The Black Liszt

Category: Healthcare

  • The forbidden question: What caused the obesity epidemic?

    There is an obesity problem. Everyone knows it. Public health authorities proclaim it. Over half the population in the US is now obese. The consequences of being obese in terms of health are serious. Solutions are proposed, but they don’t seem to work. The question that’s almost never asked, the answer to which would help us understand AND FIX the problem, is pure common sense: what started the epidemic? What changed to cause the steady rise of overweight and obese people?

    The reason no one wants to ask the question is because the most probable answer is something our major institutions, Experts and Authorities don’t want us to know: Their nutrition recommendations, widely promoted and visible on most food labels that you buy, are based on bad, corrupted science.

    We now know how and why the science was wrong. After much study and careful trials, we know what's right. But because of the refusal of the authorities to admit and correct their error, millions of people continue to suffer and die of diseases they would not have if our Medical Health Elites would suck it up, admit error, and fix it.

    There is an epidemic of obesity

    The epidemic. Well known, accepted. Here's the FDA:

    111

    Here's the CDC:

    Obesity is a serious chronic disease, and the prevalence of obesity continues to increase in the United States. Obesity is common, serious, and costly. This epidemic is putting a strain on American families, affecting overall health, health care costs, productivity, and military readiness.

    Is it under control? The CDC again:

    From 1999 –2000 through 2017 –2018, US obesity prevalence increased from 30.5% to 42.4%. During the same time, the prevalence of severe obesity increased from 4.7% to 9.2%.

    What's bad about being obese?

    According to the CDC, here are some of the consequences of being obese:

    11

    What are the medical costs resulting from obesity?

    A highly detailed study was published in 2021 going into depth to determine the direct medical costs of obesity.

    RESULTS: Adults with obesity in the United States compared with those with normal weight experienced higher annual medical care costs by $2,505 or 100%, with costs increasing significantly with class of obesity, from 68.4% for class 1 to 233.6% for class 3. The effects of obesity raised costs in every category of care: inpatient, outpatient, and prescription drugs. …  In 2016, the aggregate medical cost due to obesity among adults in the United States was $260.6 billion.

    In other words, obese people have more than double the medical care costs compared to those who are not obese. More important, the obese people themselves suffer the poor health resulting from their condition!

    How are we told to prevent and/or fix it?

    From the CDC:

    Obesity is a complex health issue resulting from a combination of causes and individual factors such as behavior and genetics.

    Healthy behaviors include regular physical activity and healthy eating. Balancing the number of calories consumed from foods and beverages with the number of calories the body uses for activity plays a role in preventing excess weight gain.

    A healthy diet pattern follows the Dietary Guidelines for Americans which emphasizes eating whole grains, fruits, vegetables, lean protein, low-fat and fat-free dairy products, and drinking water.

    In other words, exercise more, eat less, and follow the official diet guidelines which emphasize avoiding fat in meat and dairy.

    The origins of the obesity epidemic

    Did the obesity epidemic appear out of nowhere, for no reason? Nope. The key to understanding and responding to any epidemic is to trace its origins to the time and place of its start. Only then can you understand the problem and often get good ideas about how to mitigate the epidemic and prevent similar ones from getting started.

    Look at this chart from the CDC:

    Estat-adults-fig

    A sharp upwards turn in Obesity and Severe Obesity took place in 1976-1980 and has continued rising. From the tables in the document from which this chart was taken, Obesity was about 14% and has risen to 43%, while Severe Obesity was about 1% and has risen to over 9%. That's about 3X and 9X increases. Total Obesity is now over 50% of the population! During this period the Overweight share has remained about the same (about 32%), which means that a large number of people "graduated" to higher levels of weight, probably many normals becoming Overweight while as many Overweights became Obese.

    What happened when the "hockey stick" upwards trend in obesity started? It turns out something big happened, with lots of public attention. According to the government website on the history of nutritional guidelines:

    A turning point for nutrition guidance in the U.S. began in the 1970s with the Senate Select Committee on Nutrition and Human Needs….

    In 1977, after years of discussion, scientific review, and debate, the U.S. Senate Select Committee on Nutrition and Human Needs, led by Senator George McGovern, released Dietary Goals for the United States. …

    The recommendations included:

    Increase the consumption of complex carbohydrates and “naturally occurring” sugars…

    Reduce overall fat consumption…

    Reduce saturated fat consumption to account for about 10 percent of total energy intake…

    The widely publicized recommendations were followed up by the first in the series of official expert-approved documents:

    In February 1980, USDA and HHS collaboratively issued Nutrition and Your Health: Dietary Guidelines for Americans,

    It's important to note that the focus was NOT on obesity. It was on diet-related health, with a particular focus on heart disease. The consensus of Expert opinion at the time was that eating saturated fat causes heart disease. In an effort to reduce heart disease, the authorities started the drum-beat of "Stay healthy! Eat less saturated Fat!"

    Obesity took off when we obeyed the Experts

    The new dietary advice was shouted from the hill tops. It was pushed by government agencies. It was endorsed by every major health institution, and pushed by nutritionists and doctors everywhere. It was emblazoned on food packaging by law, each package stating how much of the evil, heart-killing saturated fat was in each serving, and how much of your "daily allowance" it used up.

    The food that was offered in grocery stores and restaurants changed to reflect the "scientific" consensus. Bacon was bad. If you had to eat meat (even though you shouldn't), you should eat lean (no fat) meat. All these things are still what we see!

    Here is a study based on the US National Health and Nutrition Examination Survey (NHANES) that demonstrates the strong linkage between the diet recommendations and the growth of obesity.

    From a valuable study on obesity (behind a paywall):

    When we put together the following…

    1) Obesity is not a simplistic imbalance of energy in and energy out, but a far more complex matter of how, biochemically, the body can store or utilize fat. Carbohydrate is the best macronutrient to facilitate fat storage and prevent fat utilization.

    2) Fat/protein calories have jobs to do within the body – they can be used for basal metabolic repair and maintenance. Carbohydrate is for energy alone; it needs to be burned as fuel or it will be stored as fat.

    … carbohydrates can be seen as uniquely suited to weight gain and uniquely unsuited to weight loss. The macronutrient that we have been advising people to eat more of is the very macronutrient that enables fat to be stored and disables fat from being utilized.

    Increasingly people ate what they were told to eat. Young people grew up eating in the new style, with vastly more packaged foods, sugar and carbohydrates than earlier generations. No surprise, they got fat early in life, and stayed fat.

    Marty Makary MD, surgeon and Professor at Johns Hopkins, Makary
    treats this from a different angle in his recent book.

    Dr. Dariush Mozaffarian, dean of Tufts University’s Friedman School of Nutrition—the nation’s leading nutrition school … recently wrote in the Journal of the American Medical Association, “We really need to sing it from the rooftops that the low-fat diet concept is dead, there are no health benefits to it.” As a gastrointestinal surgeon and advocate for healthful foods, I’m well aware how this low-fat teaching is based on the medical establishment’s embarrassing, outdated theory that saturated fat causes heart disease. A landmark 2016 article in the Journal of the American Medical Association found that the true science was actually being suppressed by the food industry. Highly respected medical experts like my former Johns Hopkins colleague Dr. Peter Attia are now correcting the medical establishment’s sloppy teachings. He and many other lipidologists know that the low-fat bandwagon has damaged public health. It was driven by an unscientific agenda advanced by the American Heart Association and the food industry, which sponsored the misleading food pyramid. These establishment forces spent decades promoting addictive, high-carbohydrate processed foods because the low-fat foods they endorsed require more carbohydrates to retain flavor. That 40-year trend perfectly parallels our obesity epidemic. Medical leaders like Dr. Attia have been trying to turn this aircraft carrier around, but it’s been a challenge. Despite the science, the dogma remains pervasive. In hospitals today, the first thing we do to patients when they come out of surgery, exhausted and bleary-eyed, is to hand them a can of high-sugar soda. Menus given to hospitalized patients promote low-fat options with a heart next to those menu items. And when physicians order food for patients in electronic health records, there’s a checkbox for us to order the “cardiac diet,” which hospitals define as a low-fat diet. Despite science showing that natural fats pose no increased risk of heart disease and that excess sugar is the real dietary threat to health, my hospital still hands every patient a pamphlet recommending the “low-fat diet” when they’re discharged from the cardiac surgery unit, just as we have been doing for nearly a half century. But nowhere is that now debunked low-fat recommendation propagated as much as in wellness programs.

    For more study

    The experts are clear on this subject. You already know this, but here are highlights of their views on fat and on cholesterol. Here is background on how saturated and cholesterol became menaces. Here is why you should eat lots of saturated fat and why should not take drugs to lower your cholesterol.

    With the billion-dollar-revenue American Heart Association continuing to villanize saturated fat, this insanity is unlikely to stop soon.

    Before all this nonsense began…

    We had a sensible approach to obesity:

    1

    Conclusion

    The cause of the obesity epidemic is clear. No one talks about it because the people in charge refuse to admit their role in causing it. As the evidence from RCT's continues to pile up, careful reading shows that the emphatic language about saturated fat has lightened up a bit, but we're not even close to the equivalent of acknowledging, for example, that smoking cigarettes is bad for you. We should be shouting "eat lots of natural saturated fat, the kind in meat, milk, cheese and eggs." We're not there yet. Educated people can nonetheless make their own decisions and do just that — and improve their health as a result.

     

  • The Facts are Clear: Don’t Take Cholesterol-lowering Drugs

    I have described the background and evidence of the diet-heart fiasco — the hypothesis-turned-fake-fact that you shouldn't eat saturated fat because it raises your "bad" LDL cholesterol, which causes heart disease. Not only is it wrong — eating saturated fat is positively good for you!

    This deadly farce has generated a medical effort to lower the cholesterol of patients in order to keep them healthy. There have been over a trillion dollars in sales for cholesterol-lowering statin drugs so far.The entire medical establishment has supported this as a way to prevent heart disease.There's just one little problem, now proved by extensive, objective real-world evidence and biochemical understanding: Cholesterol, including the "bad" LDL, is NOT a cause of heart disease. Even indirectly. Lowering LDL via diet change or statins does NOT prevent heart disease. So don't avoid saturated fats or take statins!

    Here's the kicker: higher cholesterol is associated pretty strongly with living longer, particularly in women! And the side effects of the drugs are widespread and serious!

    Basic facts

    Let's start with a few facts:

    • Eating fat will NOT make you fat. Eating sugar will make you fat.
    • The human brain is 70% fat.
    • 25% of all cholesterol in the body is found in the brain.
    • All cells in your body are made of fat and cholesterol.
    • LDL is not cholesterol! HDL isn't either! They are proteins that carry cholesterol and fat-soluble vitamins. Lowering it lowers your vitamins.

    To get the big picture about the diet-heart hypothesis (the reason why you're supposed to take statins in order to lower your cholesterol in order to prevent heart disease), see this post on the Whole Milk Disaster. For more detail, see the post on why you should eat lots of saturated fat.

    To get lots of detail, read this extensive review of Cholesterol Con and this extensive review of The Clot Thickens — and by all means dive into the books. Here is an excellent summary written by an MD explaining the situation and the alternative thrombogenic hypothesis. Here is a recent paper in a peer-reviewed journal reviewing to what extent blood cholesterol causes heart disease.

    The Bogus Hyposthesis

    How did thing get started? Stupidity mixed with remarkably bad science. Here is a brief summary of a PhD thesis examination of the build-up to the Cholesterol-is-bad theory:

    The cholesterol hypothesis originated in the early years of the twentieth century. While performing autopsies, Russian pathologists noticed build-up in the arteries of deceased people. The build-up contained cholesterol. They hypothesised that the cholesterol had caused the build-up and blocked the artery leading to a sudden death (the term “heart attacks” was not much used before the end of World War II).

    An alternative hypothesis would be that cholesterol is a substance made by the body for the repair and health of every cell and thus something else had damaged the artery wall and cholesterol had gone to repair that damage. This is the hypothesis that has the memorable analogy – fire fighters are always found at the scene of a fire. They didn’t cause the fire – they went there to fix it. Ditto with cholesterol. The alternative hypothesis did not occur to the pathologists by all accounts.

    The pathologists undertook experiments in rabbits to feed them cholesterol to see if they ‘clogged up’ and sure enough they did. However, rabbits are herbivores and cholesterol is only found in animal foods and thus it’s not surprising that feeding animal foods to natural vegetarians clogged them up. When rabbits were fed purified cholesterol in their normal (plant-based) food, they didn’t clog up. That should have been a red flag to the hypothesis, but it wasn’t.

