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!