After the phone call about the financial history, the next time I saw him was Ethan’s wedding. He hugged me and asked about the data analysis course. I told him about it. He asked a specific question about how operational data analysis worked in healthcare settings.
I answered. He listened. We had a conversation that was, mostly, just a conversation.
This is the kind of resolution that doesn’t look like resolution if you’re expecting something dramatic. It looks like two people having a normal conversation with the accumulated weight of something difficult between them, and both of them choosing to have the normal conversation anyway.
That’s probably the best version of this.
The Course and What Comes Next
The healthcare data analysis course runs twelve weeks, three evenings a week, from seven to nine-thirty.
By the third week I knew it was the right choice.
We work in R, which I’d done a small amount of in the health administration program but not seriously. The professor — a woman in her forties who runs the department’s research division and teaches this course because she thinks data literacy in healthcare workers is systematically undervalued, which I agree with — teaches it with the assumption that you have a reason for being there and can be trusted with complexity.
I have a reason for being there. I can be trusted with complexity.
The course is expensive in the way that things worth doing are often expensive: not exorbitantly, but more than free. Twenty-two hundred dollars, which I paid without asking anyone’s permission or opinion, which is the kind of thing that only feels notable because of the context.