rcdmd

The conclusion is basically this (the last sentence before the "conclusion" section... > But it does mean that we cannot afford to compound these problems through the use of an RCA tool that is so deeply and fundamentally flawed. Other more systems-focused techniques, such as fishbone75 or lovebug diagrams,72 causal tree diagrams,21 Causal Analysis based on Systems Theory (CAST)76 or even prospective risk assessment approaches,77–81 should be considered instead.

I find it odd that the paper cites so many theoretical problems with "5 whys" and then elevates these other methods as preferred solutions without any discussion. It's possible RCA committees already recognize the limitations of "5 whys" and use it as a heuristic that helps focus their efforts. That doesn't mean these committees all sit around a table and say "well, X sounds like a major problem, but it doesn't fit our '3rd why,' so we have to ignore it."

I think you're both right. The commenter above you is just taking the short view and you're taking the long view. Automation is great for long-term productivity and the supply of better, cheaper goods/services, but you can't argue it makes for a happy former file-clerk 5 years away from retirement who now has to find a new gig.

In the abstract, you get this statement: "The drop in wages depressed the labor supply of men and increased that of women, especially in married couples."

Seems to get cause and effect backwards. Isn't it more likely that an increase in labor supply (women entering the workforce) had, simply by the laws of supply and demand, decreased wages?[1] [1] https://www.dol.gov/wb/stats/NEWSTATS/facts/women_lf.htm#one

The paper is full of complicated-looking economic models and nice graphs-- but if you don't get the basic assumptions right it's hard to trust the fancy models.

Are you trolling? You're accusing management of onboarding an H1-B, paying a sign-on bonus, paying relocation expenses and then paying them for 2 months to surreptitiously "pad the relatively useless team" so you can initiate a layoff instead individual firings. Nope. Generally, firings at big corp go like this: 1. Create an improvement plan for your under-performing worker. 2. Evaluate worker based on that plan in 1 month. 3. Fire worker.

You can make any number of arguments why X, Y or Z is bad (or, "considered harmful"). The truth is, if you want to get stuff done, objects often fit the domain well enough and put state in predictable places. A bandaid here or there, "friend" classes and so on may be required. But, you'll get stuff done even if it's not in some perfect stateless beauty.

I'm assuming you're referring to RATHL? RATHL attempted to show a treatment regimen was non-inferior to bleo, and didn't. The results are quite controversial, and bleo remains standard of care for many Hodgkin's cases. However, that may change with future trials and more data. Bleo is, as you say, truly a poison. It hurts a lot of people. But on balance, it saves lives better than the alternatives when appropriately used.

Thanks. I clarified what I meant above.

It's genius marketing-- they were guaranteed a "surprising" conclusion that people widely share.

edit: The point I'm making, perhaps too tersely based on the below response, is a flawed study can be designed where every outcome would be "surprising" but obviously the rationale supporting that outcome would be poor. That people tend to share surprising outcomes (ie-- post it on Hacker News)-- makes it genius marketing.

Seems like MetaMed tried working on every buzzword in medicine. * Artificial Intelligence and diagnosis (check). * Evidence-based medicine (check). * Personalized medicine for all (check). Consider, for a moment, all the capital and smart minds working on those things. I'm certainly not saying that's a reason not to work in any of those fields. Rather, a small startup is probably better suited focusing on 1 specific hard problem and gaining sufficient domain knowledge in that area to do meaningful work.

Think of what this means for voter representation. You just made it much easier for people with computer access to vote, compared to those without who still must trek to the polling place. I doubt the demographics represented in this vote were the same as the last comparable one.

Nope. Docker's value isn't just its software. It's the support built around it, tutorials, familiarity and common usage, Dockerfiles, huge Docker Hub, existing setups relying on it and so on. Articles like this tend to overlook the value of entrenched technology that works well enough.

Vagueish advice for a vaguiesh problem-- When presenting issues, I'll almost always fallback on something like this-- 1. Details of the problem with history of other related issues. 2. 1-2 sentence assessment of the problem that helps summarize everything. 3. 1-2 possible solutions.

I think most consumers take "savings" to mean "reduction in purchase price." Obviously, (or not so obviously) Tesla's sales-page means something different. But even if you dig into the asterisk next to the "after savings price" you find some aggressive assumptions. And $4300 gas savings over 6 years is not worth $4300 today to any rational person on this Earth. They need an asterisk explanation within their asterisk explanation stating they assume a 0% discount rate.

Just put a prominent link with ?raw=true in README.md.

https://github.com/pjimenezmateo/curriculum-bootloader/blob/...

Explanation here (from 2004): https://gcc.gnu.org/ml/gcc/2004-12/msg00681.html

It's not that GCC proves the uninitialized variable must be 0, it's just that CCP sets it to 0 and everything happens to work out in specific cases.

This library has a GPDR consent problem-- just putting it at the end of the README doesn't cut it. I wonder if this is the first open source library to violate GPDR.

A few things off the cuff as a physician-- the US has dangerously unequal access to care. I suspect most of the "drag" on life expectancy is from patients without access (this is conjecture but based on personal experience). Even patients eligible for medicaid don't necessarily go through the steps to get it. Often we see patients show up to the hospital who haven't seen docs in a many years until they've developed terrible sequelae like gangrene requiring an amputation. At that point, during admission, the hospital generally helps get them on medicaid. Also, obesity is becoming the new normal in US with all of its associated co-morbidities (a common morbidity/mortality sequence is obesity -> diabetes, hypertension -> coronary artery disease, end stage renal disease, general vascular disease -> death. More healthcare spending is required to treat patients, but the root cause for a growing part of the population's illnesses can't be cured by medicine yet. Also, economically speaking-- the US spends a lot more per capita on mostly everything-- its GDP per capita is higher than these other countries. But, mostly, I suspect the US's health mortality problem is access related. We're spending a lot of money on things that don't help people with poor access to care until their original diseases have done irreversible damage.

