Are Bitmap Fields Containing Only One 1 Appropriate for K-Modes Hamming Distance

I have a dataset with mixed datatypes:

id    amount    creator    accounts
1     100       jane       cash
1     100       jane       accounts receivable
2     200       john       tax account


Each id can have only one creator. Each id can have one or more accounts. For the accounts data, I am one hot encoding the accounts and then joining them into a bitmap:

id    amount    creator    accounts
1     100       jane       110
2     200       john       001


My plan was to apply k-prototypes to the resulting dataset. K-prototypes uses k-modes and the Hamming (# of replacements) distance to calculate similarity between categorical features and the modes. I think this works well for the bitmaps with multiple 1s. However, Hamming distance does not make sense for creator, because my assumption is that people are not more similar just because they have similar names. Therefore, I need to one hot encode the creator feature as well.

After one hot encoding, does it make sense to combine the creator features into a bitmap like the accounts? Each id can only have creator, so the bitmaps would only have replacement counts of 0 or 1.

Alternatively, am I overthinking this? Should k-modes actually be applied directly to single-value categorical variables?