    Then Ancel Keys got involved, and the bad idea became gospel.

    Population studies

    Before taking drugs like statins to reduce cholesterol, doesn't it make sense to see if people with lower cholesterol lead longer lives? The question has been examined. Short answer: people with higher cholesterol live longer. 

    Here is data from a giant WHO database of cholesterol from over 190 countries:

    Men

    More cholesterol = longer life for men, a strong correlation. Even more so for women, who on average have HIGHER cholesterol than men:

    Women

    When you dive into specific countries and history, the effect is even more striking. Check out the Japanese paradox

    To illustrate the Japanese paradox, he reported that, over the past 50 years, the average cholesterol level has risen in Japan from 3.9 mmol/l to 5.2 mmol/l. Deaths from heart disease have fallen by 60% and rates of stroke have fallen seven-fold in parallel. A 25% rise in cholesterol levels has thus accompanied a six-fold drop in death from CVD (Ref 6).

    And the strange things going on in Europe led by those cheese-loving French:

    The French paradox is well known – the French have the lowest cardiovascular Disease (CVD) rate in Europe and higher than average cholesterol levels (and the highest saturated fat consumption in Europe, by the way). Russia has over 10 times the French death rate from heart disease, despite having substantially lower cholesterol levels than France. Switzerland has one of the lowest death rates from heart disease in Europe with one of the highest cholesterol levels.

    Hard-core RCT's (Randomized Controlled Trials)

    RCT's are the gold standard of medical science and much else. You divide a population into a control group for which nothing changes and a test group, which is subjected to the treatment you want to test. It's hard to do this with anything like diet! But it has been done in controlled settings a few times at good scale. The results of the RCT's that have been done did NOT support the fat-cholesterol-heart-disease theory and so were kept hidden. But in a couple cases they've been recovered, studied and published.

    A group of highly qualified investigators has uncovered two such studies and published the results in the British Medical Journal in 2016: "Re-evaluation of the traditional diet-heart hypothesis: analysis of recovered data from Minnesota Coronary Experiment (1968-73)." They summarize the results of their earlier study:

    Our recovery and 2013 publication of previously unpublished data from the Sydney Diet Heart Study (SDHS, 1966-73) belatedly showed that replacement of saturated fat with vegetable oil rich in linoleic acid significantly increased the risks of death from coronary heart disease and all causes, despite lowering serum cholesterol.14

    Lower cholesterol meant greater risk of death. Clear.

    The Minnesota study was pretty unique:

    The Minnesota Coronary Experiment (MCE), a randomized controlled trial conducted in 1968-73, was the largest (n=9570) and perhaps the most rigorously executed dietary trial of cholesterol lowering by replacement of saturated fat with vegetable oil rich in linoleic acid. The MCE is the only such randomized controlled trial to complete postmortem assessment of coronary, aortic, and cerebrovascular atherosclerosis grade and infarct status and the only one to test the clinical effects of increasing linoleic acid in large prespecified subgroups of women and older adults.

    Moreover, it was sponsored by the most famous proponent of the diet-heart hypothesis: Ancel Keys. So what happened? Here's a brief summary from an article in the Chicago Tribune after the 2016 BMJ study was published:

    Second, and perhaps more important, these iconoclastic findings went unpublished until 1989 and then saw the light of day only in an obscure medical journal with few readers. One of the principal investigators told a science journalist that he sat on the results for 16 years and didn't publish because "we were just so disappointed in the way they turned out."

    From the BMJ 2016 paper:

    The traditional diet heart hypothesis predicts that participants with greater reduction in serum cholesterol would have a lower risk of death (fig 1⇑, line B). MCE participants with greater reduction in serum cholesterol, however, had a higher rather than a lower risk of death.

    …

    The number, proportion, and probability of death increased as serum cholesterol decreased

    Wowza. The "better" (lower) your blood cholesterol levels, the more likely you were to die. In fact, "For each 1% fall in cholesterol there was a 1% increase in the risk of death."

    Problems with Statins

    Not only do statins not work to lengthen lives, taking them is a bad idea because of their side effects. This is a starting place. For example, check the side effects of a leading statin:

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    Good effects vs. side effects

    We know for a fact that lowering your blood cholesterol is a bad idea. We know the drugs that do it have side effects. It's natural to think that the drugs normally do their thing and in rare cases there are side effects. Often, this is far from the truth. Here are excerpts from an article that explains the basic medical math concept of NNT

    Most people have never heard the term NNT, which stands for Number Needed to Treat, or to put it another way, the number of people who need to take a drug for one person to see a noticeable benefit. It's a bit of a counterintuitive concept for people outside medicine, since most people probably assume the NNT for all drugs is 1, right? If I'm getting this drug, it must be because it is going to help me. Well, wrong.

    What about the side effects of statins?

    Many people who take the drug develop chronic aches and pains. The drug also causes noticeable cognitive impairment in a proportion of those taking it, and some even end up being diagnosed with dementia – how big the risk is unfortunately isn't known, because proper studies haven't been carried out that could answer that question. Additionally, the drug causes blood sugar levels to rise, resulting in type 2 diabetes in around 2% of those taking the drug – it is in fact one of the most common causes of type 2 diabetes.

    NNT applied to statins:

    Well, if you've already had a heart attack, i.e. you've already been established to be at high risk for heart attacks, then the NNT over five years of treatment is 40. In other words, 39 of 40 people taking a high dose statin for five years after a heart attack won't experience any noticeable benefit. But even if they're not the lucky one in 40 who gets to avoid a heart attack, they'll still have to contend with the side effects.

    How many patients are told about NNT? If you haven't had a heart attack, the NNT is vastly greater than 40, and yet statins are prescribed when cholesterol is "too high" no matter what. Many of the side effects happen in 10% of the cases, which is four times greater than the number of people who are "helped." Doctors who do this are indeed members of the "helping profession;" the question is, who exactly are they helping?

    Here, here and here are more details about NNT for statin use.

    Conclusion

    If you value science, you should not worry about lowering your cholesterol. If you value your life and health, you should be happy to have high cholesterol. Likewise, you should avoid taking cholesterol-lowering drugs because in the end they hurt you more than they help you. If you're worried about pharma companies losing profits, it's a much better idea to just send them a monthly check — forget about their drugs!

     

  • The Facts are Clear: Eat Lots of Saturated Fat

    The experts and authoritative institutions are clear: you should eat a low-fat diet and take drugs to reduce your blood LDL cholesterol to safe levels in order to make your heart healthy.  Here is their advice about saturated fat and about blood cholesterol. The capital-E Experts are wrong. They were wrong from the beginning. There was never any valid evidence in favor their views, in spite of what you might read. The quantitative and biochemical evidence is now overwhelming.  Here is my summary of the situation. In this post I’ll cover more of the evidence.

    Origins and growth of the saturated fat – cholesterol – heart hypothesis

    How did such a bogus theory get started? An experiment with intriguing results was one start. Here's a summary:

    The hypothesis harks back to the early part of the twentieth century, when a Russian researcher named Nikolai Anitschkow fed a cholesterol [animal fat] rich diet to rabbits and found that they developed atherosclerosis (hardening of the arteries, the process which in the long run leads to cardiovascular disease). … Rabbits, being herbivores, normally have very little cholesterol in their diets, while humans, being omnivores, generally consume quite a bit of cholesterol. Regardless, the data was suggestive, and led to the hypothesis being formulated.

    A paper titled “How the Ideology of Low Fat Conquered America” was published in the Journal of the History of Medicine and Allied Sciences in 2008. Here is the abstract:

    This article examines how faith in science led physicians and patients to embrace the low-fat diet for heart disease prevention and weight loss. Scientific studies dating from the late 1940s showed a correlation between high-fat diets and high-cholesterol levels, suggesting that a low-fat diet might prevent heart disease in high-risk patients. By the 1960s, the low-fat diet began to be touted not just for high-risk heart patients, but as good for the whole nation. After 1980, the low-fat approach became an overarching ideology, promoted by physicians, the federal government, the food industry, and the popular health media. Many Americans subscribed to the ideology of low fat, even though there was no clear evidence that it prevented heart disease or promoted weight loss. Ironically, in the same decades that the low-fat approach assumed ideological status, Americans in the aggregate were getting fatter, leading to what many called an obesity epidemic. Nevertheless, the low-fat ideology had such a hold on Americans that skeptics were dismissed. Only recently has evidence of a paradigm shift begun to surface, first with the challenge of the low-carbohydrate diet and then, with a more moderate approach, reflecting recent scientific knowledge about fats.

    The early chapters of The Big Fat Surprise book provide a good summary with details of the rise to dominance of the low-fat & cholesterol-is-bad theory.

    Strong Data Showing that Saturated Fat is Good

    There were problems with the diet-heart hypothesis from the beginning.

    The first chapters of The Big Fat Surprise have summaries of studies that were made on peoples around the world who subsisted almost exclusively by eating animals and/or dairy, all of them strongly preferring fatty organs over lean muscle.

    A Harvard-trained anthropologist lived with the Inuit in the Canadian Arctic in 1906, living exactly like his hosts, eating almost exclusively meat and fish. “In 1928, he and a colleague, under the supervision of a highly qualified team of scientists, checked into Bellevue Hospital  … to eat nothing but meat and water for an entire year.” “Half a dozen papers published by the scientific oversight committee that scientists could find nothing wrong with them.”

    George Mann, a doctor and professor of biochemistry, took a mobile lab to Kenya with a team from Vanderbilt University in the 1960’s to study the Masai. They ate nothing but animal parts and milk. Their blood pressure and body weight were 50% lower than Americans. Electrocardiograms of 400 men showed no evidence of heart disease, and autopsies of 50 showed only one case of heart disease.

    Similar studies and results came from people in northern India living mostly on dairy products, and native Americans in the southwest. There were many such studies, all of them showing that the native peoples, eating mostly saturated fat, were not only heart-healthy, but free of most other modern afflictions such as cancer, diabetes, obesity and the rest.

    Of course the question was raised of other factors that might lead to these results. The questions have been answered by intensive studies. For example, some formerly meat-eating Masai moved to the city and lost their health. For example, Inuit who changed their diet to include lots of carbohydrates supplied by government were studied by doctors who determined they lost their health.

    From the book:

    In 1964, F. W. Lowenstein, a medical officer for the World Health Organization in Geneva, collected every study he could find on men who were virtually free of heart disease, and concluded that their fat consumption varied wildly, from about 7 percent of total calories among Benedictine monks and the Japanese to 65 percent among Somalis. And there was every number in between: Mayans checked in with 26 percent, Filipinos with 14 percent, the Gabonese with 18 percent, and black slaves on the island of St. Kitts with 17 percent. The type of fat also varied dramatically, from cottonseed and sesame oil (vegetable fats) eaten by Buddhist monks to the gallons of milk (all animal fat) drunk by the Masai. Most other groups ate some kind of mixture of vegetable and animal fats. One could only conclude from these findings that any link between dietary fat and heart disease was, at best, weak and unreliable.

    One of the foundational studies in the field is the Framingham Heart Study, started in 1948 and still going on.

    In 1961, after six years of study, the Framingham investigators announced their first big discovery: that high total cholesterol was a reliable predictor for heart disease.

    This cemented things. Anything that raised cholesterol would lead to heart disease. The trouble came thirty years later, after many of the participants in the study had died, which made it possible to see the real relationship between cholesterol and mortality due to heart disease. Cholesterol did NOT predict heart disease!

    The Framingham data also failed to show that lowering one's cholesterol over time was even remotely helpful. In the thirty-year follow-up report, the authors state, "For each 1% mg/dL drop of cholesterol there was an 11% increase in coronary and total mortality."

    Only in 1992 did William P. Castelli, a Framingham study leader, announce, in an editorial in the Archives of Internal Medicine:

    In Framingham, Mass, the more saturated fat one ate … the lower the person's serum cholesterol … and [they] weighed the least.

    Game over! No wonder they've kept it quiet. And not just about heart health — about weight loss too!

    Here is an excellent article with references to and quotes from many journals. Here is the introduction:

    Many large, government-funded RCTs (randomized, controlled clinical trials, which are considered the ‘gold-standard’ of science) were conducted all over the world in the 1960s and 70s in order to test the diet-heart hypothesis. Some 75,000 people were tested, in trials that on the whole followed subjects long enough to obtain “hard endpoints,” which are considered more definitive than LDL-C, HDL-C, etc. However, the results of these trials did not support the hypothesis, and consequently, they were largely ignored or dismissed for decades—until scientists began rediscovering them in the late 2000s. The first comprehensive review of these trials was published in 2010 and since then, there have been nearly 20 such review papers, by separate teams of scientists all over the world.