Give criticism, sure, but keep some civility too. It's Valentine's Day! Be kind.

The linked CNN article is a very poor summary. It doesn't even include a proper citation, and the link to the study isn't directing to the one being discussed!? Come on, CNN.

I recommend reading the editorial in Stroke instead: https://www.ahajournals.org/doi/pdf/10.1161/STROKEAHA.119.02...

And you can get the article here if you have access to Stroke: https://www.ahajournals.org/doi/10.1161/STROKEAHA.118.023100

I'm sorry but I have to point out the irony in showing so much disgust about a few lines of code that happen to literally say "I love you."

It's okay, just fork it. Ethereum Classic Classic.

I too wish everything in medicine was cut and dry. But oftentimes precise numbers are unavailable. More qualitative reasoning such as "high risk," "serious morbidity or mortality" is usually given in medical assessments. Plans are developed based off that assessment. Doctors and patients routinely make well-considered decisions and get consent knowing that exact numbers aren't known. On the other hand, many treatments (pharmaceuticals and screening being 2 major ones) are backed by very reliable studies where numbers are known.

Reading some comments in this thread you might think physicians are unable to apply Bayesian statistics to medical care. As a physician myself, I'd encourage a more considered line of thinking.

Clearly, physicians here failed to calculate an exact positive predictive value in the example. The question is does that inability affect their 1) medical care delivered and 2) communication with the patient and the patient's own informed decision-making.

In speaking to 1-- there are many examples to choose from from probably any medical specialty but let's stick to breast cancer screening since that's the example from the article. USPSTF presents their recommendations[1]. I'd encourage anyone with interest to at least skim the rationale presented on the page below those recommendations. They very well consider prevalence as well as efficacy of specific tests given the presence of different risk factors in a patient (age, family history, etc). Importantly, those and many other screening guidelines are applied by primary care physicians who may not otherwise be able to calculate exacting probabilities.

[1] https://www.uspreventiveservicestaskforce.org/Page/Document/...

In speaking to 2-- patient autonomy of course requires an appropriate understanding of the tests they receive, any risk to those tests and the benefits and harms of true positives, false negatives, etc. The associated frequencies, albeit with some degree of imprecision are avaialble by reference and I'd suspect they're memorized by most radiologists reading mammograms and the breast surgeons involved in tested positives-- even if they may not be able to calculate them. If the doctor doesn't have them memorized-- they should be available by referencing the relevant guideline.

APRN's Q3 filings are ominous-- although margins are decent at 33%, they've never been profitable and their customer base decreased 25% Sept. 2017 to Sept. 2018.

No-- the patient's weight was just under 40kg-- the system logic completely disabled dosing by total dose.

Cliff notes-- New EMR/ordering system. New physician. New nurse. New pharmacy dispensing system. The physician couldn't order 160mg of Bactrim because per kg dosing was required. They mistakenly ordered 160 "mg/kg" (40x the intended dose of 4mg/kg) on the order screen. The UX on the screen was partly to blame-- dosing mg or mg/kg apparently came down to a just a dropbox. With EMR ordering systems I've used, this mistake is virtually impossible to make since weight-based dosing pops up a completely different window, calculates the dose and then goes back to the original dose screen showing the total dose.

That order went to a pharmacy robot which diligently counted out 40pills, put them in baggies and sent them to the nurse. The nurse thought it was strange, but ultimately trusted the dispensing system that said everything was correct.

The medication error was noticed after the kiddo felt whole-body tingling. Poison control was called, but it didn't seem like they were able to give a clear treatment advice. A "rapid response" was called, they came and evaluated the patient. He was left in a non-ICU room. Several hours later he had a seizure. He recovered from the seizure and was then monitored in the ICU.

From the article, "Because the manufacturers haven’t yet proven there is significant enough life-safety benefit to a laser-based matrix system, regulatory reworking is a tough sell."

Because of the regulations, the burden is on the manufacturer to show the matrix light technology is actually safer than the traditional one.

https://adoptopenjdk.net/

They're baking up soy hemoglobin in yeast and purifying it to add to non-meat burgers. This is particularly neat considering how complex the human heme synthetic pathway is. I suspect even in soy, it's more than just producing a "pre-(a-)"protein-- you'd have to make a few other enzymes along the heme synthetic pathway and provide an environment conducive to them working.

It does make me wonder, why soy? Corn and rice hemoglobins, unlike soy hemoglobin, are basically ubiquitous in our diet as far as I know. I suppose soy hemoglobin may be more meat-like or easier to produce.

Heh, I'll chime in as I did residency at a busy program and advanced my coding skills on the side. Even working 80hr+ weeks you find downtime. Some of that you use for sleeping and studying. With whatever's left, some of my co-residents liked to read. Others had sort of social lives outside the hospital. For me, I coded with most of my freetime. It helped scratch an itch-- problems are solved with 100% certainty, errors can be found with testing preventing many mistakes before they actually affect people, you can build something with your creative juices and get a level of independence not possible in medicine... The list goes on. But my point is, residency is demanding, but you still have a little downtime here and there.