Brief summary for those interested. Bangladesh mask was a cluster RCT, (cluster because unit of randomization was a village) Treatment group had public policy intervention to increase use of masks, Control group was basically a poorly enforced govt. mask mandate)
Per pre-print 342,126 individuals in study. Endpoint was COVID 19 +ve symptoms AND positive antibodies.
Key Table shows of ~150k pts in each arm, blood samples could only be collect from ~5k patients in each arm.
It would appear that the primary endpoint differs by 20 cases from the data provided. (Is poxXsymp the right column heading @Jabaluck ?).
One of the problems of the study is that despite the vast size of the study, the primary endpoint depends on ~5000 blood samples collected.
So we are left to extrapolate from a 20 case difference tested in ~10,000 patients to a 300,000 patient study.. which gets us to a discussion made for headlines --> A policy intervention that increased mask wearing 29%, reduces symptomatic Sars COV2 by 9%!
But how robust can this possibly be? It seems a bit much to go from these small differences to the police tracking down and fining people who don't mask in public.. (this from the author of the Bangladesh RCT)
I wish I could say most health policy was based on stronger sauce than this.. What's a billion here or there when the taxpayer foots the bill?
By the way, most of these incidents that the US Attorney General, and almost Supreme Court Judge Merrick Garland wants to make a federal crime involve face covering incidents.
I find it pretty disconcerting as well that disagreeing with the conclusions of the Bangladesh RCT is disqualifying in some way when arguing in court!
Statistical significance matters little when the outcomes isn't clinically significant. Especially relevant in very large trials when even small differences in 2 groups give highly statistically significant differences which may be clinically irrelevant.
The Cost Conundrum was an article written in 2007 in the New Yorker by famed surgeon and author, Atul Gawande that sought to explain the high cost of American medical care.
It was inspired by data from a health policy researcher from Dartmouth named Eliot Fisher. Fisher’s group had mapped Medicare spending of every county in the U.S.
McAllen, Texas had the distinction of having the second highest per capita Medicare spending in the country, and it was this town Gawande traveled to, to write his article.
Gawande, an academic surgeon from one of the elite medical centers in America wrote with some distaste of a two filled with strip malls with small independent private practices dotting the landscape that were making handsome profits by billing fee for service Medicare to the max.
Gawande provided a stark contrast to this low value, profit driven care by traveling to a high value, low cost county — the Mayo Clinic.
A visit to a surgeon’s clinic at the Mayo Clinic told the story of an hour long discussion with a patient followed by a cardiologist materializing within 15minutes from another floor to help ready a patient for surgery the next day.
How did they do this?
Gawande’s words :
“..decades ago Mayo recognized that the first thing it needed to do was eliminate the financial barriers. It pooled all the money the doctors and the hospital system received and began paying everyone a salary, so that the doctors’ goal in patient care couldn’t be increasing their income. Mayo promoted leaders who focused first on what was best for patients, and then on how to make this financially possible.
No one there actually intends to do fewer expensive scans and procedures than is done elsewhere in the country. The aim is to raise quality and to help doctors and other staff members work as a team. But, almost by happenstance, the result has been lower costs.”
The answer to the health care cost problem lay in this elegant article. The plan as initially forwarded by Eliot Fisher from Dartmouth and now gracing the pages of the New Yorker was to create “Accountable Care Organizations” in the image of the Mayo Clinic.
Convert McAllen, Tx to Rochester, MN and the nations problems would be solved.
As a young medical trainee reading his article, I was sold.
But I never stopped to think of how Mayo was operating in this manner. How could a surgeon at Mayo afford to spend a whole hour with a patient? How exactly does a cardiologist have time to run down in the middle of the day to discuss a complicated patient? If the cardiologist doesn’t bill the consultation, how is the cardiologist being paid?
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Gawande never provided these details, and more importantly no one of any importance asked these questions.
