UPDATE: Still Attempting to Resolve NYC Hospital Data Discrepancy - Email to Austin Parish & John Ioannidis
This is an update on my attempts to resolve a discrepancy involving COVID death data for New York City’s public hospital system (which I previously described in another post).
I reached out to Dr. Austin Parish (the lead author of the study described in my September 7, 2023 article) again this week with all-cause death data I obtained via public records request. I copied Dr. John Ioannidis in his capacity as co-director of METRICS.1
See below for the text of my email2 and corresponding attachments. I haven’t yet received a response.
May 7, 2024
Good day, Dr. Parish (& Dr. Ioannidis)
I previously reached out to you regarding your 2021 study - specifically, data reported in Supplemental Table 2. Our previous correspondence is attached as a PDF.
Since then, I took additional steps to try to reconcile the discrepancies between the COVID-19 death data you obtained from NYC HHC and the data NYC HHC reported to New York State for the 11 public hospitals (source).
You and I seemed to agree that the two datasets represent a “time-shift.” (Slide 1 in attached PPT). When I sum the data from your study and from the NYS file, there is a peak “between” the two datasets and a toll approaching 5,000 patients. (Slide 2 in PPT) An HHC report for fiscal year 2020 shows a daily average census of 3,200. This suggests the hospitals as a system lost 150% of census in a very short timeframe.
Since contacting you, I took additional steps to try to resolve the discrepancies, as part of my ongoing independent inquiry into the New York City spring 2020 event.
1) In August 2023, I contacted the HHC Office of the Inspector General about the difference. They referred me to a HHC COVID-19 Research Committee but did not receive a response. I’ve attached those emails for your reference.
2) In October 2023, I received relevant data for HHC hospitals. Via FOI request, I had asked for daily deaths in HHC hospitals (all causes) for 1/1/2017-12/31/2020. HHC denied the 2017-2019 data, saying it is in another database that would require creating a new code to access - and therefore be creating “new record,” which they are not required to do in response to FOI requests. I’m not a lawyer and find that excuse deeply concerning, but they did provide the 2020 data, which is relevant to your study (Slides 3 and 4 in PPT).
3) Plotting the all-cause deaths alongside COVID-19 deaths reported in your study and by NYS (Slide 5 in PPT) suggests at least two things:
a) nearly every death in HHC hospitals which occurred during the city’s spring 2020 mass-casualty event was counted as a COVID-19 death, and
b) the data in Supplemental Table 2 of your study are discrepant with the other sources.
I would love to understand the discrepancy and expect you might as well.
Is there a chance you could reach out to HHC to confirm the correct timeframe of the data they provided to you?
I presume METRICS is still your affiliation, as it was when the study was published, and am therefore copying Dr. Ioannidis, in his capacity as co-director.
Respectfully,
Jessica Hockett, PhD
PPT attachment slide 1
PPT attachment slide 2
PPT attachment slide 3
PPT attachment slide 4
PPT attachment slide 5
Emails between Hockett & Parish
Emails between Hockett & HHC
Related post
Dr. Parish’s affiliation when the study was published.
This version of the email contains some “hyperlinks” that aren’t linked in the email I sent to Drs. Parish & Ioannidis. I linked it in the Substack version for reader convenience.
Tough position to be in for the likes of Ioannidis, Bhattacharya, Kulldorff and the like.
"Gee we kinda knew some things OK maybe we were part of the machinery etc..."
"Um, we're sorry also for promoting masks, lockdowns, vaccines etcetera- we didn't know, did the best we could with the information at the time, focused protection, blah, blah, blah...."
So here we are again. Either they knew at least some aspects of the scam or they were incompetent.
Either way they should be removed from all considerations as worthwhile discussants, proving their lofty positions and all of their Pee-Aitch-Dees only makes them more arrogant and institutionally corrupt.
And that's the charitable explanation.
Thank you for relentlessly tracking this data down, Jessica!