    Far from believing that saturated fat causes heart disease, we can be quite certain that it's positively healthy on multiple dimensions to eat it — it's people who don't eat enough saturated fat who end up overweight and sickly!

    Sadly, there are still Pompous Authorities who assure us with fancy-sounding studies that we really should avoid eating fat. This study from 2021 dives into just such a fake study — a RCT (random controlled trial) study — that purported to show that eating fat remains a bad idea. Wrong. Here's the summary:

    Hiding unhealthy heart outcomes in a low-fat diet trial: the Women’s Health Initiative Randomized Controlled Dietary Modification Trial finds that postmenopausal women with established coronary heart disease were at increased risk of an adverse outcome if they consumed a low-fat ‘heart-healthy’ diet.

    These books by Dr. Malcolm Kendrick dive in more deeply and are moreover a pleasure to read. Among other things, The Clot Thickens explains the underlying mechanisms of arteriosclerosis (blood clots, heart disease) and what actually causes them.

    Here are several articles with evidence from many scientists on the subject of saturated fat.

    Latest Results

    The evidence continues to pour out — not that the vast majority of "professionals" change their tune about what constitutes a healthy diet. Here is a new paper published by Oxford written by cardiologists.

    1

    The authors asked exactly the right question:

    Cardiovascular disease (CVD) is the leading global cause of death. For decades, the conventional wisdom has been that the consumption of saturated fat (SFA) undermines cardiovascular health, clogs the arteries, increases risk of CVD and leads to heart attacks. It is timely to investigate whether this claim holds up to scientific scrutiny.

    They found and went through more than ten years of recent published studies, p through 2021. Here is their conclusion:

    Findings from the studies reviewed in this paper indicate that the consumption of SFA is not significantly associated with CVD risk, events or mortality. Based on the scientific evidence, there is no scientific ground to demonize SFA as a cause of CVD. SFA naturally occurring in nutrient-dense foods can be safely included in the diet.

    Here is a summary in a journal of the history and latest research on the subject, focused on the national nutrition guidelines, which maddeningly fail to reflect the facts about this subject.

    What more needs to be said?

     Conclusion

    This is an incredibly important issue regarding the health of people. It's also an in-progress example of the difficulty of shifting a paradigm, even when the evidence against the dominant paradigm (avoid eating saturated fat, use drugs to keep your cholesterol low) is overwhelming. Could it be possible that billions of dollars a year of statins and related cholesterol-lowering drug sales has something to do with it? Then again, when was the last time you heard a prestigious Expert or institution say "Sorry, we were wrong, we'll try hard not to blow it again; we won't blame you if you never trust us again."

  • Barriers to Software Innovation: Radiology 2

    Value-creating innovations are rarely the result of a bright new A-HA moment, though an individual may have that experience. A shocking number of innovations are completely predictable, partly because they've already been implemented — but put back in the vast reservoir of ready-to-use innovations, or implemented in some other domain. This fact is one of the most important patterns of software evolution.

    Sometimes the innovation is created, proven and fully deployed in production, like the optimization method Linear Programming, which I describe here. In other cases, like this one, the innovation is built as a functioning prototype with the cooperation of major industry players — but not deployed.

    In a prior post I described how I went to the San Francisco bay area in the summer of 1971 to help a couple of my friends implement a system that would generate a radiology report from a marked-up mark-sense form. We got the system working to the point where it could generate a customizable radiologist's report from one of the form types, the one for the hand. Making it work for all the types of reports would have been easy — we demonstrated working software, and wrote a comprehensive proposal for building the whole system. It was never built.

    True to the nature of software evolution, the idea probably pounded on many doors over the years, always ignored. But about 10 years ago, a pioneering radiologist in Cleveland came up with essentially the same idea. Of course, instead of paper mark-sense forms, the radiologist would click on choices on a screen, and would usually look at the medical image on the computer screen. This enabled the further benefit of reducing the work, and letting doctors easily read images that were taken in various physical locations. Tests showed that doctors using the system were much more productive than those who worked in the traditional way. Finally, they decided that mimicking the radiologist's normal writing style was a negative, and that the field would be improved by having all reports follow a similar format, with content expressed in the same order in the same way. This was actually a detail, because the core semantic observations would be recorded and stored in any case, enabling a leap to a new level of data analytics. It also, by the way, made the report generation system much easier to build than the working prototype we had built decades earlier, which enabled easy customization to mimic each radiologist's style of writing.

    The founding radiologist was a doctor, of course, and knew little about software. He did his best to get the software written, got funding, and got the system working. Professional management was hired. My VC group made an investment. Many people saw the potential of the system; it was adopted by a famous hospital system in 2015. But in the end, the company was sold off in pieces.

    Nearly 50 years after software was first written that was able to produce medical imaging diagnostic reports quickly and reliably while also populating a coded EMR to enable analytics, the system is sitting in the vast reservoir of un-deployed innovations. It can be built. It saves time. It auto-populates an EMR.

    Many people have opined on why this particular venture failed to flourish. It's a classic example of the realities of software innovation and evolution. The reasons for failure were inside the company and outside the company. For the inside reasons, let's just say that the work methods of experienced, professional managers in the software development industry lead to consistently expensive, mediocre results. Nonetheless, the software worked and was in wide production use, delivering the advertised benefits. For the outside reasons, let's say that, well, the conditions weren't quite right just yet for such a transformation of the way doctors work to take place.

    The conditions that weren't right just yet for this and uncountable other innovations add up to the walls, high and thick, behind which a reservoir of transformative innovation and "new" software awaits favorable conditions. In other words, the reservoir of innovations wait for that magic combination of software builders who actually know how to build software that works, with a business/social nexus that accepts the innovation instead of the standard no-holds-barred resistance.

    Corporations promote what they call innovation. They are busily hiring Chief Innovation Officers, creating innovation incubation centers, hanging posters about the wonders of innovation, etc. etc. They continue to believe the standard-issue garbage that innovation needs to be invented fresh and new.

    The reality is that there is a vast reservoir of in-old-vations that are proven and frequently deployed in other domains. All that's needed is to select and implement the best ones. HOWEVER, a Chief Innovation Officer is STILL needed — to perform the necessary function of identifying and breaking down the human and institutional barriers that have prevented the in-old-vations from being deployed, in many cases preventing roll-out for — literally! — decades!!

  • Barriers to Software Innovation: Radiology 1

    There is a general impression that software innovation in one of its many forms e.g. “Digital Transformation” is marching ahead full steam. There are courses, consultants, posters hanging in common spaces and newly-created Chief Innovation Officer positions.  What’s new? What’s the latest in software?

    The reality is that there are large reservoirs of proven, tested and working software innovations ready to be rolled out, but these riches are kept behind the solid walls of dams, with armies of alert guardians ready to leap in and patch any holes through which these valuable innovations may start leaking into practice. Almost no one is aware of the treasure-trove of proven innovations kept dammed up from being piped to the many places that could benefit from them; even the guardians are rarely fully conscious of what they’re doing.

    If anyone really wanted to know what was coming in software, all they would have to do is find the dams and peer into the waters they hold back.  In spite of the mighty dams, it sometimes happens that the software finds its way into practice, normally in a flood that blankets a small neighborhood. Sometimes the flood has been held back for decades. There are cases I know of where an innovation was proven 50 years ago, and is still not close to being rolled out.

    The dams are built in many ways with many materials. The raw materials appear to include aspects of human nature: ignorance, sloth, greed — you know, the usual. The really high, solid dams have broad institutional support, in which “everyone” is fine with things as they are, and won’t so much as give the time of day to an amazing innovation that would change many things for the better – except of course for a key interest group.

    Here is one of the examples I personally know about. It was one of my introductions to what innovation is all about, and the sad fact that creating a valuable innovation is generally the easy part – the hard part is usually overcoming the human and institutional barriers to deploying it.

    Automating Medical Image Reading and Reporting

    When a radiologist gets an X-ray, there are two phases of work. The first is to “read” the X-ray and observe anything non-typical that it shows, anything from a broken bone to a tumor. The second is to generate a report of the findings. Most radiologists, then and now, dictate their findings; then someone transcribes the dictated report and sends it as needed. The details of the report can vary depending on the purpose of the X-ray and the kind of person for whom it’s intended.

    There has been technology first tested decades ago that appears to show that software is capable of “reading” an X-ray at least as accurately as a human radiologist. I will ignore that work for now, and focus on what should be the less threatening technology, which is translating the doctor's observations to an appropriate report.

    While I was in college, I worked on the early ARPAnet with an amazing group of people, one of whom was an MIT student from the San Francisco area who later went on to fame making major advances in integrated circuits, among other things. The summer after we did most of our ARPAnet work, he got involved with a new initiative to transform the way radiologist reports of X-rays were created. He knew that some of my skills in automated language parsing and generation were relevant, so he invited me out to pitch in. I went.

    GE, then and now, was a major maker of medical imaging systems. They were seriously experimenting with ways of enhancing their systems to make it easier for radiologists to produce reports of their findings. They created a set of mark sense forms, of the kind widely used at the time for recording the answers to tests, to enable a radiologist to quickly mark his observations of the part of the body in question. Here is the form for a person's guts: X form

    Here is part of the form for the hand, showing how you can mark your observations: X observe

    Here is part of the form for the spine, showing how you can customize the report output as needed: X type

    My friends had gotten most of the system together — all I had to do was build the software that would create the radiologist's report. Because of uncertainty about radiologist's accepting the results, I had to make the report generator easily customizable, so that the radiologist's typical style of writing was created.

    Leaving out the details, in a few weeks I created a domain-specific language resembling a generative grammar and rules engine to do the job — along with the necessary interpreter, all written in PDP-8 assembler language, which was new to me. My friends wrote a clear and compelling report describing our work and included an example of our working software in it. Here was the sample filled-out form: X ex pic

    And here was part of the report that was generated by the software we wrote from the input of that form: X ex rep

    The software worked! And yes, the date on the report, 1971, is the date we did the work.

    A major company, prominent in the field, had taken the initiative to design mark-sense forms, incorporating input from many radiologists. A few college kids, in contact with one of GE's leading partners, created a working prototype of customization report-generating software, along with a proposal to bring the project to production.

    Just as a side effect, this project would have done something transformative: capture the diagnostic observations of radiologists into fully coded semantic form. This is a form of electronic medical record (EMR) that still doesn't exist, even today! For all the billions of dollars that have been spent on EMR's, supposedly to capture the data that wil fuel the insights that will improve medical care, a great deal of essential medical observation is still recorded only in un-coded, narrative form — including medical imaging reports!

    The bottom line is that this project never got off the ground. Not because the software couldn't be written, but because … well, you tell me.

    See the next post for the continuation of this sad but typical story.

  • Medicine as a Business: Medical Testing 2: Doing the Test

    This is the pinnacle post of the series on medical testing, which starts here.

    It's the pinnacle because I've finally climbed the mountain of scheduling, and I'm going to the radiation center for my test. Hooray! I'm at the top of the mountain! It will be easy after this, just getting the results and the bill.

    I've been to the imaging center before. I'm well aware of their attempts to hide behind misleading signage:

    11

    Its nearly-secret location is several floors deep in the basement — only those who really want to get there, and have the persistence to get there, make it.

    I arrive more than the half hour early they requested, to allow plenty of time for the front-office staff to do their work. What's there to do? I've been there before; how can there possibly be anything about me they don't already know?

    First of all, it's an iron-clad tradition to give entering patients a clip board full of paper that needs to be filled out, with lots of boxes to check. Have I been through this before? Yes. Every single time I visit. There's a simple explanation for this. Think back to cop shows you've seen where there's a witness or suspect the cops think might be lying or leaving something out. Or where there are two people who they think have concocted a story, and they interview them separately, trying to trip them up. The cop usually starts by saying, "I know you've been through this with my doughnut-eating colleague X, but I need you to take me through it again slowly, step by step." If it works for the cops, it should work even better for the medical staff, right? They carefully check every answer I give and cross-check it with all the previous answers I've given and analyze the differences. This way they can tell when a patient is lying, or when their memory is crashing because of whatever is wrong with them. Or simply to gauge the patient's intelligence and memory, to rank all the patients and do something wonderful with the results that only members of the doctors' cabal know about. AlI I know is that I have to waste time on each visit, only to have the staff glance at the first page, and file it.

