electriccatblan

Would Statistical Rethinking help me interpret web app metrics? E.g. if I have a canary out and the response times are longer after x requests, is that significant?

Bike commuting during winter is fine as long as you have the right clothes. I have commuted in a -55F wind chill in perfect comfort. I will concede that it takes a few weeks to calibrate clothing if you're not used to it, but it's not some huge barrier if it's something you're interested in

Disclaimer: My Epic experience is around a decade old.

I never saw a riot, but I definitely saw providers who hated Epic when it was installed. As in people literally screaming at the top of their lungs at IT nerds. I saw a few contributing factors:

1. Epic supports making all the technically-mandatory-but-not-mandatory-if-you're-in-a-hurry data actually mandatory, so providers have more typing and less ability to just get stuff done when needed (which minimizes agency).

2. Related to above, Epic will make the updates for any new regulation, which increases the amount of data providers need to collect.

3. The customizability of the Epic UI and workflows for each type of visit was completely insane; many permutations of steps in a visit had to be supported which meant a huge maintenance surface with ok coverage rather than an opinionated workflow for each visit that could be optimized and improved over time.

My wife and I have good insurance (like $200 out of pocket for surgery good) and I still hate going to the doctor because I know I'm going to get stuck with an involuntary side hustle as a medical billing clerk if I want the benefits we're entitled to to actually be honored. Our insurance paid maybe ~6k in charges one time, then 6 months later retroactively denied the claims and billed us for them. There's just no repose ever at any time, and you have to deal with a system that is always stacked against you.

How did you practice system design? Did you work from problem sets or just study principles?