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SAS® USER PROFILE
Name: Kevin Druhan
Location: Halifax, Nova
Scotia
Company: Nova Scotia
Department of Health
(Continuing Care Branch)
SAS® History: I’ve
been a SAS user for about five years now.
I first started using SAS on OpenVMS to perform data quality analysis
of large population-health data sets (hundreds of millions of records).
These days, I use SAS to provide decision support to government using
SAS 9.1.3 for the windows platform including SAS Enterprise Guide®,
which has become an indispensable tool for supporting evidence-based
decision making.
In the Continuing Care Branch, I use SAS primarily
to extract and analyze data for planning, program evaluation, policy
development, and performance management activities. In 2007, the branch
undertook a major planning project around a hot political issue in
Nova Scotia: building $74 million in new long-term care facilities
(such as nursing homes) to provide quality care for our aging population.
The branch felt strongly that decisions about the number of beds that
should be built, and where they should be located, would be best determined
by understanding the health needs of the population. SAS software was
a key part of the development and validation of a fairly sophisticated
population- and frailty-based bed-allocation methodology that integrated
data from many different sources. I needed to analyze a lot of data
quickly, and SAS was used to calculate many key components of the model
including wait times, demand drivers, population projections, and the
pattern of frailty in seniors across the province.
The results of this methodology were so comprehensive
and convincing that they were accepted with very minor changes by politicians
and the sector. Perhaps most importantly, political and advocacy factors
were managed much more effectively than they have been in the past
through the use of such a strong evidence-based planning approach.
I was honored to receive the Innovation Award for Excellence and Creativity
in Supporting Quality Care Across the Continuum at the 2007 Canadian
InterRAI/CIHI (Canadian Institute of Health Information) conference
for this work – and I couldn’t have done it without SAS!
I’ve also presented a number of times at our
local SAS Halifax Regional Users Group (SHRUG), and I always enjoy
the opportunity to meet other SAS users and share insights into how
SAS can help people understand what is going on in their business
and facilitate better decision making.
Pets: Our
family has grown by an average of one feline
per year over the past three years – Mr. Nibblesworth,
Icky, and Biscuit. Although I love all of our
cats equally, Biscuit is definitely the cutest!
Family: My
wife is the smartest woman I know, but the
one time I tried to explain SAS programming
to her, I think she fell asleep long before
I got to the good part!. My 10-year-old son
is a rabid video-gamer, so perhaps he will
catch the programming bug.
Sports/Hobbies: Ultimate
Frisbee, squash, underwater pool hockey.
:Ideal
Weekend: A
hot day at the beach with my family,
followed by BBQ and an evening
playing Settlers of Catan (What
can I say? I’m a simple man!).
Favorite
Food: Curry,
curry and curry. Oh yeah, did I
mention curry?
If
I could do anything (besides
being a SAS developer), I would
be: A
rock star.
When
I am not working with SAS, I like
to: Sing,
play guitar, make homebrew, swill
homebrew, “chillax” (as my son says).
One
thing every SAS programmer should
know: PROC
SQL! The relative merits of PROC
SQL vs. the data step merge seems
to be the perennial question among
SAS programmers. My advice is to
spend just a little time learning
how to link your data sets using
PROC SQL, and you’ll never look back!
There have been some great presentations
around this topic at recent SAS Global
Forum/SUGI conferences and it’s a
snap to pick up, so grab the papers
online and start PROC SQLing!
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