    I end up waiting for about an hour. Finally someone calls my name, and I follow her out of the waiting room through the trackless maze of hallways. After a bit of walking, I'm introduced to a person who, she tells me, will take my blood for testing.

    The pre-MRI blood test

    I've been through this before, and nothing bad happened. It just caused, as usual, another delay in starting the MRI, because they wait for the results of the blood test. Which results (of course) no one gives to me, the person blood was tested.

    But there are a couple things to note about this practice.

    • The main purpose of the test is to see if I'm likely to have an adverse reaction to the extremely safe contrast material that will be injected for some of the images.
      • The main concern is with the few subjects who have abnormal kidney function.
      • I had an MRI with contrast just 3 months prior. How likely is it that my renal function went south during the interval?
      • Doing the test for everyone is just not needed. See this, for example.
      • Doing the test for me was a waste of time and money.
      • In any case, it's clear that there are no standards that are followed here!
    • Given that you're going to do a test, of course my blood needs to be drawn.
      • My blood was drawn by … an RN.
        • Registered Nurses are amazing people with years of training, often including an undergraduate degree and more.
      • My blood could just as well have been drawn by a phlebotomist.
        • You can train to become a phlebotomist by having a high school diploma, taking a month-long full time course, and taking a certification test. Boom, you're done.
      • I don't think I need to comment about the different in cost.

    After more waiting in a special waiting room, I'm finally called into the MRI room.

    The MRI itself

    The MRI nurse/technician was courteous and professional, like everyone else I encountered during the testing process. But the process was inexcusably bad, wasting time and money and reducing quality.

    First, the nurse asked me where the tumor was that was to be imaged. This could have been good. It's classic checklist, the sort of thing you should do to avoid error. See this for details. Why wasn't it good here? She wasn't double-checking to make sure the computer-based instructions were correct — she was asking to find out!

    Imaging studies have been done on me of this area. Multiple times. Including at Mount SInai. Mount Sinai has incredibly detailed information about exactly where the tumor is, more accurate by far than anything I know. Nonetheless, I was the nurse's primary source of information about exactly where the pictures should be taken! She placed pieces of tape on my body indicating the limits, and those pieces of tape were her only source about where to take pictures.

    Next, I laid down on the MRI bed. The nurse had me slide my shoulder into a little compartment, something which had never happened on any prior MRI. Clearly the dial on my paranoia control was set way too low, because I just vaguely thought, hmm, this is different, well she must know what she's doing. After adjusting me a couple times, I got to enjoy the usual loud noises in a confined space during which I was to remain rock-solid motionless; this pleasure went on for 20 minutes or so. Then I got rolled out.

    The nurse tells me that the compartment my shoulder is in is a "camera." Unfortunately, the camera wasn't capturing all the area of the tumor, so she would have to use a different camera and do everything again. She gets out a thick, flexible plastic sheet and places it on my shoulder. I recognize it immediately, because it's exactly the same device that has been used on each MRI I've had, regardless of the imaging center that has done the work.

    Amazing. Frightening. When I go a hair-cutting place, they record my visit and the choices and selections I made for getting a cut. When I go again, even if it's a different person, they'll ask something like "same as last time?" And then they'll normally do the checklist thing of confirming their understanding of what last time was. The point is: they know what I got last time. They recorded it. A hair-cut place. The only thing I can imagine is that the advanced technologies that hair salons use for keeping information about their customers haven't yet made it to the world of medicine. The plain fact was that Mount Sinai had either not recorded (probable) or not used (possible) key information about the image that was taken and how to take it. I would use the word "inexcusable" for this, but without a few choice 4-letter words, such a word would be far too mild to describe what went on here.

    About 3 hours after I arrived, the MRI had been taken and I was free to go.

    The MRI technology and equipment

    This isn't part of my test specifically, but it's on my mind every time I encounter medical equipment. I'm a computer guy since forever (see this for details of my background), and I know too much about the technologies and the companies that are used in this equipment, and the hardware and software processes that create it.

    The highly regulated companies using highly regulated processes to build this hardware and software are unique in technology. The regulation is supposed to protect the public and assure high quality. In fact what it does is assure that only a couple companies can supply the equipment in a government-protected monopoly, at absurdly high cost.

    The net result of this is that specialized equipment and software are built to meet the regulations, even when COTS (commercial off-the-shelf) equipment is widely available to do the job with high quality and great performance at a fraction of the price. A prime example of this is the PACS (Picture Archiving and Control System) that all medical imaging systems include. This is basically a standard file storage system with a database that logs everything put in and enables access to images.

    At the heart of the MRI is a body of software that could be built, maintained and enhanced at a tiny fraction of today's cost — a 10X improvement is the minimum one could expect under a rational set of rules. Here is a detailed post with examples of the insanity and, just as important, a specific proposal for how to fix it.

    Conclusion

    I got the MRI. Nothing awful happened to me. I'm grateful that medical science/engineering has gotten to the point that something as truly amazing as an MRI is even possible. I can certainly imagine things being much worse than they were.

    That being said, the opportunities for improvement on multiple fronts are HUGE. The patient's time and inconvenience could be greatly improved. The operational cost of performing the MRI could be considerably reduced, and the quality and consistency improved. Finally, the capital cost and rate of innovation of imaging machines in general could be HUGELY enhanced by drastic changes to the regulations controlling the design and manufacturing of the devices.

    Even more good news: my saga was not yet over. I don't have the results yet! Wait until you read about what I went through to get them…

  • Getting Results from ML and AI 4: Healthcare Examples

    While the success patterns laid out in the prior posts in this series may seem clear in the abstract, applying them in practice can be hard, because nearly everyone who thinks or talks about AI (these sets over overlap very little, sadly) takes a different approach.

    https://blackliszt.com/2018/03/getting-results-from-ml-and-ai-1.html

    https://blackliszt.com/2018/04/getting-results-from-ml-and-ai-2.html

    https://blackliszt.com/2018/04/getting-results-from-ml-and-ai-3-closed-loop.html

    So here are a couple examples in healthcare to illustrate the principles.

    The spectrum of problems

    One useful way of understanding the winning patterns in AI is to understand the range of problems to which it may be applied. It's not difficult to arrange the problems as a spectrum. While there are many ways to characterize the spectrum — here's a prior attempt of mine to characterize the spectrum in healthcare — perhaps it's easiest to understand it in terms of the typical salary of the person whose work is being replaced or augmented by the AI technology.

    At one end of the spectrum are low-paid people performing relatively mundane, repetitive tasks. These people have relatively little education and minimal certifications compared to those higher on the spectrum. Think back-office clerical staff.

    At the other end of the spectrum are highly paid, educated and certified people performing what are understood to be highly skilled and consequential tasks. Think doctors.

    The very name "artificial intelligence" tells you at which end of the spectrum AI is normally applied. The popular image, supported by the marketing of the relevant vendors, is that AI is amazingly smart, smarter than the smartest person in the room, just like the way that IBM's Deep Blue (predecessor of Watson) beat the human world champion playing "Jeopardy," and beat the then-reigning world champion playing chess.

    To put it plainly, while these achievements of Deep Blue were amazing, they were victories playing games. They were not victories "playing" in the real world. Games are 100% artificial. The data is 100% clear and unambiguous. There are no giant seas of uncertainty, ignorance or unknowability — unlike the real world, which is chock full of them. Nonetheless, IBM and whole piles of people who self-identify as being "smart," and are widely perceived as being smart, jumped on the "AI does what smart people do" bandwagon.

    This was and is incredibly stupid and 100% bone-headed wrong. Not only is it bone-headed in terms of intelligent application of AI, it violates simple common sense. If you knew a talented high school kid who played a mean game of chess, would you drop them into a hospital and give them a white coat? Even after the kid claimed to have read and understood all the medical literature?

    The smart thing to do is to apply AI to tasks that are relatively simple for humans, at the "low" end of the spectrum, and see if you can get a win. If you can make it work, by all means graduate to the next more complicated thing. It turns out that replacing/augmenting human tasks that are mundane, "simple" and repetitive is amazingly challenging! Yes, even for super-advanced AI!

    IBM Watson in healthcare

    I know I've made some strong statements here. It's little old me vs. a multi-billion dollar effort by that world-wide leader in AI technology, IBM. Who's going to win that one? Turns out, it's easy. See this, for example. 11

    IBM claims to get many billions of dollars in revenue from Watson. But everything about getting it to do what doctors can do has proven to be vastly more challenging than anyone thought, and its advice rarely makes any difference, even when it's not wrong. And this, after years of work by top doctors at top institutions doing their best to help IBM "train" it!

    Here is a summary of the situation: 12

    Let's note: the Watson effort is built on the most famous "smart computer" technology ever, funded to the tune of billions of dollars, with technology acquisitions and expert help from all corners. The "disappointing" outcomes are not the result of having picked the wrong algorithm or something easily fixed. The failures are a direct result of not following the success patterns described in the earlier posts of this series, combined with applying AI to the wrong end of the job-complexity spectrum described earlier in this post.

    Olive in healthcare

    If IBM can't manage to pull off a win in healthcare, after years of applying the most advanced AI and spending billions of dollars with the best help that money can buy, I guess it's impossible, right?

    Wrong. IBM made a fatal strategic mistake. They used AI to attack the hardest problem of all, at the wrong end of the complexity spectrum. Has anyone done this the right way? Applied modern AI and related automation technology to the right end of the complexity spectrum? Yes! Olive has!

    Olive is making a positive difference today (please note the use of the present tense here) in many hospital systems by reducing costs, reducing error rates and getting patient information where it needs to go more quickly and efficiently, saving time and aggravation of medical workers along the way. The money and time it saves in the back office may not seem glamorous or "leading edge," but every minute and dollar it saves is time and money that can go to making patients healthier, instead of disappearing down the "overhead" sink-hole.

    Getting a pre-auth for a key procedure so it can be performed. Submitting all the right information so a claim can be paid. Getting information to pharmacies so patients can get the life-saving drugs they need. Getting all the information from incompatible, hard-to-navigate EMR's so doctors have all the information they need to give patients the most appropriate care. These absolutely essential tasks are largely performed in windowless rooms far removed from patient settings by people who work hard at largely thankless jobs that aren't well-paid — but are absolutely essential to providing care to patients. And they're harder than they look! Anyone who's spend any time with a modern EMR can't help but think of the endless meetings attended by skilled professionals at the software vendor trying to find yet new ways to confuse and confound the users. And anyone who has dealt with getting insurance companies the information they demand can't help but think of a cranky three-year-old who lost emotional maturity when he grew up. Bottom line: this stuff is hard!

    Olive gets it done, using an exotic collection of works-today technology, silently learning from the people who do the work today. And gets it done without having to upgrade or replace existing computer systems. Amazing.

    The founders at Olive are doing AI the right way, attacking the right end of the complexity spectrum. They follow most of the rest of the success patterns laid out in the prior posts of this series, above all attention to data and detail, working from the bottom up in terms of algorithmic complexity, and using closed loop. It's a hard problem, and it was hard work to get it done. But they did it, without the massive armada IBM fruitlessly assembled.

    Disclosure: Olive is an investment of Oak HC/FT, the venture firm at which I'm tech partner.

     

  • Who Owns your Health Data?

    You own all the data about yourself, right? It's your blood pressure, your date of birth and your test results, after all.

    Forget about owning your data — just try to get your hands on it! You may think you own it, but the sad fact is that you don't possess it! (Remembering hearing about how possession is nine tenths of the law? It applies here in spades.)

    Health systems like to appear to be great folks who really care about you. These days, they all talk about how great their patient information portal (or whatever) is. Hah. Just try to use it!

    I've talked about how essential it is to have a personal EMR. I've sarcastically described a big break-through in EMR interchange with details from a personal example. And most recently why portability is essential for the EMR.

    I've just had another MRI and want to get my hands on it, so I can see the details. So I went to the hospital system website, and found right on the first page that they offer a patient portal that lets you get your information. Great! Here's what they say:

    Follow my health

    I took the next step and immediately ran into a bit of a problem:

    Gotcha

    Hmmm. I wonder which of these my doctor uses? And which one the MRI will be under?

    After lots more work, I finally got to the right portal that had my stuff. I dove right in. I found my list of test results:

    Results

    Hmmm, something is wrong here. There's got to be more than that! And what's that second item, the path report?

