Wednesday, January 17, 2024

Finding SEP1 data on CMS website after 5 or 6 years

 it's easy when you have the link...


In 2018 I dug down the CMS rabbitt holes to get SEP1 spreadsheets.   I reproduced the process (slightly different rabbit holes) in 2024.


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I found the blog where I originally described it as " a consumer facing portal" and "a professional portal."   The former lets you compare a few hospitals on a web page.  The latter let you down load an Excel of 4000 hospitals and their data.

Here is the Nov 16 2018 blog where I wrote about this (which is why I could remember the blog, but have long since lost memory of exactly what web page it was!)

Aug 4 2018



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OK, so what I have above is stuff that worked in 2018, let's say if the CMS website will still get us to what we need.

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So what I called the "professional" website now redirects to here (link just above) which is called PROVIDER DATA CATALOG.

I no longer see a link for 'download flat files' but there's a symbol for Hospitals so that sounds promising.  You land here:

Which just has the drawback it leads you to 69 hospital datasets.  There are 48 keywords (right column) one of which is Timely and Effective Care, which worked in 2018, so I'll try that.  








This gives Timely and effective care for Nation, State, and Hospital.  Each is a CVS file.  
We would want "hospital" level.  







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This gives an CSV file which I immediatley save as a Xls file.

I'm now looking at a spreadsheet about 15 columns wide (P) and 115,000 rows deep.  It gives about 25 rows for every hospital, each a different measure.   The main SEP1 measure is "SEP1" but there are several sub measures like Sepsis Care SEP_SH_3HR and a few others.   The first hospital is facility 10001, Southeast Health Medical Center, Dothan, AL.  In line 16, it scores 55 for SEP1 on a sample of 128 available patints.  The data is for CY2022 (1/1/ to 12/31).   

In Column I and J, the strcture is 5 rows for Sepsis Care and each row has a different measure ID (like SEP_SH_3R).





I made a copy where I deleted all the rows except the sepsis rows.  This brought the size down to 2 MB which I attach.

 





QED

BQ






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