Harvardx course Practical Improvement Science in Health Care with the Institute for Healthcare Improvement.
So very traditionally in almost every setting, whether it’s health care or education or business, people look at data all the time. But they don’t necessarily look at data in a way that’s helpful for understanding what’s happening. So this is a perfect example. This is data on a program trying to have people stop smoking. And it is 24 weeks of data looking at the percentage of smokers who had quit smoking after a four week program. So as you’re looking at this, do you see improvement? Is there a difference? So a common thing that people might do to be able to help you interpret this data is they’ll maybe break it down. And they’ll say well, let’s look at before our program from weeks 1 to 12 — here’s the average that we had, here’s maybe the maximum number and the minimum number. And then after we did our program here’s weeks 13 through 24. And we’ll also do an average and maximum and minimum. Now, let’s compare those. Right? We’re looking at a snapshot of before and after we did this program. And we’re trying to make a conclusion about whether improvement happened.
Now, if I give you enough time, you can circle the numbers, and you’ll try really hard to interpret this data. And you may actually come up with a good impression of whether our program made a difference. But if I put it over time. And I display it in a simple line chart, now you’re able to really make some strong conclusions. So not only can you tell that before our program that there was a lot more variability in the results that we were achieving, but you can also see where we made our change we had a straight to directory in an upward direction. We would call this a direction of goodness, where we wanted to go, that is very, very consistent and reliable. It really looks like our program resulted in some pretty significant improvement.
So you can talk about the data that you see in this line chart in such a way that’s so much more powerful. And there’s so much more analytics that you can do than when you were looking at it in a simple table of data. And this is one of the reasons we emphasize displaying data in such a way over time that enables you to be able to interpret the behavior of the data.
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