    The path report, somehow dated both 11/23/2016 and 1/06/2017 is actually a copy of a report that was done at my first hospital, Mount Sinai, shortly after the biopsy procedure on Feb 21, 2014:

    North path results

    Bad data!

    The first item is the most recent MRI I had done at Northwell. When you read the report:

    MRI 2017

    You find that Northwell has a prior MRI they did dated 9/14/2016, and two earlier "outside examinations" dated 9/24/15 and 1/22/2015, in other words, MRI's done at some other hospital they choose not to name. But they had those MRI's in their system! They just chose not to show them to me.

    Even worse, they admit that they performed a prior MRI themselves on 9/14/2016, and somehow it isn't made available to me, though it was in the system and available to the person who wrote this report less than a month ago.

    They've thrown away or (more likely) withheld from me, either maliciously or incompetently or some combination, a report they did and two reports sent to them by Mount Sinai, helped in part by the miraculous digital system I described here.

    Well, at least I should be able to go to the Mount Sinai portal and get the two missing MRI's, right? Let's see. Here is the top of the Mount Sinai patient portal test results page:

    Mychart test results

    Score: one out of two. The MRI from 1/22/2015 is available, but Mount Sinai has decided I don't deserve to have the latest one, 9/24/2015. The reason is clear. That is the very MRI that was transferred to Northwell by the amazing digital process I described. When I removed the MRI from Mount Sinai on the DVD, I guess it was no longer there, right? That's how computer data works, right, when you take it from someplace it's no longer in the original place? How can it be???

    Just in case, I decided to put in a request to the portal to supply the missing information. I was constructive, polite and provided the facts. Here was the cheerful, non-helpful response:

    11 mychart

    In other words, not my problem. As though the providers had anything to do with what information in the EMR makes it into the patient portal.

    The only possible explanation for all this madness is that the hospitals involved are using some cheap new software written by a bunch of hacks. They can't possibly be using any of the most famous, widely used, expensive enterprise software systems, can they?

    Let's see. Here's what you see at Northwell:

    Followmyhealth northwell

    And here's what you see at Mount Sinai: Mychart Epic Mt Sinai

    Oops. Two of the premier, widely used, non-cheap vendors. Each of whom is committed to modern, state-of-the-art EMR's with rich portals to enable patients to access their own data. Except on days that end in "y." Or when it's too hot or too cold outside. Or something.

    Oh, I know! Their backs must be against the wall, humping to get all those wonderful features into their EMR's so that doctors can spend even more time staring at screens instead of being bothered by patient contact. They must be stretched so thin, they just can't afford to get the work done, and all my sarcasm is just nasty and uninformed!

    Let's see. Here's AllScripts:

    Allscripts

    Lack of money is not the issue at Allscripts. Epic is privately held, so there's no way of knowing their profitability, but by every indication, they're doing just fine. 

    I guess it all comes down to the simple fact of who owns the data: possession being 9/10's of the law, the fact that they have it means that we patients can have what we fantasize to be our own data when we are able to pry it out of their cold, dead hands.

     

  • How to Avoid Cutting off Breasts by Mistake

    I think we can all agree that if a breast is not diseased, it should not be removed. High on the list of modest, achievable healthcare goals should be avoiding misdiagnosing breast cancer, and avoiding cutting off healthy breasts.

    There are widely known methods and proven technologies that are available for achieving this goal. Instead of applying them, the leading minds in the healthcare technology field ignore them, and instead invest billions of dollars in exotic, cool-sounding AI software that may deliver benefits sometime in the future. Something is deeply wrong here.

    Yes, breasts are cut off by mistake

    Perhaps you think I'm exaggerating? Here is a recent cover from the NY Post:

    NY Post cover

    The woman felt a lump and had a biopsy. The diagnosis was cancer. She was sent to another hospital for surgery.

    Authorization

    Makes, sense, right? Someone should double-check. The rule in carpentry is "measure twice, cut once." When breasts are involved? Double-check should be the minimum; triple-check would be nice.

    Checklists

    Wait, hasn't someone gone into this already? For healthcare, specifically? Oh, yeah, there's that book written by that famous doctor on this very subject, Atul Gawande:

    Checklist cover

    He dives real deep into checklists in many fields, medicine in particular. Here's a partial summary by Malcolm Gladwell he puts on his site:

    Gladwell review

    The hospital at which the healthy breast was removed knew about checking.They wrote a procedure for it!

    What was the procedure? More paperwork. Another in the long list of things doctors have to plow through before they can do their jobs. If doctors actually took all the paperwork seriously, they'd get nothing done. In other words, the "procedure" was just paperwork created by lawyers and bureaucrats that makes life harder and helps nothing. As usual.

    Effective, automated workflow checklists

    What the healthy-breast-removing hospital did was not what Gawande had in mind, of course. He was thinking group meetings at which everyone goes through each step and signs off. Something meaningful. But that doesn't exactly apply here, since the double-check pathology exam should have taken place before surgery was scheduled. Thinking about it, there are many similar situations in which the checklists are spread out.

    There's a concept and proven technology that applies here: workflow. Think of a flowchart with worksteps, lines and conditional branches. Here's a trivial example:

    Workflow

    Think of the workflow as being driven not by paper diagrams like this, but implemented in software that interacts with EMR's and people, and tells them what to do.

    In this case, when the patient was referred for breast surgery, a proper workflow would have scheduled the pathologist to examine the cancer biopsy data before anything else happened. If the results were negative, as they would have been, the patient would have been notified and that would be the end of it. Only if the results were positive would the system allow breast surgery to be scheduled.

    Workflow systems assure that all the work that should be done is done. They eliminate paperwork by putting the checking and doctor sign-offs into the system. No lawyers. No bureaucrats. Near-zero errors. Corrections and enhancements can be made to the workflow without massive re-training and human error. Workflow is like a system-wide, automated checklist, with all the checklist benefits and more.

    Let's do AI instead!

    Workflow software exists. It's implemented in many industries, even sometimes in healthcare. It works. It reduces human labor and improves outcomes. Why isn't it ubiquitous in healthcare?

    Workflow works, solves problems and is understandable. AI, by contrast, is cool, the coming thing and few of the people yakking about it understand it. AI is exploding:

    AI market

    I see a recurring pattern here: people jumping on the new trend, the leading edge, the cool new stuff that "everyone says" is the coming thing, that none of them really understands. And ignoring relatively prosaic technology that works and can provide real benefits today.

    Conclusion

    Cutting off healthy breasts tells us everything we need to know about exotic new AI, which is at the far end of the innovation spectrum I've described for healthcare here, and illustrated here. Workflow is at the simple end of the spectrum: proven, works, understandable and understood, delivers immediate benefits. I guess that's why the leading thinkers ignore it and all the "smart money" avoids it. 

  • Hospital Computer Disasters and Iatrogenic Disease

    I finally figured out why hospital administrators (1) don’t care that their computer systems go down, and (2) refuse to admit that they go down. It’s been driving me nuts. When the systems are down, patient health and lives are put at risk! Why the lack of concern and the secrecy?

    The answer is simple: people die in hospitals all the time! And on top of the people who would have died anyway, hospitals kill people all the time! Yes, “kill” – either through negligence (such as failure to sterilize) or positive error (wrong treatment). In fact, medical error is the fourth leading cause of death in the US! And how often do you hear about that?! In that context, a few more people dying because of an unavailable computer system is a drop in the bucket. And refusing to talk about it fits the pattern.

    Hospital Computer Failures

    Hospitals know they have to have computers. They know computers are complicated and they know software is hard. So nearly all use a couple simple, common-sense strategies:

    • Give high salaries to the top IT people to make sure they’re getting the best
    • Spend lots of money on computing for the same reason
    • Buy only what the best places are buying to reduce risk

    Sounds good, right? Sure, if you don’t know the facts. The result of these common strategies is consistent: most hospitals use incredibly expensive, generations-old technology that regularly fails. Comforted by the fact that they’re no worse than most of their peers, the hospital big-wigs nonetheless keep a solid lid on the problems and outages that are so severe, they would cripple any other business.

    Here are details about disastrous computer systems decisions in hospitals. Here is the story of my personal encounter with outages and keeping the problems secret. Since hospitals know they can’t count on their computers, in practice they’re all about the paper.

    BUT … when real people are dying, the “death” or severe crippling of a piece of electronics is, like, who cares?

    Causes of Death: the Public Information

    Tracking causes of death makes perfect sense. It’s something we want to know for each person who dies; it’s recorded on the death certificate. Here is the relevant section from my great-grandfather’s death certificate in 1923:

    Death

    It’s something we want tracked, so we can see trends and know where to put our efforts to reduce the causes of death. Here is recent data from the CDC, the US government agency that is supposed to track these things:

    FastStats - Leading Causes of Death 2015-07-01 12-36-04

    Heart disease and cancer are the biggies, right?

    Unfortunately, that’s not the whole picture. Hospital executives and government bureaucrats go to great lengths to make sure we don’t know the full story. People might get upset if they knew how many of them had relatives who died in the hospitals as a direct result of negligence and/or medical error! Important people could conceivably lose their jobs!!

    Causes of Death: the Information they try to Hide

    Even hospitals that have great doctors and special experts can have horrible levels of medical error. But the ones that are really bad? They’re really, REALLY bad. Here’s an example of a death-trap masquerading as a hospital in Brooklyn:

    Brookdale

    Unfortunately, it’s not just a couple of bad eggs that are the problem. We know it’s widespread and big, but unfortunately because of all the secrecy, it’s hard to know exactly how bad it is. We know it’s bad enough that the equivalent of a jumbo jet of people die of medical error every day:

    Jumbo

    This makes medical error the fourth-leading cause of death, shown here in terms of deaths per 100,000 in 2010:

    Jumbo 2

    Because the people in charge are so anxious to keep the facts from us, the only thing we can be confident about is that, whatever the reported data on medical errors is, the actual number is far greater.

    Then there are preventable deaths. Even when there are strict rules about reporting problems, hospitals break them. Reuters did some investigating in 2016:

    Reuters

    Among other things, they discovered that there was a superbug outbreak in a New Mexico nursing home the January 2014 that was supposed to be reported. There was repeated delay and denial. In the end, here’s what happened:

    Reuters dead

    What about the CDC? The agency that publishes the bogus statistics that ignores all the hospital-caused deaths? They don’t seem to care:

    Infections

    Things are getting worse:

    Superbugs

    A book has just come out by Dr. Robert Pearl, CEO of the Permanente Medical Group, responsible for the health care of 3.8 million Kaiser Permanente members. He states that medical error is directly responsible for more than 200,000 deaths per year, and another 200,000 preventable deaths as a result of substandard care.

    The theme is clear: suppress the information and focus elsewhere.

    Conclusion

    With so much energy going into suppression and denial of hospital-caused deaths of human beings, it’s finally clear to me why hospital administrators, bureaucrats and most of the “big thinkers” in the medical profession can’t give the time of day to concerns about computer systems. First, they use paper anyway. Second, it’s someone else’s problem. Finally, however bad the computer systems are, they don’t hold a candle to the ongoing death-and-destruction horror show of real human beings dying. Human beings who, except for the incompetence and ineptitude of some doctors, hospital staff and administrators, would be alive today.

  • Use Advanced Software Methods to Speed Drug Discovery

    Drug discovery is like the worst imaginable, old-style software development process, guaranteed to take forever, cost endless amounts of money, and far under-achieve its potential. There are methods that the most advanced software people use to build effective software that works in the real world, quickly and inexpensively. These small groups invent all the new things in software, and then get bought by the big companies.

    Can these fast, agile, effective methods be applied to invent and test new, life-saving drugs and get them to the patients who are dying without them? Yes. The obstacles are the usual ones: the giant regulatory bureaucracies and the incumbents who would be disrupted. Yes, the very people who claim to keep you healthy and cure your ills are the very ones standing between us and speedy drug discovery.

    Drug Discovery and Software

    While I'm not an expert in drug discovery, I've learned more than I wish to know about the regulations through the software providers to the industry. And like many other people, I've learned from being a patient with a disease that could be addressed by drugs that I am not allowed to take, because they are deep in the labyrinth of the years-long approval process.

    I've explained elsewhere how a revolution in medical device innovation could be enabled by transforming the applicable regulations from complex, old-style software prescriptions to simple, goal-oriented ones.

    A similar concept can be applied to the process of drug discovery itself.

