Note that your 4 options aren't mutually exclusive - for example, with the Multi-choice grid, you could choose to analyze it as 3 separate CBCs or as a single CBC with covariates. The outlier here is your third option and like you I would NOT prefer to run the model with patient type as an attribute.
I have done very many studies where we have the multi-choice grid and if the grid doesn't get too crazy (like if there are 10 patient types instead of the more manageable 3) the it works very nicely.
A white paper we've prepared on the subject of pharmaceutical choice experiments can be found here: https://www.sawtoothsoftware.com/download/techpap/Choice_Experiments_for_Physicians_
To answer your specific question about analyzing as 3 separate CBCs or as one CBC with a 3-level covariate, a couple of years ago I fielded a study where we tested both options. I had each respondent answer each CBC grid response question that included choices for each of 6 situations. It turned out that whether I modeled this as 6 separate CBCs or as a single CBC with a 6-level covariate didn't matter much at all. Both methods returned very similar utilities and simulations. It just doesn't seem to matter much which route you go.