Data Definitions – Wait Times

If one is going to use data to make decisions or measure performance, definition of data is very important.  I had a discussion recently with a friend about "Waiting Times" in the delivery of health services in Canada.   The reason for this discussion is I get many questions from my American friends about whether the health care system in Canada works.   I pointed out to the dilemma we have with the way our system works.  The Federal Government provides a lot of money to the provinces to deliver health care, which is a provincial responsibility.  However the Feds want to influence the delivery and made a condition of some of the money, reduction in "Wait Times". 

Now the fun begins because now we must define "Wait Time".  Lets us take a simple example.   I go to an emergency department with a broken leg and in pain.  I get service in thirty minutes.  Then another time I go to emergency because I have a bad cold and it is on the weekend.  I wait for eight hours before I am seen by somebody who can give me an examination.  I think it is obvious we cannot consider these wait times in the same category. Similarly elective and emergency surgery and not the same.  So we now need data definitions that all provinces and the federal government agree on.

Then we can start collecting meaningful data and evaluating the performance of our health care system in some meaningful ways.   Unfortunately the issues are complex and people want simple models. 

I intend over the next few months to do some research on the issue of data definitions with "Wait Times" because I think it demonstrates the importance of data and data definitions for business intelligence.  I should I say for businesses to act intelligently.   

If we have bad data because of poor data definitions, then we will likely make bad decisions, based on bad business intelligence.

  1. Graham Boundy Reply

    I had to get three stitches in my finger (don’t ask how or why – that’s a story in itself). I went to the emergency at my local hospital (in Toronto). Within 15 minutes the triage nurse had seen me. Within 20 minutes I was admitted. I waited another five hours to see an actual doctor. He did a great job stiching me up, although I wish he had used a little more freezing (ouch). The nurse who cleaned me up and applied the dressing took another 30 minutes.
    Now if I had arrived with massive bleeding or had severed the finger from my hand, I expect the response and wait time would have been shorter. That’s why there is triage.
    I think we need to do the same with data. There is a certain amout of triage we need to perform on data. Mission critical dimesions and measures garner a lot more attention that the status values that no one cares to look at. We may perscribe to the notion of universal data capture (like universal health care). We need to apply the right emphasis to the cases that truely have an urgent need to be serviced and relegate the lesser cases to a lower priority (we’ll get to it when the “real” emergencies are over.)

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