    Old-style Software is Like the FDA's New Drug Regulations

    The classic software development process is a long, expensive agony. It's an agony that sometimes ends in failure, and sometimes ends in disaster. It most resembles carefully constructing Frankenstein's monster. It starts with requirements and goes on to various levels of design, planning and estimation. Finally the build takes place. But wait — we can't "release" the software until we know that its quality is top-notch. And that it meets all the requirements. It's gotta work! So let's make absolutely sure that it's up to snuff before inflicting it on the innocent users. Here are details.

    Yes, those innocent users — who are, by the way, chomping at the bit to get at the long-awaited new software whose requirements they signed off on years ago, and that they actually need to get their jobs done.

    So is software development like drug discovery? Let's see.

    • Development that's a long, expensive agony. Check.
    • Don't release it until its adequacy is PROVEN. Check.
    • People who are just dying to use it. Check.

    But here's the difference: for software, usually one company both builds it and decides whether and when to release it. That means the business leaders of the company can balance the tension between adequacy and getting it out there. In the case of drugs, it is adversarial: the FDA declares how each step of drug discovery and testing has to be done, and has armies of people to impose its will on the companies that do the work.

    The FDA Nightmare

    The FDA nightmare has two main parts.

    The first nightmare assures that development and testing is performed in what is claimed to be the "safest" way possible — it's all about protecting patient health! In fact, this means incredibly slow and incredibly expensive. The overhead is far more burdensome than the work itself, which really tells you something. There is a multi-billion company, Documentum, that got started with and still is the leading provider of software to the pharmaceutical industry for handling the documents required by the FDA. Right away, this expense and overhead burden assures that no group of brilliant people will create a start-up and create a new cure for a disease.

    The second nightmare is that the process is incredibly high risk. The FDA can kill your new drug at any time, including near the end, after all the time and money is gone. This again reduces the number of groups performing new drug development to a tiny number of rich, giant, risk-averse corporations.

    This is like big-corporate software development — only far worse.

    Wartime Methods for Drug Discovery

    I've written a lot about wartime software development. A good way to understand it is to look at bridges in peace and war. In wartime, we build effective bridges while under fire in a tiny fraction of the time needed in peace. And the bridges work.

    The methods translate well to software. They are practical. They work. They are in regular use by groups that are driven to innovate and get stuff done. There are details in my book on the subject, with lots of examples and supporting material in my other books.

    It's very clear that the methods also apply to the FDA's regulation of software. Here is an example. There is no reason other than the usual obstacles to innovation that the principles couldn't be applied to drug discovery in general.

    Wartime Drug Development

    What we should try is Wartime Software Development morphed into Wartime Drug Development. Here are the principles:

    • Grow the baby.

    Instead of going through a whole long process and supposedly coming out with perfection at the end, you start with something that sort of works, try it (on volunteers), see how it goes, make changes and iterate.

    • Principles of e-commerce and social media

    When you think of buying a product, do you just walk into a store and trust the salesperson? If so, you're probably in your 100's and hope to get a computer someday. Everyone else goes on-line, checks reviews, and above all checks comments from real users. The sheer number of comments tells you how popular something is. Of course, you don't blindly believe everyone, and of course you translate what people say to your own situation. There could be awful risks and side effects, but if it sometimes works and your alternative is misery shortly followed by death, you might decide it's worth the risk.

    It's a decision that should be in your hands, informed by full sharing and disclosure, not decided on your behalf by a bunch of bureaucrats sitting in offices.

    • Open source and full disclosure.

    Of the top million servers on the internet, over 95% run linux, an open source operating system. Linux was created by an interesting nerd, and developed by an evolving band of distributed volunteers. It is superior to any commercial operating system. And operating systems are complex; linux contains more than 12 million lines of code! Why shouldn't we make drug discovery open to a similar process? With open source, everything about a drug and its results so far would be open and available for anyone, including patients, to see. Patients and researchers would all be active participants in the open discussions.

    • Continuous release

    The most advanced sites first bring up their software in extremely limited, volunteer-only releases. Everything is tracked. If things go well, more people can be invited in. Incredible tracking, lots of feedback, explicit and implicit. As software goes into wider release, a new version of it may be made available to a combination of new and existing users. Its use may be expanded, or it may be withdrawn. The process is continuous and iterative. It's called continuous improvement. We use it in lots of domains, ever since its use was formalized by W Edwards Deming in car manufacturing. It's not exactly weird or marginal. We simply refuse to apply its proven principles to drug discovery.

    Conclusion

    The FDA says its mission is to keep us safe. The gigantic bureaucratic monolith in practice assures that new drug development is performed by a tiny number of elite corporations at great expense, and rarely. Let's at least try a better way of doing things!

  • My Cat Taught me about the state of Healthcare Provider Data

    My daughter's cat taught me a major lesson about healthcare as I described here. Pretty amazing. But Jack the cat also thought I should learn about the advanced databases that providers and insurers maintain about each other. While not as brilliant as the inter-provider EMR interchange breakthrough I've described, the databases have a similar effect to the brilliant gamification strategies for wellness implemented by leading hospitals, but take a whole different approach. The depth and extent of innovation in this industry never fails to amaze me.

    Jack's learning environment

    As I described before, the terrified cat was outdoors and I had to pick him up to bring him inside. He was scared, so he scratched and bit me. I saw my doctor and got a mis-prescription for antibiotics. Then I needed an X-ray to see what was going on inside the hand that was painful after weeks. That's the situation.

    Jack the cat decided this was an opportunity for me to learn about databases and get some extra exercise, no doubt as penance for failing to pet him well or often enough.

    The search for the X-ray provider

    First, I got a referral to a provider that was way far away from where I live. How did this happen? The doctor claims she called me to find where I live twice and got no answer. Hmmm. I guess the information was mysteriously missing from my records and no one thought it was important to get it, and I guess the fact that I only got one message, and it had no request for where I live was just … whatever. So I decided I better get active, rather than waiting another couple of days for a referral.

    I went onto the Anthem site — the provider of my health insurance in spite of their horrible computer security track record. I discovered a provider that is covered by them just a couple blocks from where I live:

    X-ray

    That should be an easy walk. After more fumbling with the doctor's office, I finally got them to give me a referral.

    Here's the place to which I was referred:

    XX

    Same place. Good. I called them up, and they said no appointments were required, just show up with the referral. I walked right over, but they weren't in the building directory. Hmmm. I asked the person at the desk, who had clearly seen confused and lost people like me before. She told me they've moved, and gave me the new location. Great!

    I went back home, and discovered that someone else at my doctor's office had also given me a referral, only to a place that actually has an X-ray machine. So out I walked again, and got my medicinal dose of radiation.

    Anthem didn't know that they'd moved. The people on the phone at the X-ray place had no idea. One person at my doctor's office did know — but another one didn't. In normal life, companies that acted like these did — my doctor, the X-ray place and the insurer — would be out of business. But as we all know, healthcare isn't normal life.

    Big Data and Blockchain

    What happened with me was no big deal. Business as usual in healthcare, and in this case had no consequences beyond getting me to walk more, which is a good thing whether I decide to do it or I'm tricked into doing it.

    But let's consider the consequences of this trivial episode.

    Where are the Big Minds, the elite in healthcare, spending their oh-so-valuable time and effort? Lots of things, of course, but two of the big obsessions are Big Data and Blockchain. Each of these, for different reasons, is a holy grail of technology for healthcare, if you pay attention to the talks, conferences, articles and real dollars invested.

    Big Data is a focus because the leading thinkers and influential, powerful people are convinced that if all this healthcare data is poured into a giant Hadoop data lake and poured over by ultra-modern machine learning tools, we'll discover important things that will make us all healthier.

    We already knew that EMR's are riddled with data problems; now Jack has shed light on problems elsewhere:

    • If the data is missing or wrong, no amount of bathing in Data Lakes will cause accurate results to pop out. Bad data in, bad results out.
    • If there are protocols that have been proven to be the best for treating patients and doctors simply refuse to follow them, nothing improves.

    Blockchain has attracted the attention of leading figures among the healthcare elites because of its awesome promise to solve the problem of data interchange and effortlessly created universal health data — on which Big Data can proceed to work its magic.

    BUT … if no ones cares or is allowed the time to get the data accurate and complete and the data is no good, spreading it around hardly helps anything.

    As usual, all the attention goes to the highly visible frosting on the cake, while the underlying layers of the cake rot from inattention.

    The consequences of extraordinary cat knowledge

    This valuable knowledge about provider databases and the reliability of doctor decision making came from just a couple days of cat-sitting our daughter's cat. The experience was so rich that we decided to get a cat of our own, Priss:

    2016-11-27 14.37.03 - Copy

    We eagerly await the medical knowledge that Priss will bring our way!

  • What can Cats Teach us about Healthcare?

    If you had asked me what cats can teach me about healthcare a year ago, I would have answered, probably nothing. Well, live and learn. My daughter's cat has just taught me a couple major lessons about healthcare. Who would have thought cat-sitting could lead to valuable knowledge about how doctors prescribe drugs?

    Here's Jack:

    2012 04 26 Jack

    Jack is a good cat. He knows how to relax, and is definitely not anxious about things:

    2012 07 13 Jack 003

    Jack is a rescue cat. Something bad involving men wearing boots must have happened to him in his early days, because he gets really scared and is desperate to get away from any man wearing boots.

    Jack sets up the learning environment

    A few weeks ago we were cat-sitting him. He had been outside for too long; workers came onto our property to work on an extended project. It was getting dark. Jack wasn't responding to the usual "come home" inducements. I spotted him hunched down in a hiding spot intensely watching the workers. I went to him. He was too scared to follow me home, since that would bring him out of his hiding place and closer to the scary men. So I picked him up. He got really scared. He scratched and bit my hand pretty well. I managed to hold onto him and get him into the house. Now that he was safe, he was OK, and I just had to treat my badly hurt and bleeding hand, which I did with a thorough wash and bandaging.

    First Lesson: Doctors, prescribing and protocols

    By the next day my hand had swollen up pretty badly. I got an appointment with my primary care doctor. I provided all the details. She put in an order for antibiotics in case the swelling and redness continued. It did, and I filled the order. I took it as directed, and after 5 days there was still lots of pain and swelling. So she gave me a different kind of antibiotic, which was supposed to cover the kinds of things the first one doesn't.

    After a couple days, things weren't improving by much. Here's my hand at that point — notice the lack of knuckles showing how swollen it still was:

    Hand

    My daughter, who's an MD, had been following the events and asked to see my medications. She then sent me information that made it clear that my doctor had given me the wrong antibiotic! Just as bad, the doctor had advised a wait and see approach, while the literature clearly shows that the right approach is to give the drug right away. I gave this information to my doctor; the only appropriate reaction would have been embarrassment and apology, and that is not what happened.

    Finally, I wondered what if you didn't have an amazing daughter who happened to be an MD with access to the literature? This makes it even worse for my doctor: Dr. Google came up with the right answer — the answer to the question MY doctor got wrong. And wouldn't admit it.

    I've had an incurable form of cancer. As my cancer doctor said, I've won the lottery, and I'm OK for now. That was hard. The cat bite was easy. There's no excuse for failing to learn the right approach if you don't already know it and following the approved protocol. My trust in doctors other than my daughter for doing simple things is now below zero.

    Details of the first lesson

    The points been made. If you are skeptical or want details, here we go:

    First prescription:

    22 Bac

    Second prescription:

    22 kef

    The article on UptoDate (a resource used by doctors to make sure they're up to date) recommending Augmentum (commercial name of a combination of amoxicillin and calvulanate):

    33 up to date

    The part of the article on prophylaxis:

    22 proph

    I gave the information to my doctor. Here is the key part of her response:

    111 doc

    In other words, she decided to violate the authoritative protocol because of "anecdotes." Not because there's an emerging body of evidence-based thought. Anecdotes.

    Here's what I should have done before accepting her treatment. I should have asked Dr. Google. Here's the question:

    11 aa

    The first result is Google's attempt at giving the answer:

    11 bb

    Prophylactic Augmentin. How about that? But the article's 10 years old. Let's check the first "regular" result:

    11 cc

    Same thing. Respectable source. But undated. Check the next result:

    11 dd
    Just two years old, in a real medical journal, same advice. We're done here.

    Conclusion

    Too many doctors just do the wrong thing. Even when they know it's the wrong thing, they do it anyway! Doctors increasingly complain about having everyone second-guess them and look over their shoulders. Well, guess what: when you screw up, you deserve that and more.

    I've long since preferred to get my cash from an ATM rather than a teller. I'm now at the point where, for anything that's at all routine, I will strongly prefer an automated medical knowledge agent to a doctor who can't be bothered to do the right thing. Until that's available, I will just have to endure doctors not liking me because I check each and every thing they do to make sure it's the right thing.

