Hi! Training a span categorizer from data annotated with ner.manual should just work out of the box, because the underlying format is the same 
So instead of passing your dataset in as --ner when you train or export the Prodigy annotations, you can use --spancat instead.
Whether or not it improves the results really depends on the data and type of annotated spans. In case you haven't seen it, here's an overview of the advantages of NER vs. span categorization, depending on the problem type: https://prodi.gy/docs/span-categorization#ner-vs-spancat).
After training a spancat model from your data, you can then load it in and improve it using spancat.correct.