Well, I think things are beginning to be better managed in some centers. If that's your case, then good for you. In my center, it's basically the wild west and data management is a catastrophe.
But are you working the clinical wards? Because things are definitely much better managed in places such as epidemiology units. The true horrors mostly come from clinical researchers digging into excel spreadsheets without knowing a mean from a median.
I'm in a computational lab, but I think I understand what you're describing. My medical school was acquired a few years ago by a hospital network, encouraging us to collaborate with our new clinical researchers. The medical school itself had a strong background in rigorous basic research with animal models, and the clinical samples are a relatively smooth transition. The data is obviously nowhere as clean or plentiful as with animal models, but that's to be expected.
So for example, my lab's expertise was in single cell developmental models, primarily for organ development in mice. Extended that to tumors from clinical samples was relatively straightforward. One of my colleagues is working on an autism dataset, but I wouldn't expect that to be nowhere nearly as clean.
But are you working the clinical wards? Because things are definitely much better managed in places such as epidemiology units. The true horrors mostly come from clinical researchers digging into excel spreadsheets without knowing a mean from a median.