    The best thing is — Jack the cat wasn't done! I'll tell the next important thing he taught me in a post soon to come.

  • Hospital-based Innovation in Wellness

    I was shocked to discover on a recent visit that a giant but innovative local hospital system has implemented a break-through in wellness. They have adapted some of the industry's leading-edge employee wellness techniques and made them work for patients visiting their hospital, thus adding a whole new dimension in the way they make their patients healthy. Much like my previous report of a EMR interchange break-through, it's so radical and unexpected I wouldn't have believed it unless I had experienced it myself.

    Employee Wellness

    There has been growing recognition that healthy, happy employees are productive and good for business. There has also been growing recognition that being healthy goes way beyond responding effectively when you get sick. People increasingly understand that when you're active, fit, engaged and have good eating habits, you are more likely to be healthy and happy.

    There's an amazing Oak HC/FT company that's at the forefront of this movement, Limeade. Here's their summary of what they do:

    Logo

    You can see that they clearly understand the relationship between wellness and health.

    Limeade group

    Even the picture implies that getting people moving, fit and engaged is a major key to success.

    Wellness for patients in the hospital

    Hospitals are all about old-style health, i.e., responding effectively when people get sick. But some hospitals are really innovative. I visited one today, and the banner they had proudly hanging in a busy central hallway made their commitment to innovation clear.

    2016-10-06 09.57.15

    I admit I thought their innovations were limited to "just" making sick people better. Hah! They are actually pioneering the application of modern wellness techniques to patients visiting for treatment!

    Wellness techniques

    I guess it's worth reviewing briefly what some of the most important techniques are. I don't think it's mysterious; most people know what they are:

    • Exercise. Without exercise, good things don't happen. You've got to move those muscles!
    • Heart Rate. Yes, you can lazily move your muscles. But that's not exercise — you've got to elevate your heart rate, so that key muscle also gets exercise!
    • Mental exercise. Particularly as you age, exercising your mind in new ways helps keep you young. But even for young people, learning new things and thinking outside your normal comfort zone can give you a major boost.

    Wellness during a hospital visit

    It would be one thing for a stodgy old hospital to put up signs that encouraged wellness. No big deal! But that's not what these guys did. The very best techniques are ones that don't feel like a burden. They "trick" you into doing something you might think is fun, and along they way, something good takes place, like wellness in this case. It's called "game-i-fi-cation." And that's exactly what I experienced during the course of a normal, every-day visit for a diagnostic procedure at this amazing hospital.

    The game started before I got in the door. I was given the address: right on Fifth Avenue, that can't be too hard. But right away, I couldn't find it! I walked up and down the street, finding addresses that are larger and smaller than the one I had been given, and finally concluded that this numberless entrance was probably the right one.

    2016-10-06 10.02.30

    You might think that this is just someone having trouble finding an address. But it's really the low-key start of the game — they draw you in slowly. I looked and looked, and there just was no number! In retrospect, the conclusion is obvious: this is the building in which wellness is slyly delivered to improve everyone's health.

    I walked in and found myself in a huge open space. Where should I go?

    2016-10-06 10.01.45
    I walked and turned my head as I went and finally noticed the place where it had to be:

    2016-10-06 10.01.40

    This is surely it — it's clearly labelled cardio-vascular repeatedly, and I was having a heart test. Done. Still clueless about the wellness being delivered to me, I walked in and talked with the nice ladies at the counter. After they determined that I wasn't in the process of dying in front of them, they returned to what they were doing and eventually found out who I was and what I wanted. Oops. I'm in the wrong place. I should return to the giant hall and ask the guard.

    Eventually, the helpful guard pointed and gave directions involving walking, turning left and/or right, and going through various doors. Here's the view at this point: 2016-10-06 10.00.59

    It's a good thing I paid attention, because part of the game is the absence of signs and directions. The theme of finding the right building was intensified once you were inside. And I was beginning to get anxious. While I had left lots of time, this was taking a while, and I didn't want to be late.

    I followed the directions carefully and eventually found myself at another counter with friendly people. After identifying myself, I received another set of directions involving things like going straight that way until you get to the grey doors, then go through them and immediately turn right until you get to the end of the hall … well, leaving out details, I found another counter.

    Please pay attention to the pattern here, and notice the clear and obvious relationship to wellness techniques:

    • Exercise. Definitely.
    • Heart rate. I didn't walk that fast, but those clever people managed to get my heart rate up by inducing anxiety!
    • Mental exercise. Definitely. Finding the place was at least as good as a Pokemon search! Not having signs or directions is part of the plan! They're really committed to this wellness thing — imagine the trouble they took to assure that all the old signs were removed.

    Finally I got to what turned out to be the right place:
    2016-10-06 09.53.20

    But needless to say, my adventure wasn't over. What's a visit to a health professional without a good solid dose of papers with minuscule print, the obvious result of welfare work for lawyers and bureaucrats? But I got a break. Whoever designed the system decided that after such a large and unexpected dose of wellness, the patient should be given a light load of paperwork. 2016-10-06 09.03.03
    It was laughably small.

    And to put it in context, dealing with it was a good way to "cool down" after my adventure in exercise, heart rate elevation and mind stretching achieved by next-generation, gamified wellness techniques.

    With any luck, other hospitals will copy this amazing innovation. Who knows, maybe some of them already are!

    But that's how hospitals are!

    Yes, you're right. But it doesn't have to be that way. Retail stores, for example, compete for customers. They compete on multiple dimensions — product selection, quality and price, but also convenience and overall customer experience. There is no reason why hospitals couldn't pay some moderate amount of attention to the people who are, after all, their paying customers.

    Giant, multi-national companies like Ikea, which is many times larger than any hospital, show that it's possible. Ikea puts real effort into creating a good customer experience. Which includes helping customers go where they need to go. They have a mobile app which helps you. They have maps:

    Elizabeth_new
    And they have signs in the stores, even on the floor and hanging from the ceiling:

    111

    Hospitals aren't too big. Their executives are not under-paid. They just have to care.

  • Investing in Healthcare Innovation

    There is a clear spectrum of innovation in healthcare. I've described the spectrum here, ranging from simple, blocking-and-tackling at one end to exotic AI-related things at the other end, with smart, data-driven ventures in the middle. The exotic end of the spectrum gets most of the money and attention, while the simple end is largely ignored. The middle of the spectrum is occupied by smart, data-driven people who see a problem in the way healthcare works today, and build here-and-now solutions to make it better. Even though there are sometimes structural obstacles to overcome, these entrepreneurs find ways to work with the system and overcome the obstacles, because their solutions benefit everyone involved: payers, providers and above all patients.

    Oak HC/FT invests in this kind of middle-spectrum venture, ventures that are bold and smart, but also practical with right-now benefits. Here are a couple of examples.

    Aspire Health     1 Aspire

    Aspire Health uses analytics to identify patients who may be approaching the end of their lives, often as shown by increasingly serious health problems. In the normal course of events, these patients would spend an increasing fraction of their time bouncing from one facility to another, each provider doing his or her best, but each acting in completely isolated silos. With Aspire, the patient has the opportunity to have a dedicated care team that meets with them and their families, understands their situation and their desires, and takes charge of each aspect of their care from that point on, making adjustments as required. The Aspire team is a true, takes-charge primary care team, assuring that your needs are met. Typically, patients spend more time at home and less time in hospitals and ER's. The result is that patients and their families are much happier and less stressed, with a primary care team that takes responsibility and gets things done.

    Limeade     1 limeade

    At first glance, Limeade may not seem like a healthcare company. But what else would you call a company that works with a group of employees to encourage them to eat, exercise and generally act in ways that promote health? While many diseases just happen to people regardless of their actions, many others either start or are exacerbated by behaviors. Limeade applies analytics and smart technology to identify, support and promote healthy behavior. Result? Employees that are not only healthier, but happier and more productive. Everyone wins.

     Quartet Health     1 Quartet

    Quartet Health applies analytics to identify people who have behavioral problems and significant non-behavioral health problems that could be interacting with each other to make things worse for the patient. They pay special attention to these patients, and apply an evolving set of automated tools and human intervention to understand the interaction among the issues. In particular, they identify particular combinations for which intervention can make things better for the patient, and then guide the concerned parties to take the actions that will lead to a better outcome, involving the patient and care providers as appropriate. Net result: patients get healthier than they otherwise would have been. And by the way, costs are lower.

    VillageMD     1 village

    When you have a problem, the first person you're supposed to see is your primary care doctor. Founded by visionary, award-winning Dr. Clive Fields, VillageMD has done extensive longitudinal analytics on patient outcomes, and discovered things the primary care physician can do to improve care while reducing costs by an average of over 20%. Having proven the methods in their own practice, VillageMD is now delivering their techniques to other primary care practices in a highly systematic, targeted way. Everyone wins: payers pay less, patients are healthier, and primary care doctors have greater impact and make more money. The VillageMD techniques are evolving and becoming more powerful with additional experience.

    Conclusion

    Oak HC/FT has invested in excellent companies in healthcare. The four companies briefly described here are particularly good examples companies in the center of the "simple-to-exotic spectrum" that I have described. These companies deliver here-and-now results using advanced but non-exotic technology combined with win-win business models. Companies like this that use "big data" in practical ways are out of fashion in the world of healthcare IT investment for reasons that are a mystery to me. All I can say is that they're all the rage in the world of Oak HC/FT.

     

  • The Healthcare Innovation Spectrum: From Washing Hands to AI

    There's a spectrum of ways to innovate in healthcare. On one end is simple stuff, like making sure things are clean and germ-free. On the other end is exotic stuff, like using AI: Artificial Intelligence and Cognitive Computing. Obvious questions: (1) where is the money going? (2) where is the value? (3) Is the money going where the value is? Simple answer: the "smart" money is going to exotic gee-gaws, ignoring near-term value and patient health.

    Where the Money is going

    The money is clearly going to exotica. Ignoring for the moment the billions IBM and others are pouring into what they call Cognitive Computing, VC's are investing heavily in healthcare-directed AI. See this:

    AI healthcare 1

    We're talking serious money here:

    AI healthcare 2

    While there are loads of conferences, trials, talks and articles talking about the great future here, there is an obvious conclusion to be drawn: while the money is being spent now, the benefits (if any) are in the future.

    That's about all you need to say about it.

    The middle of the spectrum

    While things like AI are clearly at one far end of the spectrum of healthcare innovation, there are intelligent, educated things in the middle of spectrum. Lots of people are pursuing these innovations with great energy. I've discussed an example of one such approach here.

    The Oak HC/FT portfolio company VillageMD is another clear example of data-driven innovation in healthcare. No new math or fancy computers are required. "Just" educated, dedicated people looking at the data and making required behavioral changes based on those facts. The founder of VillageMD, Clive Fields, just won a major award for his work, using all-organic and natural intelligence — no artificial ingredients! Guess what: it's here and now! The outcomes of real patients are being improved as you read this!

    The basic end of the spectrum

    On the other end of the spectrum from AI, we've got things that shouldn't need "innovation." They should be standard practice. They have huge impact. They are the shocking, scandalous modern equivalent of antiseptic surgery — things that no one seriously disagrees with, but which the important experts and leadership type people somehow can't lower themselves to pay serious attention to. Or when they pay attention, it's with actions that do nothing to solve the problems.

    A good candidate for the poster child of this end of the spectrum is what the CDC calls healthcare-associated infections, HAI's. In other words, getting sick from going to the hospital. Here is the CDC's summary of the situation:

    11 HAI

    I don't know about you, but this makes me sick. 75,000 preventable deaths in a year, preventable using non-exotic methods. No Cognitive Computing required! There are cures, demonstrated at multiple hospitals that have put serious effort into it. This article summarizes the efforts and approaches, ranging from simple changes of cleaning practices to fancy new machines.

    Conclusion

    There's a clear spectrum of innovation in healthcare, ranging from blocking-and-tackling basics at one end, to exotic new things based on various forms of Artificial Intelligence at the other end, with smart, non-exotic, data-driven methods occupying the middle ground. Most of the "smart" money appears to be going to the fancy exotic end, with results sometime in the indefinite future, while the rest of the spectrum trundles along, largely under the radar, delivering results to patients today.

  • Healthcare Innovation: How to Achieve EMR Interchange

    EMR interchange has been a major goal of the tens of billions of dollars that have been spent to buy and install EMR's. The theory is that making it easy for the next medical provider you see to have access to your complete health record will improve health. It might! But the current methods for achieving integration are not working. Not. Working. It's easy to understand why they will NEVER work, and what can be done to achieve the same result.

