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Which is kinda silly because if they just sat back and listened they could learn more about the thing that other people are talking about so that the next time this topic comes up they won't feel uncomfortable and can jump in and add something to the conversation instead of just nervously pivoting to talking about Alatucky or Boeing or the number of street poops in SF.
I for one look forward to learning more about the medical system of Brazil from this post.
If the user-base is predominantly American then of course if you tally up the random nonsense comments on any given day, they will also be predominantly made by Americans, due to probability.
But this brings me to the other important reason, statistical check can only get you so far and that is assuming we can now trust it was even done. Some people do rely on being able to say, 'this was false positive once, you know what are the odds of it being false positive twice'? Now, we add variable of uncertainty into the system in the form of 'well, it was outsourced so there is a non-zero chance it is bs anyway'.
Not exactly a recipe for success.
I don't think that is useful at all in case of rare diseases. You would just get two reports saying that the random sample is free of HIV.
Much better would be to send some known control samples. Making sure that some of the samples is known HIV+, and then check if the supplier can tell which ones are those.
I agree that sending control samples can also be effective, though. But if you need to send the whole organ to the test lab (and not just a small tissue sample), you probably don't want to be wasting healthy organs by infecting them. Better to just wait until you have an organ that's known to be infected already.
Why would you need to do that? Realistically the sample needed here is a small vial of blood from the organ donor’s body.
> You can still do this kind of audit, but you need to test a statistically significant number of samples in your "spot check" such that you know you some of them will be infected.
Nah. It really doesn’t work. The problem is that HIV is very rare. (HIV incidence per 1000 population adults 15-49 in Brazil is between 0.34 - 0.45[1])
Let’s be ultra conservative and set the “spot check” rate at 100%. That is you are sending samples from every single body to two labs. Because of the low incidence rates you would still expect hundreds and hundreds of those samples to return as negative from both labs. This might work if you would somehow have a “gold standard” lab you trust and an other “less trusted lab”. But in reality there is no such a thing as a “gold standard” lab you can trust without QA. (And if there would be you would just use them, instead of the other lab.) Even with that ridiculously high “spot check ratio” you wouldn’t know if you are getting negative results because they are in fact negative, or because both of your labs are falling for some reason and giving you constant false negatives.
In conclusion spot checking the results with a second lab simply doesn’t work. Even if you spot check every single organ donor you would be still blind for even the most basic error cases for unacceptably long times.
On the other hand if you intermingle a control sample into every single batch that changes the game. Lets say they run the tests on batches of 10 and you make sure that a random one of those is always known to be positive. Now if something goes wrong and they don’t detect the sample you can straight away reject the whole batch of tests as faulty. And it only costs you an 11% extra over not doing any QA.
So with the “spot checking” test you can pay as much as 100% extra and still not know if the tests are having the most elementary kind of fault for hundreds and hundreds of organ donors. Or you can go with the “control sample” strategy and have a reasonably high confidence for every batch right away at much less of a cost. Yeah you can do the “spot check” audits but it is ridiculously bad at catching issues even if you spend a lot of money on it.
1: https://www.unaids.org/en/regionscountries/countries/brazil
A bit of data is most informative if the entropy is 1 bit as well. A signal that is true most of the time, or a different signal that is false most of the time is less informative. Use pooled testing such that the result is true or false half of the time.
Had information theoretically justified pooled testing been applied from the start, then:
* 1) control-testing the testing contractors would have been straightforward and passing 10 control samples by chance would have a likelihood of 1 over 1024.
* 2) it would have made obvious that saving money on control-testing the contractors would hardly save any money
* 3) even in the bad scenario that control testing was skipped, the issue of contractors cheating would have surfaced much faster, since combining the pooled tests to identify which patient tests positive would constantly result in mysteries, meaning control-testing needs to be enabled, not the mathematics of pooled testing brought in doubt.
* 4) testing pharma industry hates pooled testing, as it means technological competition instead of sales growth by abusing the naive but false "common sense" that you need as many tests as patients tested.
on a side note: assuming tests with different operating point on the RoC curves (having different false positive vs false negative ratios) have different prices, do we know if the operators blatantly provided fabricated results, or if they blatantly ignored basic mathematics and thought the more expensive tests could be substituted by the cheaper ones even if intended for a different purpose?
consider a test designed for telling a patient that we diagnosed HIV, and then consider a test designed for screening an organ to be inserted into a patient.
do you think they should both use the same test? or do you think it wiser to have the diagnosis test have lower false positive rates, and the organ screening test to have lower false negative rates?
Another option is to send "control samples" to the testing lab, something you know already is infected with something they should be testing for. Do this enough times, and you'll know if they're accurately reporting the bad samples.
This type of thing is the only way for anyone in any kind of organization to verify that their outsourcing is effective and they're getting the result they want.
The problem is corruption. I don't see why you think that wouldn't plague internal operations.
You can still get rogue employees in ether case, but an outsourcing company is like a ready made conspiracy where any corners cut automatically turns into money.
If we anthropomorphise the regulatory body, sure. In reality, there isn’t evidence either way. Corrupt governments handing work to the private sector is a proven efficiency booster. Meanwhile, competent governments Severn Trenting everything is textbook (on the political left).
If your reaction is that Apple’s core competency is in marketing and design and not manufacturing then i will ask if the same pattern couldn’t be applied to Boeing.
The issue is: Public service in Brazil is expensive and is virtually impossible to fire anyone. On top of that the cost of public service has second order effects in the public balance sheet for the municipalities plus it has a huge burden in the public retirement system.
Not saying that is right or wrong, but this is very common in the Brazilian heath system.
You don’t check the organs. You check the process by intermingling known HIV+ samples and check if they are being detected.
> Checking means re-testing, so might as well get rid of outsourcing.
Thing is you need to do QA on the testing system no matter what. Doesn’t matter if it is performed by contractors, in house staff or little grey aliens. If you are not doing QA you won’t know if the testing is done correctly or not.
At some point, your recursive watchers of watchers watching watchers has to have a base case of "we trust this entity" (or maybe, "you, the public, trust this entity").
Outsourcing only matters for this if it provides a break in the chain of responsibility. That is, if the person selecting the outsource provider can (successfully) say "hey, not my fault" by pointing to... some entity that whoever they answer to doesn't already trust.
I agree provided that "checks" isn't just the narrow sense of "verification upon receipt of the product", but also the supporting framework of "violators will get punished."