Take Two Tylenol and Call Me in the Morning

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Mariko Gordon It's funny how a set of data can lead to two completely different conclusions in the space of 15 minutes.

Let me explain.

My mother had been suffering from a baffling joint ailment; one that would flare up periodically, leading to swelling, pain and immobility. She was having trouble being heard by her doctor, so I went with her to get her test results and the diagnosis.

Overflowing with arrogant confidence, the doctor explained that my mother had no inflammation of any kind. Rather, her symptoms were most unquestionably the result of age-related osteoarthritis, where bone starts rubbing against bone as cartilage thins out.

Yes, there was one stray bit of data in the blood tests that was a little abnormal, but it was not a marker for any kind of rheumatoid arthritis. Given that the rest of the tests and x-rays for rheumatism were negative, he concluded that she most definitely did not have rheumatoid arthritis.

All that pain and suffering? A figment of her imagination. He told my mother to take some Tylenol and get over it.

Not so fast, Doc. Based on the symptoms I had witnessed when she was not taking anti-inflammatory meds, I challenged his diagnosis. And, after nearly coming to blows with the doctor (what a condescending, patronizing, tone-deaf jerk!), I finally got him to really LISTEN to my mother.

And he changed his diagnosis completely.

Her real-life experience (now that he had bothered to find out what that was), in conjunction with that slightly anomalous blood reading (the one indicator of what she does have!), meant that she has something entirely other than osteoarthritis. Living happily ever after with Tylenol wasn't going to cut it.

She has a new doctor now - surprise, surprise - and is doing fine.

I share all this (with my mother's permission) because there is an important investment - if not life - lesson in this incident: The data were never in dispute. However, the correct interpretation of the data was dependent on having the proper context. A context that is qualitative and derived from asking a lot of good questions.

Without context, data are often misleading at best, and worthless at worst. Unfortunately, as an industry, we miss a lot of context.