Date: Mon, 29 Mar 2010 11:32:06 -0400
Reply-To: Gene Maguin <email@example.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Gene Maguin <firstname.lastname@example.org>
Subject: Re: insurance claims risk adjustment takes forever
Content-Type: text/plain; charset="us-ascii"
I can't comment on spss vs sas or on your computer. It seems to me, though,
that your dataset+required computations is at a place were the computational
algorithm matters, maybe a great deal. I'm pretty sure there are others on
the list that have experience with big datasets and can comment better than
I can. I wondering if you have the most efficient algorithm for the required
operations. Have you tested alternatives and, if so, was there enough
difference to matter? And, if you'd care to, I'd be interested to hear a
description of your computational algorithm.
I'm trying to run an insurance claims risk adjustment program. But by my
calculations it could take several thousand hours to run.
The program takes the over 16,000 ICD9 codes and puts diagnoses into groups.
My data has 8 diagnoses per claim. And I have almost 3 million claims.
My machine is a dual core Pentium, using the python plugin, 2 gigs of ram,
Does it make sense that it could take so long? Someone asked me if spss runs
from memory, compared to sas which runs from the disk. Could this be part of
Bottom line. Does this type of analysis sound possible with SPSS.
Matthew Pirritano, Ph.D.
Research Analyst IV
Medical Services Initiative (MSI)
Orange County Health Care Agency
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