Hi! You might find the NER annotation flowchart helpful, which should answer your main questions and give you some inspiration for what to try:
It might make sense to start off with a blank model instead of the pre-trained NER component of the en_core_web_md model. If there are entity types you want to keep (like PERSON), you can use the ner.make-gold recipe with the existing labels plus DISEASE. This will pre-highlight the existing predictions and lets you correct them, and manually add the annotations for your new DISEASE label. When you train your model later on, make sure to set the --no-missing flag to tell spaCy that the annotated spans are complete and unannotated tokens are not part of any entity.