Copyright 2021 Tony Lima. All rights reserved.
For at least a year I’ve been asking a simple question: “Where are the big data people who should be analyzing COVID death data looking for contributing factors?” The answer is there is no good data (at least in the U.S.) Read on to find out how the government screwed up COVID-19 data.
Short version: the government paid higher rates for COVID-related tests, deaths, etc. An axiom of economics is that when you offer a higher price for an activity, you tend to get more of that activity. Result: Santa Clara County just announced they were reducing their COVID death count by 22 percent:
The county reported that it had reviewed each COVID-19 fatality and was only counting those whose cause of death was from the virus and not those who tested positive for COVID-19 at the time of death but did not necessarily die from the virus.
Senator Jensen Blows the Lid Off the Pricing
Our story begins on April 8, 2020. Senator Scott Jensen (R-MN) stated the government was paying hospitals and doctors premium rates for COVID diagnoses. On April 15, Dr. Jensen (a genuine MD) wrote this on Facebook:
Here is a brief article. Read the first four paragraphs. Clearly New York and California are using vastly different methods for reporting COVID-19 deaths. How can anyone not believe that increasing the number of COVID-19 deaths may create an avenue for states to receive a larger portion of federal dollars. Already some states are complaining that they are not getting enough of the CARES ACT dollars because they are having significantly more proportional COVID-19 deaths.
‘Presumed Covid-19’: NYC corona deaths suddenly soar past 10,000 after more than 3,700 victims added to list on PROBABLE grounds — RT USA News
THIS MATTERS AND SHOULD BE SHARED!
The article linked by Sen. Jensen is from RT, the U.S. outlet for Russia Today. Take this with a grain of salt. But make that a small grain because there’s plenty of evidence supporting Sen. Jensen’s claim.
The additional deaths – 3,778, to be exact – include people who are “presumed to have been infected because of their symptoms and medical history,” according to two sources cited by the New York Times, which reported the deaths on Tuesday. These “probables” bring the total number of casualties for New York City to 10,367 and raise the nation’s total death toll by a whopping 17 percent. Over 26,000 people are now considered to have died with the coronavirus in the US, according to the Times.
Exactly. Several fact-checking organizations rated this true. Factcheck.org said,
It is true, however, that the government will pay more to hospitals for COVID-19 cases in two senses: By paying an additional 20% on top of traditional Medicare rates for COVID-19 patients during the public health emergency, and by reimbursing hospitals for treating the uninsured patients with the disease (at that enhanced Medicare rate).
Both of those provisions stem from the Coronavirus Aid, Relief, and Economic Security Act, or CARES Act.
A factcheck by Michelle Rogers at USA Today rated Sen. Jensen’s claim True, adding
The coronavirus relief legislation created a 20% premium, or add-on, for COVID-19 Medicare patients.
There have been no public reports that hospitals are exaggerating COVID-19 numbers to receive higher Medicare payments.
Jensen didn’t explicitly make that claim. He simply suggested there is an “avenue” to do so now that “plausible” COVID-19, not just laboratory-confirmed, cases can be greenlighted for Medicare payment and eligible for the 20% add-on allowed under the relief act.”
“We rate the claim that hospitals get paid more if patients are listed as COVID-19 and on ventilators as TRUE.
Hospitals and doctors do get paid more for Medicare patients diagnosed with COVID-19 or if it’s considered presumed they have COVID-19 absent a laboratory-confirmed test, and three times more if the patients are placed on a ventilator to cover the cost of care and loss of business resulting from a shift in focus to treat COVID-19 cases.
All this was confirmed by the American Hospital Association’s Special Bulletin on the CARES Act:
During the emergency period, the legislation provides a 20% add-on to the DRG rate for patients with COVID-19. This add-on will apply to patients treated at rural and urban inpatient prospective payment system (IPPS) hospitals.
The Economics of Increasing Price
As noted earlier, paying a higher price for an activity tends to increase the quantity of that activity. That’s historically been true of homelessness. It almost certainly describes the market for COVID data. This does not imply fraudulent reporting. Indeed, CDC encouraged reporting “probable” cases. And the PCR testing was done at such a fine level that a COVID positive test was virtually meaningless. As Dr. Robert Hagen put it in Medpage Today,
So how does a qualitative RT-PCR test work? Basically, the manufacturer sets the test to turn off the cycling or amplification process when a certain number is hit. For a qualitative test set at 40, after 40 amplification cycles, if any viral material is detected, it turns off and is reported as positive. If none is detected, it would be reported as negative. If the number of amplification cycles was really 15 or 25, it would still run until it gets to 40 and be reported as positive.
With these type of tests, it’s critical to use an agreed-upon cycle threshold value such as 33 (CDC) or 35 (Dr. Fauci) rather than setting it at a potentially misleading 40 or 45. Many of the current tests in use are preset by the manufacturer to these higher numbers.
The World Health Organization issued a notice last week telling the labs “the cut-off should be manually adjusted to ensure that specimens with high Ct values are not incorrectly assigned SARS-CoV-2 detected due to background noise.” Could this be a reason why many people test positive but remain asymptomatic? In that same memo, WHO said all labs should report the cycle threshold value to treating physicians.
Recall that CDC was paying a 20 percent premium for COVID testing and treatment. Increasing the number of PCR cycles was an easy way to catch even the mildest exposures.
Data analysis is only as good as, well, the data. COVID data was very noisy. A number of deaths were recorded as COVID when, in fact, there was another, more important factor. That means sorting out the factors contributing to COVID severity could not be done because so many deaths and diagnoses were either wrong or misleading. Even today, about the only causative factors we’re sure of are obesity and age.
This is public health malpractice. Today, fully 18 months into the pandemic, we still do not know why some seemingly healthy 40-year-olds end up in the hospital while others spend a day or two in bed and recover quickly. If we knew those factors, we could target treatments much more precisely.