In 2004, Atul Gawande – a thoroughly accomplished doctor and writer – published a long essay in The New Yorker entitled “Annals of Medicine”.  It offers a remarkable insight into the present state of Health Care, and informs you about the evils of relying on superficial “analyses” or nation-wide averages.  More importantly, it also teaches you the significance of understanding numbers and what they really mean to you and your Life. 

Here’s an example :

“Let’s look at the numbers,” he said to me, ignoring Janelle. He went to a little blackboard he had on the wall. It appeared to be well used. “A person’s daily risk of getting a bad lung illness with CF is 0.5 per cent.” He wrote the number down. Janelle rolled her eyes. She began tapping her foot. “The daily risk of getting a bad lung illness with CF plus treatment is 0.05 per cent,” he went on, and he wrote that number down. “So when you experiment you’re looking at the difference between a 99.95-per-cent chance of staying well and a 99.5-per-cent chance of staying well. Seems hardly any difference, right? On any given day, you have basically a one-hundred-per-cent chance of being well. But”—he paused and took a step toward me—“it is a big difference.” He chalked out the calculations. “Sum it up over a year, and it is the difference between an eighty-three-per-cent chance of making it through 2004 without getting sick and only a sixteen-per-cent chance.”

Do the math and you will find out that there is indeed a difference of nearly 80 percentage points between the two figures of 99.95% and 99.5%, when seen in that light!  Takes you back to your school or college days of learning ratios and probability, doesn’t it?

Recently, my wife had to undergo a particular ‘statistical probability’ test, related to the child we’re expecting.  Since the numbers were on the “riskier” side, another test was recommended, the results of which would take a few weeks to come. 

In the end, every thing turned out well.  But the few weeks we had to undergo, ‘not knowing’ the outcome of the lab test, were some of the most demanding we’ve encountered.  We ended up using that time to fully understand the implications of the statistical projections we were reading off the first test, and tried not to think about negative outcomes, as much as possible.

Isn’t it funny how you really come to understand the importance of a concept when your Life (or someone else’s life) depends on it?!