    Not to be mysterious about it, here's how: forget EMR interchange. It's not working because it's hard and none of the people who build and control EMR's really want it to work. Instead, enable a new generation of personal EMR's. It's literally hundreds of times easier.

    My EMR vs. Integrated EMR's

    Everything is great if I go to a single integrated hospital system that uses a single EMR. I go from place to place in the hospital complex, and everyone knows who I am, where I've been and what's going on:

    1 EMR_0005

    No problem.

    The problem happens when I go to an office, a clinic and a hospital. They each have EMR's. What all the "experts" think is best, backed by tens of billions of dollars, is for the systems to talk with each other. What I suggest instead is MyEMR app, which gets the latest information from each EMR and uploads everything to the next place I visit. Here's the choice:

    1 EMR_0004

    They look pretty similar, right? There are three unique lines (data paths) connecting my EMR to each of the places I've visited, and there are three unique lines connecting each of the providers (H-C, H-O and C-O).

    When the numbers grow, they start looking not quite so equivalent. Let's look at six distinct EMR's. With My EMR, there are just six possible connections:

    1 EMR_0001

    But if the six have to interchange with each other, we're up to 15 possible connections.

    1 EMR_0002

    Hmmm. Not a good trend. What about when the number gets bigger? What if 100 EMR's had to talk with each other? How many unique connections (data paths) would there be then? Here it is:

    1 EMR_0003

    You may say there aren't that many vendors. But getting two different installations of EMR software from the same vendor to talk is still a lot of work! Not to mention the fact that there are many different versions, configurations and customizations of each piece of software. The real number is likely to be much larger!

    Conclusion

    Just installing an enterprise EMR tends to be an incredibly expensive, years-long disaster. There's a good reason based on simple arithmetic that many years and tens of billions of dollars have yet to achieve any meaningful amount of interchange between EMR's — there's a combinatorial explosion. The same arithmetic strongly favors the personal EMR approach.

    Incentives also favor the personal EMR as the center point of integration. How eager is one hospital CEO to make it real painless for patients to go to the competitor? Patients, on the other hand, are highly incented to want the data in their hands; not only would it save endless hours filling out paperwork and avoiding yet another history interview with its inevitable misinformation, but it's likely to help their providers avoid errors and keep them healthier. Of course, the vendors and systems have a death-grip on patient data, and really don't want to give it to patients, regardless of what they might say. But at least sending data to personal EMR's is a solvable problem without a combinatorial explosion of work to get it done.

    I want a personal EMR!

  • Healthcare Innovation: Getting Data out of EMR Prison

    EMR's have a few problems. Selecting and installing them is too often a multi-year disaster. Getting information from one of them to the other is supposed to be routine, but is in fact a rarity. And the data in them is too often incomplete, inconsistent and/or just plain wrong. How can we get our data out of EMR prison and free it to be fixed up and actually useful?

    The position of the EMR prison wardens and guards is clear: you can pry your data from my cold, dead hands.

    What we'd like

    A personal EMR is the solution to many EMR problems, among them interoperability. If data in my own EMR, corrected and completed by me, were uploaded to a provider's EMR, all the data would be up to date with almost no labor.

    What we'd like is to have our personal EMR app log into the provider's EMR, download the data, let us fix it and complete it, and then upload the corrected and completed results. Not too hard.

    What we're up against

    The great Lords who build and operate the grand and glorious EMR's have their own ideas about letting us dusty peons gain access to our own data. Put simply, they're against it. But they'd rather not say they're against it. In fact, supported by legions of government bureaucrats, they insist that our data is fully available to us. All we need to do is follow a few simple procedures, and it can be ours!

    Oh, great! Maybe I am being too cynical here. Maybe there really is a way I can take my data out of prison for a walk in the wild.

    I recently accompanied someone close to me for a procedure at what is now called Northwell Health, formerly various other names including North Shore-LIJ.

    Northwell health

    I got all sorts of documents from them in the course of the interaction, and went through them to find out how I could get my friend's information from the EMR. Here's the main document:

    1

    Getting the data

    First and foremost, can I get my data? You betcha! It says so right in the very official document I was given:

    1

    Hooray! I can get a copy! Uh-oh, I hope this doesn't mean just a paper copy. Let's see:

    2

    Okay, I can get an electronic copy. So where's the API? Where does my app plug into the EMR? Let's see:

    3

    Oh, no!!!! In writing! Somehow I suspect they don't mean emails are fine. But at least after I go through all the nonsense I guess I get my data. Let's read further:

    4

    What do you mean "may deny access"??!! It's my data!! Wait. It gets worse.

    5
    Nice. I get a redacted version of my own stuff.  Unless they just feel like giving me a summary. Like what, this? "You came in to the hospital. You were sick. You felt like crap. We worked hard. You felt better, and left." Like that? What can I do to actually get my data? Here's how:

    6

    Very comforting! Instead of an API, it's a nightmare, obviously intended so that no one actually ends up with their own data.

    Correcting the data

    Maybe they're better about correcting the data. I showed elsewhere how crappy the data tends to be, and how paper-reliant even places with fancy EMR's are. You'd think they'd want all the data they have to be correct and complete, so they can do Big Data and get the much-vaunted benefits of the tens-of-billions-of-dollars-worth of EMR's we've bought, right?

    I'm tired, so I'm not going to drag this one out. Here's the deal with correcting EMR data:

    Rights p3

    In other words, NFW.

    Bottom line

    The conclusion is simple: my data, the data about me and my health, is imprisoned in an EMR. The prison guards say, sure, you can visit, any time. Just submit your request in writing in the proper way, and you'll get your data real quick. Maybe. What if my data is sick and needs healing? Forget it.

    They say loud and clear that I have a "right" to my data. But it's clear that they'll do everything in their power to make sure that right is never exercised.

  • Healthcare Innovation: EMR’s and Paper

    EMR's are essential. They are going to bring healthcare into the digital age — finally! Healthcare organizations are spending billions of dollars to implement EMR's, and the government is doing the same.They're preparing the ground for the incredible benefits of Big Data and Cognitive Computing!

    There is no doubt that the money is being spent. EMR's are certainly being implemented. Are they working? Eliminating paper? Not so much. One thing they are certainly doing is making doctors spend less time with patients and more time with computer screens.

    I could go wild with statistics, but all this got tangible for me when I accompanied a family member to a surgical procedure with a top-flight provider at a first class facility in Manhattan recently.

    Here is the notebook of papers that accompanied the patient everywhere:

    Notebook

    Some of the papers were computer-generated, but most were not. We spend loads of time fielding questions whose answers had already been entered into various systems — including the provider's! Various papers whose text had nothing to do with medicine had to be signed — papers concerning regulators, administrators and lawyers.

    I heard the dialog in other booths, with huge amounts of time trying to get information out of the memory of patients and onto paper. Here is a nurse doing her job:

    Nurse paper

    I could see that there were also lots of computers all over the place. Not that it mattered.

    It turns out that the medical care was excellent, and the procedure successful. Good news! Would eliminating the paper have made it better? Hard to see. If the medical history had already been available, would it have saved some time? Well, the medical history was all available — the provider had already gotten everything required and entered it into his own system before agreeing to conduct the procedure! So everything done at the hospital was just a bunch of wasted effort anyway, whether it was on paper or on computer! Could the provider's EMR have transferred the information about the patient to the hospital's EMR for this scheduled procedure? Maybe. But it didn't happen, and we know from government statistics that it rarely does.

    Tens of billions of dollars are being spent implementing EMR's so we can experience the wonderful benefits of getting rid of paper. Sounds good, but I suspect that no true science or even engineering has been done here. How do we know things will be better in the gold-plated EMR future? Has anyone done patient outcome studies? How about time utilization studies? Has anyone tried alternatives? After all, EMR's can't possibly be a goal — who cares about EMR's except EMR vendors? EMR's can only be a means to an end; and the only end worth anything is better patient care at lower cost.

    What we know for sure is that we're achieving higher costs by implementing EMR's. We're not eliminating the paper. Too much of the data that ends up in the EMR is crap, and too much is missing or wrong. We're not getting accurate data into a single place. We don't have a clue whether we're making patients healthier as a result; we don't know whether we could make patients healthier by spending the money in a different way. Maybe it's time to apply some fresh thinking here.

    I'm computer guy. And a facts kind of person. I know that computers and software can make things better for everyone in medicine. I'm NOT saying we should forget this new-fangled computer thing. I'm saying we could get dramatically better results for a fraction of the money we're spending.

  • Healthcare Innovation: EMR’s and Data Quality

    Tens of billions of dollars are being spent to implement EMR's in healthcare. There's still a long way to go. Everyone seems to agree that EMR's will make things better than they were with paper. But it's hard to imagine that things will be better if the data is incomplete, inconsistent, and simply wrong.

    The big strategic thinkers and powerful people who push EMR use ignore this issue. I guess it's a detail, beneath them, unworthy of their notice. But for anyone who lives in the world of software, numbers and math, data quality is the foundation on which everything is built. Ever hear of "bad data in, bad data out?" It's true!

    I can run some personal tests on this issue because I'm being treated for a kind of cancer at one of the world's best hospitals, Mount Sinai. I'm getting excellent care and doing well. Mount Sinai is completely up to date with EMR's. It's clear from my experience to date that my excellent care has nothing to do with the EMR — arguably, the good care I'm receiving is in spite of the EMR.

    Let's look at some details. I recently waded through the hospital website to access my medical records. If whoever designed the website had tried to make it difficult for patients to access their records, they couldn't have done much better.

    I finally managed to get a PDF for an encounter. The document makes clear that the hospital's computer graciously deigned to share information with me, the patient:

    1 note

    The document makes equally clear that information is missing. What information isn't here? We have to guess. What an attitude.

    2 may not

    Think of an incredibly unpleasant, arrogant class of professionals. What did you come up with? My guess was lawyer. Even with lawyers, when you fire them and request your files they give them to you, minus snarky notes about how things "may be" missing.

    There was a section with my name and address. Also how to communicate with me:

    3 phone

    They included the identical number for Home and Mobile. You think the computer could have checked for that? This is one of the fatal flaws of the whole EMR approach: the patient is barred from entering and/or correcting his own data! In a sensible, modern system, I would have received an email or text asking me if this information was correct, and asking me to correct it if it's not. But an Enterprise EMR system with layers of security, bureaucracy, administrators, regulators and lawyers involved? Maybe next century.

    Now we get to my meds. Here they are. Notice anything?

    4 meds

    You may notice that information is missing from the second drug, losartan. What I noticed is that the dosage is wrong. What I have actually been prescribed is 100 mg tablets. This record is from the encounter with the cardiologist who prescribed the drugs! If it's wrong, anything can be wrong!

    In my case, it makes little difference, since I'm on top of things. But not everyone is so fortunate, and this is just the kind of error that could, with a different patient and drug, have awful consequences.

    Now let's look at my "social history."

    5 alcohol

    It's wrong too. And I'm not allowed to correct it. If I did use alcohol, it's missing the amounts. But I don't use alcohol. If it were correct, it would be incomplete; but it's incorrect.

    Finally, let's look at my plan of care:

    6 plan of care

    An appointment. But that's wrong too! The appointment I actually have is for a diagnostic procedure, not what's written here, and the follow-up with the doctor is just missing.

    Bad data wrecks everything

    You want benefits from Big Data? Nothing good comes from data that's bad, no matter how big it is.

    There is very little data exchange among EMR's, in spite of all the tens of billions of dollars that have been spent. Here is the latest stat from the government:

    14 percent share

    Do you think that's bad? In principle I think it's bad, until I consider all the inconsistent and incomplete piles of crap data that's sitting out there in EMR's. Then I think of the lack of interchange as being more like keeping the bad data in isolation so it doesn't wreck anything. And who's allowed to fix it? I'm certainly not allowed anywhere near it, even though it's my data.

    Conclusion

    What's the solution? Make health care providers spend even more time bent over computer screens than they do today, which is already excessive?

    The core problem is that our whole approach to hospital, health care and provider automation is rooted in the ancient approach to "enterprise software" that was created in the days of mainframes, and lives on in the incredibly expensive, ponderous and user-hating world of modern healthcare IT. The data will become accurate, complete and high-quality when the systems are built correctly, using modern techniques, and when they interact with all concerned parties — including patients!! — to get their jobs done.

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