“The Cost Conundrum” was required reading for the framers of the ACA, and so health care was reimagined and jiggered to make winners out of large health care systems. Cuts from CMS targeted private practice reimbursement. Regulations that required reporting of practices through an electronic health record were applied. The incentives quickly melted away to become penalties. Private practitioners faced a choice : accept the lump of coal or join a hospital. Most fled to hospitals, dotting the landscape with soup to nuts health care systems and realizing the dream Gawande had written about.
Except, Gawande and his adoring readers (that would include me) had been hoodwinked. The secret sauce for this high value care being provided to patients by the very best in the field wasn’t in the Medicare data that Eliot Fisher’s group in Dartmouth had put out. The drunk looking for keys under the lamp post doesn’t find his keys for a reason. The keys in this case was where no one was looking – payments from private insurers.
2/x
Just down the road from where I grew up, another group of researchers at Carnegie Mellon University published a paper based on claims data from private insurers that showed a much more complex landscape than the Eliot Fisher data had presented.
The dollars paid by private companies was multiple of what was paid by medicare. A knee MRI paid by private insurers was $1331, Medicare paid $353. Even more startling was how Rochester, MN ranked relative to its peers in per capita cost.
While Rochester, MN was a bargain when it came to Medicare spending per beneficiary, it was one of the most expensive markets when it came to private spending per beneficiary. The other large vertically integrated health systems (Grand Junction, CO – La Crosse, WI) that Gawande had highlighted? Also some of the most expensive on the private market.
Apparently, creating large integrated health system created a monopoly that could effectively name its price for the services it was rendering. Medicare gets to set its prices – the private insurers have to negotiate with providers. The fewer health systems in a county, the higher the prices negotiated. THIS is what was paying for one hour patient visits with a surgeons and made Cardiologists materialize out of thin air. The idea that any of these large health systems were low cost was a myth.
Ok. So my summary on the @Change_HC @Optum @UHC cyberattack debacle.
TL,DR : Govt. regulation creates billion dollar revenue streams for large corporations. Regulatory capture by large organizations means a healthcare system that is incredibly susceptible to single points of failure, and most of the players in the space have no clue/ don't really care!
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Feb 21, 2024, cyberhackers compromise @Change_HC (formerly Emdeon, acquired a few years prior by @UHC for $13billion).
@Change_HC is the largest medical clearing house that takes electronic claims generated by hospitals and doctors offices , scrubs them, and puts them in a format that insurance companies accept. Insurance companies process claims, and make payments to hospitals and doctors.
The first reaction of @Change_HC is to disconnect from all of its clients, which means, no medical claims are processed to be delivered to insurance companies.
Change HC / United then proceeds to say absolutely nothing of substance for the next 2 weeks with regards to any timeline of coming back online
If the goal is truth, then the real bias everyone should lean into is against the academic-peer-review industrial complex that spends most of its time generating data that doesn’t replicate and then exacerbates the problem with hyperbolic conclusions
“If the only tool you have is a hammer, you tend to see every problem as a nail.”
Academia is full of people who have spent 20 years becoming masters of a particular domain that usually has no practical, real world application.
The coverage of this wildly speculative paper linking sars-cov2 is much worse than the actual paper is.
To give you a flavor.
The study is based on 8 autopsies of patients with a diagnosis of COVID.
Let’s take Patient 1.
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59 year old black man with a history of CAD.
He was admitted to the hospital 3 times before dying.
Hospitalizations 1 was with a clot in his lungs. His only treatment was heparin and xarelto. This means he didn’t present with a COVID pneumonia.
Hospitalization 2 was listed for heart failure. His ejection fraction was 40-45%. He spent 5 days in the hospital. He was still COVID positive.
Hospitalization 3 was with an acute heart attack. A circumflex artery occlusion associated with rupture of a component of the mitral valve — the papillary muscle. He was now COVID negative. He died of the heart attack and resultant heart failure, I assume.
The authors of this study took coronary artery tissue and looked for evidence of sars-cov2
They show representative samples of tissue in their main figure. They do not , even in their supplement, show all tissue sampled and stained.
The presence of sars-cov2 rna In patients who were infected by itself doesn’t mean much, but researchers probed tissue for the antisense strand of the S gene (S antisense), which is only produced during viral replication.