Sure we can be technically more surgical in our terminology, but GP is addressing the usage of 'accuracy' in the news headline. In that context, 'accuracy' is kinda a catchall term for both accuracy and precision.
My goal in pointing out the difference was not to be snarky. It was to point out the very real statistical consequences. Any model can be accurate on a sufficiently biased dataset, but what matters once a screening test hits the real world are the precision (positive predictive value) and negative predictive value. These are the hurdles that the test will have to pass to see widespread adoption.