I have a dataset that I am trying to use to predict a patient's outcome based on a bunch of factors related to the pateint's care. One of the independent variables is a unique ID number of the primary care doctor. In addition to that variable, I have some attributes about the primary care doctor such as his age and gender. I'm not so much concerned about measuring the effects of age and gender on the outcome, but want to be sure I take variability due to it into account during my analysis. My question is, is it necessary to even include these doctor attributes (age and gender) in my analysis, or will this automatically be taken into account by including a doctor ID term in my analysis? It seems to me that if I leave a doctor ID term in the model, it will accounts for all the features/characteristics related to that doctor so I wouldn't need to include them separately. Is my intuition correct here?
If another title is more appropriate, please let me know. I'm not really sure what this problem is called (and hence I couldn't search for other posts like it).