My point is that you need a lot of work to make this work even for one hospital, let alone scale to many, even more so scale at the level of a national health service. I don't see that the paper you link contradicts this.
Edit: if I may summarise: I said "it's not simple" not "you can't do it".
Transfer learning is not generalisation to unseen data. If the pre-trained model and the end model don't have any common instances it doesn't work [Edit: "don't have any instances with a common feature space" is more clear].
Also, you're talking about generalisation to new devices. My understanding is that this is only one aspect of the difficulties with scaling image recognition for medical diagnoses to data from different sites.