither the original genius, nor the missionaries, knew anything about the epidemiology of water-borne disease. Whether or not there is any substance to this legend, it has stayed in my mind as a metaphor appropriate for many of our problems today. Inventions such as Newcomen’s steam engine, Faraday’s electrical machines, and the idea that fresh urine is a sterile fluid, all came long before their scientific understanding.
James Lovelock, A Rough Ride to the Future. This is like so much of real discovery in clinical medicine, although the academy gets to write the history of how it is supposed to work.
If a doctor expressed concern about a patient showing signs of addiction, Ms Panara was trained to counter those fears by educating them on so-called pseudo-addiction, she says. For example, an addict might turn up at the surgery requesting a fresh batch of pills before their 30-day supply should have run out, claiming they had lost the tablets or accidentally dropped them down the toilet. The advice that she was told to give the doctor was that the patient’s dosing was too low and should be increased, she says.
“The theory of pseudo-addiction was that a patient might exhibit these drug-seeking behaviours, but if their pain were adequately managed by giving a higher dose, then that drug-seeking behaviour would cease,” she says. “Thereby we were building their tolerance, building their physical dependence, and making them an addict.”
I still fail to see why we need drug representatives, nor why they are allowed.
For a baseline life expectancy of 80 years:
Well these are all taken from John Ioannadis’ article in JAMA. He asks : “Could these results possibly be true?”
The great financial crash led to some (but not enough) soul-searching about the state of academic economics and, in turn, the academy. Whole swathes of the modern research university are geared to the production of unreliable knowledge. There is money in it. Without wishing to understate in any way Ioannadis’ major contributions, we have known that there are fundamental methodological flaws in much of observational epidemiology for a long time (for instance see the late Alvan Feinstein’s article in Science). A must read.
(The Challenge of Reforming Nutritional Epidemiologic Research John P. A. Ioannidis, AMA. Published online August 23, 2018. doi:10.1001/jama.2018.11025)
It is not only taxi drivers that are being “uberised” but radiologists, lawyers, contractors and accountants. All these services can now be accessed at cut rates via platforms.
The NHS became such a platform, for good and bad. That is the real lesson here. The tech is an amplifier, but the fundamentals were always about power.
Those who rent seek on biomedical knowledge wish to seek to define the norms of what is foundational. What is foundational for the practice of medicine should be contested more. Anatomy for surgeons is an easy case to make. But for most non-surgeons, the case for much anatomy is far from simple.
In any historical account of the ascent of modern medicine, Versalius looms large. But this Nature article (Sex, religion and a towering treatise on anatomy) intrigues me for a not so obvious reason: the counterpoint between how such knowledge was represented and understood.
Even Vesalius realized that his images could be confusing, and devised an ingenious method to explain them. A letter or number was printed onto the image of each body part, with a separate key. Unfortunately, the characters were often too small to pick out against the swirling background….
Faced by such challenges, many medics might have given up on the images. Indeed, when we reconstructed what early modern readers and scholars found fascinating about the Fabrica, it was evidently the text. The clear majority of sixteenth- and seventeenth-century readers who annotated the book focused on that and left no traces of having engaged with the illustrations. Sixteenth-century reviews of the Fabrica confirm this impression, because they tended to discuss only the text.
This is no surprise. The Fabrica’s scholarly readership was trained in the traditions of Renaissance humanism, which put a strong emphasis on textual analysis. Even if they found it difficult to interpret visual information, medical practitioners were expert at making sense of long Latin texts.
Davidson had had enough. “I wasn’t even making 6 figures, and I was killing myself,” she recalled.
“Frustrated, she googled “ideal practice” one sleepless night and came across Atlas MD in Wichita, Kansas. That practice does not accept insurance, although patients still need to have insurance to cover health care beyond the scope of primary care. Instead of co-payments and deductibles, Atlas MD patients pay a monthly “membership fee” that covers all of the primary care their physician provides. But more importantly, this retainer guarantees unhurried, same-day appointments and round-the-clock accessibility to their physician, who would get to know their story “inside and out,” thanks to having to care for only around 500 patients.”
The most interesting thing in this article is the lengths the opponents go to to oppose such a change:
“For now, said Weisbart, chair of the Missouri chapter of Physicians for a National Health Program, there’s no evidence to support the argument that DPC [the model describe here], by allowing physicians to spend more time with patients, can prevent expensive downstream medical problems. “If they could prove it, I’d be one of their advocates,” he said, adding that he understands the attraction of DPC for physicians. “They can see a third or a quarter of the number of patients (as fee-for-service practices) and preserve their income.”
“Weisbart remains skeptical, though. Direct primary care practices might attract a different population of patients. The only way to compare how well the 2 models improve health and cut costs would be to conduct a trial that randomly assigned patients to DPC or fee-for-service practices. But, Weisbart added, such a trial would be difficult if not impossible to conduct. For one, it’s unlikely that a representative sample of US patients would agree to enroll in a study in which they were randomly assigned to a primary care physician. “And,” he added, “it would have to be large to show meaningful impact, which means the study would be expensive.”
Polling undertaken for the NHS recruitment campaign found that many people had an outdated view of nursing. It suggested most saw nurses primarily as “caring”, with far fewer regarding them as “leaders” or “innovators”.
Apparently this is not approved of. My mother would be turning over in her grave.
Did the NHS save your life, or did Doctors and Nurses save your life?
It’s an earnest question. A comment on an excellent FT piece: “Is Britain loving the NHS to death?”
I posted this awhile back, but it still makes me smile. I wrote:
Well my knowledge of Neanderthals is rather limited to the work showing that some of them would likely had red hair. But now a reviewer (Clive Gamble) in Nature of a book on Neanderthals states that
Wynn and Coolidge conclude that today, Neanderthals would be commercial fishermen or mechanics, based on their enormous strength and ability to learn the motor procedures needed. Their capacity for empathy might even have made them competent physicians, the authors say, although a lack of mathematical ability means that they would never have been able to graduate from medical school. Neanderthals would also make excellent army grunts, with their high levels of pain tolerance, and would be good tacticians in small combat units. They would never rewrite the tactical manual — although tearing it up, however thick, would not be a problem.
“It’s quite obvious that we should stop training radiologists,” said Geoffrey Hinton, an AI luminary, in 2016. In November Andrew Ng, another superstar researcher, when discussing AI’s ability to diagnose pneumonia from chest X-rays, wondered whether “radiologists should be worried about their jobs”. Given how widely applicable machine learning seems to be, such pronouncements are bound to alarm white-collar workers, from engineers to lawyers.
The Economist’s view is (rightly) more nuanced than Hinton’s statement on this topic might suggest, but this is real. For my own branch of clinical medicine, too. The interesting thing for those concerned with medical education is whether we will see the equivalent of the Osborne effect (and I don’t mean that Osborne effect).